Search Results (359)

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

To address the insufficient visible-light absorption of Bi₄O₅Br₂ photocatalysts, first-principles density functional theory (DFT) calculations were employed to systematically investigate the effects of I doping at different concentrations (12.5%, 25%, 50%, 75%, 87.5%, and 100%) on the geometric structure, electronic structure, optical properties, and photocatalytic CO₂ reduction performance of Bi₄O₅Br₂. Formation energy calculations and Ab initio molecular dynamics (AIMD) simulations indicate that the I-doped systems possess good thermodynamic and kinetic stability. Geometric analysis shows that I doping leads to a gradual expansion of lattice parameters along the c-axis (from 14.80 Å to 15.16 Å), due to the larger ionic radius of I⁻ compared to Br⁻. Electronic structure results reveal that all doped systems remain indirect band gap semiconductors, with the band gap decreasing from 2.56 eV for the pristine system to 2.25 eV at 87.5% doping. This reduction is mainly attributed to the progressive substitution of Br 4p states by I 5p states near the valence band maximum, which modifies the valence band structure. Differential charge density analysis shows electron transfer from Bi to I, enhancing local polarization effects. Optical property calculations demonstrate a pronounced red shift in the absorption edge and significantly enhanced absorption intensity in the visible region after I doping. The real and imaginary parts of the dielectric function also exhibit red shifts and increased peak intensities in the low-energy region. Gibbs free energy analysis indicates that the Gibbs free energy for *COOH formation decreases from 2.83 eV in the pristine system to 2.68 eV after I doping, while the free energy of the *CO intermediate decreases from 1.28 eV to 0.98 eV, significantly improving the CO₂ reduction pathway. This study provides a theoretical basis for improving the optical response and the thermodynamics of the CO₂ reduction reaction through halogen substitution, suggesting a promising strategy for enhancing the photocatalytic potential of Bi₄O₅Br₂. Full article

We report the study of Cur@HKUST-1 composites, obtained through one-pot infiltration of HKUST-1 with curcumin (Cur) as a guest-sensitizing molecule. Cur features a HOMO energy above the valence band (VB) of HKUST-1, enabling modulation of the electronic structure of the host framework by introducing additional energy states within the bandgap. Structural characterization, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA), confirmed successful guest incorporation and preservation of HKUST-1 crystallinity. An initial Cur amount of 50% (relative to the BTC linker) was added to the synthetic mixture, and differential UV-vis analysis has shown an infiltration efficiency of 28.0%, corresponding to an infiltration degree of 14% in the Cur@HKUST-1 composite, highlighting a challenging loading process, primarily due to the size and conformations of the Cur structure. Textural analysis revealed a reduction in surface area and pore volume, consistent with a high degree of guest infiltration. Optical properties evaluated by diffuse reflectance UV-vis spectroscopy revealed new absorption bands and a notable decrease of 1.83 eV in the bandgap energy from 3.68 eV (HKUST-1) to 1.85 eV (Cur@HKUST-1) due to guest molecule infiltration. Density functional theory (DFT) calculations supported the experimental findings, showing that guest HOMOs promoted the formation of a new valence band (VB), while the original VB remains lower in energy. Density-of-states analysis confirmed that the new VB originates from 2p orbitals belonging to the guest, while the conduction band remains predominantly Cu-based from the HKUST-1 framework. Photoelectrochemical characterization revealed that the guest-modified material exhibits an enhanced photocurrent response compared to HKUST-1. Cur@HKUST-1 displayed higher stability and stronger photocurrent density, attributed to its narrower bandgap and increased charge carrier density. These results demonstrate the potential of rational guest selection to engineer band structure and improve the light-harvesting performance of MOFs in solar-driven applications. Full article

