Search Results (937)

Over the past several decades, there has been an accelerating trend to ever more accurate quantum sensors: sensors of time intervals (i.e., atomic clocks), sensors of magnetic fields (i.e., quantum magnetometers), and sensors of inertial motions (i.e., atom interferometers), to name just a few. With this trend has come a renewed interest in the problem of quantum mechanical measurement (i.e., collapse of the wavefunction), and though there have been many attempts to resolve the problem, there is still no wholly accepted resolution. Here, we discuss a little-explored path for resolving the issue that exploits wavefunction phase. To illustrate this path’s potential, we consider the notion of “eigenphase” sets that are disjoint among orthogonal eigenvectors. Wavefunction collapse then occurs because of constructive/destructive interference when a classical measuring device “phase-locks” to an incoming wavefunction. While the present work examines one method for exploiting wavefunction phase, its primary purpose is to more generally re-focus attention on wavefunction phase as a means for resolving the measurement problem that avoids many other solutions’ problematic aspects. Full article

The optical microscope is an indispensable observation instrument that has fundamentally contributed to progress in science and technology. Dark-field microscopy and scattered light imaging techniques enable high-contrast observation of nanoparticles in water. However, the scattered light is focused by the optical lenses, resulting in a blurred image of the nanoparticle structure. Here, we developed a projection optical microscope (PROM), which directly observes the scattered light from the nanoparticles without optical lenses. In this method, the sample is placed below the focus position of the microscope’s objective lens and the projected light is detected by an image sensor. This enables direct observation of the sample with a spatial resolution of approximately 20 nm. Using this method, changes in the aggregation state of nanoparticles in solution can be observed at a speed faster than the video frame rate. Moreover, the mechanism of such high-resolution observation may be related to the quantum properties of light, making it an interesting phenomenon from the perspective of optical engineering. We expect this method to be applicable to the observation and analysis of samples in materials science, biology and applied physics, and thus to contribute to a wide range of scientific, technological and industrial fields. Full article

In the previous research that aimed to enhance the toughness and tribological properties of silicon nitride ceramics, a lignin precursor was added to the ceramic matrix, which achieved conversion through pyrolysis and sintering, resulting in a silicon nitride-based composite ceramic containing nitrogen-doped graphene quantum dots (N-GQDs). This composite material demonstrated excellent comprehensive mechanical properties and friction-wear performance. Based on the existing experimental results, the first-principles plane wave mode conservation pseudopotential method of density functional theory was adopted in this study to build a microscopic heterostructure model of Si₃N₄-based composite ceramics containing N-GQDs. Meanwhile, the surface energy of Si₃N₄ and the system energy of the N-GQDs@Si₃N₄ heterostructure were calculated. The calculation results showed that when the distance between N-GQDs and Si₃N₄ in the heterostructure was 2.3 Å, the structural energy was the smallest and the structure was the steadiest. This is consistent with the previous experimental results and further validates the coating mechanism of N-GQDs covering the Si₃N₄ column-shaped crystals. Simultaneously, based on the results of the previous experiments, the stress of the heterostructure composed of Si₃N₄ particles coated with different numbers of layers of nitrogen quantum dots was calculated to predict the optimal lignin doping amount. It was found that when the doping amount was between 1% and 2%, the best microstructure and mechanical properties were obtained. This paper provides a new method for studying the graphene quantum dot coating structure. Full article

This study addresses the issue of cross-interference that occurs when locked continuous light and signal photons are collinear during interferometer measurements. To tackle this, a temperature-controlled Fabry–Pérot cavity filter with a heterogeneous cascaded structure is proposed and applied. The system consists of six filtering stages, created by designing Fabry–Pérot cavities of three different lengths, each used twice (to match optical frequencies), along with temperature control settings. By applying differentiated linewidth regulation, the approach effectively suppresses interference from locked light while significantly enhancing the signal-to-noise ratio in photon detection. This method overcomes the challenge of interference from same-frequency noise photons in atomic ensemble-entangled sources, achieving a noise–photon extinction ratio on the order of 10⁶ and surpassing the frequency resolution limit of a single filter. Experimental results demonstrate that the system reduces the noise floor in the detection optical path to below 10⁻¹⁶, while maintaining a photon transmission efficiency above 53% for the signal. This technology effectively addresses key challenges in noise suppression and photon state fidelity optimization in optical fiber quantum communication, offering a scalable frequency–photon noise filtering solution for long-distance quantum communication. Furthermore, its multi-parameter cooperative filtering mechanism holds broad potential applications in areas such as quantum storage and optical frequency combs. Full article

