The achievement of size uniformity and monodispersity in perovskite quantum dots (QDs) requires the implementation of precise temperature control and the establishment of optimal reaction conditions. Nevertheless, the accurate control of a range of reaction variables represents a considerable challenge. This study addresses the aforementioned challenge by employing manganese (Mn) doping to achieve size uniformity in CsPbBr₃ perovskite QDs without the necessity for precise control of the reaction conditions. By optimizing the Mn:Pb ratio, it is possible to successfully dope CsPbBr₃ QDs with appropriate concentrations of Mn²⁺ and achieve a uniform size distribution. The spectroscopic measurements on single QDs indicate that the appropriate Mn²⁺ concentrations can result in a narrower spectral linewidth, a longer photoluminescence (PL) lifetime, and a reduced biexciton Auger recombination rate, thus positively affecting the PL properties. This study not only simplifies the size control of perovskite QDs, but also demonstrates the potential of Mn-doped CsPbBr₃ QDs for narrow linewidth light-emitting diode applications.

Polyvinyl Alcohol (PVA)/ Graphene Quantum Dots (GQDs) polymer nanocomposite films have been prepared, and the relationship between their structural, thermal and nanoscale morphologi-cal properties, and their photoluminescent response, has been investigated. Although according to X-ray Diffraction (XRD), Fourier-Transform Infrared Spectroscopy (FT-IR) and Differential Thermal Analysis (DTA) the incorporation of GQDs does not significantly affect the percentage crystallinity of the PVA matrix, for a range of added GQD concentrations, Atomic Force Micros-copy (AFM) showed the formation of islands with apparent crystalline morphology on the surface of the PVA/GQD films, with GQD presumably acting as a nucleating agent for island growth. The incorporation of GQD also led to the formation of characteristic surface pores with increased stiffness and frictional contrast, according to Ultrasonic Force Microscopy (UFM) and Frictional Force Microscopy (FFM) data. The photoluminescence (PL) spectra of the films were found to de-pend both on the amount of GQD incorporated and on the film morphology. For GQD loads > 1,2wt%, a GQD-related band was observed at ~ 1650 cm-1 in FT-IR, along with an increase in the PL band at lower energy. For a load of ~2wt% GQD, the surface morphology was characterized by extended cluster aggregates with lower stiffness and friction than the surrounding matrix, and the PL signal decreased.

This research review explores the synthesis of graphene quantum dots (GQDs) from biowaste for supercapacitor applications, driven by the need for sustainable and efficient energy storage technologies. GQDs, with their unique properties like high surface area and excellent conductivity, hold promise for enhancing supercapacitor performance. Various synthesis methods, including hydrothermal/solvothermal processes, chemical exfoliation, carbonization/pyrolysis, and microwave-assisted synthesis, are discussed alongside characterization techniques to evaluate GQD properties. Biowaste-derived GQDs demonstrate significant potential by improving specific capacitance and cycling stability in supercapacitor electrodes. Challenges such as scalability and material purity are identified, with future directions focusing on enhancing energy density, cycle life, and cost-effectiveness to propel the adoption of biowaste-derived GQDs in commercial energy storage applications.

Graphene quantum dots (GQDs) have garnered significant attention in recent years due to their unique properties and promising applications in various fields such as electronics, optoelectronics, bioimaging, and sensing. The synthesis of GQDs is a critical step in harnessing their potential, and numerous methods have been developed to produce GQDs with specific properties. This review provides an overview of the different techniques employed for synthesizing GQDs, including top-down and bottom-up approaches. Furthermore, it discusses the advantages, limitations, and potential applications of each method, offering insights into the future direction of GQD synthesis research.

The first hyperpolarizability of graphene quantum dots (GQDs) suspended in water was determined using the hyper-Rayleigh scattering (HRS) technique. To the best of our knowledge, this is the first application of the HRS technique to characterize GQDs. Two commercial GQDs (Acqua-Cyan and Acqua-Green) with different compositions were studied. The HRS experiments were performed with an excitation laser at 1064 nm. The measured hyperpolarizabilities were (1.0±0.1) × 10^(-27) esu and (0.9±0.1) × 10^(-27) esu for Acqua-Cyan and Acqua-Green, respectively. The results were used to estimate the hyperpolarizability per nanosheet obtained by assuming that each GQDs has five nanosheets with 0.3 nm thickness. The two-level model, used to calculate the static hyperpolarizability per nanosheet, provides the values of (2.4±0.1) × 10^(-28) esu (Acqua-Cyan) and (0.5±0.1) × 10^(-28) esu (Aqua-Green). The origin of the nonlinearity is discussed on the basis of polarized resolved HRS experiments, and an electric quadrupolar behavior with a strong dependence on surface effects is found. The nontoxic characteristics and order of magnitude indicate that these GQDs may be useful for biological microscopy imaging.

In this work, we investigate by ab initio calculations and optical experiments the sensitiv- ity of graphene quantum dots in their use as devices to measure the presence, and concentration, of heavy metals in water. We demonstrate that the quenching or enhancement in the optical response (absorption, emission) depends on the metallic ion considered. In particular, two test cases of opposite behaviour are considered: Cd 2+ , where we observe an increase in the optical response for increasing concentration, and Pb 2 whose emission spectra are quenched along the concentration rise. We envisage that quantum dots of graphene may be routinely used as cheap detectors to measure the degree of poisoning ions in water

Copper (Cu) is a critical element for cancer cell proliferation and considerably accumulates in the nucleus. 64Cu2+ is an anticancer radiopharmaceuticals targeting the copper requirement of cancer cells. However, intravenously injected 64Cu2+ ions primarily accumulate in the liver. Ligand complexation of 64Cu2+ would be a promising method for increasing tumor delivery by reducing liver uptake. Herein, we used three tripodal amine ligands [tris(2-aminoethyl)amine (Tren), diethylenetriamine (Dien), and tris(2-pyridylmethyl)amine (TPMA)] to enclose 64Cu2+ ions and compared their in vivo tumor and liver uptake using a tumor-bearing xenograft mouse model of the extrahepatic bile duct carcinoma cell line TFK-1. We examined intracellular Cu distribution using microparticle-induced X-ray emission (micro-PIXE) analysis for these compounds. 64Cu2+-Tren and 64Cu2+-Dien showed higher tumor uptake than 64Cu2+-TPMA and 64Cu2+ ions in TFK-1 tumors. Among the three 64Cu2+ complexes and 64Cu2+ ions, liver uptake was inversely correlated with tumor uptake. Micro-PIXE analysis showed that in vitro cellular uptake was similar to in vivo tumor uptake and nuclear delivery was the highest for 64Cu2+-Tren. Conclusively, an inverse correlation between tumor and liver uptake was observed using three 64Cu2+ complexes of tripodal amine ligands and 64Cu2+ ions. These results provide useful information for the future development of anticancer 64Cu radiopharmaceuticals.

Thermal camouflage is a highly sought-after technology to increase the survivability of military equipment against infrared (IR) detectors. Recently, two-dimensional (2D) nanomaterials have shown low IR emissivity, widely tunable opto-electronic properties and compatibility with stealth-applications. Among them, graphene and graphene-like materials are the most attractive 2D materials used for thermal camouflage applications. In particular, in multilayer graphene (MLG) charge density can be effectively tuned through sufficiently intense electric fields or through electrolytic gating. Therefore, MLG optical properties, like infrared emissivity and absorbance, can be controlled in a wide range by voltage bias. The large emissivity modulation achievable with this material makes it suitable in the design of thermal dynamic camouflage devices. Generally, the emissivity modulation in the multilayered graphene medium is governed by an intercalation process of non-volatile ionic liquids under a voltage bias. The electrically-driven reduction of emissivity leads to a decrease in the apparent temperature of the surface, which can match that of the background enabling thermal camouflaging. Since this property is common to other graphene-based materials, here we present a review specifically focused on the recent advances in the field of the thermal camouflage properties of graphene in the form of composite film and aerogel structures. A summary of the current understanding of the working principle of thermal camouflage materials, current limitations, and future opportunities is presented and discussed.

In this work, we firstly explored a mild, clean, and highly efficient approach for the synthesis of graphene quantum dots (GQDs). GQDs with carboxyl groups or amino groups, were prepared from one-pot environmentally friendly method assisted by hydrogen peroxide, respectively. It was proved that carboxyl groups played an important role in the fluorescence quenching. Based on these findings, we developed a novel fluorescent nanosensor by combining molecularly imprinted polymers (MIPs) with carboxyl functionalized GQDs for the determination of tetracycline (TC) in aqueous samples. The nanocomposite was prepared using a sol-gel process. GQDs-MIPs showed strong fluorescent emission at 410 nm when excited at 360 nm, which was subsequently quenched in the presence of TC. Under optimum conditions, the fluorescence intensity of GQDs-MIPs decreased in response to the increase of TC concentration with good linearity rage of 1.0-104 µg L-1. The limit of detection was determined to be 1 µg L-1. The fluorescence intensity of GQDs-MIPs was more strongly quenched by TC compared to the corresponding non-imprinted polymers, GQDs-NIPs. With the high sensitivity, the material was also successfully worked for the detection of TC in real spiked milk samples.

A low-cost bio-mass-derived carbon substrate has been employed to synthesize MoS₂@carbon composites through a hydrothermal method. Carbon fibers derived from natural cotton provide a three-dimensional and open framework for the uniform growth of MoS₂ nanosheets, thus constructing hierarchically coaxial architecture. The unique structure could synergistically benefit fast Li-ion and electron transport from the conductive carbon scaffold and porous MoS₂ nanostructures. As a result, the MoS₂@carbon composites, when served as anodes for Li-ion batteries, exhibit a high reversible specific capacity of 820 mAh g^-1, high-rate capability (457 mAh g^-1 at 2 A g^-1), and excellent cycling stability. The superior electrochemical performance makes the MoS₂@carbon composites to be low-cost and promising anode materials for Li-ion batteries.

We study theoretically the Josephson diode effect (JDE) realized in a system composed of parallel-coupled double quantum dots (DQDs) sandwiched between two semiconductor nanowires deposited on an s-wave superconductor surface. Due to the combined effects of the proximity-caused superconductivity, strong Rashba spin-orbit interaction and Zeeman splitting inside the nanowires, a pair of Majorana bound states (MBSs) may possibly emerge at opposite ends of each nanowire. Different phase factors arisen from the superconductor substrate can be generated in the coupling amplitudes between the DQDs and MBSs prepared at the left and right nanowires, and will result in the Josephson current. We find that the critical Josephson currents in positive and negative directions are different from each other in amplitude within an oscillation period with respective to the magnetic flux penetrating through the system, a phenomenon known as the JDE. It arises from the quantum interference effect in this double-path device, and can hardly occur in system of one QD coupled to MBSs. Our results also show that the diode efficiency can reach up to 50%, and depends on the overlap amplitude between the MBSs and the energy levels of the DQDs adjustable by gate voltages. The present model is realizable within current nanofabitication technologies and may find practical use in interdisciplinary field of Majorana and Josephson physics.

A challenge in building large-scale superconducting quantum processors is the precise control and manipulation of the qubit state. However, the crosstalk between the microwave control lines impedes the parallel execution of high-fidelity digital and analog quantum operations. Here, we propose and demonstrate a universal compensation protocol for calibrating the microwave signal crosstalk. We also introduce amplified error sequences to optimize the accuracy. Furthermore, we show a definitive improvement in parallel gate operations with crosstalk cancellation, demonstrating the technique's effectiveness. This work paves the way for superconducting hardware that features automated calibration of microwave crosstalk, leading to enhanced fidelities in multiqubit circuits.

The electric vehicle (EV) industry challenges battery joining technologies by requiring higher energy density both by mass and volume. Improving the energy density via new battery chemistry would be the holy grail but is seriously hindered and progresses slowly. In the meantime, alternative ways, such as implementing more efficient cell packaging by minimizing the electrical resistance of joints are of primary focus. In this paper we discuss the challenges associated with the electrical characterisation of laser soldered joints in general, and the minimization of their resistive losses, in particular. In order to assess the impact of the joint resistance on the overall resistance of the sample, the alteration in resistance was monitored as a function of voltage probe distance and modelled by finite element simulation. The experimental measurements showed two different regimes: one far from of the joint area and another in its vicinity and within the joints cross section. The presented results confirm the importance of the thickness of the filler material, the effective and the total soldered area, and the area and the position of the voids within the total soldered area in determining the electrical resistance of joints.