Accurate prediction of hydrogen storage properties is needed for accelerating the design of body-centered cubic (BCC)-type V-based alloys, where the composition–property space is too large for trial-and-error experimentation alone. Here we report a stacking ensemble framework that combines XGBoost, Random Forest, Extra Trees, and Gradient Boosting as base learners with linear or ridge meta-learners, with hyperparameters tuned by a genetic algorithm (GA). Three descriptor strategies are compared across seven target properties: composition-only (C), property-only (P), and composition–property fusion (CP). On target-specific subsets containing 95–901 experimental records and 17 alloying elements (the smallest subset, 95 records, corresponds to maximum hydrogen capacity $C_{\max }$, which may limit model stability for that property), the best model for each target gives $R^2$ values from 0.865 to 0.981 (all metrics are from five-fold cross-validation; no independent external test set was employed); the P-type model for desorption plateau pressure reaches $R^2=0.981$. SHapley Additive exPlanations (SHAP) analysis shows that physically derived descriptors, including valence electron concentration, atomic size mismatch, and electronegativity difference, dominate in P and CP models, whereas Ti and Cr contents are the leading compositional features. A Non-dominated Sorting Genetic Algorithm II (NSGA-II) optimizer then ranks 3000 final candidate alloy compositions in six alloy families using four objectives: high predicted retention, high predicted cycle count, high predicted BCC phase ratio, and a low cost proxy; these candidates represent model-based predictions and await experimental synthesis and cycling validation. The V–Ti–Cr–Fe–Mn system contains the largest number of candidates with predicted retention above 99%, while Ti-free V–Cr–Fe–Mn–Al alloys provide low-cost alternatives in the model search space. First-principles calculations on four representative alloys only show that BCC structures are lower in energy than FCC structures by about 0.08–0.13 eV/atom and that hydrogenated structures exhibit clear charge accumulation around H sites, supporting the physical plausibility of the data-driven screening results, though density functional theory (DFT) validation does not replace experimental measurement of PCI curves and cyclic stability. Full article

Two-dimensional (2D) materials have emerged as a key platform for next-generation electronics due to their atomic thickness and tunable properties. Iron disulfide (FeS₂), known as pyrite, with a bandgap of ~0.95 eV, is suitable for solar energy applications. However, its performance is limited by defects in bulk crystals. Reducing FeS₂ to a single layer eliminates bulk defects and enables strain engineering of the bandgap. In this study, First-principles density functional theory (DFT) calculations are performed using the CASTEP code and the PBEsol functional to examine the structural, electronic, and optical properties of a distorted 1T′-phase FeS₂ monolayer. Full geometry optimization yields lattice parameters a′ = 17.594 Å, b′ = 3.20231 Å, c′ = 5.28091 Å, and Fe–S bond angles of ~75.8° and ~98.2°, confirming symmetry-breaking distortion. The monolayer is dynamically stable, showing no imaginary modes in the phonon dispersion, and remains structurally intact up to 1000 K in molecular dynamics simulations. The unstrained system has an indirect bandgap of 0.70 eV, with the valence band maximum at the Γ point (dominated by S-p states) and conduction band minimum near the X point (Fe-d states). Under mechanical strain (±4%), the bandgap decreases significantly: from 0.70 eV to 0.44 eV under +4% tensile strain along the y-axis, and to 0.53 eV under −4% compressive strain. Biaxial strain causes weaker modulation, reducing the gap to 0.66 eV (+4%) and 0.62 eV (−4%). Optical absorption exceeds 10⁴ cm⁻¹ for photon energies above the bandgap, with tensile strain causing redshifts and compressive strain inducing blueshifts. These findings demonstrate that 2D FeS₂ is mechanically robust, electronically tunable, and optically active, making it a promising candidate material for flexible strain sensors and photovoltaic devices. This work is intended to motivate and inform future synthesis efforts. Full article

We present a review of theoretical studies of the structure and reactions of N = 7 and N = 8 nuclei in the vicinity of ¹¹Li, carried out within a framework based on Nuclear Field Theory. The coupling of valence nucleons to low-lying surface vibrations of the spherical core plays a central role, giving rise to self-energy processes that renormalize single-particle states and transfer form factors, as well as to an induced pairing interaction arising from the exchange of collective vibrations, which renormalizes the bare pairing force. Excitation spectra and cross sections for one- and two-nucleon transfer reactions populating states in the quasi-continuum are calculated and compared with available experimental data. Collective excitations in the particle-particle channel are investigated, with particular emphasis on Giant Pairing Vibrations and on their damping mechanisms arising from coupling to more complex configurations and continuum states. Comparisons with other theoretical schemes are also presented. We conclude that a coherent understanding of experimental data requires the detailed consideration of particle-vibration coupling effects. Full article