As quantum computing advances, traditional digital forensic techniques face significant risks due to the vulnerability of classical cryptographic algorithms to quantum attacks. This review explores the emerging field of quantum digital forensics, with a particular focus on the role of quantum entanglement in enhancing the integrity, authenticity, and confidentiality of digital evidence. It compares classical and quantum forensic mechanisms, examines entanglement-based quantum key distribution (QKD), quantum hash functions, and quantum digital signatures (QDS), and discusses the challenges in practical implementation, such as scalability, hardware limitations, and legal admissibility. The paper also reviews various entanglement detection methods critical to the validation of quantum states used in forensic processes. Full article

With the breakthroughs in quantum theory and the rapid advancement of quantum precision measurement sensor technologies, atomic magnetometers based on the spin-exchange relaxation-free (SERF) mechanism have played an increasingly important role in ultra-weak biomagnetic field detection, inertial navigation, and fundamental physics research. To achieve high-precision measurements, SERF magnetometers must operate in an extremely weak magnetic field environment, while the detection of ultra-weak magnetic signals relies on a low-noise background. Therefore, accurate measurement, modeling, and analysis of magnetic noise in shielding materials are of critical importance. In this study, the magnetic noise of permalloy sheets was modeled, separated, and analyzed based on their measured magnetic properties, providing essential theoretical and experimental support for magnetic noise evaluation in shielding devices. First, a single-sheet tester (SST) was modeled via finite element analysis to investigate magnetization uniformity, and its structure was optimized by adding a supporting connection plate. Second, an experimental platform was established to verify magnetization uniformity and to perform accurate low-frequency measurements of hysteresis loops under different frequencies and field amplitudes while ensuring measurement precision. Finally, the Bertotti loss separation method combined with a PSO optimization algorithm was employed to accurately fit and analyze the three types of losses, thereby enabling precise separation and calculation of hysteresis loss. This provides essential theoretical foundations and primary data for magnetic noise evaluation in shielding devices. Full article

Sugar beet pulp (SBP) is a by-product from the sugar industry with low value. As a feed, SBP needs to be dried. However, the drying process takes too much energy, leading to potential environmental issues caused by coal use. This paper raised and tried a crosslinking method to shorten the drying process, save energy consumption, and increase the value of SBP. This paper aimed to reduce the water-holding ability of SBP while obtaining animal feed with higher nutritional value. First, the crosslinking method was used to evaluate its dryness–strengthening effect. Second, three factors were evaluated: operating temperature, solution pH, and cationic concentration. Third, a kinetic study was performed on the drying process of SBP through its crosslinking with macro-elements (Ca²⁺, Cu²⁺) using drying models; the characterization of Ca²⁺-SBP and Cu²⁺-SBP using FTIR, SEM, and XRD; and possible drying mechanisms, which were discussed using an egg box model and a simple quantum chemical calculation. Results showed that the dryness–strengthening and value-adding idea is more practical through a Ca²⁺-crosslinking method, rather than through crosslinking with Cu²⁺. Under experimental conditions, wet SBP with 2 g of dry base reacts to Ca²⁺ under optimized conditions of 1000 mg/L Ca²⁺ solution at pH 6.0 and 40 °C for 135 min, with a moisture content of 5.23 g/g as a water-holding index. Compared with SBP, the moisture content of the crosslinking SBP on a dry basis was reduced by ~30–40%. The Midilli–Kucuk model was the most suitable model to describe the hot-air drying process of SBP, while Ca²⁺ or Cu²⁺ can crosslink to the galacturonic acid in pectin and form an “egg-box” model. SBP binds with Ca²⁺ or Cu²⁺ through its carboxyl groups, as testified by a combination analysis of FTIR, SEM, and XRD. As a result, the SBP dried through the Ca²⁺-crosslinking or Cu²⁺-crosslinking method can be directly used as a feed additive with good economic benefit and without the post-treatment problem as a bio-sorbent. Full article

We address the inverse spectral problem for a PT-symmetric Dirac operator with discontinuity conditions imposed along the entire real axis—a configuration that has not been explicitly solved in prior literature. Our approach constructs fundamental solutions via convergent recursive series expansions and establishes their linear independence through a constant Wronskian. We derive explicit formulas for transmission and reflection coefficients, assemble them into a PT-symmetric scattering matrix, and demonstrate how both spectral and scattering data uniquely determine the underlying complex-valued, discontinuous potentials. Unlike classical treatments, which assume smoothness or limited discontinuities, our framework handles full-axis discontinuities within a non-Hermitian setting, proving uniqueness and providing a constructive recovery algorithm. This method not only generalizes existing inverse scattering theory to PT-symmetric discontinuous operators but also offers direct applicability to optical waveguides, metamaterials, and quantum field models where gain–loss mechanisms and zero-width resonances are critical. Full article

