Search Results (9,789)

Developing sustainable lithium-ion batteries (LIBs) requires binder–carbon interfaces that combine mechanical compatibility, interfacial cohesion, and reduced environmental impact. In this work, density functional theory calculations were used to evaluate the interactions of representative binder monomers acrylonitrile (AN), pyrrole (PY), vinylidene fluoride (VDF), and tetrafluoroethylene (TFE) with pristine graphene and chitosan-functionalized graphene oxide (GO/chitosan). Structural, energetic, electronic, and topological features were analyzed using counterpoise-corrected interaction energies, frontier-orbital descriptors, molecular electrostatic potential maps, projected density of states, noncovalent interaction analysis, and quantum theory of atoms in molecules topology. Final interaction energies were obtained at the M06-2X/def2-TZVP level with Boys–Bernardi counterpoise correction to provide a more robust description of weak noncovalent adsorption. Most binder–surface interactions fall within a weak, near-thermoneutral adsorption regime. On pristine graphene, AN and PY exhibit weakly favorable adsorption, with minimum counterpoise-corrected interaction energies of −3.13 and −2.10 kcal mol⁻¹, respectively, whereas TFE and VDF show orientation-dependent, near-neutral behavior. GO/chitosan introduces oxygen-containing and amino functionalities that modify the adsorption balance, particularly for selected perpendicular configurations of fluorinated monomers, although the net stabilization remains modest. NCI, QTAIM, MEP, and PDOS analyses indicate that surface functionalization increases the chemical heterogeneity and directionality of local contacts; however, these local descriptors do not necessarily translate into strong global adsorption energies. Overall, the results identify GO/chitosan as a chemically tunable interface for binder–carbon compatibility in LIB electrodes and demonstrate the importance of triple-ζ, counterpoise-corrected calculations for evaluating weak binder–surface interactions. Full article

The complex morphology and optical anisotropy of anisotropic sea-fog particles make it difficult to accurately describe the multiple scattering behavior of polarized light. To overcome the insufficient coupling between polarization evolution and scattering direction in conventional Monte Carlo models, as well as their limited representation of particle parameters, this study proposes a polarization transmission model combining an improved Discrete Dipole Approximation with a direction-adaptive Monte Carlo method. In this model, the probability density function of scattering direction is constructed as a functional of the photon Stokes vector, enabling tight coupling between polarization state updates and photon propagation. Particle structures are refined by incorporating size, aspect ratio, Euler angles, morphological perturbations, and complex refractive indices. Meanwhile, an equivalent scattering kernel containing higher-order statistical moments is introduced to balance computational efficiency and physical fidelity. An indoor sea-fog polarization transmission platform was established to measure six incident polarization states at 450, 532, 671, and 808 nm. The results show over 80% agreement with model predictions and a root mean square error below 0.1. The study further indicates that circular polarization retains polarization better than linear polarization under high optical thickness, while longer wavelengths provide more stable polarization transmission. This framework offers theoretical support for polarization imaging and optical communication in sea-fog environments. Full article