Three-dimensional V₂O₅ hollow structures have been prepared through a simple synthesis strategy combining solvothermal treatment and a subsequent thermal annealing. The V₂O₅ materials are composed of microspheres 2–3 μm in diameter and with a distinct hollow interior. The as-synthesized V₂O₅ hollow microspheres, when evaluated as a cathode material for lithium-ion batteries, can deliver a specific capacity as high as 273 mAh·g⁻¹ at 0.2 C. Benefiting from the hollow structures that afford fast electrolyte transport and volume accommodation, the V₂O₅ cathode also exhibits a superior rate capability and excellent cycling stability. The good Li-ion storage performance demonstrates the great potential of this unique V₂O₅ hollow material as a high-performance cathode for lithium-ion batteries.

We propose and experimentally realize a scheme of the optical nonreciprocity (ONR) using degenerate two-level atoms embedded in an optical ring cavity. For the degenerate transition Fg=4→Fe=3, we first study the cavity-transmission property in different coupling field, and verify that within the strong-coupling regime, the single-dark-state peak formed by electromagnetically induced transparency (EIT) shows ONR. Qualitative theoretical analysis shows that the stable ground-state Zeeman coherence is necessary for intracavity EIT. However, due to the frequency degeneracy, the large Rabi frequency of counter-propagating coupling field can reduce the number of effective atoms and weaken the strong-coupling of the atom-cavity, which determines that ONR based on intracavity EIT occurs only at weaker probe intensity. Furthermore, the ONR transmission with high contrast, linewidth-narrowed and broadband is experimentally demonstrated.

Quantum cryptography revolutionizes secure information transfer, providing defense against both quantum and classical computational attacks. The primary challenge in extending the reach of quantum communication comes from the exponential decay of signals over long distances. Addressing this challenge, we have developed Quantum-protected Control-based Key Distribution (QCKD), overcoming transmission range limitations by monitoring signal leakages and rendering leaked quantum states significantly non-orthogonal. This paper reports on the experiments with the QCKD, conducted over a 1,707 km fiber line. We demonstrate advancements in critical components of the protocol, showing its remarkable scalability and adaptability for extended distances and multi-user configurations.

Composite membranes formed by sulfonated poly(ether ether ketone) (SPEEK) with embedded carbon quantum dots (CQDs) were used for detection and removal of heavy metal ions, such as lead and cadmium, from water. SPEEK is responsible for the capture of heavy metals based on the cation exchange mechanism, while CQDs detect their contamination by exhibiting changes in fluorescence. Water-insoluble “red” carbon quantum dots (rCQDs) were synthesized from p-phenylenediamine so that their photoluminescence was shifted from that of the polymer matrix. CQDs and the composites were characterized by several techniques: FTIR, Raman, UV/VIS, photoluminescence, XPS spectroscopies and AFM microscopy. The heavy metal ion concentration was analyzed by inductively coupled plasma–optical emission spectroscopy (ICP-OES). The concentration ranges were 10.8 - 0.1 mM for Pb2+ and 10.0 - 0.27 mM for Cd2+. The composite achieved 100% removal efficiency for lead and cadmium if the concentration was below a half of the ion exchange capacity of SPEEK. The regeneration of membranes in 1 M NaCl was also studied. SPEEK/rCQDs showed a turn-off effect more pronounced for lead. A second order law was effective to describe the kinetics of the process.

The Aether Physics Model (APM) presents a radical reinterpretation of fundamental physics, offering potential solutions to long-standing problems in Quantum Mechanics and General Relativity. This paper explores the core concepts and equations of the APM, demonstrating how they provide a unified framework for understanding the nature of space, time, matter, and fundamental forces. We examine the implications of the APM's quantized Aether structure, the role of the Singularity and Gforce, and the reinterpretation of fundamental constants and forces. The model's predictions regarding dark matter, neutron content in stable matter, and the unification of forces are discussed, along with potential experimental tests. Additionally, we introduce the loxodrome concept and toroidal particle topology as central elements in explaining fundamental particles and forces. While highly speculative, the APM offers a thought-provoking alternative to standard physics models and warrants further investigation.

The temperature-dependent intensities of the exciton (X) and biexciton (XX) peaks from single GaAs cone-shell quantum dots (QDs) are studied with micro photoluminescence (PL) at varied excitation power and QD size. The QDs are fabricated by filling of self-assembled nanoholes, which are drilled in an AlGaAs barrier by local droplet etching (LDE) during molecular beam epitaxy (MBE). This method allows the fabrication of strain-free QDs with sizes precisely controlled by the amount of material deposited for hole filling. Starting from the base temperature T = 3.2 K of the cryostat, single-dot PL measurements demonstrate a strong enhancement of the exciton emission up to a factor of five with increasing T. Both, the maximum exciton intensity and the temperature Tx,max of the maximum intensity depend on excitation power and dot size. At an elevated excitation power, Tx,max becomes larger than 30 K. This allows an operation using an inexpensive and compact Stirling cryocooler. Above Tx,max, the exciton intensity decreases strongly up to its disappearance. The experimental data are quantitatively reproduced by a model which considers the competing processes of exciton generation, annihilation, and recombination. Exciton generation in the QDs is given by the sum of direct excitation in the dot plus additional bulk excitons diffusing from the barrier layers into the dot. The thermally-driven bulk-exciton diffusion from the barriers causes the temperature enhancement of the exciton emission. Above Tx,max, the intensity decreases due to exciton annihilation processes. In comparison to the exciton, the biexciton intensity shows an only very weak enhancement, which is attributed to more efficient annihilation processes.

Talbot effect is a self-imaging or lensless imaging phenomenon of a periodic grating illuminated by a collimated light beam at regular distances from the grating. Research on the Talbot effect has recently made significant strides thanks to the quick development of optical superlattices. The emergence of various applications of this effect in fields such as optics, acoustics, X-ray, plasmonics, and information processing has led to the increasing importance of obtaining a Talbot carpet with the use of different structures. In this paper, we investigate the Talbot effect that originates from the tunneling effect between an ensemble of vertically coupled cylindrical quantum dots (QDs). The Talbot carpet can be manipulated by changing the parameters of the QD system. In the current paper, two modified Pöschl-Teller potentials were used to model the QDs ensemble. The exciton’s lifetime and tunneling time’s dependence on the first QD’s potential half-width is found for a fixed value of the external electric field. The nonlinear changes in the refractive index and absorption spectrum dependent on the tunneling effect are obtained. Afterward, the Talbot carpet formation is investigated, particularly the dependences of the formed periodic wavefront’s visibility on medium length, coupling field’s strength, and tunneling parameter. Finally, we have observed the intensity distribution of the diffraction field at Talbot half-distance.

To realize precise control of the quantum dots (Qdots) device, multi-channel precision bias source plays the key role. In this paper, the 16-channel high precision bias source with 18-bit resolution for Qdots device was designed. The prototype was made and its performance was tested. The short time fluctuations can reach 50μV. The step response time is less than 3μs. The resolution, stability, linearity and dynamic range of the bias source exhibits good performance. What's more, the bias source can be controlled locally and online. The results show that it is one effective and feasible topology for experiments in Qdots device application.

A novel type of graphene-like quantum dots, synthesized by oxidation and cage-opening of C60 buckminsterfullerene, has been studied as a fluorescent and absorptive probe for heavy-metal ions. The lattice structure of such unfolded fullerene quantum dots (UFQDs) is distinct from that of graphene since it includes both carbon hexagons and pentagons. The basic optical properties, however, are similar to those of regular graphene oxide quantum dots. On the other hand, UFQDs behave quite differently in the presence of heavy-metal ions, in that multiple sensitivity to Cu2+, Pb2+ and As(III) was observed through comparable quenching of the fluorescent emission and different variations of the transmittance spectrum. By dynamic light scattering measurements we confirmed, for the first time in metal sensing, that this response is due to multiple complexation and subsequent aggregation of UFQDs. Nonetheless, the explanation of the distinct behaviour of transmittance in the presence of As(III) and the formation of precipitate with Pb2+ require further studies. These differences, however, also make it possible to discriminate between the three metal ions in view of the implementation of a selective multiple sensor.

In this work, we report on the first attempt using size-controlled ZnO nanoparticles (NPs) to analyze role of thioacetamide (TAA) in forming ZnS nanostructures from ZnO. The size-controlled B(blue)_, G(green)_, Y(yellow)_ZnO QDs, and NC (nanocrystalline)_ZnO NPs were synthesized by sol-gel process as well as hydrothermal method, respectively and then reacted with an ethanolic TAA solution as sulfur source. After reacting with TAA, the formation of ZnS QDs was observed over time. The chemical reactions were identified using X-ray diffraction (XRD), Transmission Electron Microscope (TEM), UV-vis spectroscopy, and Photoluminescence (PL). All results indicate that ZnS formation is due to direct crystal growth and/or chemical conversion of ZnO to ZnS. Our results enable a broader understanding of the synthetic mechanisms involved in the use of TAA as a sulfur source in forming ZnS nanostructures from ZnO.

Graphene quantum dots (GQDs) possess the photosensitive absorption for photoelectrochemical hydrogen evolution owing to special band structures. Whereas they usually confront with photo-corrosion or undesired charge recombination during photoelectrochemical reactions. Hence, we establish the heterojunction between GQDs and MoSe2 sheets via hydrothermal process for improved stability and performance. Photoanodic water splitting with hydrogen evolution boosted by heteroatom doped N,S-GQDs/MoSe2 heterojunction has been attained due to the abundant active sites, promoted charge separation and transfer kinetics with reduced energy barriers. Diphasic 1T and 2H MoSe2 sheets hybridized quantum dots contribute to the Schottky heterojunction, which can play a key role in expedited carrier transport to inhibit accumulative photo-corrosion and increase photocurrent. Heteroatom dopants lead to favored energy band matching, bandgap narrowing, stronger light absorption and high photocurrent density. The external quantum efficiency of doped heterojunction has been elevated twofold over that of the non-doped pristine heterojunction. Modification of graphene quantum dots and MoSe2 heterojunction demonstrate a viable and adaptable platform toward photoelectrochemical hydrogen evolution processes.

Patterning, stability, and dispersion of the semiconductor quantum dots (scQDs) are the three issues strictly interconnected for successful device manufacturing. Recently several authors adopted direct optical patterning (DOP) as a step forward in photolithography to position the scQDs in a selected area. However, the chemistry behind the stability, dispersion, and patterning has to be carefully integrated to obtain a functional and therefore, commercial device. In this review are described different chemical strategies suitable to stabilize the scQDs both at a single level and as an ensemble with a special focus on the ones compatible with direct optical patterning (DOP). With the same purpose, the scQDs dispersion in a matrix was described in terms of the scQDs surface ligands interactions with the matrix itself. The chemical processes behind the DOP are illustrated and discussed for five different approaches that consider together stability, dispersion, and the patterning itself of the scQDs.

The rapid advancements and the merging of hybrid quantum-classical computing, artificial intelligence (AI), machine learning (ML), and deep learning (DL) pose a potentially unseen and significant threat to encryption that may impact Post-Quantum Cryptography (PQC) transition timelines. There is a direct hybrid quantum-classical computing threat on cryptography, and there is also a direct threat AI/ML on cryptography. However, the synergistic combination of these technologies presents known and unknown threats that need attention, focus action, and research. This paper reviews Grover's Adaptive Search (GAS), which combines Grover's Algorithm with adaptive techniques to optimize search further, potentially making it even more efficient for attacking encryption. This work also examines the quantum-accelerated Harrow-Hassidim-Lloyd (HHL) Algorithm, designed to solve systems of linear equations exponentially faster than classical algorithms in certain conditions. The HHL algorithm can solve some lattice-based problems, which have implications for lattice-based encryption. This technological confluence and its potential impact on cryptography and encryption necessitate a proactive and coordinated approach to developing and implementing quantum-resistant AI/ML cryptographic solutions. This paper reviews the technological confluence and its potential implications for classical cryptography and PQC transition timelines and calls for further research.

