ABSTRACT In this paper, nonlinear stochastic differential systems with variable‐order fractional derivatives driven by noise are considered. The introduced framework will capture both the nonlocal memory effects and abrupt stochastic perturbations, hence becoming a general model for complex dynamical processes. First, we determine sufficient conditions that ensure the existence and uniqueness of solutions by applying the Picard successive approximation method within the stochastic analysis framework. The long‐term dynamics are then analyzed in detail, proving Mittag–Leffler Ulam–Hyers and Ulam–Hyers–Rassias stability by using a generalized Grönwall inequality and analytical properties of the Mittag–Leffler functions. Numerical simulations confirm the theoretical results and point out the effects of variable‐order operators and nonlinear growth functions on the stability of systems. The manuscript further develops existing models by incorporating variable‐order fractional calculus together with non‐Gaussian noise and provides a strong tool for analysis and control of such complex systems, also in finance, biology, and engineering.
ABSTRACT Intercalating metallic nanoclusters into layered materials provides a versatile strategy for tuning interfacial electronic coupling and charge redistribution at the nanoscale. Here, we investigate an Al nanocluster confined between MXene layers as a model metal–2D heterostructure using real‐time time‐dependent density functional theory and fragment‐resolved analysis. Ground‐state charge analysis reveals substantial electron transfer from the Al nanocluster to the MXene host, establishing a pre‐existing interfacial polarization. Under resonant optical excitation, induced charge densities, energy‐resolved carrier distributions, and transition‐contribution maps show that the response is dominated by near‐Fermi electronic transitions involving both subsystems. These transitions lead to selective carrier partitioning, with electron density preferentially associated with the MXene host and hole density retained on the Al nanocluster. The results identify nanoscale confinement and interfacial electronic coupling as key factors governing excitation‐induced charge redistribution in MXene‐based heterostructures.
ABSTRACT Hydrogen cyanide (HCN) is a highly toxic industrial compound that requires efficient sensors to prevent mishaps. In this study, nitrogen‐rich nanosheets and nanoribbons are investigated for HCN sensing applications using first‐principles computational methods. Our study proposes a novel dual‐strategy approach that leverages defect engineering for reversible room‐temperature sensing and nanoribbon edge chemistry for irreversible high‐temperature scavenging. HCN is adsorbed onto a pristine monolayer only through physical interactions, causing insufficient perturbation for reliable detection. Nevertheless, HCN molecules exhibit significant adsorption over the surface at the nitrogen vacancy site. Further, comprehensive investigation suggest that can be an effective material for HCN gas sensing. In addition, the HCN adsorption behavior on nanoribbons revealed that HCN molecules exhibit strong binding affinities at nanoribbon edges, suggesting their potential applications in filters or scavengers. The electronic structure and quantum transport properties indicate that a chemiresistance‐based electronic device for HCN detection is viable at room temperature, using with an N‐vacancy, with reasonable recovery times. Furthermore, the nanoribbons can serve as scavengers through the edge‐binding process, even at elevated temperatures. Such advancements can significantly enhance the development of sensors capable of identifying and responding to HCN.
ABSTRACT Two‐dimensional (2D) goldene has recently emerged as an intriguing metallic nanosheet, yet its electrochemical potential remains largely unexplored. Using comprehensive density functional theory (DFT) calculations, the present work demonstrates that goldene exhibits exceptional promise as a high‐performance electrode material for lithium‐ion batteries and supercapacitors. Pristine goldene shows excellent structural stability with a favorable cohesive energy of −2.63 eV atom −1 . Lithium preferentially adsorbs at the hollow site with moderate binding (−0.92 eV), ensuring reversible storage without clustering while preserving metallic conductivity. Goldene displays an ultralow Li‐ion migration barrier of only 0.046 eV, which is further reduced to 0.032 eV when in contact with ethylene carbonate medium, enabling rapid ion transport. At full lithiation, the system maintains metallic behavior and delivers a specific capacity of 174 mAh g − 1 and a volumetric capacity of 1.17 Ah cm − 3 finding application as electrode materials. AIMD simulations confirm robust thermal stability and Li + diffusivity of 3.00 × 10 −10 m 2 s −1 at 300 K. Moreover, goldene exhibits outstanding quantum capacitance, reaching 832.21 µF cm − 2 , surpassing graphene and several reported 2D materials. These results establish goldene as a versatile and highly promising electrode for next‐generation energy storage devices.