Wearable and intelligent bioelectronic systems are emerging as a key enabling technology for continuous, non-invasive health monitoring, coupling physiological sensing with data-driven inference. Within this paradigm, electroencephalography (EEG) provides a wearable-compatible biosensing modality for capturing the pre-sleep neurophysiological dynamics linked to emotional regulation and sleep onset. Insomnia affects approximately 10–15% of adults worldwide and is often associated with dysregulated emotions and pre-sleep hyperarousal. Existing EEG-based affective and sleep-onset processing pipelines often rely either on deep-learning architectures with limited interpretability or on hand-crafted spectral descriptors with weak theoretical motivation. This study presents an exploratory proof-of-principle bioelectronic processing framework in which EEG sensing features are organized according to ANT-7 (artificial neurotransmitter seven-dimensional model), a neurotransmitter-inspired computational taxonomy introduced as a heuristic feature-design prior rather than as a validated neurochemical theory. The proposed feature set includes the alpha/theta power ratio, sample entropy, Higuchi fractal dimension, and phase-locking value extracted from the public DREAMER and DEAP datasets (23 and 32 subjects, respectively). SVM, Random Forest, and 1D-CNN classifiers are trained under subject-independent leave-one-subject-out cross-validation with strict within-fold normalization to prevent data leakage, and interpretability is assessed through SHAP values and permutation importance (PI). To stress-test whether this feature organization transfers beyond the affective benchmarks on which it is trained, classifier outputs are then related to sleep-onset latency in Sleep-EDF Expanded through a deliberately cautious cross-dataset transfer analysis. Within this protocol, the best model reaches 88.4% accuracy in three-class affective-state recognition (stress/neutral/relaxed; AUC-ROC = 0.93). As an exploratory secondary analysis, classifier-derived relaxation estimates show a statistically significant negative association with polysomnographic sleep-onset latency and improve over a single alpha/theta-ratio baseline; this cross-dataset result is reported as a proof of concept, not as a validated sleep-onset predictor. Interpretability analyses (SHAP and permutation importance) indicate that the learned feature rankings are internally consistent with the neurotransmitter-inspired feature design, a property we interpret as internal coherence rather than as independent confirmation of the taxonomy. Together, these elements outline a complete sensor-to-AI processing chain—from EEG biosensing, through neurotransmitter-inspired signal-feature extraction, to interpretable and computationally lightweight inference—designed for compatibility with low-density wearable EEG devices and edge deployment. However, EEG does not measure neurotransmitter concentrations, the study does not benchmark ANT-7 directly against competing taxonomies such as valence-arousal/circumplex or RDoC-inspired feature organizations, and the Sleep-EDF analysis should not be interpreted as evidence that the model measures a validated latent construct of sleep readiness. Accordingly, the manuscript should be read as a framework-validation study of one interpretable feature taxonomy, not as a theory-validation study of ANT-7 or as a clinical validation study. Full article

We present a first-principles investigation of the layered ternary manganese tellurides ${\mathrm{MgMnTe}}_2$, ${\mathrm{Mg}}_3{\mathrm{MnTe}}_4$, and ${\mathrm{MgMn}}_3{\mathrm{Te}}_4$ using density functional theory with GGA and meta-GGA functionals. The optimized tetragonal structures (space group No. 115) satisfy the Born elastic stability criteria, with the structural derivatives exhibiting enhanced ductility. Unlike analogous alkali-based half-metals, these systems emerge as ferromagnetic semiconductors featuring substantial energy gaps in both spin channels. The calculated total spin magnetic moments are strict integers ($5 {\mathrm{\mu }}_{\mathrm{B}}$ for ${\mathrm{MgMnTe}}_2$ and ${\mathrm{Mg}}_3{\mathrm{MnTe}}_4$; $15 {\mathrm{\mu }}_{\mathrm{B}}$ for ${\mathrm{MgMn}}_3{\mathrm{Te}}_4$), driven predominantly by localized Mn d-states. Although advanced meta-GGA functionals modulate the magnitude of the predicted band gaps, the overarching electronic topology and magnetic character remain highly consistent. Ultimately, their calculated elastic response and intrinsic ferromagnetic semiconducting behavior identify these phases as candidates for further theoretical and experimental investigation for spintronic applications. Full article

The main objective of this study is to obtain the average parameters of gas-discharge plasma when controlling the steady position of the bow shock wave (BSW) using the combined action of a gas discharge initiated by a current from an external source and a magnetic field near the frontal surface of the model. The studies were carried out using both experimental and numerical methods in xenon and air. A comparison of the numerical and experimental dependences of the relative distance of the steady BSW from the model on the discharge power showed good agreement. Based on the conducted flow modeling, taking into account the dependence of the adiabatic index on the degree of ionization and the degree of nonequilibrium, and using the theory of Burm et al., gas-discharge plasma characteristics were obtained, such as the degree of ionization and the degree of nonequilibrium, the electron density and the electron temperature in the absence and presence of a magnetic field. By this way an integrated experimental–computational system was formed in which the measured characteristics of the discharge and BSW, as well as the numerically obtained averaged plasma parameters in the impact zone, are combined with the theory of Burm et al. to clarify the thermodynamic state of the medium and determine the corresponding characteristics of the gas-discharge plasma. The obtained results can be used for assessing the characteristics of plasma gas dynamic and magnetohydrodynamic phenomena in high-speed flows; for example, in the development of control systems that take into account the influence of plasma parameters and the electric and magnetic fields. Full article

