Search Results (1,044)

:Solvents represent the quiet majority in biomolecular systems, yet modeling their influence with both speed and ri:gor remains a central challenge. This study maps the state of the art in implicit solvent theory and practice, spanning classical continuum electrostatics (PB/GB; DelPhi, APBS), modern nonpolar and cavity/dispersion treatments, and quantum–continuum models (PCM, COSMO/COSMO-RS, SMx/SMD). We highlight where these methods excel and where they falter, namely, around ion specificity, heterogeneous interfaces, entropic effects, and parameter sensitivity. We then spotlight two fast-moving frontiers that raise both accuracy and throughput: machine learning-augmented approaches that serve as PB-accurate surrogates, learn solvent-averaged potentials for MD, or supply residual corrections to GB/PB baselines, and quantum-centric workflows that couple continuum solvation methods, such as IEF-PCM, to sampling on real quantum hardware, pointing toward realistic solution-phase electronic structures at emerging scales. Applications across protein–ligand binding, nucleic acids, and intrinsically disordered proteins illustrate how implicit models enable rapid hypothesis testing, large design sweeps, and long-time sampling. Our perspective argues for hybridization as a best practice, meaning continuum cores refined by improved physics, such as multipolar water, ML correctors with uncertainty quantification and active learning, and quantum–continuum modules for chemically demanding steps. Full article

This study presents a simulation-based analysis of a steel modular building that integrates technologies that support the energy transition in the built environment. The focus is placed on the implementation of building-integrated photovoltaics (BIPVs), with photovoltaic modules incorporated into the façade and balcony railings. Several modern photovoltaic façade systems were examined. In addition, the study considers the application of photovoltaic glazing enhanced with active quantum coatings. Seven distinct BIPV modules were analysed, each characterised by unique features, with particular emphasis on the influence of colour in tinted variants. A performance degradation analysis was conducted for railing-mounted modules with varying glass tints. The simulation results were correlated with the building’s electricity demand. Full article

Polymer matrix composites (PMCs) are crucial for their applications in aerospace, electronics, defense, and structural materials. PMCs reinforced with nanofillers offer substantial potential for enhanced thermal and mechanical performance. Although there have been significant developments in nanofiller-based high-performance composites involving graphene, carbon nanotubes, and metal oxides, the smallest of all the fillers, the graphene quantum dot (GQD), has not been explored thoroughly. The objective of this study is to investigate the effects of GQDs on the thermal properties of epoxy nanocomposites using all-atom molecular dynamics (MD) simulations. Specifically, the influence of GQDs on the glass transition temperature (T_g) and coefficient of linear thermal expansion (CTE) of the bisphenol F epoxy is evaluated. Further, the effects of surface functionalization and edge functionalization of GQDs are analyzed. Results demonstrate that the inclusion of functionalized GQDs leads to a 16% improvement in T_g, attributed to enhanced interfacial interactions and restricted molecular mobility in the epoxy network. MD simulations reveal that functional groups on GQDs form strong physical and chemical interactions with the polymer matrix, effectively altering its dynamics at the T_g. These results provide key molecular-level insights into the design of the next generation of thermally stable epoxy nanocomposites for high-performance applications in aerospace and defense. Full article

The electrical properties of contacts to p-type nitride semiconductor devices, based on gallium nitride, were simulated by ab initio and drift-diffusion calculations. The electrical properties of the contact are shown to be dominated by the electron-transfer process from the metal to GaN, which is related to the Fermi-level difference, as determined by both ab initio and model calculations. The results indicate a high potential barrier for holes, leading to the non-Ohmic character of the contact. The electrical nature of the Ni–Au contact formed by annealing in an oxygen atmosphere was elucidated. The influence of doping on the potential profile of p-type GaN was calculated using the drift-diffusion model. The energy-barrier height and width for hole transport were determined. Based on these results, a new type of contact is proposed. The contact is created by employing multiple-layer implantation of deep acceptors. The implementation of such a design promises to attain superior characteristics (resistance) compared with other contacts used in bipolar nitride semiconductor devices. The development of such contacts will remove one of the main obstacles in the development of highly efficient nitride optoelectronic devices, both LEDs and LDs: energy loss and excessive heat production close to the multiple-quantum-well system. Full article