A novel metal-doped carbon quantum dot, zinc-chlorine co-doped carbon quantum dots (Zn/Cl-CQDs), has been developed for the fluorescent probe detection of vitamin B2 and the analysis of the correlation properties of this carbon quantum dot and vitamin B2. Stability experiments demonstrate that Zn/Cl-CQDs possess good fluorescence properties under alkaline conditions. However, when vitamin B2 is added into Zn/Cl-CQDs, the fluorescence intensity decreases sharply, indicating that a fluorescence quenching phenomenon occurs between vitamin B2 and Zn/Cl-CQDs. Lastly, the use of Zn/Cl-CQDs in the detection of vitamin B2 tablets and vitamin B2-rich fruits resulted in recovery rates of 98.2% and 100.6%, respectively. Therefore, this method can be well applied to the detection and analysis of vitamin B2, and has great development prospects in the pharmaceutical industry and food monitoring fields.

We provide an extensive and systematic investigation of exciton dynamics in droplet epitaxial quantum dots comparing the cases of (311)A, (001) and (111)A surfaces. In spite of a similar s-shell exciton structure common to the three cases, the absence of a wetting layer for (311)A and (111)A samples leads to a larger carrier confinement with respect to (001), where a wetting layer is present. Moreover, this leads to a more pronounced dependence of the binding energies of s-shell excitons on the quantum dot size and to a strong anti-binding character of the positive charged exciton for smaller quantum dots. In-plane geometrical anisotropies of (311)A and (001) quantum dots lead to a large electron-hole fine interaction (fine structure splitting, FSS ~ 100 ueV) whereas for the three-fold symmetric (111)A counterpart this figure of merit is reduced of about one order of magnitude. In all these cases we do not observe any size dependence of the fine interactions. Heavy-hole/light-hole mixing is present in all the studied cases leading to a broad spread of linear polarization anisotropy (from 0 up to about 50%) irrespective of surface orientation (symmetry of the confinement), fine interactions and nanostructure size. These results are important for the further development of ideal single and entangled photon sources based on semiconductor quantum dots.

Silica on Silicon is a major optical integration platform, while the emergent class of integrated Laser written circuits' platform offers additionally high customizability, and flexibility for rapid prototyping. However, the inherent waveguides' low core/cladding refractive index contrast characteristic compared to other photonic platforms in silicon or silicon nitride, sets serious limitations for on-chip efficient coupling with single photon emitters, like semiconductor nanowires with quantum dots limiting the applications in quantum computing. A new light coupling scheme proposed here overcomes this limitation providing means for light coupling >50%. The scheme is based on the incorporation of an optical microsphere between the nanowire and the waveguide, properly optimized and arranged in terms of: size, refractive index, distance of microsphere between nanowire and waveguide. Upon suitable design of the optical arrangement, the photonic nanojet emitted by the illuminated microsphere excites efficiently the guided eigenmodes of the input channel waveguide, thus launching light with high coupling efficiency. The method is tolerant in displacements, misalignments, and imperfections and is fabricationally feasible by current state of the art techniques. The proposed method enables the on-chip multiple single photon emitters' integration thus allowing the development of highly customizable and scalable quantum photonic integrated circuits for quantum computing.

An ethanol vapor sensor based on a microfiber with quantum-dots (QDs) gel coating is proposed and demonstrated. The QDs gel was made from UV glue as the gel matrix and the CdSe/ZnS QDs with a concentration of 1mg/mL. The drawing and coating process were conducted by using a simple and low-cost home-made system. The bending, ethanol sensing, temperature response and time response tests were carried out, alternatively. The experimental results show that the fabricated sensor has a high sensitivity of -3.3%/ppm, a really low temperature cross-sensitivity of 0.17 ppm/℃ and a fast response time of 1.1s. The robust structure with ease of fabrication and excellent sensing performance render it a promising platform for real ethanol sensing application.

Semiconductor nanocrystals or quantum dots (QDs), have unique optical and physical properties that make them potential imaging tools in biological and medical applications. However, concerns such as the aqueous dispersivity, toxicity to cells and stability in biological environments may limit the use of QDs in bioapplications. Here, we report an investigation into the cytotoxicity of aqueously dispersed CdSe(S) and CdSe(S)/ZnO core/shell QDs in the presence of human colorectal carcinoma cells (HCT-116) and a human skin fibroblast cell line (WS-1). The cytotoxicity of the precursor solutions used in the synthesis of the CdSe(S) QDs was also determined in the presence of HCT-116 cells and compared to that of the heat-shock protein (Hsp90) inhibitor, 17-AAG. CdSe(S) QDs were found to have a low toxicity at concentrations up to 100 µg/ml, with a decreased cell viability at higher concentrations, indicating a highly dose-dependent response. Meanwhile, CdSe(S)/ZnO core/shell QDs exhibited lower toxicity than uncoated QDs at higher concentrations. Confocal microscopy images of HCT-116 cells after incubation with CdSe(S) and CdSe(S)/ZnO QDs showed that the cells were stable in aqueous concentrations of 100 µg of QDs per ml, with no sign of cell necrosis, confirming the cytotoxicity data. Key words: HCT-116, WS1, water dispersive QDs, aqueous synthesis, cytotoxicity of QDs.

Fluorescent semiconductor nanocrystals called quantum dots (QDs) have gained attention in biomedical applications, including imaging, molecular tracking, and drug delivery, due to their unique optical properties. However, their use is limited because of safety issues. This study was aimed at assessment the acute toxicity of QDs with different core chemical compositions and surface charges in mice. In addition, the immunotoxicity of CdSe/ZnS QDs was estimated. CdSe/ZnS, PbS/CdS/ZnS, and CuInS2/ZnS QDs were synthesized and modified with PEG derivatives. The hydrodynamic diameters and surface charges of solubilized QDs were characterized. The QD acute toxicity has been shown to depend on both surface charge and core composition. The immunotoxicity of CdSe/ZnS-PEG-OH QDs in mice was assessed after a single intravenous administration of 0.2 LD100 of the QDs. The QDs have been found to increase the spleen weight and cause spleen, thymus, and bone marrow cell depletion. However, these changes are reversible. A transient increase in the levels of proinflammatory cytokines (MCP1 and IL-6) indicates an acute inflammatory response to a single low dose of QDs. Thus, systemic comparative analysis of QD toxicity has shown how the QD core composition and surface properties affect living organisms.

Uniform water soluble MoS2 quantum dots (WS-MSQDs) are synthesized via a sequential combination of sintering/etching/exfoliation method and solvothermal route. The obtained WS-MSQDs with average size of approximately 3.4 nm exhibit sufficient water solubility and remarkable fluorescence properties. The WS-MSQDs have been utilized as a probe for detection of Fe3+ ions with high selectivity and specificity. Furthermore, the WS-MSQDs exhibit high fluorescence stability under different conditions. Finally, the WS-MSQDs are successfully applied for the fluorescence imaging of Fe3+ in living cells, which exhibited practical potential for biomedical applications.

We present here a theory of Majorana excitons, photo-excited conduction electron-valence band hole pairs, interacting with Majorana Fermions in a Kitaev chain of semiconductor quantum dots embedded in a nanowire. Using analytical tools and exact diagonalisation methods we identify the presence of Majorana Zero Modes in the nanowire absorption spectra.

Droplet epitaxy allows the efficient fabrication of a plethora of 3D, III-V-based nanostructures on different crystalline orientations. Quantum dots grown on (311)A-oriented surface are obtained with record surface density, with or without a wetting layer. These are appealing features for quantum-dot lasing, thanks to the large density of quantum emitters and a truly 3D lateral confinement. However, the intimate photophysics of this class of nanostructures has not yet been investigated. Here we address the main optical and electronic properties of s-shell excitons in individual quantum dots grown on (311)A substrates with photoluminescence spectroscopy experiments. We show the presence of neutral exciton and biexciton as well as positive and negative charged excitons. We investigate the origins of spectral broadening, identifying them in spectral diffusion at low temperature and phonon-interaction at higher temperature, the presence of fine interactions between electron and hole spin, and a relevant heavy-hole/light-hole mixing. We interpret the level filling with a simple Poissonian model reproducing the power excitation dependence of the s-shell excitons. These results are relevant for the further improvement of this class of quantum emitters and their exploitation as single photon sources for low density samples as well as for efficient lasers for high density samples.

In this article, we describe an immunochromatographic test system developed for rapid serodiagnostics of cattle brucellosis using two markers: gold nanoparticles (GNPs) and quantum dots (QDs). The test system was compared with immunochromatographic serodiagnostics systems that use only one marker. The approbation of the test system was conducted on samples of cattle sera with low, but diagnostically significant titers of specific antibodies. We show that when two conjugates are used, the intensity of the detectable signal increases by 2–3 times compared with the test system using the QD conjugate and by more than 9 times compared with the system using the GNP conjugate.

Carbon Quantum Dots (CQDs) have emerged as promising nanomaterials for enhancing the performance of supercapacitors, offering unique advantages such as high surface area, excellent electrical conductivity, and tunable surface chemistry. This review provides a comprehensive overview of recent advancements in the synthesis, characterization, and integration of CQDs into supercapacitor devices. Various synthesis methods, including chemical oxidation, hydrothermal/solvothermal methods, microwave-assisted synthesis, and pyrolysis, are discussed, highlighting their impact on the structural and electrochemical properties of CQDs. Characterization techniques such as transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman spectroscopy, and photoluminescence (PL) spectroscopy are elucidated for assessing the morphology, crystallinity, and optical properties of CQDs. The integration of CQDs into supercapacitors, including their utilization in composite electrodes, binder-free electrodes, and doping strategies, is explored to enhance specific capacitance, energy density, power density, and cycle stability of the devices. Challenges and future perspectives in the field are outlined, emphasizing the need for scalable synthesis methods, enhanced electrochemical performance, and sustainable device engineering to realize the full potential of CQD-based supercapacitors for various energy storage applications. This review aims to provide insights into the current state of research and guide future endeavors towards developing high-performance and environmentally sustainable energy storage technologies.

This review study, delves into the groundbreaking potential of quantum dots in revolutionizing the field of stem cell tracking for regenerative medicine. Beginning with an introduction that underscores the pivotal role of stem cell tracking in regenerative medicine, this review introduces quantum dots as promising tools for this purpose. It proceeds to explore the fundamental properties of quantum dots, including the quantum confinement effect, size-dependent emission, and exceptional brightness, which render them ideal candidates for stem cell tracking. The historical evolution and recent advancements of quantum dot technology in biomedicine are discussed, emphasizing their growing importance in terms of biocompatibility and safety. Furthermore, various labeling strategies for stem cells using quantum dots are detailed, encompassing surface modification and internalization techniques, with a comparison of their respective advantages and drawbacks. A comprehensive exploration of the wide range of imaging modalities that synergize with quantum dots for stem cell tracking is presented, accompanied by an evaluation of their strengths and limitations. Real-world applications of quantum dot-based stem cell tracking in regenerative medicine, spanning tissue regeneration to disease modeling, are showcased, with illuminating case studies. Current challenges and limitations in quantum dot-based stem cell tracking, including long-term stability and regulatory considerations, are addressed, and innovative directions and emerging trends in quantum dot technology are proposed. Safety considerations and strategies to enhance quantum dot biocompatibility within biological systems are discussed, while ethical and regulatory implications related to their use in stem cell tracking are explored, promoting responsible research and development practices. Finally, the review concludes by summarizing key insights and takeaways, reaffirming the transformative potential of quantum dots in advancing stem cell tracking and the field of regenerative medicine.

In recent years, genetic research has been developing rapidly and taking on a larger role in research and medicine. The synthesis of any particle that can be used in this research can pave the way for new developments in this field. This research aims to develop a chemical method to produce nitrogen-doped carbon quantum dots - economical and bio-sourced substances that bind to genomic DNA. Carbon quantum dots are produced by the green synthesis hydrothermal method from radish, which is abundant in nature, and economically affordable. Nitrogen is added to increase the fluorescence properties of the produced carbon quantum dots and to improve their binding to DNA. The synthesized nitrogen-doped carbon quantum dots (N-CQDs) were tested through chromosome imaging subsequently. It was shown that N-CQDs can bind to the chromosomes, and N-CQDs reflected green light better than DAPI under the FITC filter, a potential advantage of using N-CQDs over DAPI in chromosome imaging.