Liquid crystal (LC) is a key enabling technology for continuously phase-reconfigurable microwave devices, offering analogue-tuning capabilities distinct from discrete alternatives such as MEMS and p-i-n diodes. However, the insertion loss of LC-based phase shifters is inevitably influenced by conductor surface roughness—a factor often neglected in idealised simulations. This paper presents, for the first time, a rigorous numerical quantification of how metal surface roughness affects the insertion loss and phase shift of a 60 GHz LC-filled coaxial delay line (0–180° phase shifter) with radial conductor surfaces instead of conventional planar ones. Using full-wave finite-element simulations incorporating Groisse’s phenomenological model and Huray’s snowball model, four surface configurations are analysed at 54–66 GHz: perfectly smooth conductors, roughness on both inner and outer conductors simultaneously, and roughness applied to each conductor individually. Results show that roughness induces a measurable increase in insertion loss—worst when both conductors are rough—but its impact on differential phase shift remains minimal (<0.32°). Huray’s model predicts conductor losses 1.77 times higher than Groisse’s model, yielding more conservative metrics. For the insertion loss evaluation in Case 2 at 60 GHz under the reference isotropic LC state, Groisse’s model predicts 1.90921 dB, while Huray’s model predicts 2.16319 dB, a 0.25 dB discrepancy (12% uncertainty relative to the mean). The inner conductor dominates roughness-induced losses due to concentrated current density, suggesting prioritised surface finishing of the core line. This study isolates loss mechanisms in a coaxial LC structure, providing insights into low-loss reconfigurable devices. Practical PCB copper foil fabrication methods are also evaluated with quantitative analysis of non-ideal cylindrical geometries. Full article

Dixie Valley, located in west-central Nevada within the Basin and Range Province, is one of the most important geothermal systems in the western United States and an increasingly attractive target for critical-mineral exploration. The valley combines active extensional tectonics, major range-front and intrabasin fault systems, high heat flow, hydrothermal alteration, and thick sedimentary basins that may provide favorable conditions for the development of geothermal reservoirs and lithium-bearing brines or clays. This paper presents an integrated multiphysics interpretation of gravity, magnetic, helicopter-borne time-domain electromagnetic (HeliTEM), and magnetotelluric (MT) data from Dixie Valley, with emphasis on the Grover Point area investigated by the Basin and Range Investigation for Developing Geothermal Energy (BRIDGE) program. We apply joint Gramian inversion of gravity and magnetic data to recover mutually consistent density and magnetization models, including separate induced and remanent magnetization components. We also perform rigorous 3D inversion of HeliTEM data and cooperative 3D inversion of HeliTEM and MT data to obtain a resistivity model extending from the shallow basin fill to deeper fault-controlled geothermal structures. The integrated interpretation identifies low-density sedimentary basins, induced magnetization highs related to magnetic basement or intrusive rocks, remanent magnetization variations associated with basement architecture and hydrothermal alteration, and conductive corridors interpreted as clay-rich alteration zones and possible hydrothermal pathways. These results demonstrate that integrated gravity, magnetic, HeliTEM, and MT inversion can substantially reduce interpretation ambiguity and improve targeting of concealed geothermal systems and associated lithium resources in extensional terranes. Full article