Monolayer and few-layer MoS₂ are promising two-dimensional electronic materials, but proton irradiation can trigger ultrafast electronic excitation and charge transfer before defect formation. Here, real-time time-dependent density functional theory (RT-TDDFT) is used to investigate proton-induced electronic stopping and localized charge capture in monolayer and bilayer MoS₂ under normal incidence. Four impact positions are examined in monolayer MoS₂, namely, the hollow channel, the Mo–S bond center, and two trajectories close to Mo and S atoms. Under hollow channel incidence, the stopping power shows a non-monotonic dependence on proton velocity. When comparing the different trajectories, the hollow channel path gives the lowest stopping power, whereas the Mo–S bond center path gives the highest values, indicating strong sensitivity to the in-plane valence charge distribution. By contrast, the time-averaged localized captured charge decreases with increasing velocity and is generally largest for the close to Mo trajectory. Under the same hollow channel condition, the monolayer stopping power exceeds the bilayer value in the main stopping region, whereas the bilayer generally shows slightly enhanced localized charge capture. These results show that electronic stopping and localized charge capture are distinct but coupled microscopic components of proton-induced electronic response in MoS₂ and provide first-principles insight relevant to ion-beam processing and radiation-tolerant two-dimensional devices. Full article

Growing concerns about health and sustainability have increased interest in meat consumption and reduction. Emotions evoked during the consumption of meat and plant-based alternatives can significantly shape choices. This review examines theoretical and empirical evidence on emotions experienced during the consumption of meat and plant-based alternatives. Drawing on practice theory and the theory of constructed emotion, it proposes a mechanism through which emotions evoked during consumption influence subsequent decisions to consume or reduce meat. This narrative review first defines emotions and examines their role in meat consumption and reduction and then evaluates studies on emotions elicited by tasting meat and plant-based alternatives. The findings suggest that discussions around meat consumption evoke emotions of both positive and negative valence, which may create cognitive dissonance. However, during actual meat consumption, emotions of positive valence are most commonly reported. In contrast, plant-based alternatives tend to elicit emotions of negative valence, particularly when their sensory characteristics differ substantially from those of meat. This review hypothesises that emotions experienced during meat consumption generate prediction errors that update the brain’s internal model, thereby reinforcing or adjusting subsequent attitudes and choices. This mechanism is conceptualised as the Consumption-Emotion-Update (CEU) framework. Understanding how consumption-evoked emotions shape food choice behaviour may inform strategies aimed at promoting healthier and more sustainable diets. Full article

DNA conformational transitions in aqueous environments are strongly influenced by electrostatic interactions with surrounding cations. This review/perspective article summarizes the experimental findings reported during the last decade on the competitive/cooperative effects of cations with different valencies on DNA conformational behavior. Recent experimental studies based on single DNA observations have shown that divalent cations, such as Mg(2+) and Ca(2+), can inhibit DNA compaction induced by the trivalent cation spermidine (SPD(3+)), revealing that the effects of coexisting cations are not simply additive. Such competitive behavior cannot be adequately explained within the conventional Debye–Hückel framework, which predicts always additive electrostatic screening contributions from cations of different valencies. To elucidate the underlying mechanism of competitive effects, a theoretical framework has been proposed by extending the framework of current counterion condensation theory, which incorporates changes in translational entropy arising from the ion-exchange process between monovalent counterions and divalent or trivalent cations interacting with DNA as a highly negatively charged polyelectrolyte. In the theoretical framework, the increase in translational entropy arises from the ion exchange process between monovalent counterions and trivalent cations in the absence of divalent cations, whereas the presence of divalent cations diminishes the entropic gain associated with this exchange. By interpreting the recent experimental findings through the aid of the development of theoretical modeling, this review/perspective article provides a coherent insight on how coexisting multiple cations regulate DNA conformation. Full article