Cs2NaInCl6 double perovskites, which have excellent photoelectric conversion properties and are non-toxic and lead-free, have recently attracted much attention. In particular, double perovskite quantum dots (QDs) are considered to be a promising material for optoelectronic device applications. Ligands such as oleic acid (OA) and oleylamine (OAm) are essential for the synthesis of perovskite QDs, but their roles on double perovskite QDs are not yet clear. In this study, we have investigated the binding of OA and OAm to Cs2NaInCl6 QDs through FTIR and NMR and their effects on the surface defect reduction and stability improvement for Cs2NaInCl6 QDs. We found that only OAm was bound to the QD surfaces while OA was not. The OAm has a great effect on photoluminescence quantum yield (PLQY) improvement by passivate the QD surface defects. The stability of the QDs was also investigated, and it was shown that OA played a significant role in the stability of the QDs. Our findings provide critical insights into the roles of the ligands for photophysical properties and stability of lead-free double perovskite QDs.

porous silicon-based photodetectors have attracted more researches due to their high luminous efficiency, good stability and low cost. In this paper, a PbS quantum dots/porous silicon hybrid structure has been fabricated. The PbS quantum dots (QDs) partly infiltrated into the porous silicon (PSi) layer and partly deposited on its surface, which could increase the absorption of near-infrared wavelength range and extend the light absorption in silicon for wavelengths longer than 1100 nm. After that, A metal-semiconductor-metal (MSM) device is fabricated and its response spectrum could extend to the 1200 nm at -3 V. As a silicon-based photodetector (PD), one can envision its role for operation from visible light to short-wavelength infrared range.

We study Einstein's gravity coupled to nonlinear electrodynamics with two parameters in Anti-de Sitter spacetime. Magnetically charged black holes in an extended phase space is investigated. We obtain the mass and metric functions, their asymptotic and corrections to the Reissner--Nordstr\"{o}m metric function when the cosmological constant vanishes. The first law of black hole thermodynamics in extended phase space is formulated and the magnetic potential and the thermodynamic conjugate to the coupling are obtained. We proved the generalized Smarr relation. The heat capacity and the Gibbs free energy are computed and phase transitions are studied. It was shown that the electric field of charged objects at the origin and electrostatic self-energy are finite within the nonlinear electrodynamics proposed.

In this study, two heterogeneous fluorescence immunoassays using CdSe/ZnS quantum dot (QD) to label anti-progesterone antibody (P4Ab) for the determination of progesterone (P4) were performed in the wells of a 96-well microtiter plate. First, P4Ab was conjugated to hydrophilic CdSe/ZnS QDs via ethyl-3-(dimethylaminopropyl) carbodiimide(EDC)-N-hydroxysuccinimide) chemistry(NHS) (QDs-P4Ab conjugates). The QDs-P4Ab conjugate was employed as a second antibody in a sandwich assay, where the P4Ab was immobilized onto the 3-aminopropyltrimethoxysilane (APTMS) sol-gel membrane of the wells of a 96-well microtiter plate, and P4 was bound between the immobilized P4Ab and the QDs-P4Ab conjugate. In this assay, the fluorescence intensity of the QDs increased with increasing P4 concentrations. This assay had a detection limit of 553.9 pg/ml and a sensitivity of 18,251.96 pg/ml with a linear range of 2,184.6 – 117,082 pg/ml. In the direct binding assay, P4 was directly bound to the QDs-P4Ab conjugates immobilized onto the APTMS sol-gel membrane of the wells of a 96-well microtiter plate. In this direct binding assay the fluorescence intensity of the QDs decreased with increasing P4 concentrations, and this assay had a linear range of 28.95 – 26,607.7 pg/ml with a detection limit of 3.32 pg/ml and a sensitivity of 987.24 pg/ml. These fluorescence immunoassays have been successfully applied for the determination of P4 in real human serum, and the results were well correlated with those of a certified radioimmunoassay (RIA) method.

Quantum computing is tipped to lead the future of global technological progress. However, the obstacles related to quantum software development are an actual challenge to overcome. In this scenario, this work presents an implementation of the quantum search algorithm in Atos Quantum Assembly Language (AQASM) using the quantum software stack my Quantum Learning Machine (myQLM). We present the creation of a virtual quantum processor whose configurable architecture allows the analysis of induced quantum noise effects on the quantum algorithms. The codes are available throughout the manuscript so that readers can replicate them and apply the methods discussed in this article to solve their own quantum computing projects. The presented results are consistent with theoretical predictions and demonstrate that AQASM and myQLM are powerful tools for building, implementing, and simulating quantum hardware.

In this paper, we introduce a novel controlled quantum communication protocol utilizing a quantum random walk involving one sender, one receiver, and multiple controllers. Inspired by classical random walk theory, quantum random walk serves as the foundation of our proposed protocol. With this protocol, we demonstrate the ability to transfer any n- dimensional quantum state to any party facilitated by any m number of controllers. Furthermore, any of the (m+1) individuals has the freedom to accept the role of the receiver. Rigorous testing of the protocol’s performance is conducted through quantum state tomography. We have run different variations of the circuits in IBMQ QASM simulator. Additionally, we explore the effectiveness of a weak measurement-based protocol designed to mitigate amplitude-damping noise’s detrimental effects on quantum states. By analyzing fidelity versus amplitude damping noise-strength plots for scenarios with and without the weak measurement protocol, we provide valuable insights into its protective capabilities across various levels of noise. These find- ings illuminate the protocol’s potential applications in quantum information processing

We report on the application of time-resolved inline digital holography to study the nonlinear optical properties of quantum dots deposited onto the sample glass. Fresnel diffraction patterns of the probe pulse due to noncollinear degenerate phase modulation induced by the femtosecond pump pulse were extracted from the set of inline digital holograms and analyzed. Absolute values of the nonlinear refractive index of both sample glass substrate and the deposited layer of quantum dots were evaluated using the proposed technique. To characterize the inhomogeneous distribution of samples’ nonlinear optical properties we proposed to plot an optical nonlinearity map calculated as a local standard deviation of diffraction patterns intensity induced by noncollinear degenerate phase modulation.

Surface Plasmon Resonance (SPR) is an attracting property of certain transition metals when they are synthesized in nano-range giving rise to promising optical applications. However, most SPR and associated applications are limited to the noble metal nanoparticles, which limits their potential due to high production cost. We report surface plasmon resonance in copper-copper oxide core-shell quantum dots synthesized via chemical route studied by using UV-Visible spectrophotometry. Tuning of the plasmonic resonance with respect to the particle diameter is achieved by an inexpensive all chemical route. Photoluminescence measurements also support the data. This size reduction leads to remarkable changes in its optical response as compared to the bulk metal. The results point towards applications of these materials in tunable SPR based biosensors.

Oxygen evolution reaction is a momentous part of electrochemical energy storage and conversion devices such as rechargeable metal-air batteries. It is particularly urgent to develop low-cost and efficient electrocatalysts for oxygen evolution reactions. As a potential substitute for noble metal electrocatalysts, transition metal selenides are still challenging in improving the activity of oxygen evolution reaction and the research of reaction intermediates. In this study, a simple one-step solvothermal method was used to prepare a polymetallic compound carbon matrix composite (Co9Se8/Ni3Se4/Fe3O4@C) with a multilayered nanosheets structure. It exhibited good OER activity in an alkaline electrolyte solution with an overpotential of 268 mV at 10 mA/cm2 in an alkaline medium. Besides, this catalyst also showed excellent performance in the 24 hours stability test. The composite presents a multi-layer sheet structure, which effectively improves the contact between the active site and the electrolyte. The selenide formed by Ni and Co has a synergistic effect, Fe3O4 and Co9Se8 form a heterojunction structure, which can effectively improve the reaction activity by initiating the electronic coupling effect through the interface modification. In addition, carbon quantum dots have rich heteroatoms and electron transferability, which improves the electrochemical properties of the composites. This work provides a new strategy for the preparation of highly efficient OER electrocatalysts utilizing the multimetal synergistic effect.

Graphene was synthesized through a two-step pyrolysis method using waste candlenut (Aleurites moluccanus) shells as the precursor. Cerium (Ce)/graphene composites were prepared via an impregnation technique. The resulting graphene and Ce/graphene were characterized using various analytical methods, including Scanning Electron Microscopy with Energy-Dispersive Spectroscopy (SEM-EDS), X-ray Diffraction (XRD), X-ray Photoelectron Spectroscopy (XPS), Transmission Electron Microscopy (TEM), Thermo Gravimetric Analysis (TGA), Fourier Transform Infrared (FTIR) spectroscopy, Cyclic Voltammetry (CV), and Linear Sweep Voltammetry (LSV). The bio-carbon produced predominantly exhibited a graphene structure with flat carbon morphology and an interlayer distance of 0.33 nm. This structural information is supported by XRD data, which shows a broad and weak peak at 2θ = 26° corresponding to the C (002) plane, indicative of graphene presence. FTIR, XPS, and Raman spectroscopy further confirmed the presence of graphene through the detection of Csp2 aromatic bonds and the characteristic D, G, and 2D peaks. Notably, the performance of cerium can be enhanced by the incorporation of graphene, attributed to the large surface area and chemical interactions between Ce and graphene. Consequently, candlenut-derived graphene shows potential as a supportive material for modifying the properties of cerium, thereby opening avenues for various advanced applications, such as sustainable and high-performance energy storage systems.

Ice accumulation poses considerable challenges in transportation, notably in the domain of general aviation. The present study combines the strengths and limitations of conventional aircraft de-icing techniques with the emerging trend toward all-electric aircraft. The study aims to utilize laser-induced graphene (LIG) technology to create a multifunctional surface, seamlessly integrating hydrophobic properties with efficient electrical heating to mitigate surface icing effectively. We investigated the utilization of a 10.6 μm CO2 laser for direct writing on polyimide (PI), a widely-used insulating encapsulation material. From the thermomechanical perspective, our initial analysis using COMSOL Multiphysics software revealed that when the laser power P exceeds 5 W, the PI substrate experience ablative damage. The experimental results show that when P ≤ 5W, an increase in power has a positive impact on the quality, surface porosity, roughness reduction, line-spacing reduction, and water contact-angle enhancement of the graphene. Conversely, when P > 5 W, higher power negatively affects both the substrate and the graphene structure by inducing excessive ablation. However, it influences the graphene line height positively and is consistent with overall experimental-simulation congruence. Furthermore, the incorporation of high-quality graphene resulted in a surface that exhibited higher contact angles (CA > 120°), lower energy consumption, and higher heating efficiency compared to the use of traditional electrically heated materials for anti-icing applications. The potential applications of this one-step fabrication method extend across various industries, particularly aviation, marine engineering, and other ice-prone domains. Moreover, the method has extensive prospects for addressing pivotal challenges associated with ice formation and serves an innovative and efficient anti-icing technology.

The electronic structure of 7/9-AGNR superlattices with up to eight unit cells has been studied by means of state of the art Density Functional Theory (DFT) and also by two model Hamiltonians, the first one including only local interactions (Hubbard model, Hu) while the second one is extended to allow long-range Coulomb interactions (Pariser, Parr and Pople model, PPP). Both are solved within mean field approximation. At this approximation level, our calculations show that 7/9 interfaces are better described by spin non-polarized solutions than by spin-polarized wavefunctions. Consequently, both Hu and PPP Hamiltonians lead to electronic structures characterized by a gap at the Fermi level that diminishes as the size of the system increases. DFT results show similar trends although a detailed analysis of the density of states around the Fermi level shows quantitative differences with both Hu and PPP models. Before improving model Hamiltonians, we interpret the electronic structure obtained by DFT in terms of bands of topological states: topological states localized at the system edges and extended bulk topological states which interact between them due to the long-range Coulomb terms of Hamiltonian. After careful analysis of the interaction among topological sates, we find that the discrepancy between ab initio and model Hamiltonians can be resolved considering a screened long-range interaction that is implemented adding an exponential cutoff to the interaction term of PPP model. In this way, an adjusted cutoff distance λ = 2 allows a good recovery of DFT results. In view of this, we conclude that the correct description of the density of states around the Fermi level (Dirac point) needs the inclusion of long-range interactions well beyond Hubbard model but not completely unscreened as is the case for the PPP model.