Fused deposition modeling (FDM) of polylactic acid (PLA) is widely used, yet most parameter studies tune one mechanical property at a time and leave the conflicts between properties unresolved. This work treats three responses of FDM PLA together: ultimate tensile strength, flexural strength, and Shore D hardness. A Taguchi L9 orthogonal array varied infill density, raster angle, and layer thickness; signal-to-noise ratios and analysis of variance ranked the factors, linear regression linked the parameters to each response, and the NSGA-II algorithm mapped the trade-off surface between them. Layer thickness proved the leading factor for tensile and flexural strength, while hardness answered mainly to infill density; raster angle stayed weak for every response. The Pareto front showed that low infill favors tensile strength while high infill favors flexural strength and hardness, all at the finest layer setting, and these trends were converted into parameter guidelines for tensile-led, flexure-led, and balanced parts. The statistical limits of the screening design are stated openly, the flexural and hardness campaigns are flagged as provisional, and a replicated, standard-compliant confirmation study is set out as the next step. Full article

Phloroglucinol is an oxygen-rich aromatic precursor whose thermal evolution can yield emissive carbonaceous materials with excitation-dependent photoluminescence. However, the influence of the reaction atmosphere on its low-temperature transformation remains insufficiently understood. In this work, phloroglucinol was thermally treated at 200 °C under air or static vacuum for 5 and 10 h. The resulting materials were investigated by electron microscopy, energy-dispersive X-ray spectroscopy, Raman spectroscopy, steady-state and time-resolved photoluminescence, transient absorption spectroscopy, and density functional theory calculations. The reaction atmosphere mainly affected the early stages of structural evolution. Air-treated samples formed irregular networks of filamentous substructures, whereas vacuum-treated samples displayed more compact quasi-spherical aggregates with a fibrous internal organization. Raman spectra indicated the progressive transformation of crystalline phloroglucinol into a disordered carbonaceous network containing small sp²-rich domains. Optical measurements revealed violet/deep-blue and cyan emissive centers whose relative contributions depended on atmosphere and treatment time. Transient absorption supported a multi-center photophysical picture involving ultrafast relaxation, intermediate trapping or interconversion, and longer-lived decay. Calculations on representative molecular motifs identified furan-containing conjugated domains as plausible candidates for the violet/deep-blue centers and compact triangular phloroglucinol-derived structures for the cyan center. Overall, oxygen availability and treatment duration modulate the morphology and emissive-center distribution of phloroglucinol-derived carbonaceous materials. Full article

TLSs are ectopic, non-encapsulated aggregates of immune cells that develop de novo in non-lymphoid tissues in response to persistent antigenic stimulation and have emerged as clinically relevant features of many solid tumours. However, conventional TLS assessment based on presence/absence, density, or simplified maturation scales does not adequately explain why TLSs are associated with favourable, neutral, or even adverse clinical outcomes across tumour types and treatment settings. In this review, we synthesise the current biological, spatial, and clinical evidence and argue that TLSs should be interpreted not as static histologic findings but as functional immune niches shaped by three interacting axes: structural maturity, spatial localisation, and the functional immune context. We discuss how mature germinal centre-positive TLSs often reflect coordinated B-cell–T-cell cooperation and sustained antigen-driven anti-tumour immunity, whereas partially organised or suppressive TLSs may display transitional or immunoregulatory properties. On this basis, we propose a pragmatic, pathology-oriented conceptual framework that groups TLSs into three simplified functional states: TLS-A, representing mature effector TLSs with germinal centre activity; TLS-B, representing organised but incompletely matured or functionally intermediate TLSs; and TLS-C, representing TLSs dominated by regulatory or suppressive immune programs. We further place these states within recurrent tumour microenvironment archetypes and outline the rationale for a “proposed functional TLS score” integrating histopathologic and molecular readouts. Rather than introducing a definitive biological taxonomy, this framework is intended as a translational model for harmonising TLS interpretation, refining biomarker development, and supporting future studies on prognosis, immunotherapy response, and standardised pathology reporting in solid tumours. Because this framework is derived from a narrative synthesis of published evidence rather than from formal validation, it should be regarded as hypothesis-generating and requires prospective, tumour-specific validation before clinical implementation. Full article