Soft nanocomposites were prepared by dispersing lipophilic carbon quantum dots (CQDs) in the liquid crystal compound 8CB. The quality of the dispersion was evaluated using fluorescence microscopy, while the microstructure of the samples was examined via polarized optical microscopy. We investigated the influence of CQDs on the orientational order parameter S as a function of temperature and sample composition by measuring birefringence. Additionally, the Fréedericksz transition threshold, along with the characteristic response and relaxation times, was measured for each sample as a function of temperature and applied voltage amplitude. The extracted rotational viscosity ${\gamma }_1$ exhibits a pretransitional divergence upon cooling toward the smectic-A phase. Its temperature dependence was analyzed using established models from the literature, and the corresponding activation energy was determined. Notably, our analysis suggests that the presence of CQDs alters the power-law dependence of ${\gamma }_1$ on the orientational order parameter S. The influence of CQDs on the elastic constants has been investigated. Full article

Accurate parameter identification in dynamic models of robotic arms is essential for performing high-performance control and energy-efficient procedures. However, classic methods often encounter difficulties when modeling nonlinear, high-dimensional systems, particularly in the presence of real-world uncertainties. To address these challenges, this study focuses on identifying mass center positions and inertia matrix elements in a six-jointed industrial robotic arm and comparing the influence of optimized algorithms: the classical Particle Swarm Optimization (PSO) and the Quantum-behaved Particle Swarm Optimization (QPSO). The robot’s kinematic model was validated by comparing it with actual motion data, utilizing a high-precision neural network to ensure accuracy before conducting a dynamic analysis. A comprehensive dynamic model was created using Computer-Aided Optimization (CAO) in SolidWorks Premium 2023 to simulate realistic mass parameters, thereby validating the model’s reliability in a practical setting. The real (Referenced) and optimized dynamic models of the robot arm were validated using trajectory tracking simulations under sliding mode control (SMC) to assess the impact of the optimized model on the robot’s performance metrics. Results indicate that QPSO estimates inertia and mass center parameters with Mean Absolute Percentage Errors (MAPE) of 0.76% and 0.43%, outperforming PSO significantly and delivering smoother torque profiles and greater resilience to external disturbances. Full article

Structural composite materials are being used more than ever in aeronautics, automotive and naval, or in renewable energies fields. To reconcile the contradictory needs for higher performances and lower costs, it is crucial to ensure the real-time monitoring of as many features as possible during the manufacturing process to feed a digital twin able to minimise post-fabrication controls. For thermoset composites, little information is available regarding the evolution of the polymer’s core properties during infusion and curing. The local kinetics of reticulation, in several areas of interest across the thickness of a structural composite part, are valuable data to record and analyse to guarantee the materials’ performances. This paper investigates a novel strategy curing in the core of an epoxy matrix with crosslinkable quantum-resistive nanocomposite sensors (xQRS). First, the electrical behaviour of the sensor during isothermal curing is considered. Then, the influence of the dynamic percolation and the epoxy crosslinking reaction on the resistance is examined. The evidence of a relationship between the curing state of the resin and the evolution of the xQRS resistance makes its use in the process monitoring of thermoset composites promising, especially in cases involving large and thick parts. Full article

The spectral characteristics of pump laser diodes (LDs) introduce significant ambiguity into the performance evaluation of high-power ytterbium-doped fiber lasers (YDFLs), obscuring their intrinsic efficiency and hindering reliable system design. Here, we introduce a rigorous quantitative framework that decouples these pump-induced effects by referencing laser performance to the absorbed, rather than the launched, pump power. Our analysis demonstrates that the widely reported discrepancies in conventional optical-to-optical (OO) and slope efficiencies are governed almost entirely by variations in pump absorption, while the influence of the quantum defect is negligible. This approach provides a robust metric for intrinsic laser performance that is independent of the LD’s spectral properties, proving particularly valuable for systems pumped by non-wavelength-stabilized LDs (nWS-LDs). We uncover a non-monotonic evolution of the unabsorbed residual pump power, revealing that the peak thermal load on system components occurs at an intermediate operational state, not at maximum pump power. This finding challenges conventional thermal management strategies and is critical for ensuring the long-term operational reliability of high-power YDFLs. Full article

In the evolving digital landscape, the pervasive influence of artificial intelligence (AI) on social media platforms reveals a compelling paradox: the capability to provide personalized experiences juxtaposed with inherent biases reminiscent of human imperfections. Such biases prompt rigorous contemplation on matters of fairness, equity, and societal ramifications, and penetrate the foundational essence of AI. Within this intricate context, the present work ventures into novel domains by examining the potential of quantum computing as a viable remedy for bias in artificial intelligence. The conceptual framework of the quantum sentinel is presented—an innovative approach that employs quantum principles for the detection and scrutiny of biases in AI algorithms. Furthermore, the study poses and investigates the question of whether the integration of advanced quantum computing to address AI bias is seen as an excessive measure or a requisite advancement commensurate with the intricacy of the issue. By intertwining quantum mechanics, AI bias, and the philosophical considerations they induce, this research fosters a discourse on the journey toward ethical AI, thus establishing a foundation for an ethically conscious and balanced digital environment. We also show that the quantum Zeno effect can protect SVM hyperplanes from bias through targeted simulations. Full article