ABSTRACT Density functional theory (DFT) calculations were performed to investigate the synergistic enhancement mechanism of P doping and N vacancy modification on the hydrogen evolution reaction (HER) catalytic performance of g‐C 3 N 4 . Single modification offers only limited improvement in HER activity. The combination of P doping and N vacancy exhibits a synergistic effect. This synergy tunes the hydrogen adsorption free energy to ΔG H* = 0.05 eV, comparable to that of Pt(111) (ΔG H* = −0.09 eV). Electronic structure and charge analysis reveal the electron‐rich region from P doping and the electron‐deficient region from N vacancy undergo charge compensation. This process regulates the C 2p band center at the active site and balances the hydrogen adsorption‐desorption. The synergistic system narrows the bandgap and reduces the carrier effective mass. The H* diffusion barrier decreases to 0.42 eV, and the theoretical overpotential reaches 0.18 V, indicating a substantial improvement in kinetic performance. Phonon spectrum calculations show no imaginary frequencies, confirming dynamic stability of the system. Ab initio molecular dynamics (AIMD) simulations verify that the structure remains stable at 300 K and 500 K. This work provides a reliable theoretical foundation for designing efficient non‐metal catalysts for the hydrogen evolution reaction via water electrolysis.
ABSTRACT We propose a hybrid microwave‐optomechanical system enabling high‐efficiency, nonreciprocal conversion between optical and microwave modes. The design combines a superconducting microwave cavity (MC) capacitively coupled to a mechanically compliant ring resonator, which is side‐coupled to two optical waveguides. Synthetic magnetism, induced by phase‐controlled optomechanical interactions, breaks time‐reversal symmetry to achieve directional energy transfer. By optimizing pump detuning, power, and phase, we demonstrate reconfigurable nonreciprocity with >90% conversion efficiency and low noise, supporting bidirectional mode conversion. The system further functions as a tunable multimode circulator when mechanical damping rates are engineered. Our work provides a scalable platform for integrated quantum networks and microwave‐photonic interfaces, supported by a predictive theoretical framework for parameter optimization.
ABSTRACT Long‐term exposure to toxic gases causes severe health damage, making timely detection imperative. In this work, the sensing performance of CuFe‐BTC for CO, SO 2 , NO, NO 2, and N 2 O is investigated using density functional theory calculations. The results indicate that gases preferentially adsorb at Fe sites, enabling CuFe‐BTC to effectively detect different gases through changes in the absorption spectrum. There are two absorption peaks found at 434 and 480 nm for CO adsorption, with recovery times of 2.52 × 10 2 , 7.49 × 10 −1, and 1.26 × 10 −2 s under the temperatures of 470, 570, and 670 K, respectively. Furthermore, no absorption peaks are observed for SO 2 and NO adsorption. The recovery time of SO 2 adsorption is 2.65 × 10 −3 s at 298 K, while that of NO adsorption is 2.30 × 10 2 s and 1.65 s at 570 and 670 K, respectively. Additionally, an absorption peak at 581 nm is observed for NO 2 adsorption, with favorable recovery times of 9.98 s, 5.23 × 10 −2 s, and 1.31 × 10 −3 s at 470, 570, and 670 K, respectively. However, due to weak adsorption energy and short recovery time, CuFe‐BTC cannot detect the presence of N 2 O. Overall, this study demonstrates that CuFe‐BTC shows potential for effective detection of CO, SO 2 , NO, and NO 2 at appropriate temperatures.