Polystyrene as a thin film on arbitrary substrates or pellets form defective graphene films or powders that can be dispersed in water and organic solvents. The materials were characterized by visible absorption, Raman and X-ray photoelectron spectroscopy, electron and atomic force microscopy and electrochemistry. Raman spectra of these materials show the presence of the expected 2D, G and D peaks at 2750, 1590 and 1350 cm^-1, respectively. The relative intensity of the G vs. the D peak is taken as a quantitative indicator of the density of defects in the G layer.

Context: Mental and menstrual health, two emerging aspects of health critical to the female population, are bidirectionally linked. But there is limited empirical evidence that establishes the association between these entities. This essay aims to draw the attention of researchers to this healthcare niche. Evidence Acquisition: A systematic review was carried out on literatures sourced from medical databases (e.g. PubMed, Google Scholar, Scopus, Science Direct, and Web of Science), and gray sources—popular and reputable institutional and journalistic websites that publishes mental or menstrual health research. The key words used for the search are “Menstruation, menstrual hygiene, menstrual disorders, premenstrual syndrome, period poverty, menarche, menopause, mental health, mental disorder, mental illness, depression, anxiety, phobia, mania, mood, and affect”. The initial search generated 368 results. But after the duplicates were removed, the exclusion criteria (publication before 2000) was applied, and manual review of abstract (for relevance) was done, 21 publications from the databases and 5 from gray sources were included in this essay. Results: Associations were found between menstrual cycle irregularities and disorders; and mental disorders such as premenstrual syndrome, premenstrual dysphoric disorder, major depressive disorder, major anxiety disorder, psychotic disorder, bipolar disorder, borderline personality disorder, sleep disorder, substance use/abuse, and suicidal ideation and attempts.Few positive associations between mental and menstrual health were recorded, and several research and treatment gaps were identified. Conclusion: Research into the links between mental and menstrual health should not remain a fringe area of scientific curiosity, as it shows tremendous promise in improving healthcare offered to women/girls globally.

Quantum computing (QC) has opened the door to advancements in machine learning (ML) tasks that are currently implemented in the classical domain. Convolutional neural networks (CNNs) are classical ML architectures that exploit data locality and possess a simpler structure than fully-connected multi-layer perceptrons (MLPs) without compromising the accuracy of classification. However, the concept of preserving data locality is usually overlooked in the existing quantum counterparts of CNNs, particularly for extracting multi-features in multidimensional data. In this paper, we present a multidimensional quantum convolutional classifier (MQCC) that performs multidimensional and multi-feature quantum convolution with average and Euclidean pooling and thus adapting the CNN structure to a variational quantum algorithm (VQA). Average pooling is based on the quantum Haar transform (QHT) and Euclidean pooling is based on partial quantum measurement. The experimental work was conducted using multidimensional data to validate the correctness and demonstrate the scalability of the proposed method utilizing both noisy and noise-free quantum simulations. We evaluated the MQCC model with reference to reported work on state-of-the-art quantum simulators from IBM Quantum and Xanadu using a variety of standard ML datasets. The experimental results showed favorable characteristics of our proposed techniques compared to existing work with respect to a number of quantitative metrics such as the number of training parameters, cross-entropy loss, classification accuracy, circuit depth, and quantum gate count.

Graphene hybrid-filler polymer composites have emerged as prominent materials that revolutionize heavy industries. This study encapsulates the in-depth analysis of different influential factors such as filler/graphene type, aspect ratios, dispersion methods, filler-matrix compatibility, fiber orientation, synergistic effects, different processing techniques, and post-curing conditions that affect the processing, properties and determine the resultant applications of graphene hybrid polymer composites. Additionally, it discusses the substantial role of graphene collaboration with other fillers such as carbon nanotubes, silica, nano-clays and metal oxides to produce functionalized hybrid polymer composites with synergistically enhanced tailored properties to offer solutions for heavy industries like aerospace, automotive, electronics, and energy harvesting. The review concludes with some suggestions and outlook on the future of these composite materials by emphasizing the need for continued research to fully optimize their potential.

Quantum correlations, especially time correlations, are crucial in ghost imaging in order to significantly reduce the background noise on the one hand while increasing the imaging resolution. Moreover, the time correlations serve as a critical reference, distinguishing between signal and noise, which in turn enable clear visualization of biological samples. Quantum imaging also addresses the challenge involved in imaging delicate biological structures with minimal photon exposure and sample damage. Here we explore the recent progress in quantum correlation-based imaging, notably its impact on secure imaging and remote sensing protocols as well as on biological imaging. We also exploit the quantum characteristics of heralded single-photon sources (HSPS) combined with decoy-state methods for secure imaging. This method uses Quantum Key Distribution (QKD) principles to reduce measurement uncertainties and protect data integrity. It is highly effective in low-photon-number regimes for producing high-quality, noise-reduced images. The versatility of decoy-state methods with WCSs (WCS) is also discussed, highlighting their suitability for scenarios requiring higher photon numbers. We emphasize the dual advantages of these techniques: improving image quality through noise reduction and enhancing data security with quantum encryption, suggesting significant potential for quantum imaging in various applications, from delicate biological imaging to secure quantum communication.

A key component of nanomaterials, carbon dots (CDs) are zero-dimensional solids, smaller than 10 nm in size that include carbon as their backbone structure. Herbal medicine carbon dots (HM-CDs) are nanoparticles developed from medicinal plants. Owing to their advantageous properties, they are extensively employed in biological domains such as drug administration, bio-imaging, biosensors, and DNA interactions. It's interesting to note that, carbon dots pro-duced from herbal medicines as a raw material have surfaced as the most recent addition to the CD family. This article provides an overview of the several sources of green precursor, preparation tech-niques, characterization, and applications of CDs. It reviews recent advancements in synthe-sizing CDs made from green carbon materials and their potential uses as bioimaging, catalysts and sensing. Furthermore, several difficult issues and future directions for this potent and amazing content are also covered.

We study the electron tunneling (ET) and local Andreev reflection (AR) processes in a quantum dot (QD) coupled to the left and right ferromagnetic leads with noncollinear ferromagnetisms. In particular, we consider that the QD is also side-coupled to a nanowire hosting Majorana bound states (MBSs) at its ends. Our results show that when one mode of the MBSs is coupled simultaneously to both spin-up and spin-down electrons on the QD, the height of the central peak is quite different from that if the MBS is coupled to only one spin component electrons. The ET and AR conductances which are mediated by the dot-MBS hybridization strongly depend on the angle between the left and right magnetic moments in the leads, which result in sign change of the angle-dependent tunnel magnetic resistance. This result is very different from case when the QD is coupled to regular fermonic mode, and can be used for detecting the existence of MBSs, a current challenge in condensed matter physics under extensive investigations.

In this study, based on a new quantum integral identity, the authors establish some quantum estimates of Hermite-Hadamard type inequalities for convex functions. These results generalize and improve some known results given in literatures.

The goal of this paper is to fabricate innovative diaphragm headphones using graphene oxide paper (GOP) and GOP/epoxy nanocomposites (GOPC). Initially, graphene oxide suspension is fabricated, and the vacuum filtration method is adopted to make GOP. Then vacuum bag molding is used to fabricate GOPC from GOP. Hot pressing and associated molds are adopted to fabricate line-indented (GOPC-L) or curve-indented patterns (GOPC-C) on the GOPC. The performance of one kind of GOP and three kinds of GOPC diaphragm headphones is analyzed based on their sound pressure level (SPL) curves achieved by the Soundcheck measurement system. There are four important processing parameters that will influence the performance of the diaphragm, including material type GOP versus GOPC, indented pattern type, sonication time on suspension, and graphene weight fraction in suspension. Compliances of various diaphragms are measured by the Klippel LPM laser measurement system. The results indicate that effects of sonication time and graphene weight fraction on SPL of GOP and GOPC headphones are in reverse, and this is associated with their difference on compliance (modulus), mass, damping ratio, and microstructure uniformity. Either GOPC-L or GOPC-C seems to improve the microstructure of the GOPC, and leads to better SPL performance. The correlation between the previous four factors and SPLs of four kinds of diaphragm headphones is proposed by using scanning electron microscope (SEM) to examine the microstructure of these diaphragms.

Background: Parkinson's disease (PD) is a global disease. However, there is a lack of research specifically focused on the AfrAbia population. Climate change, driven mainly by global warming, is linked to detrimental health impacts, including an increased frequency and intensity of heat waves. Neurological diseases, including neurodegenerative syndromes like Alzheimer's disease, Parkinson's disease, and motor neuron illnesses, have been increasingly seen and recorded in scientific literature. Although there is much literature demonstrating the growth in neurodegenerative disorders, the relationship between environmental variables such as global warming, air pollution, heavy metals, and pesticides and the higher occurrence of these illnesses is still unknown. Objective: The current article primarily aims to examine the relationship between climatic changes, air pollution, pesticides, heavy metals, and the occurrence of PD. Initially, we evaluate the influence of exposure to these variables on the cause or origin of Parkinson's disease. In addition, we will investigate how these variables disrupt processes such as excitotoxicity, oxidative stress, and neuroinflammation, all of which are strongly linked to Parkinson's disease (PD). Conclusions: This research presents a plausible rationale for the adverse effects of environmental influences on the brain, which are pivotal in the progression or onset of Parkinson's disease from an AfrAbian standpoint.

Imperfection sensitivity of large amplitude vibration of curved single-walled carbon nanotubes (SWCNTs) is considered in this study. The SWCNT is modeled as a Timoshenko nano-beam and its curved shape is included as an initial geometric imperfection term in the displacement field. Geometric nonlinearities of von Kármán type and nonlocal elasticity theory of Eringen are employed to derive governing equations of motion of nano-beam. Spatial discretization of governing equations and associated boundary conditions is performed using differential quadrature (DQ) method and the corresponding nonlinear eigenvalue problem is iteratively solved. Effects of value and location of the geometric imperfection, and the nonlocal small-scale parameter on the nonlinear frequency ratio and imperfection sensitivity of a curved SWCNT for various boundary conditions are investigated. The results show that the geometric imperfection plays a significant role in the nonlinear vibration characteristics of curved SWCNTs.

We introduce optically clear and resilient free-form micro-optical of pure (non-photosensitized) organic-inorganic SZ2080 material made by femtosecond 3D laser lithography (3DLL). This is advantageous for rapid printing of 3D micro-/nanooptics, including their integration directly onto optical fibers. A systematic study on the fabrication peculiarities and quality of resultant structures is performed. Comparison of microlenses’ resiliency to CW and femtosecond pulsed exposure is determined. Experimental results prove that pure SZ2080 is ∼3 fold more resistant to high irradiance as compared with a standard photo-sensitized material and can sustain up to 1.91 GW/cm² intensity. 3DLL is a promising manufacturing approach for high-intensity micro-optics for emerging fields in astro-photonics and atto-second pulse generation. Additionally, pyrolysis is employed to shrink structures up to 40% by removing organic SZ2080 constituents. This opens a promising route towards downscaling photonic lattices and creation of mechanically robust glass-ceramic structures.

The influence of short term water absorption on the mechanical properties of halloysite nanotubes-multi layer graphene reinforced polyester hybrid nanocomposites has been investigated. The addition of nano-fillers significantly increased the flexural strength; tensile strength and impact strength in dry and wet conditions. After short term water exposure; the maximum microhardness; tensile; flexural and impact toughness values were observed at 0.1 wt% MLG. The microhardness increased up to 50.3%; tensile strength increased up to 40% and flexural strength increased up to 44%. Compared to dry samples; the fracture toughness and surface roughness of all types of produced nanocomposites were increased that may be attributed to plasticization effect. Scanning electron microscopy revealed that the main failure mechanism is caused by the weakening of nano-filler-matrix interface induced by water absorption. It was further observed that synergistic effects were not effective at concentration of 0.1 wt% to produce considerable improvement in mechanical properties of produced hybrid nanocomposites.