A developed method, based on the stationary second-order Rayleigh–Schrödinger many-body perturbation theory in an irreducible tensorial form, allows us to determine the most important core–valence, core, core–core, and valence–valence correlations for any atom or ion with an arbitrary number of valence and core electrons. This paper presents the Feynman diagrams that describe these correlations. Additionally, it provides the rules for obtaining algebraic expressions in an irreducible tensorial form for any Feynman diagram coming from second-order many-body perturbation theory. Whereas some types of the valence–valence and core–valence correlations are described by the three-particle Feynman diagrams, additional developments to calculate the spin-angular parts of these diagrams have been made to the program library librang of the Grasp2018 As an example of the application of the developed method, the atomic calculations of the energy level structure and transition data for Ar II are presented. Full article

We briefly review our recent theoretical progress on one-neutron ($1n$) halo nuclei in the mass region of 15 ≲ A ≲ 50 from microscopic structure to reaction observables, by combining the deformed relativistic Hartree–Bogoliubov theory in continuum (DRHBc) and its triaxial extension (TRHBc) with the Glauber reaction model. In such an effective scheme, we first succeed in reproducing the enhanced reaction cross sections and narrow longitudinal momentum distributions of both the heaviest $1n$ p-wave halo nucleus ³⁷Mg and the heavier ³¹Ne on a carbon target, which are loosely bound and well-deformed systems with dominant p-wave configurations of the valence neutron. To test its capability for the lighter halo cases, we select neutron-rich carbon isotopes as examples. It turns out that the DRHBc + Glauber approaches are still valid for the s-wave halo in ¹⁵C, while a better description of the ground state for ¹⁹C requires the inclusion of exchange terms and tensor forces via the deformed relativistic Hartree–Fock–Bogoliubov (D-RHFB) model.Finally, these approaches are applied to search for heavier $1n$ halo candidates. It was suggested that ^40,42Al are promising candidates as $1n$ p-wave triaxial halo nuclei and ^43,45Si as $1n$ p-wave axial halo nuclei with prominent shape decoupling from the oblate core. Our studies cast a new light on future experimental measurements for new halo nuclei. Full article

Magnesium antimonide (Mg₃Sb₂) has emerged as a promising high-performance thermoelectric material, yet its efficiency is fundamentally determined by intrinsic point defects. In this study, we present a comprehensive investigation of defects in the intermetallic compound Mg₃Sb₂ using first laws of thermodynamics and density functional theory (DFT) within the generalized gradient approximation (GGA). By calculating the energy of defect formation and the charge transition energy between energy levels, it was determined how the change in chemical potential associated with phase synthesis affects the phase stability and carrier concentrations. Calculations show that donor defects dominate in Mg-rich alloys, primarily antimony vacancies and magnesium atoms in interstitial positions. This means that in a phase with a slight magnesium excess, e.g., Mg_3.01Sb_1.99 at 1400 K, n-type conductivity dominates. In the opposite case, i.e., in an Sb-rich alloy, magnesium vacancies spontaneously form in the Wyckoff 1a position. These ionized acceptors induce strong self-compensation, blocking the Fermi level about 0.38 eV above the valence band maximum. As a result of this process, the Mg₃Sb₂ phase, at elevated temperatures, becomes the non-stoichiometric Mg_2.99Sb_2.01 phase, which causes the material to retain p-type conductivity and actively block doping-induced n-type conductivity. The conducted studies demonstrate that the homogeneity range of the Mg-Sb system, although traditionally considered narrow, has a significant impact on the semiconducting properties of the material. Furthermore, they also point to the need for continued research on high temperature in the area of synthetic defect engineering, interface engineering, and optimization of the thermoelectric properties of materials based on Mg-Sb alloys. Full article