ABSTRACT Polymorphic malware poses a persistent cybersecurity challenge due to its ability to dynamically alter its code structure while preserving malicious functionality, thereby evading signature‐based defenses. We develop an adaptive multi‐variant ordinary differential equation (ODE) framework that captures the co‐evolutionary dynamics between polymorphic malware and responsive defense mechanisms, integrating mutation‐driven variant switching with a feedback‐driven antivirus response. Using the next‐generation matrix approach, we derive the basic reproduction number and show that crossing induces a transcritical bifurcation separating eradication and persistence regimes. Global asymptotic stability of the disease‐free equilibrium is proved via the Castillo–Chavez–Feng–Huang framework. Endemic equilibria are analyzed through analytical arguments and reproducible numerical simulations, demonstrating that adaptive mutation pressure can sustain persistence even under strong defensive responses. The framework provides actionable theoretical insights for designing system‐level cybersecurity strategies.
ABSTRACT Two‐dimensional Janus materials have attracted considerable attention owing to their intriguing structural, electronic, thermal, and optical properties. In this work, density functional theory calculations were employed to systematically investigate the stability, thermal transport, electronic, vibrational, and optical properties of TaXY monolayers (X = S, Se and Y = O, N, P). Cohesive energy calculations confirm the thermodynamic stability of all considered Janus monolayers. Mechanical stability analysis reveals that TaSO and TaSeO are mechanically unstable, while phonon dispersion calculations demonstrate that only TaXO and TaXN monolayers are dynamically stable, whereas TaXP monolayers exhibit dynamical instability. The lattice thermal conductivity of the stable TaSN and TaSeN monolayers was investigated using both the Slack model and first‐principles phonon Boltzmann transport calculations implemented in Phono3py. The calculated lattice thermal conductivities at 300 K are 9.55 W/mK for TaSN and 6.99 W/mK for TaSeN. The comparatively lower thermal conductivity of TaSeN originates from enhanced anharmonic phonon scattering, reduced phonon group velocity, and stronger acoustic–optical phonon interactions induced by the heavier Se atom. Furthermore, the thermal conductivity decreases with increasing temperature due to enhanced phonon–phonon Umklapp scattering. Electronic transport calculations reveal that TaSeN exhibits superior thermoelectric performance compared with TaSN, achieving a maximum figure of merit (ZT) of 2.35 at 700 K. Vibrational analysis indicates that the metallic TaXO monolayers suppress Raman activity, whereas the semiconducting TaXN monolayers exhibit distinct Raman‐active modes. In addition, frequency‐dependent optical properties, including dielectric function, refractive index, optical conductivity, absorption coefficient, loss function, and reflectivity, highlight the promising optoelectronic potential of these Ta‐based Janus monolayers. The present findings suggest that TaSeN is a promising candidate for thermoelectric and nanoscale thermal management applications.
ABSTRACT This paper presents an ultrathin, narrow‐band metamaterial (MTM)‐based refractive index (RI) sensor in the terahertz (THz) domain for precise detection of several biomedical samples. The full‐wave electromagnetic simulation software, CST, is used to simulate and investigate the proposed design. The proposed design integrates Polytetrafluoroethylene (PTFE) between the multi‐segmented gold resonator structure and the ground plane of gold. The simulation findings reveal a single narrow resonance peak with absorptivity of 99.96% at a resonance frequency of 7.346 THz with an analyte layer of RI 1.33 as a basis. By varying the RI of the ambient environment from 1.35 to 1.40, high RI sensitivity of 2000 GHz/RIU, with a high‐quality factor (Q‐ factor) and detection limit (DL) of 349.81 and 0.0067 RIU, respectively, are achieved. It also displays a notable linear response ( R 2 = 0.981). The proposed sensor exhibits a high‐ Q‐factor of 317.65, 318.04 and 332.91 with outstanding sensitivity of 1714.3, 1500, and 1454.5 GHz/RIU, while detecting cancer cells, tuberculosis (TB) bacteria and dengue virus, respectively. These aspects of ultrathin geometry, narrow‐band near‐unity absorption and sustained excellent sensitivity reflect the innovative nature and practicality of the proposed work.