Quantum technology is significantly transforming businesses, organisations, and information systems. It will have a significant impact on accounting and finance, particularly in the context of cybersecurity. It presents both opportunities and risks in maintaining confidentiality and protecting financial data. This study aims to demonstrate the application of quantum technologies in accounting cybersecurity, utilising quantum algorithms and QKD to overcome the limitations of classical computing. The literature review emphasises the vulnerabilities of current accounting cybersecurity to quantum attacks and highlights the necessity for quantum-resistant cryptographic mechanisms. It discusses the risks related to traditional encryption methods within the context of quantum capabilities. This research enhances understanding of how quantum computing can revolutionise accounting cybersecurity by advancing quantum-resistant algorithms and implementing QKD in accounting systems. This study employs the PSALSAR systematic review methodology to ensure thoroughness and rigour. The analysis shows that quantum computing pushes encryption techniques beyond classical limits. Using quantum technologies in accounting reduces data breaches and unauthorised access. This study concludes that quantum-resistant algorithms and quantum key distribution (QKD) are crucial for securing the future of accounting and finance systems. Full article

Methylation reactions catalyzed by S-adenosylmethionine (SAM)-dependent methyltransferases are essential to numerous biological functions, including gene expression regulation, epigenetic modifications, and biosynthesis of natural products. Dysregulation of these enzymes is associated with diseases, including cancer and neurodevelopmental disorders, making them attractive drug targets. This review explores the contribution of computational methods, particularly quantum chemical calculations and molecular dynamics (MD) simulations, in elucidating the mechanisms of SAM-dependent methyltransferases. These techniques enable detailed characterization of transition states and reaction pathways, often inaccessible by experimental methods. The review discusses molecular modeling approaches such as the quantum chemical cluster approach (QM-cluster) and hybrid QM/MM methods, emphasizing their applications in studying methyl group transfer, substrate specificity, and the roles of water molecules and metal ions in catalysis. Additionally, dynamic aspects of enzyme function are addressed using classical MD and QM/MM MD simulations. Case studies demonstrate how computational predictions align with experimental data and enable rational design of selective inhibitors and engineered enzymes with altered specificity. Overall, computational chemistry offers a powerful, atomistic view of SAM-dependent methyltransferases, not only complementing experimental studies but also providing a foundation for the design of future experiments in this field. Full article

Quantum computers are emerging as a major tool in the computation field, leveraging the principles of quantum mechanics to solve specific problems currently beyond the capability of classical computers. This technology holds significant promise in edge-main cloud deployments, where it can enable low-latency data processing and secure communication. This paper aims to establish a research foundation by integrating quantum computing with classical edge-cloud environments to promote performance across a range of applications that scientists are actively investigating. However, the successful deployment of hybrid quantum–classical edge-clouds requires a comprehensive evaluation framework to ensure their alignment with the performance requirements. This study first proposes a novel quantum benchmarking framework, including two distinct methods to evaluate latency scores based on the quantum transpilation levels across different quantum-edge-cloud platforms. The framework is then validated for the edge-cloud environment by benchmarking several well-known and useful quantum algorithms potentially useful in this domain, including Shor’s, Grover’s, and the Quantum Walks algorithm. An optimal transpilation level is eventually suggested to achieve maximum performance in quantum-edge-cloud environments. In summary, this research paper provides critical insights into the current and prospective capabilities of QPU integration, offering a novel benchmarking framework and providing a comprehensive assessment of their potential to enhance edge-cloud performance under varying parameters, including fidelity and transpilation levels. Full article

Against the background of the accelerating global transition towards a low-carbon energy system, the lithium-ion battery (LIB) industry has witnessed a rapid development. Concurrently, fire accidents in LIB application scenarios have occurred frequently, with safety issues becoming increasingly prominent. Thermal runaway of LIBs is the direct cause of such fires. During the thermal runaway process of LIBs, lithium salts in the electrolyte undergo thermal decomposition reactions with carbonate-based electrolytes, releasing a large amount of heat and fire gases. Among them, the thermal decomposition reactions of LiPF₆ with electrolytes are coupled and superimposed, exhibiting a significant synergistic effect. This paper employs quantum chemical calculation methods to investigate the thermal decomposition reaction mechanisms between PF₅ and POF₃, which generated from the thermal decomposition of LiPF₆ and carbonate-based electrolytes (EC, DMC, and DEC) during the thermal runaway process of LIBs; and presents detailed chemical reaction mechanism models. The P atoms in PF₅ or POF₃ combine with the O atoms of the ether oxygen groups in carbonates, while the F atoms combine with the C atoms adjacent to the ether oxygen groups. This promotes the ring-opening or chain scission of carbonate molecules, reduces the energy required for the reaction, and accelerates the thermal decomposition reaction and the generation of fire gases. Modification of EC, DMC, and DEC through fluorination can effectively inhibit the catalytic effect of PF₅ and POF₃ and improve the oxidation resistance and thermal stability of the electrolytes. Full article