This paper proposes an intelligent stress detection method based on convolutional neural networks and the DeepFace framework, addressing the challenges of increasingly prominent global mental health issues and the limitations of traditional psychological services in terms of early warning latency and coverage. A three-level cascaded strategy combining RetinaFace, MTCNN, and OpenCV is first employed for face detection and localization, and facial expression features are extracted via the DeepFace framework. By integrating Russell’s valence–arousal model with Lazarus’s cognitive appraisal theory, an emotion–stress mapping rule is constructed to convert seven-category emotion probability distributions into 1–5 scale stress values. The method employs a cloud–edge collaborative flow, with feature extraction performed at the edge and original images promptly destroyed to mitigate privacy risks. Experiments on public expression datasets indicate that the method achieves above 99% face detection accuracy, 84.99% emotion recognition accuracy, and 86.09% stress assessment consistency grounded in the emotion–stress mapping rule, with an average response time per frame of approximately 200 ms. Based on 233 multi-scenario surveys, some respondents show limited stress self-awareness, suggesting traditional self-reporting may have blind spots, and thus this method serves as a useful supplement. Full article

The twist angle serves as a geometric tuning parameter in two-dimensional layered materials, enabling modulation of interlayer coupling and band structures without altering the chemical composition. In this work, six commensurate twisted bilayer WSe₂ configurations with rotation angles of 0°, 9.4°, 13.14°, 21.9°, 27.8°, and 60° were systematically investigated using first-principles density functional theory. Structural optimization, together with calculations of electronic structures, density of states, charge redistribution, effective masses, and optical properties, was performed. The results show that AA (0°) and 2H (60°) stackings exhibit the largest and smallest interlayer separations, respectively, whereas intermediate twist angles yield similar average spacings but distinct local stacking registries. All configurations remain indirect-gap semiconductors, with the valence band maximum located at K and the conduction band minimum near the Q point along the K–Γ path. The band gap increases from 1.450 eV at 0° to 1.579 eV at 27.8°, before decreasing to 1.333 eV at 60°, indicating strong twist-angle modulation of interlayer coupling. Density-of-states analysis shows that the valence-band edge mainly originates from Se-p and W-d hybridized states, whereas the conduction-band edge is dominated by W-d states, with intermediate angles exhibiting enhanced band folding and localization features. Charge-density analyses further reveal notable interfacial charge redistribution, which is most pronounced at 9.4°. Optical responses in the in-plane directions are nearly identical and significantly stronger than those along the out-of-plane direction. Optical absorption mainly occurs in the ultraviolet region, with band-edge features appearing in the near-infrared range. Intermediate twist angles exhibit broader dielectric responses in the visible region and extended long-wavelength tails, indicating enhanced interband transition channels. These results demonstrate that twist-angle engineering enables effective tuning of electronic and optical properties in bilayer WSe₂, providing theoretical guidance for the design of tunable optoelectronic devices. Full article

Since the synthesis of ferrocene in 1951, metallocenes have attracted attention, making the accurate prediction of their electronic structure and ionization energy crucial for understanding their photophysical and electrochemical behavior in materials and in biological systems. Here, we combined Density Functional Theory (DFT), Complete Active Space Self-Consistent Field (CASSCF), NEVPT2 (N-Electron Valence State Perturbation Theory) and Coupled Cluster approaches (CCSD, DLPNO-CCSD(T)) to study the electronic structure, ionization energies (IEs) and absorption spectra of metallocene and metallocenium complexes in the gas phase and in THF implicit solvent. DFT IEs agree closely with NEVPT2 and DLPNO-CCSD(T) values and with experiment values (deviations 0.02–0.3 eV). For CASSCF and NEVPT2, the minimal active space of the d electrons at six orbitals is not enough for the accurate prediction of the IEs, while an extended active space incorporating all 3d metal electrons plus four ligand valence electrons into 15 orbitals improves the calculated IE values. In solution, computed oxidation energies (OEs) in THF reproduce experimental values and follow the Fe > Ni > Co ordering. Substitution of metallocene complexes with chromophore units results in similar OEs. Overall, the substitution effects remain modest: the effect of substitution on OE values results in differences up to 0.2 eV. These results clarify the effect of the metal center on IE and OE values and UV–vis absorption behavior. Full article