Alcoholic liver disease (ALD) develops when the immunotolerant environment of the liver is compromised due to excessive alcohol consumption. ALD progression involves variations in the expression of multiple genes, resulting in liver inflammation and the development of a leaky gut. Molecular mechanism involved for ALD progression is still unclear, and due to that there are currently no FDA-approved drugs available for its treatment. In this study, the protective effects of Graphene oxide nanoparticles (GO) was investigated against ethanol-induced damage in the gut-liver axis in in vitro. GO was synthesized using a modified Hummer's method and characterization was done. Given the general concerns regarding nanoparticle toxicity, assessment of cell viability, lipid accumulation, DNA damage, cell death, and the generation of reactive oxygen species (ROS) were conducted using various techniques. Furthermore, gene expression of pro- and anti-inflammatory cytokines was done using RT-qPCR. The findings revealed that GOs promoted cell viability even against ethanol treatment. Additionally, lipid accumulation significantly decreased when cells were treated with GO alongside ethanol compared to ethanol treatment alone, with similar trends observed for other assays. Gene expression analysis indicated that GO treatment reduced the expression of proinflammatory cytokines while enhancing the expression of antioxidant genes. Moreover, GO treatment led to improvements in gut permeability and a reduction in proinflammatory cytokines in colon cells damaged by ethanol. These findings suggest that GO holds promise as a drug carrier, exhibiting no observed toxic effects. By shedding light on the protective effects of GO against ethanol-induced damage, this study contributes to the burgeoning field of nanoparticle-mediated therapy for ALD.

Quantum-dot cellular automata (QCA) is an emerging transistor-less field-coupled nanocomputing (FCN) approach to ultra-scale ‘nanochip’ integration. In QCA, to represent digital circuitry, electrostatic repulsion between electrons and the mechanism of electron tunnelling in quantum dots are used. QCA technology can surpass conventional complementary metal-oxide semiconductor (CMOS) technology in terms of clock speed, reduced occupied chip area, and energy efficiency. To develop QCA circuits, irreversible majority gates are typically used as the primary components. Recently, some studies have introduced reversible design techniques, using reversible majority gates as the main building block, to develop ultra-energy efficient QCA circuits. However, this approach resulted in time delays, an increase in the number of QCA cells used, and an increase in the chip area occupied. This work introduces a novel hybrid design strategy employing QCA irreversible, reversible, and partially reversible gates to establish an optimal balance between power consumption, delay time, and occupied area. The hybrid technique allows the designer to have more control over the circuit characteristics to meet different system needs. A combination of reversible, irreversible, and innovative partially reversible majority gates is used in the proposed hybrid design method. We have evaluated the hybrid design method by examining the half-adder circuit as a case study. We have developed four hybrid QCA half-adder circuits, each of which simultaneously incorporates various types of majority gates. The QCADesigner-E 2.2 simulation tool was used to simulate the performance and energy efficiency of the half-adders. This tool provides numerical results for the circuit input/output response and heat dissipation at the physical level, within a microscopic quantum mechanical model.

RNA transcripts play a crucial role as witnesses of gene expression health. Identifying disruptive short sequences in RNA transcription and regulation is essential for potentially treating diseases. Let’s delve into the mathematical intricacies of these sequences. We’ve previously devised a mathematical approach for defining a “healthy” sequence (10.14218/GE.2023.00079). This sequence is characterized by having at most four distinct nucleotides (denoted as nt≤4). It serves as the generator of a group denoted as fp. The desired properties of this sequence are as follows: fp should be close to a free group of rank nt−1, it must be aperiodic, fp should not have isolated singularities within its SL2(C) character variety (specifically within the corresponding Groebner basis). Now, let’s explore the concept of singularities. There are cubic surfaces associated with the character variety of a four-punctured sphere denoted as S24. When we encounter these singularities, we find ourselves dealing with some algebraic solutions of a dynamical second-order differential (and transcendental) equation known as the Painlevé VI equation (10.3390/dynamics4010001). In certain cases, S24 degenerates, in the sense that two punctures collapse, resulting in a “wild” dynamics governed by the Painlevé equations of an index lower than VI. In our paper, we provide examples of these fascinating mathematical structures within the context of miRNAs. Specifically, we find a clear relationship between decorated character varieties of Painlevé equations and the character variety calculated from the seed of oncomirs. These findings should find applications in cancer research.

As the world grapples with a pandemic with various and expanding epicenters, a flurry of medical and scientific activity has gained speed and momentum in a race to halt COVID-19. A controversial topic has been the connection between COVID-19 and the Renin-Angiotensin system (RAS). COVID-19, like Sars before it, enters by way of the Angiotensin Converting Enzyme 2 (ACE2). ACE2 is ubiquitously expressed in many tissues in the body serving as the doorway by which the virus can enter and spread causing inflammatory havoc. Demographic evidence coming out of China and other locations make it clear that the elderly and those suffering cardiovascular complications such as hypertension etc are most at risk. The connection to RAS and the demographic nature of the data coming out has led many to advance hypothesis, recommendations and even therapies based on existing RAS inhibitors and other components of the renin-Angiotensin system. It is pertinent to review the literature in the context of our understanding of the renin-angiotesnin system to allow better judgements to be made as well as lines of research initiated advancing a quick resolution to COVID-19. Covid-19 appears invincible as if dipped in the river Styx, but even Achilles had a vulnerable heel. Understanding the homeostatic balance that the coronavirus disrupts, we can discover the arrow in corona’s heel.

We present a simple strategy to generate a family of carbon dot/iron oxide nanoparticles (C/Fe-NPs) that relies on the thermal decomposition of iron (III) acetylacetonate in the presence of a highly fluorescent carbon-rich precursor, while polyethylene glycol serves as the passivation agent. By varying the molar ratio of the reactants, a series of C/Fe-NPs have been synthesized with tuneable elemental composition in terms of C, H, O, N, Fe. The quantum yield is enhanced from 6% to 9% as the carbon content increases from 27% to 36%, while the room temperature saturation magnetization is improved from 4.1 emu/g to 17.7 emu/g as the iron content is enriched from 17 to 31%. In addition, the C/Fe-NPs show excellent antimicrobial properties, minimal cytotoxicity and demonstrate promising bioimaging capabilities, thus showing great potential for the development of advanced diagnostic tools.

A hybrid material, consisting of commercially available nitrocellulose (NC) membrane non-covalently modified with amino-polyethylene glycol functionalized reduced graphene oxide (NH2-PEG-rGO) nanoparticles, was successfully synthesized for oligonucleotide extraction. Fourier Transform Infrared Spectroscopy (FTIR) confirmed the modification of the NC membrane, revealing characteristic peaks of both compounds NC and NH2-PEG-rGO. Scanning Electron Microscopy (SEM) exhibited morphological changes in the NC/NH2-PEG-rGO hybrid membrane, marked by the introduction of NH2-PEG-rGO particles, resulting in a distinctly smothered surface compared to the porous surface of the NC control membrane. Wettability assays revealed hydrophobic behavior for the NC/NH2-PEG-rGO hybrid membrane, with a water contact angle exceeding 90°, contrasting with the hydrophilic behavior characterized by a 16.7° contact angle in the NC membrane. The performance of the NC/NH2-PEG-rGO hybrid membrane was evaluated for the extraction of ssDNA with fewer than 50 nucleotides from solutions containing various ionic species (MnCl2, MgCl2, and MnCl2/MgCl2). The NC/NH2-PEG-rGO hybrid membrane exhibited optimal performance when incubated in MgCl2, presenting the highest fluorescence emission at 525 relative fluorescence units (r.f.u.). This corresponds to the extraction of approximately 610 pg (≈13%) of the total oligo-DNA, underscoring the efficacy of the pristine material, which extracts 286 pg (≈6%) of oligo-DNA in complex solutions.

In the current era of emerging technologies and cutting-edge inventions, it is equally important to consider the ethical aspects of research and innovations to have an ethical space for the sustainable progress and safety of humanity. The field of nanotechnology research and innovation often faces criticism due to its potential adverse impacts on health, the environment, limited accessibility, high costs, and concerns about data privacy. Therefore, it is crucial to address and resolve these ethical issues systematically. In this regard, we present our findings and methods for exploring the application of the ethics technology assessment method by considering its relevance at different stages of innovation development. Specifically, the present work provides a conceptual framework for ethics technology assessment focused on evaluating a significant innovation in nanotechnology within the domain of food safety with specific reference to mycotoxin remediation. By leveraging the value-sensitive design approach, we described various strategies for analyzing the ethical implications of nanotechnology-based innovations in mycotoxin remediation. Through comprehensive ethics technology assessment, nanotechnology-based innovations can be guided toward becoming more value-oriented, thereby making substantial contributions to social progress.

The question of what generates conscious experience has mesmerized thinkers since the dawn of humanity, yet its origins remain a mystery. The topic of consciousness has gained traction in recent years, thanks to the development of large language models that now arguably pass the Turing test, an operational test for intelligence. However, intelligence and consciousness are not related in obvious ways, as anyone who suffers from a bad toothache can attest - pain generates intense feelings and absorbs all our conscious awareness yet nothing particularly intelligent is going on. Still, in the hard sciences, this topic is frequently met with skepticism because to date no protocol to measure the content or intensity of conscious experiences in an observer-independent manner has been agreed upon. Here we present a novel proposal: Conscious experience arises whenever a quantum mechanical superposition forms. Our proposal has several implications: First, it suggests that the structure of the superposition determines the qualia of the experience. Second, quantum entanglement naturally solves the binding problem, ensuring the unity of phenomenal experience. Finally, a moment of agency may coincide with the formation of a superposition state. We outline a research program to experimentally test our conjecture via a sequence of quantum biology experiments. Applying these ideas opens up the possibility of expanding human experience through brain-quantum computer interfaces.

Quantum nonlocality represents correlation properties between subsystems of a composite quantum system, usually including the four types: Bell nonlocality, steerability, entanglement, and quantum correlation (quantum discord). Given a basis $e_{AB}=\{|e_{ij}\>\}_{i\in[d_A],j\in[d_B]}$ for the Hilbert space $\H_A\otimes \H_B$ of a bipartite system $AB$, a density operator $\rho^{AB}$ (quantum state) of $AB$ can be represented as a $d_Ad_B\times d_Ad_B$ matrix $\hat{\rho}_{e_{AB}}=[\]$, called the density matrix of a density operator $\rho^{AB}$. A natural question is what is the relationship between the quantum nonlocality of a density operator $\rho^{AB}$ and its corresponding density matrix $\hat{\rho}_{e_{AB}}$? In this work, we discuss the relationships between quantum locality and basis, and prove that one type of quantum locality of density operators and that of their density matrices under a basis are the same if and only if the chosen basis is the tensor product of the bases of subsystems. Consequently, different bases define different quantum nonlocality density operators.

In recent years, advancements in brain science and neuroscience have significantly influenced the field of computer science, particularly in the domain of reinforcement learning (RL). Drawing insights from neurobiology and neuropsychology, researchers have leveraged these findings to develop novel mechanisms for understanding intelligent decision-making processes in the brain. Concurrently, the emergence of quantum computing has opened new frontiers in artificial intelligence, leading to the development of quantum machine learning (QML). This study introduces a novel model that integrates Quantum Spiking Neural Networks (QSNN) and Quantum Long Short-Term Memory (QLSTM) architectures, inspired by the complex workings of the human brain. Specifically designed for reinforcement learning tasks in energy-efficient environments, our approach progresses through two distinct stages mirroring sensory and memory systems. In the initial stage, analogous to the brain’s hypothalamus, low-level information is extracted to emulate sensory data processing patterns. Subsequently, resembling the hippocampus, this information is processed at a higher level, capturing and memorizing correlated patterns. We conduct a comparative analysis of our model against existing quantum models such as Quantum Neural Networks and their classical counterparts, elucidating its unique contributions. Through empirical results, we aim to underscore the effectiveness of our approach in optimizing energy consumption in practical scenarios.