Nitrogen (N) availability significantly influences plant metabolism and productivity. The aim of this study was to assess the effects of low N stress and subsequent N supplementation on key enzymes of nitrogen metabolism, nitrogen metabolism-related substances, and chlorophyll a fluorescence kinetic parameters in rice genotypes with different nitrogen utilization efficiencies. We used the Jijing 88 (low-N tolerant) and Xinong 999 (low-N sensitive) as test materials. During the seedling, tillering, and booting stages, the 1/2N and 1/4N treatments were restored to the 1N treatment level. Nine treatments were used in this experiment: CK (1N), A1 (1/2N), A2 (1/2N restored to 1N during the seedling stage), A3 (1/2N restored to 1N during the tillering stage), A4 (1/2N restored to 1N during the booting stage), B1 (1/4N), B2 (1/4N restored to 1N during the seedling stage), B3 (1/4N restored to 1N during the tillering stage), and B4 (1/4N restored to 1N during the booting stage). Key physiological responses, nitrogen compounds, enzymes activities, and chlorophyll a fluorescence kinetics were analyzed. Under low nitrogen conditions, the growth and nitrogen assimilation of rice were inhibited. Compared to XN 999, JJ 88 maintains higher levels of dry matter, nitrate reductase activity (NR), glutamine synthetase activity (GS), glutamate oxaloacetate transaminase activity (GOT), glutamate pyruvate transaminase activity (GPT), as well as nitrate (NO₃⁻) and ammonium (NH₄⁺) nitrogen contents. After N supplementation during the early growth stage, both JJ 88 and XN 999 exhibit recovery capabilities. However, in the late growth stage, JJ 88 demonstrates superior recovery capabilities. In addition to enhancing nitrogen metabolism levels, there is also an increase in the content of osmotic regulation substances such as soluble sugars, free amino acids, and proline, along with responses in chlorophyll fluorescence kinetic parameters. This was primarily manifested in the enhancement of performance index (PI_ABS, PI_total), and quantum yield (φ_EO, φ_RO, ψ_EO), which maintain photosynthetic performance and electron transport efficiency. The research findings indicated that reducing N supply during the early growth stage and restoring N levels in the later stage are beneficial for the recovery of low-nitrogen-tolerant rice varieties. Therefore, in the context of sustainable agricultural production, the breeding of low-nitrogen-tolerant rice varieties and the optimization of N fertilizer management are crucial. Full article

In boron neutron capture therapy (BNCT), the intracellular localization and concentration of boron-10 atoms significantly influence therapeutic efficacy. Although various boronic-acid-targeted fluorescent probes have been developed to evaluate BNCT agents, most of these probes emit at short wavelengths and are, therefore, incompatible with common nuclear-staining reagents such as Hoechst 33342 and 4′,6-diamidino-2-phenylindole (DAPI). While our previously reported probe, BS-631, emitted fluorescence above 500 nm, it exhibited limitations in terms of reaction rate and fluorescence intensity. To address these issues, we developed a boronic-acid-targeted fluorescent probe with a longer emission wavelength, rapid reactivity, and strong fluorescence intensity. Herein, we designed and synthesized BTTQ, a probe based on a 2-(2-hydroxyphenyl)benzothiazole core structure. BTTQ exhibited immediate fluorescence upon reaction with 4-borono-L-phenylalanine (BPA), with an emission wavelength of 567 nm and a sufficiently high fluorescence quantum yield for detection. BTTQ quantitatively detected BPA with high sensitivity (quantification limit of 10.27 µM), suitable for evaluating BNCT agents. In addition, BTTQ exhibited selective fluorescence for BPA over metal cations. Importantly, BTTQ enabled fluorescence microscopic imaging of intracellular BPA distribution in living cells co-stained with Hoechst 33342. These results suggest that BTTQ is a promising fluorescent probe for the evaluation of future BNCT agents. Full article

