Physics

Achieving both high sensitivity and a wide operating frequency band is a challenge for acoustic emission (AE) sensors. This paper demonstrates the design of a dual-resonance AE sensor based on a piezoelectric lead zirconate titanate (PZT) disk-ring nested configuration. Firstly, the effects of the size parameters of the individual PZT disk and ring on the impedance spectra are investigated. The simulation results suggest that the radius of the disk and the width of the ring play more important roles in determining the resonance frequency. The bandwidth can be effectively extended by coupling the resonance peaks of the disk and the ring in the nested configuration. Moreover, the sensitivity is further optimized to a peak value of 99.5 dB over a wide bandwidth of 181–1000 kHz. The disk-ring nested configuration provides a solution for designing high-performance AE sensors.

Evaporation plays a critical role in ecological and environmental processes, yet computational investigations have thus far been limited by the lack of water models with quantum-mechanical accuracy that are also computationally efficient. To address this challenge, we employ the recently developed neuroevolution potential (NEP), which is trained on extensive many-body polarization (MB-pol) reference data and achieves a favorable balance between accuracy and efficiency. Using NEP-MB-pol in molecular dynamics simulations, we perform a systematic study of water evaporation. We first establish the vapor–liquid equilibrium, finding that the liquid and vapor densities at different temperatures, as well as the fitted critical points, are in excellent agreement with reference values, underscoring the predictive capability of the employed model. We then revisit the microscopic mechanism of evaporation. Our MD simulations show that an evaporating molecule must remain in a highly energetic pre-evaporation state for several 100 fs. A successful evaporation involves the cooperative interactions of at least four water molecules, with the last collision occurring within a short time window of ∼56 fs before evaporation. Finally, motivated by recent intriguing experimental observations, such as the photomolecular effect, we investigated the impact of external electric fields on water evaporation. In contrast to experimental findings, we did not observe a consistent effect from green light on water evaporation, i.e., the photomolecular effect was not reproduced. This may be attributed to the negligence of quantum effects in our simulation. Overall, our study provides new microscopic insight into the evaporation process and offers valuable guidance for experimental studies and potential industrial applications.

In an electromagnetic resonant cavity containing a magnetic element, the cavity and magnon modes can establish a dissipative-type coupling by their mutual coupling to a third, highly dissipative mode. This dissipative coupling has been predominantly observed in semi-open cavities coupled to traveling waves. Here, we show that contrary to common expectations, even in typical nearly closed cavities, both coherent and dissipative couplings exist and interplay to determine the behaviors of cavity and magnon modes. Furthermore, their different positional dependences allow one to manipulate their interplay by changing the location of the magnon system inside the cavity. This work significantly broadens the scope of systems in which dissipative coupling can be realized and manipulated.

The development of wireless communication has grown interest in the high-performance microwave-absorbing materials. This paper presents the design of a quad-band metamaterial absorber based on a hybrid resonator integrating elliptical and square rings. The unit cell of the absorber consists of a square split-ring resonator, an elliptical SRR, and a square resonant strip, with an FR-4 dielectric substrate and a continuous metallic ground layer at the bottom. Simulation results reveal that this structure achieves near-perfect absorption efficiencies of 99.41%, 99.99%, 99.93%, and 99.25% at the resonant frequencies of 6.41, 11.69, 15.55, and 17.82 GHz, respectively. The analysis of surface current and electric field distributions indicates that each absorption peak arises from distinct mechanisms, including the synergistic interaction between the elliptical ring and the inner resonant strip, as well as the dominant contribution of the external ring resonant structure. Angular response analysis demonstrates that the absorber maintains high absorption efficiency within the oblique incidence range of 0°–45°, exhibiting excellent angular stability. The equivalent circuit of the proposed MMA was designed using ADS software, which demonstrates the designability of the metamaterial absorber. The results were validated by both waveguide and arch reflectivity tests. Compared with previously reported counterparts, the proposed design features a simple configuration, flexible frequency band selection, and high absorption efficiency, thus holding promising application potential in the fields of microwave stealth and electromagnetic protection.