This investigation explores the potential of enhancing aqueous zinc-ion batteries (AZIBs) through the introduction of a novel cathode material, NH4V4O10 (NVO), combined with reduced graphene oxide (rGO). Utilizing Density Functional Theory (DFT), it was hypothesized that the incorpora-tion of rGO would increase the interlayer spacing of NVO and diminish the charge transfer in-teractions, thus promoting enhanced diffusion of Zn2+ ions. These theoretical predictions were substantiated by experimental data acquired from hydrothermal synthesis, which indicated a marked increase in interlayer spacing. Significantly, the NVO-rGO composite exhibits remarkable cyclic durability, maintaining 95% of its initial specific capacity of 507 mAh g−1 after 600 cycles at a current density of 5 A g−1. The electrochemical performance of NVO-rGO not only surpasses that of pristine NVO but also outperforms the majority of existing vanadium oxide cathode materials reported in the literature. This study underscores the effective integration of theoretical insights and experimental validation, contributing to the advancement of high-performance energy storage technologies.

In the context of improving aircraft safety, this study focuses on the development and evaluation of a graphene-based ice detection system using an environmental chamber. The research is driven by the need for more accurate and efficient ice detection methods, crucial in mitigating in-flight icing hazards. The methodology employed involves testing flat graphene-based sensors in a controlled environment, simulating a variety of climatic conditions that could be experienced in an aircraft during its entire flight. The environmental chamber enabled precise manipulation of temperature and humidity levels, thereby providing a realistic and comprehensive test bed for sensor performance evaluation. The results were significant, revealing the graphene sensors’ heightened sensitivity and rapid response to the subtle changes in environmental conditions, especially the critical phase transition from water to ice. This sensitivity is the key to detecting ice formation at its onset, a critical requirement for aviation safety. The study concludes that graphene-based sensors, tested under varied and controlled atmospheric conditions, exhibit a remarkable potential in enhancing ice detection systems for aircraft. Their lightweight, efficient and highly responsive nature makes them a superior alternative to traditional ice detection technologies, paving the way for more advanced and reliable aircraft safety solutions.

This paper draws upon the theory of turbulence in physics to explore the similarities and differences between volatility in financial markets and turbulent phenomena at a statistical physics level. By analogizing the dynamics of financial markets with fluid turbulence, we have developed an innovative analytical framework aimed at deepening the understanding of the complexity inherent in financial markets. Our research methodology includes a comparative analysis of simulated time series data for the Standard & Poor's 500 Index and fully developed turbulent velocity time series. We focus on the similarities in key statistical physical properties, including probability distributions, correlation structures, and power spectral densities. Furthermore, we have established a model of capital flow in financial markets and proposed corresponding solutions. Through computational simulations and data analysis, we find that while financial market volatility shares some statistical characteristics with turbulent phenomena, significant differences exist in the shapes of probability distributions and the temporal scales of correlations. This suggests that although financial markets exhibit patterns akin to turbulence, the behavior of this complex, multi-variable driven system does not completely correspond to natural turbulence, highlighting the limitations of directly applying turbulence theory to financial market analysis. Our study offers a new perspective for the theories of financial markets and the field of econophysics, providing fresh insights into the complexity of financial markets and contributing to the prevention and management of financial risk.

Carbon dots (C-dots) represent an emerging class of non-toxic nano-emitters that show excitation wavelength dependent photoluminescence (PL) with high quantum yield (QY) and minimal photobleaching. The vast majority of studies focus on C-dots that exhibit the strongest PL emission in the blue/green region of the spectrum, while longer wavelength emissions are ideal for applications such as bioimaging, photothermal and photodynamic therapy and light emitting diodes. Effective strategies to modulate the PL emission of C-dot based systems towards the red end of the spectrum rely on extensive conjugation of sp2 domains, heteroatom doping, solvatochromism, surface functionalization and passivation. Those approaches are systematically presented in this review, while emphasis is given on important applications of red-emissive suspensions, nanopowders and polymer nanocomposites.

Carbon dots are carbon based nanoparticles, which have the characteristics of simple preparation process, photoluminescence, biocompatibility, adjustable surface function, water solubility, and low toxicity. They are widely used in biological applications such as imaging, biosensing, photocatalysis, and molecular transfer. It has also aroused great interest among researchers in agriculture and has made significant progress in improving crop growth and production. This review presents the physiological functions of carbon dots for crop growth and development, photosynthesis, water and nutrient absorption, and abiotic stress resistance and their applications in improving ecological environment and agriculture as biosensors, and the future application prospects and research directions of carbon dots in agriculture were prospected.

The graphene based highly conductive and flexible devices has received momentous attraction and growth in recent years for potential multifunctional uses. The development of flexible and washable textile sensors, actuators, energy storage and energy harvesting systems. Textile fabrics coated with graphene and conductive polymers have been used for wearable self-powered e-textiles, such as tribo-electric, piezoelectric, and Thermoelectric. Herein this research, 100% woven cotton fabric is Fictionalized with graphene oxide (GO) using industrial-scale cold pad batch dyeing technique for the development of low-grade body heat into self-powered wearable e-textiles. The conductive polymer PEDOT: PSS was coated using layer by layer approach. The study demonstrates that the resultant textile electrodes showed reduced electrical sheet resistance from 2.5 MΩ to 15KΩ, with a reduced graphene oxide and further reduced to (2.5 -12.5 Ω) for conductive polymer. The sheet resistance was decreased with the number of dyeing cycles (10-15) and increased with 20 washing cycles vice versa. The study demonstrates that the sensor response and performance were improved with increasing the content percent of rGO and PEDOT: PSS. The tensile strength of as coated fabric electrodes was improved from (25.0-85.5 mPa) and fabric thickness was increased to (26-38µm) without compromising or influencing the air permeability. The resultant textile electrodes may potentially be used in smart textiles for self-powered flexible wearable generators, sensors, and energy storage. The study demonstrates that the cold pad batch dyeing method is a suitable and effective method for the fabrication of graphene-based textiles.

Abstract. Graphene family (GF)-Calcium phosphate (CaP) composites, holds great potential as components of bone regeneration materials. GF nanomaterials can be modified physically as well as chemically, which are to be biomimetic, mechanically to be hard due to their capability to support exceptional mechanical, thermal and electronic properties. These biocompatible GF composites coated on the calcium phosphate can enhance and tolerate stem cell growth and differentiation, proliferation into various lineages or interact with bioorganisms. The development in CF-CaP materials and their physicochemical/biointeractions and strategies towards osteoblasts is a great concern to promote faster healing and reconstructions of large bone imperfections or defects. In this review, we explain the influence of the CF-CaP and summarize recent developments on designing CF-CaP architectures as multifunctional bone regeneration platforms. We have also explored the typical biological applications concerning these CF-CaP based bioactive nanocomposites. Furthermore, the future viewpoints and evolving challenges will also be emphasized. Due to the shortage of full-length reviews in this emerging research field, this review would be caught great attention and encourage various new chances across a wider range of disciplines.

The discovery of the quantum tunnelling effect---the transmission of particles through a high potential barrier---was one of the most impressive achievements of quantum mechanics made in the 1920s. Responding to the contemporary challenges, I introduce a novel deep neural network (DNN) architecture that processes information using the effect of quantum tunnelling. I demonstrate the ability of the quantum tunnelling DNN (QT-DNN) to recognise optical illusions like a human. Hardware implementation of QT-DNN is expected to result in an inexpensive and energy-efficient neuromorphic chip suitable for applications in autonomous vehicles. The optical illusions recognition tests developed in this paper should lay foundations for cognitive benchmarking tasks for AI systems of the future, benefiting the fields of sociophysics and behavioural science.

On 17 October 1947, Niels Bohr was made a knight of the Order of the Elephant by the King of Denmark in view of his outstanding achievements and contributions to science. Bohr designed his own coat of arms that featured a pattern of Yin and Yang (Tai Chi symbol) to symbolize the wave-particle complementarity. However, Bohr’s Yin-Yang diagram (YYD) was neither drawn based on the principles of quantum mechanics, nor did it originate from the traditional Taoist YYD. Scientists still have doubts about the legitimacy of using YYD as the icon of the wave-particle complementarity, because the YYD belonging to quantum mechanics itself is unknown so far. This article reports the YYDs existing in quantum mechanics and justifies the role of YYD in the wave-particle duality by showing that any system, whether classical or quantum, has an ideal YYD as long as it satisfies Bohr’s principle of complementarity (BPC). The deviation of a deformed YYD from the ideal YYD indicates the extent to which a real system satisfies BPC. This article constructs the quantum YYD by the complex quantum trajectory of a particle tunneling via a step barrier, which displays the continuous transition between the wave behavior and the particle behavior. It appears that the YYD designed by Bohr in his coat of arms resembles the YYD generated by tunneling motion, not only in appearance but also in the governing equation.

Nano medicine seeks to deliver a valuable set of research tools and clinically useful devices in the near future. The current medical field is in dire need of new commercial applications in the pharmaceutical industry that may include advanced drug delivery systems, new therapies, and in vivo imaging. Here in this experimental study, the nano materials used in DNA biosensors like silver nano dots were incorporated as nano biosensors are used for both therapeutic and diagnostic applications. The most important step while preparing a DNA biosensor is the immobilization of DNA probe on the surface of a sensing device such as an electrode. The amount of immobilized DNA probe will influence the accuracy sensitivity, selectivity and life of a DNA biosensor directly. Because of the high surface to volume ratio and excellent biological compatibility, nano materials can enlarge the sensing surface area to increase the amount of immobilized DNA and the DNA mixed with nano materials can keep its biologically activity well.In this study,silver nano dots created in our lab were functionalized with thio nucleides and were used as nano sensor probes in bio bar code assays.

The band gap research in graphene is still a very important topic for materials application. Here, we report a band gap opening and p-type semiconducting property of the graphene by using an electrochemical doping on graphene surface. The manganese-oxide nanopar-ticles adsorbed on the graphene were used as the dopants in an electrolyte, which induce the band gap opening and the change of electronic structure. In addition, the fabricated graphene FET shows the p-type semiconductor behaviors. The temperature dependent conductivity of the p-type doped graphene at applied potential of 1.5 V during electro-chemical doping shows the formation of band gap of 0.23 eV, which is obtained from the fitting of conductivity equation. The semiconducting properties of manganese-oxide doped graphene is attributed to the formation of manganese-oxide nanoparticle on the surface of graphene.

Artificial intelligence (AI) systems of autonomous systems such as drones, robots and self-driving cars may consume up to 50% of total power available onboard, thereby limiting the vehicle’s range of functions and considerably reducing the distance the vehicle can travel on a single charge. Next-generation onboard AI systems need an even higher power since they collect and process even larger amounts of data in real time. This problem cannot be solved using the traditional computing devices since they become more and more power-consuming. In this review article, we discuss the perspectives of development of onboard neuromorphic computers that mimic the operation of a biological brain using nonlinear-dynamical properties of natural physical environments surrounding autonomous vehicles. Previous research also demonstrated that quantum neuromorphic processors (QNPs) can conduct computations with the efficiency of a standard computer while consuming less than 1% of the onboard battery power. Since QNPs is a semi-classical technology, their technical simplicity and low, compared with quantum computers, cost make them ideally suitable for application in autonomous AI system. Providing a perspective view on the future progress in unconventional physical reservoir computing and surveying the outcomes of more than 200 interdisciplinary research works, this article will be of interest to a broad readership, including both students and experts in the fields of physics, engineering, quantum technologies and computing.

Investigations into the properties of generalized effective temperature are conducted across arbitrary dimensions. Maxwell-Boltzmann distribution is displayed for one, two, and three dimensions, with effective temperatures expressed for each dimension. The energy density of blackbody radiation is examined as a function of dimensionality. Effective temperatures for non-uniform temperature distributions in one, two, three, and higher dimensions are presented, with generalizations extended to arbitrary dimensions. Furthermore, the application of generalized effective temperature is explored not only for linearly non-uniform temperature distributions but also for scenarios involving the volume fraction of two distinct temperature distributions. Finally, the effective temperature is determined for a cryogenic system supplied with both liquid nitrogen and liquid helium.

The advancement of performance in the domain of flexible wearable strain sensors has become increasingly significant due to extensive research on laser-induced graphene (LIG). An innovative doping modification technique is required owing to the limited progress achieved by adjusting laser parameters to enhance LIG’s performance. By pre-treating with AgNO3, we successfully manufactured LIG with a uniform dispersion of silver nanoparticles across its surface. The experimental results for the flexible strain sensor exhibit exceptional characteristics, including low resistance (183.4 Ω), high sensitivity (426.8), a response time of approximately 150 ms, and a relaxation time of about 200 ms. Moreover, this sensor demonstrates excellent stability under various tensile strains and remarkable repeatability during cyclic tests lasting up to 8,000 s. Additionally, this technique yields favorable results in finger bending and hand back stretching experiments, holding significant reference value for preserving the inherent characteristics of LIG preparation in a single-step and in situ manner.