The biological effects of nanoparticles are closely related to their intracellular content and location, both of which are influenced by various factors. This study investigates the effects of surface charge on the uptake, intracellular distribution, and exocytosis of CdSe/ZnS quantum dots (QDs) in Raw264.7 macrophages. Negatively charged 3-mercaptopropanoic acid functionalized QDs (QDs-MPA) show higher cellular uptake than positively charged 2-mercaptoethylamine functionalized QDs (QDs-MEA), and serum enhances the uptake of both types of QDs via protein corona-mediated receptor endocytosis. QDs-MEA primarily enter the cells through clathrin/caveolae-mediated pathways and predominantly accumulate in lysosomes, while QDs-MPA are mainly internalized through clathrin-mediated endocytosis and localize to both lysosomes and mitochondria. Exocytosis of QDs-MPA is faster and more efficient than that of QDs-MEA, though both exhibit limited excretion. In addition to endocytosis and exocytosis, cell division influences intracellular QD content over time. These results reveal the charge-dependent interactions between QDs and macrophages, providing a basis for designing biocompatible nanomaterials. Full article

The elastic and photoelastic coefficients of Ba₃TaGa₃Si₂O₁₄ (BTGS) crystals were determined by the quantum–mechanical calculation technique. Based on these data, extreme piezo-optic surfaces π′°_km were constructed, which describe the change in the path difference in light beams in the crystal under the influence of mechanical stress. The results for BTGS crystals are compared with the ones for other crystals of the langasite group (La₃Ga₅SiO₁₄, Ca₃Ga₂Ge₄O₁₄, Ca₃TaGa₃Si₂O₁₄ and Ca₃NbGa₃Si₂O₁₄). The global maxima of the π′°_km surfaces for BTGS crystals significantly exceed the ones for the other crystals mentioned above and, accordingly, BTGS crystals can be suitable for use in polarization-optic light modulators and devices based on them. The acousto-optic efficiency of BTGS crystals was evaluated. The correlations between the magnitude of the piezo- and elasto-optic coefficients and the parameters of the unit cell of the studied crystals were determined. Full article

Fibrate pharmaceuticals (fibrates), as a widespread class of emerging contaminants, pose potential risks to both ecological systems and human health. The photocatalytic system based on nitrogen (N) and fluorine (F) co-doped TiO₂ nanotube arrays (NF-TNAs) provides a renewable solution for fibrate pharmaceutical removal from water, powered by inexhaustible sunlight. In this study, the degradation of two typical fibrates, i.e., bezafibrate (BZF) and ciprofibrate (CPF), under simulated sunlight irradiation through NF-TNAs were investigated. The photocatalytic degradation of BZF/CPF was achieved through combined radical and non-radical oxidation processes, while the generation and reaction mechanisms of associated reactive oxygen species (ROS) were examined. Electron paramagnetic resonance detection and quenching tests confirmed the existence of h⁺, •OH, O₂^•−, and ¹O₂, with O₂^•− playing the predominant role. The transformation products (TPs) of BZF/CPF were identified through high-resolution mass spectrometry analysis combined with quantum chemical calculations to elucidate the degradation pathways. The influence of co-existing ions and typical natural organic matters (NOM) on BZF/CPF degradation were also tested. Eventually, the ecological risk of BZF/CPF transformation products was assessed through quantitative structure–activity relationship (QSAR) modeling, and the results showed that the proposed photocatalytic system can largely alleviate fibrate toxicity. Full article

This study focuses on the analysis of soliton solutions within the framework of the time-fractional cubic–quintic nonlinear Schrödinger equation (TFCQ-NLSE), a powerful model with broad applications in complex physical phenomena such as fiber optic communications, nonlinear optics, optical signal processing, and laser–tissue interactions in medical science. The nonlinear effects exhibited by the model—such as self-focusing, self-phase modulation, and wave mixing—are influenced by the combined impact of the cubic and quintic nonlinear terms. To explore the dynamics of this model, we apply a robust analytical technique known as the sub-ODE method, which reveals a diverse range of soliton structures and offers deep insight into laser pulse interactions. The investigation yields a rich set of explicit soliton solutions, including hyperbolic, rational, singular, bright, Jacobian elliptic, Weierstrass elliptic, and periodic solutions. These waveforms have significant real-world relevance: bright solitons are employed in fiber optic communications for distortion-free long-distance data transmission, while both bright and dark solitons are used in nonlinear optics to study light behavior in media with intensity-dependent refractive indices. Solitons also contribute to advancements in quantum technologies, precision measurement, and fiber laser systems, where hyperbolic and periodic solitons facilitate stable, high-intensity pulse generation. Additionally, in nonlinear acoustics, solitons describe wave propagation in media where amplitude influences wave speed. Overall, this work highlights the theoretical depth and practical utility of soliton dynamics in fractional nonlinear systems. Full article