The spatial pattern of building damage produced by an earthquake carries information that classical building-by-building vulnerability indices cannot capture. This study presents one of the first frameworks to use Topological Data Analysis (TDA), a set of methods that quantify the “shape” of data, to characterise the spatial topology of seismic damage across an urban building inventory. Using the geo-referenced centroids of buildings as a point cloud, a sequence of connectivity graphs (a Vietoris–Rips filtration) is built at increasing distance scales, and persistent homology is used to track which spatial features appear and disappear. From this we extract four interpretable descriptors: Betti numbers (the numbers of connected building clusters and of enclosed gaps), persistence entropy (a measure of how disordered the damage pattern is), total persistence (the combined lifespan of all topological features), and the Wasserstein-2 distance (how far the post-earthquake pattern has moved from the intact pre-earthquake pattern). These descriptors form a physics-informed feature vector that is used to predict the building-cluster damage state. The developed framework was trained, tested, and validated on 1490 buildings over seven post-earthquake scenarios. Lognormal fragility parameters were estimated with maximum likelihood estimation, and an Artificial Neural Network (ANN) and a Random Forest (RF) were retrained on the same 593-building training dataset for comparison. On the 847-building benchmark, the TDA framework reached 93.3% accuracy (95% CI: 91.4–94.9%), F1 = 0.921 (0.902–0.940), and AUC = 0.933, using a stratified 70/15/15 split (training = 593, validation = 127, test = 127). This is a 6.0-percentage-point gain over the retrained ANN and a 12.1-percentage-point gain over the HAZUS-MH index (McNemar p = 0.017). Damage was recorded on the six EMS-98 states DS0–DS5, with DS4 and DS5 merged into a single class to give a five-class taxonomy, and building-type-specific inter-storey drift ratio thresholds were validated against EN 1998-3 (Eurocode 8 Part 3). Exact Rips computation is practical only for clusters up to about 2000 buildings; for larger populations, a CGAL (Computational Geometry Algorithms Library)-based sparse approximation with O(N log N) cost is recommended. It seems that the topological descriptions of the damage field may provide predictive information above and beyond that given by density and ground motion intensity and offer a reproducible tool for post-earthquake screening. Full article

The dynamics of active particles are increasingly being leveraged to design and control micro-robotic swarms. Local interactions play a crucial role in the phase transitions of active particles; how the combined effects of alignment, short-range repulsion, and boundary interactions regulate their packing structure and collective order with different confinement scales remains less systematically explored. In this study, we investigate the packing of active particles within a confined region, focusing on the role of local interaction rules in shaping both the packing structure and the polar order parameter. The effects of key controlling variables related to local interaction rules, including interaction radius, repulsion radius, confined boundary radius, and noise strength, are numerically studied. Specifically, by comparing systems with and without velocity–alignment interactions, we reveal the role of alignment in dictating both structural and dynamical properties of the ensemble. To quantify the packing structure, we employ Voronoi tessellation to evaluate both local and global packing densities. The results show that strong confinement induces a jammed state in which alignment effects are suppressed, resulting in high global packing density and low polar order, regardless of the noise amplitude. Upon increasing the boundary radius beyond a critical threshold, the system unjams, enabling alignment interactions to significantly enhance both the polar order parameter and packing density. Interestingly, the relationship between global packing density and micro-structural parameters, such as coordination number and Voronoi tessellation metrics, is similar in the systems with and without alignment. Our results demonstrate that collective packing and phase behaviour of active matter are governed by the nontrivial interplay between alignment, confinement, and noise, with alignment interactions driving the transition from disordered to ordered states as geometric constraints are relaxed, offering critical insights for the design of targeted micro-robotic swarms and active microfluidic sorting systems. Full article