This study explores the properties and behavior of bi-close-to-convex functions, introducing new subclasses defined by their relationship with fractional differential operator and bi-univalent functions. Using the Faber polynomial technique, we derive upper bounds for the n^{th} coefficient of functions in these classes. We also investigate the erratic behavior of initial coefficients in bi-close-to-convex functions, as characterized by the (λ,q)-fractional differintegral operator. Furthermore, we address Fekete-Szegö problems and present notable findings from our investigation, contributing to the continued growth and refinement of geometric function theory, yielding new insights and practical uses.

1) We shall discuss what modern interpretations say about the Heisenberg's uncertainties. These interpretations explain that a quantity begins to 'lose' meaning when a conjugate property begins to 'acquire' definite meaning. We know that a quantity losing meaning means that it has no fixed value and has an uncertainty . In this paper we look deeper into this interpretation and the outcome reveals more evidence of the quantity losing meaning. Newer insights appear. 2) We consider two extreme cases of hypothetical processes nature undergoes, without interference by a measurement: One, a system collapses to an energy eigenstate under the influence of a Hamiltonian instantaneously at a time $t$. This is thus what would happen if we would measure the system's energy. Next, when a particle becomes localised to a point at a time $t_0$ under the influence of a Hamiltonian. This is thus what would happen if we would measure the system's position. We shall prove that both these situations cannot arise under ordinary circumstances and thus measurement processes cannot be modelled by physical Hamiltonians.

Highly-doped graphene samples show the conductance reduced and the shot-noise power enhanced compared to standard ballistic systems in two-dimensional electron gas. These features can be understood within a model assuming incoherent scattering of Dirac electrons between two interfaces separating the sample and the leads. Here we find, by adopting the above-mentioned model for the edge-free (Corbino) geometry and by means of the computer simulation of quantum transport, that another graphene-specific feature should be observable when the current flow through a doped disk is blocked by high magnetic field. In case the conductance drops to zero, the Fano factor approaches the value of $F\approx{}0.56$, with a very weak dependence on the disk radii ratio. The role of finite source-drain voltages and the system behavior upon tuning the electrostatic potential barrier from a rectangular to parabolic shape are also discussed.

The growing production and application of carbon-based nanomaterials (CNMs) represent possible risks for aquatic systems. However, the variety of CNMs with different physical and chemical properties, and different morphology complicated the understanding of their potential toxicity. This paper aims to evaluate and compare the toxic impact of four most common CNMs, namely multiwalled carbon nanotubes (CNTs), fullerene (C60), graphene (Gr), and graphene oxide (GrO) in marine microalgae Porphyridium purpureum. The microalgae cells were exposed to the CNMs for 96 h and measured by flow cytometry. Based on the obtained results, we determined no observed effect level (NOEL), calculated EC10 and EC50 concentrations for growth rate inhibition, esterase activity, membrane potential, and reactive oxygen species (ROS) generation changes for each tested CNMs. According to the sensitivity (growth rate inhibition) of P. purpureum, the used CNMs can be listed in following order: CNTs > GrO > Gr > C60. The toxicity of CNTs was significantly higher than the toxic effect of the other used CNMs and only this sample caused increase of ROS generation in microalgae cells. This effect caused by trace metal residuals in CNTs and high affinity between particles and microalgae associated with the presence of exopolysaccharide coverage on P. purpureum cells.

Nanotechnology sparks discussions and concerns about the impacts of new nanomaterials on health and the environment. It holds importance in various domains due to its unique struc-tures. Carbon dots (C-dots) are versatile nanomaterials with applications in bioimaging, sensing, catalysis, polymers, solar cells, and more. They offer desirable characteristics such as stability, cost-effectiveness, biocompatibility, and high photoluminescent quantum yield. C-dots have the potential to replace expensive fluorophores in solar cells. They are catego-rized as carbon quantum dots, graphene quantum dots, and carbonized polymer dots. C-dots have outstanding optical and photoelectric properties with low toxicity. Bottom-up and top-down approaches are used for the synthesis of carbon dots (CDs), with each method im-pacting their physicochemical characteristics. The choice of synthesis method depends on de-sired properties and application requirements. Researchers combine these methods and ex-plore new approaches to enhance synthesis efficiency and tailor CD properties. CDs have di-verse chemical structures with modified oxygen, polymer-based, or amino groups on their surface. Various characterization methods such as HRTEM, XPS, and optical analysis (PL, UV) are used to determine CD structure. Carbon dots (CDs) are cutting-edge fluorescent nano-materials with remarkable qualities such as biocompatibility, low toxicity, environmental friendliness, high water solubility, and photo-stability. They are easily adjustable in terms of their optical properties, making them highly versatile in various fields. CDs find applications in bio-imaging, nanomedicine, drug delivery, solar cells, LEDs, photo-catalysis, elec-tro-catalysis, and other related areas.

Carbon dots have received much attention due to their unique physicochemical properties and diverse applications in bioimaging, optoelectronic devices, catalysis, and agriculture. Here in this work, we report a simple hydrothermal synthesis of nitrogen and phosphorus-doped carbon dots (N, P-CDs). The optical and physical properties of the synthesized N, P-CDs were analyzed using systematical spectroscopy and electrical characterization. The synthesized N, P-CDs show strong photoluminescence at 626 nm and demonstrate high stability under UV light and other conditions. Moreover, we incorporate the synthesized N, P-CDs into water spinach by root spraying and leaf spraying. It was found that N, P-CDs could effectively promote the growth of water spinach by increasing the photosynthetic rate, and the content of total phenols and anthocyanins in water spinach

Nearest-neighbour clustering is a simple yet powerful machine learning algorithm that finds natural application in the decoding of signals in classical optical-fibre communication systems. Quantum k-means clustering promises a speed-up over the classical k-means algorithm; however, it has been shown to currently not provide this speed-up for decoding optical-fibre signals due to the embedding of classical data, which introduces inaccuracies and slowdowns. Although still not achieving an exponential speed-up for NISQ implementations, this work proposes the generalised inverse stereographic projection as an improved embedding into the Bloch sphere for quantum distance estimation in k-nearest-neighbour clustering, which allows us to get closer to the classical performance. We also use the generalised inverse stereographic projection to develop an analogous classical clustering algorithm and benchmark its accuracy, runtime and convergence for decoding real-world experimental optical-fibre communication data. This proposed `quantum-inspired' algorithm provides an improvement in both the accuracy and convergence rate with respect to the k-means algorithm. Hence, this work presents two main contributions. Firstly, we propose the general inverse stereographic projection into the Bloch sphere as a better embedding for quantum machine learning algorithms; here, we use the problem of clustering quadrature amplitude modulated optical-fibre signals as an example. Secondly, as a purely classical contribution inspired by the first contribution, we propose and benchmark the use of the general inverse stereographic projection and spherical centroid for clustering optical-fibre signals, showing that optimizing the radius yields a consistent improvement in accuracy and convergence rate.

Biomass-derived carbon dots (CDs) are gaining much interest in recent times as it is a sustainable option with abundant availability, low cost, and tunable luminescence. Herein, we report a simple green synthesis method to produce highly fluorescent CDs from Eucalyptus globulus leaves using the one-pot hydrothermal approach. The fabricated CDs exhibit strong blue fluorescence with an excitation and emission maxima of 340 nm and 442 nm respectively. The highest quantum yield (QY) obtained was 60.7%. Due to its promising optical properties and biocompatibility, CDs can be a potential candidate for biosensing applications. Moreover, we employed a life cycle assessment (LCA) cradle-to-gate approach to study the environmental impacts of the synthesis strategy used for the fabrication of CDs. The results point out that citric acid is a main hotspot in CDs synthesis, regarding environmental impacts in most categories. This justifies the introduction of biomass, which reduces the amount of citric acid, thus leading to a more sustainable synthesis strategy for fabricating CDs.

The report introduces hybrid polyelectrolyte-stabilized colloids combining blue and green emitting building blocks, that are citrate carbon dots (CDs) and [TbL]+ chelate complexes with 1,3-diketonate derivatives of calix[4]arene. The joint incorporation of green and blue emitting blocks into the polysodium polystyrenesulfonate (PSS) aggregates is carried out through the solvent-exchange synthetic technique. The coordinative binding between Tb3+ centers and CD surface groups in initial DMF solutions both facilitates joint incorporation of [TbL]+ complexes and the CDs into the PSS-based nanobeads and affects fluorescence properties of [TbL]+ complexes and CDs, as well as their ability to temperature sensing. The variation of the synthetic conditions is represented herein as a tool for tuning the fluorescent response of the blue and green emitting blocks upon heating and cooling. The revealed regularities enable developing either dual band luminescent colloids for monitoring temperature changes within 25-50 C through double color emission, or to transform the colloids into ratiometric temperature sensors via simple concentration variation of [TbL]+ and CDs in initial DMF solution. Novel hybrid carbon dots-terbium chelate PSS-based nanoplatform opens an avenue for new generation of sensitive and customizable single excited dual band nanothermometers.

Nanoporous membranes promise energy-efficient water desalination. Hexagonal boron nitride (h-BN), like graphene, exhibits outstanding physical and chemical properties, making it a promising candidate for water treatment. We employed Car–Parrinello molecular dynamics simulations to establish accurate modeling of Na+ and Cl- permeation through hydrogen passivated nanopores in graphene and h-BN membranes. In these complex systems the classical potentials cannot properly account for the physics at play. We demonstrate that ion separation works well for the h-BN by imposing a barrier of 0.13 eV and 0.24 eV for Na+ and Cl- permeation respectively, compared to the graphene where the Cl- ion faces a negative barrier of 0.68 eV and is prone toward blockade and Na+ permeation is associated with a slightly negative barrier of 0.03 eV. From the change in the solvation shell, we get the following trend: Na/h-BN > Na/G > Cl/G > Cl/h-BN. We argue that the trend in the permeation barrier changes to Cl-h-BN > Na-h-BN > Na-G > Cl-G due to a combination of several interactions, including the distortion of the water network induced by the ions, the ion-water interaction, and the ion-nanopore interaction. Overall, the desalination performance of h-BN surpasses that of their graphene counterparts.

The thermal surface properties of graphenes and carbon materials are of crucial importance in chemistry of materials, chemical engineering, and many industrial processes. (1) Background: The determination of these surface properties is carried out using inverse gas chromatography at infinite dilution which leads to the retention volume of organic solvents adsorbed on solid surfaces. This experimental and fundamental parameter actually reflects the surface thermodynamic interactions between injected probes and solid substrates. (2) Methods: The London dispersion equation and the Hamieh thermal model were used to quantify the London dispersive and polar surface energy of graphenes and carbon fibers as well their Lewis acid-base constants by introducing the coupling amphoteric constant of materials. (3) Results: The London dispersive and polar acid-base surface energies, the free energy of adsorption, the polar enthalpy and entropy, and the Lewis acid-base constants of graphenes and carbon materials were determined. (4) Conclusions: it was showed that graphene exhibited the highest values of London dispersive surface energy, polar surface energy, and Lewis’s acid-base constants. These highest characteristics of graphene justify its great potentiality and uses in many industrial applications.

This paper discusses the Quantum Temporal Resonator (QTR), a theoretical device leveraging quantum entanglement and metamaterials with negative refraction indices to achieve controlled temporal displacement. By establishing a network of entangled particles within a Bose-Einstein Condensate (BEC) and utilizing a resonant cavity made of advanced metamaterials, the QTR creates localized distortions in space-time. The frequency and amplitude of temporal harmonics within this cavity are finely tuned to allow for precise temporal displacement of matter and information. Numerical simulations demonstrate the coupling between the quantum wave function and electromagnetic fields, validating the theoretical model. The results show distinctive patterns in the wave function and perturbations in the electric field, supporting the feasibility of achieving controlled temporal displacement. This study explores the theoretical framework, mathematical modeling, experimental setup, and potential applications of the QTR, providing a comprehensive analysis of its feasibility and implications.