Sunset yellow (SY) is a synthetic azo dye widely used in food and cosmetics. However, concerns have been raised about its potential health risks, including its nephrotoxicity and genotoxicity, when used in excessive amounts. Illegal addition of SY may cause allergic reactions or genetic damage. Therefore, a rapid method for detecting SY is needed. To develop a rapid detection method for sunset yellow (SY) with the aim of preventing its illegal addition in food, this study utilized agricultural waste asparagus peel (AP) as a carbon source and synthesized amino-functionalized carbon quantum dots (AP-CDs) via a green hydrothermal method. A highly sensitive detection platform was established based on the fluorescence quenching mechanism of AP-CDs in the presence of SY. The microstructure of AP-CDs was characterized using transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). Their optical properties were assessed via ultraviolet–visible absorption spectroscopy (UV-vis) and fluorescence spectroscopy (FS). Furthermore, key experimental parameters affecting SY detection were systematically optimized. Results revealed that the synthesized AP-CDs possessed surface hydrophilic functional groups, including hydroxyl, amide, and carboxyl groups, and were composed of carbon (C), oxygen (O), and nitrogen (N) elements. Optical performance studies demonstrated that AP-CDs exhibited a strong fluorescence emission at 470 nm under 380 nm excitation, with a quantum yield (Φ) of 15.9%. Under the optimized conditions (pH 7.0, 0.5 mg/mL AP-CDs), the fluorescence intensity showed a linear response to the concentration of SY over the range of 0.1 to 100 μM (R² = 0.9929), achieving a detection limit of 0.92 μM. This strategy not only enables sustainable resource utilization but also provides a sensitive and practical approach for food safety monitoring, demonstrating significant potential for real-world applications. Full article

Elastic isotropy is a phenomenon in which a material responds uniformly to stress, regardless of its direction. In the case of cubic crystals, which possess distinct crystallographic directions, this represents a remarkable manifestation of quantum mechanics in macroscopic objects. Such behavior of a crystal cannot be explained within the framework of classical physics. The phenomenon is closely related to the balancing of internal forces resulting from Coulomb interactions, Pauli repulsion, and the overlap in the bands when stress is applied to the crystal. On the macroscopic level, this corresponds to the relationship between elastic constants given by 2 C₄₄/(C₁₁ − C₁₂) = 1. The subject of the present work is to demonstrate the influence of the number of valence electrons per atom in binary titanium alloys with vanadium, niobium, and tantalum on the shape of the anisotropy curve. The result of the work is the identification of a new Ti-53Nb alloy exhibiting elastic isotropy, and the demonstration that this phenomenon cannot occur for TiTa alloys, in the range of mechanical stability of these alloys. This study includes a summary of the main trends exhibited by the elastic constants, Young’s modulus, and bulk modulus of the discussed Ti-based alloys, based on ab initio methods. Additionally, the work addresses the well-known difficulty in determining the elastic constants of vanadium and niobium, along with a proposed solution that offers significant improvement in reproducing experimental results compared to the conventional use of the PBE (Perdew–Burke–Ernzerhof) functional. Full article

Identifying the most reactive conformation of a molecule is a central challenge in computational chemistry, particularly when reactivity depends on subtle conformational effects. While most conformation search tools aim to find the lowest-energy structure, they often overlook the electronic descriptors that govern chemical reactivity. In this work, we present GAELLE, a cheminformatics tool that combines conformer generation with quantum reactivity descriptors to identify the most reactive structure of a molecule in solution. GAELLE integrates an evolutionary algorithm with fast semiempirical quantum chemical calculations (xTB), enabling the automated ranking of conformers based on HOMO–LUMO gap minimization (Pearson’s principle of maximum hardness) and electrophilicity index (Parr’s electrophilicity scale). Solvent effects are accounted for via implicit solvation models (GBSA/ALPB) to ensure realistic evaluation of reactivity in solution. The method is fully SMILES-driven, open-source, and scalable to medium-sized drug-like molecules. Applications to reactive intermediates, bioactive conformations, and pre-reactive complexes demonstrate the method’s relevance for mechanism elucidation, molecular design, and in silico screening. GAELLE is publicly available and offers a reactivity-focused alternative to traditional energy-minimization tools in conformational analysis. Full article