ABSTRACT Rapid socioeconomic development has intensified air pollution, making accurate air quality forecasting essential for effective pollution management and public health protection. However, short‐term PM 10 prediction remains challenging because of complex temporal dependencies, nonlinear pollutant–meteorological interactions, and rapidly changing pollution episodes. To address these challenges, this study proposes the AWE‐Bi‐GRU‐EA‐TCN‐LR hybrid framework, where Bi‐GRU captures bidirectional temporal dependencies, EA‐TCN extracts multi‐scale temporal patterns through enhanced attention, and Linear Regression (LR) statistically calibrates residual relationships. The framework is evaluated using hourly air quality and meteorological observations from an industrialized urban area. As a consequence of the estimate, the RMSE value of 17.740 obtained with the comparison model, the persistence model, was decreased to 12.228 in the proposed model, while the R 2 values were obtained as 0.786 and 0.899 in the same models, respectively. A number of different models were used in this research for the purpose of predicting PM 10 , and the Enhanced Temporal Convolutional Network (EA‐TCN) model was found to have a root mean square error (RMSE) value of 12.804. Consequently, this proposed synergistic model has the capability to generate accurate results while maintaining robustness in air quality forecasting using complex datasets in regions with different environmental characteristics and meteorological variables.
ABSTRACT In this work, we benchmark three leading composition based Machine Learning (ML) frameworks, MODNet, CrabNet, and a random forest model based on Magpie features, predicting the properties of battery electrode materials using the Materials Project Battery Explorer dataset. We evaluate these models based on predictive accuracy, visualize numerical features using two‐dimensional embeddings, and quantify performance using standard metrics. Our results demonstrate that CrabNet consistently outperforms the other models across all tests. To validate these findings, we employ bootstrap resampling and two cross‐validation (CV) strategies (leave one cluster out and stratified 5‐fold CV), comparing each model against a control baseline, using unseen experimental data as a hold‐out test. We also apply unsupervised clustering using t‐SNE and DBSCAN on physically observed features extracted from matminer, revealing coherent material groupings without prior labels. The final selected model consistently improves over controls, and we believe can be used as a early stage oracle for electrode materials composition screening. Our study aims to identify the error distributions and limitations of the approach, discussing the challenges with developing robust ML models. Despite these constraints, our findings suggest the final selected model is effective for early‐stage compositional screening.
ABSTRACT Accurate prediction of the properties of all relevant polymorphs is necessary for rational design of stable, high‐performance perovskite materials. While the discovery of cubic perovskites has been hastened by machine learning (ML), the orthorhombic (Pnma) phase needed for device performance at room temperature has been little studied due to its complicated structural distortions. This work addresses this gap by developing a specialized ML framework for orthorhombic ABX 3 halide perovskites. We assembled a curated dataset of 3000 Pnma structures and developed a set of 67 descriptors specifically describing octahedral tilting, anisotropic distortion, and electrical effects. A thorough benchmark of twelve algorithms revealed XGBoost to be the best model, yielding credible predictions for formation energy (test R2 = 0.939) and band gap (test R2 = 0.619). Interestingly, the recursive feature removal showed that a low‐dimensional electronic subspace controls formation energy, while the prediction of the band gap requires a complicated interplay of structural and electronic features. In contrast, prediction of thermodynamic stability (energy above hull) remained a challenge, revealing the limitations of existing compositional descriptors. This work introduces a verified and interpretable pathway for high‐throughput screening of orthorhombic perovskites and provides fundamental insight into the descriptor‐property connections governing different perovskite polymorphs.