Magnesium-ion batteries have attracted extensive attention due to their abundance, high safety, and superior volumetric energy density. However, their development remains constrained by the sluggish diffusion of Mg²⁺ ions and the limited magnesium storage capacity of electrode materials. In this work, we systematically investigate the Mg storage performance and underlying mechanisms of monolayer MoS₂ anodes substitutionally doped with Cu, Ag, and Au at a concentration of 4% on the Mo sublattice. The results reveal that all three dopants maintain the structural integrity of the two-dimensional MoS₂ framework after optimization while introducing localized electronic states near the Fermi level, thereby enhancing Mg adsorption. Compared with intrinsic MoS₂, the doped systems exhibit markedly improved Mg binding. Sequential adsorption calculations indicate that, at the investigated 4% substitution concentration, Cu- MoS₂, Ag-MoS₂, and Au- MoS₂ can stably accommodate up to five Mg atoms, elevating the theoretical specific capacity to ~67 mAh/g while maintaining low open-circuit voltages during magnesium intercalation. Diffusion kinetics analysis further shows that Cu-MoS₂ possesses the lowest Mg migration barrier (0.25 eV), surpassing Ag- MoS₂ (0.38 eV) and Au-MoS₂ (0.61 eV). Considering both thermodynamic stability and ion transport kinetics, Cu- MoS₂ achieves an optimal balance among storage capacity, operating voltage, and diffusion performance, highlighting its promise as a high-performance anode material for magnesium-ion batteries. Full article

Lithium metal batteries (LMBs) represent the frontier of high−energy−density energy storage, promising gravimetric energy densities exceeding 400 Wh kg⁻¹ and volumetric densities exceeding 1000 Wh L⁻¹, substantially outperforming conventional lithium−ion batteries, which are constrained by the graphite anode. Despite growing interest in solid−state chemistries, liquid electrolytes remain central to near−term LMB development due to their superior ionic conductivity and compatibility with existing manufacturing infrastructure. However, practical commercialization requires solving several fundamental electrolyte design challenges, such as ensuring compatibility with both Li metal anodes and high−voltage Ni−rich cathodes, suppressing uncontrolled lithium deposition and dendrite formation, and maintaining compatibility with existing Li−ion manufacturing infrastructure. This review synthesizes advanced strategies in liquid electrolyte design that address these challenges, including solvent−family selection, fluorination and concentration engineering, and solvent−functionality engineering. Emphasis is placed on landmark studies demonstrating practical high−voltage, long−life−cycle LMB architectures with thin lithium anodes and lean electrolyte loadings, thereby establishing emerging benchmarks for commercial viability. Full article

Hydrogen-rich compounds under high pressure are promising for high-temperature superconductivity, but many high-$T_{\mathrm{c}}$ hydrides rely on rare-earth or alkaline-earth elements and remain difficult to tune chemically. Transition-metal hydrides offer an alternative platform because partially filled d states can modify the electronic density of states, metal–hydrogen hybridization, and electron–phonon coupling. Here, ${\mathrm{VH}}_3$ is used as a parent high-pressure transition-metal hydride framework, and Ti substitution is introduced as a chemically compatible way to tune the d-derived states near the Fermi level. Two ternary hydrides, ${\mathrm{Ti}}_3{\mathrm{VH}}_{12}$ and ${\mathrm{TiV}}_3{\mathrm{H}}_{12}$, are therefore constructed from the ${\mathrm{VH}}_3$ lattice and investigated by first-principles calculations at 200 GPa. Both compounds are thermodynamically and dynamically stable under this pressure condition, as indicated by formation energies, the Ti–V–H convex hull, and phonon spectra. Within the same ultrasoft-pseudopotential computational framework, ${\mathrm{Ti}}_3{\mathrm{VH}}_{12}$ and ${\mathrm{TiV}}_3{\mathrm{H}}_{12}$ yield Allen–Dynes $T_{\mathrm{c}}$ values of 42.1 K and 36.8 K, respectively, higher than the corresponding ${\mathrm{VH}}_3$ value. A norm-conserving cross-check for ${\mathrm{VH}}_3$ gives a different absolute value, indicating that the $T_{\mathrm{c}}$ estimates are method-dependent. Electronic structure analysis indicates that Ti incorporation shifts pronounced van Hove singularities close to the Fermi level, enhances the density of states, and changes the Fermi surface topology. These results suggest that Ti–V–H hydrides are a useful model system for examining how transition-metal substitution can couple structural stability with electronic tuning in compressed hydride superconductors. Full article