ABSTRACT In the modern era, metasurfaces have gained significant attention for their potential in light manipulation, including focusing, bending, blocking, and wavefront control, as well as designing ultra‐thin optical components. Metasurfaces comprising high‐index dielectric nanostructures have emerged as an inevitable platform for high‐performance flat optical devices. Among these, a dichroic beam splitter is a crucial optical component that selectively reflects and transmits light based on the wavelength, enabling precise control over beam routing. In this work, we demonstrate a polarization‐ and angle‐tolerant metasurface‐based dichroic beam splitter that operates as a harmonic separator, efficiently separating the fundamental wavelength (1560 nm) and its second harmonic (780 nm) wavelength. Using a 2D array of gallium phosphide (GaP) cylindrical nanostructures, the proposed device exhibits high transmission at 1560 nm while simultaneously achieving near‐unity reflection at 780 nm over a bandwidth of approximately 168 nm. This device finds application in fluorescence microscopy, multispectral imaging and advanced laser systems due to its precise spectral selectivity in the near‐infrared regime. Beyond these applications, our result highlights a versatile design route to compact dichroic beam splitters that can replace conventional bulky optical devices, with promising prospects for on‐chip photonics and portable optical elements.
ABSTRACT The advancement of materials science increasingly focuses on predicting novel and functional materials, often driven by rapid screening enabled through density functional theory calculations. The current work on structural, mechanical, optoelectronic, photocatalytic, and thermoelectric X 2 LaAuI 6 (X = K/Rb/Cs) were analyzed using DFT. Crystal structure stability was confirmed through the phonon dispersion, while optoelectronic and thermoelectric properties were investigated using TB‐mBJ and SOC exchange‐correlation potentials, revealing that these compounds X 2 LaAuI 6 (X = K/Rb/Cs) are indirect with an accurate value of 2.28, 2.23, and 2.23 eV, respectively. The ductile nature of these materials was confirmed by Poisson's ratio and Pugh's modulus. The prominent absorption peaks in the near‐visible region underscore the suitability of these compounds for solar cells and optoelectronic devices. SLME calculations indicated efficiencies of up to 7.5%, further support their potential for photovoltaic applications. Thermoelectric calculations were assessed using semi‐classical Boltzmann theory (SCBT) across the temperature range of 200–1000 K. The materials exhibited promising ZT metrics at 1000 K, with values of 0.88, 0.86, and 0.89 for X 2 LaAuI 6 (X = K/Rb/Cs), respectively. These findings highlight the potential of X 2 LaAuI 6 (X = K/Rb/Cs) compounds for applications in solar cells, thermoelectric devices, and photocatalysis.
ABSTRACT We numerically demonstrate a broadband long‐wave infrared (LWIR) absorber with near‐zero visible–near‐infrared (Vis–NIR) absorption, enabling daytime radiative cooling with colored display. The structure comprises two patterned black phosphorus (BP) resonator layers separated by a dielectric spacer and backed by an optically thick metallic reflector. Although BP inherently exhibits strong in‐plane optical anisotropy, polarization‐ and angle‐insensitive behavior is achieved through the fourfold rotational symmetry of the metasurface unit cell. Full‐wave electromagnetic simulations show an average absorptance exceeding 98% across the LWIR (8–14 ) for both transverse electric (TE) and transverse magnetic (TM) polarizations, with stable performance for incident angles up to , while absorptance in the VIS–NIR range (0.4–2.5 ) remains below 5.5%. Under realistic daytime conditions, the resulting spectral emissivity yields a maximum net cooling power of approximately 94 W and a steady‐state temperature reduction of about 7.8 below ambient. Colorimetric analysis based on the CIE 1931 standard illuminant D65 confirms a warm‐yellow reflected appearance, demonstrating stable color display alongside efficient radiative cooling. The proposed BP‐based dual‐layer metasurface thus offers a compact, polarization‐ and angle‐insensitive, spectrally selective platform for infrared thermal management, daytime radiative cooling, and multifunctional photonic applications.
ABSTRACT Local coordination plays a crucial role in determining the activity and selectivity of transition‐metal single‐atom catalysts (TM SACs) for the CO 2 reduction reaction (CO 2 RR). Using density functional theory (DFT), we investigate the influence of B and N coordination on the catalytic performance of 3 d TM single atoms (Sc–Zn) stabilized on B/N‐codoped graphene (TM@B x Nᵧ–Gr, x + y = 4). We also look on the role of the adopted DFT functional in predicting the CO 2 RR efficiency of TM SACs supported on B/N‐codoped graphene, by assessing the performance of the widespread PBE functional against the self‐interaction corrected PBE+ U one. Our results show that the stability of TM SACs improves significantly with increasing N content in the coordination environment. Among the 30 TM SAC–support combinations examined, only a limited number are able to effectively activate CO 2 . We further investigate the competition between CO 2 RR and the hydrogen evolution reaction (HER). In addition, we examine the effect of explicit water molecules acting as ligands at the active site. Eventually, Fe@B 3 N–Gr is identified as an efficient catalyst for CO 2 RR to CH 4, and it remains stable under the strongly reducing conditions required for CO 2 RR.
ABSTRACT In this work, the unsteady heat and mass transport properties of a Casson fluid passing over an oscillating vertical cylinder embedded in a Darcy–Forchheimer porous medium are examined. The growing industrial application of oscillatory cylindrical systems in drilling operations, increased oil recovery, biochemical reactors, and polymer processing, where non‐Newtonian fluids interact with porous materials under periodic motion is the motivation behind this work. In order to effectively represent transport phenomena found in petroleum reservoirs, chemical mixing towers, food processing facilities, and heat exchange devices, this model integrates Soret and Dufour effects, viscous dissipation, chemical reaction, and heat generation/absorption. A dimensional partial differential system of equations is created by formulating the governing equations of momentum, energy, and concentration. The suitable transformations are then applied in the governing model to obtain the dimensionless form in terms of partial differential equations. To solve the equations numerically, a reliable and effective Crank‐Nicolson finite difference technique is implemented. The understanding of how to regulate heat and mass flow in porous geometries is made easier by this work. The effects of significant parameters on velocity, temperature, and concentration are investigated numerically and graphically.
ABSTRACT This work reports a density functional theory (DFT) study of the adsorption and desorption of hydrogen on the van der Waals (vdW) heterostructure (1QL)/Gr(ML). Three configurations are compared: pristine, single, and double Se‐vacancies. The calculations are performed along with the investigation of charge density distribution within a specific energy window. Our results indicate that hydrogen atoms chemisorb through the bond formation with the surface atoms. The adsorption energy, charge transfer, and electronic properties are analyzed to understand the interaction strength. The adsorption energies for one H atom on pristine and vdW heterostructures are –2.12 and –2.67 eV, respectively, while the system shows moderate adsorption (–1.03 eV) with moderate desorption time, indicating reversible hydrogen behavior. For multiple hydrogen adsorption (2H, 4H, 6H) on system, adsorption energy becomes progressively more negative, suggesting that the Se vacancy enhance hydrogen binding with increasing coverage. Desorption‐time calculations indicate excellent hydrogen‐sensing and recovery potential at elevated temperatures. Linear Dirac dispersion of graphene remains preserved near the Fermi level, and defected surfaces shows improved stability and reversible behavior highlighting their potential for hydrogen‐storage and catalytic applications.
ABSTRACT Hydrogen generation from seawater splitting has attracted increasing attention as a sustainable approach to achieve large‐scale, carbon‐neutral energy conversion while alleviating freshwater scarcity. However, the presence of chloride and other ions introduces side reactions, corrosion, and scaling that hinder catalytic performance and stability. In recent years, density functional theory (DFT) has become a key tool for understanding these challenges and guiding the rational design of efficient and durable catalysts. This review provides a comprehensive overview of DFT‐based research on seawater splitting, including statistical trends, representative findings, and emerging theoretical directions. Most DFT studies focus on Gibbs free energy analyses for oxygen, hydrogen, and chlorine evolution reactions, while others explore electronic properties such as density of states, d‐band center, and charge distribution. Theoretical results have clarified mechanisms underlying OER selectivity, Cl‐evolution‐reaction suppression, and corrosion resistance, complementing experimental insights. Finally, the review identifies major gaps in current modeling approaches, such as the lack of explicit solvent, dynamic stability, and ion effects, and outlines perspectives for integrating solvation and kinetics to enable rational catalyst design.