The purity of ferromagnetic chromium dioxide (CrO2) is critical for its applications and fundamental research. However, the presence of Cr2O3 contamination is frequently observed in CrO2 obtained commercially or prepared under ambient or low oxygen pressures. High oxygen pressure is crucial to keep CrO2 thermodynamically stable during preparation. In this study, the synthesis conditions for pure CrO2 were optimized by controlling oxygen pressure, temperature, and reaction time. Rod-like CrO2 particles with straight edges and an average length of 5 μm were successfully synthesized under an oxygen pressure of 13 MPa. Different from commercial CrO2 particles, no Cr2O3 layer was observed over the surface of the prepared CrO2 particles. The CrO2 powders showed a much lower coercivity and a much higher saturation magnetization than that of commercial CrO2, indicating high purity of the samples. X-ray photoelectron spectroscopy analysis further confirmed a +4-oxidation state of Cr on the surface of the CrO2 products. A symmetric derivative line with a relatively broad linewidth of 30.1 mT and a shifted g-factor of 1.96 was observed via electron paramagnetic resonance in CrO2 at 405 K, indicating strong electron correlations within the system. This study optimized the preparation process for large scale synthesis of pure CrO2.

Electrical discharge and electrochemical hybrid sinking machining (EDCSM) using a water-in-oil (W/O) nanoemulsion demonstrates high-quality machined surface and good machining accuracy. However, the specific machining mechanism of this technology remains unclear, lacking direct observational comparisons between machining phenomena and the multiphysics simulation model. To investigate the machining mechanism of EDCSM using a W/O nanoemulsion, this study employs experimental methods, multiphysics simulations, and high-speed imaging techniques to compare machining processes across different media. This study elucidates the advantages of the W/O nanoemulsion as a machining medium in electrical discharge machining and electrochemical machining (ECM) processes compared to kerosene medium and electrolytes, along with the synergistic mechanism of EDCSM. The results demonstrate that the W/O nanoemulsion exhibits significant advantages, revealing its dual characteristics of alternating discharge effects and electrolytic dissolution at the microscopic scale. High-speed imaging data reveal that discharge channels in the W/O nanoemulsion medium exhibit finer structures, shorter durations, and higher electrochemical localization. Microbubbles generated during discharge play a crucial role in regulating energy release within the localized reaction zone and facilitating the removal of molten products. Combined with multiphysics simulation results, this confirms the presence of larger discharge craters, fewer recast layers, and highly localized electrochemical machining phenomena, consistent with experimental observations.

Assessing and forecasting the long-term behavior of glass fiber-reinforced polymer (GFRP) rebars continue to pose significant challenges. To address this, the present study introduces a predictive framework aimed at estimating the retained tensile strength of GFRP rebars when exposed to alkaline environments. A total of 350 experimental data points were collected through keyword-based literature retrieval and subsequently augmented using a Gaussian Copula-based generative model. Six machine learning algorithms, combined with grid search and five-fold cross-validation, were employed to develop predictive models for residual tensile strength in alkaline environments. SHAP (SHapley Additive exPlanations) was used to conduct parameter importance and sensitivity analyses. Unlike prior ML-based durability studies that often suffer from data scarcity and limited generalization, this work uniquely integrates a statistical generative approach to rigorously expand small-scale experimental datasets while preserving their underlying physical correlations, thereby significantly enhancing model robustness. The results show that the Gaussian Copula model effectively captures the primary distributional characteristics of the experimental data, and that XGB (eXtreme Gradient Boosting) is the most suitable model for predicting residual tensile strength. Among the input parameters, environmental temperature has the greatest influence on residual tensile strength, while pH exhibits the least impact. Fiber content and rebar diameter positively affect residual tensile strength—higher values lead to greater strength. Conversely, higher pH, elevated temperature, and longer exposure duration negatively influence residual tensile strength. These findings on parameter importance and sensitivity provide valuable insights for durability studies of GFRP rebars.

Controlling the point defects that contribute to non-radiative recombination in GaInN/GaN quantum well structures has become more important recently. We have varied the growth temperature, thickness, and V/III ratio of the buffer layer and studied their influence on the non-radiative lifetime of the quantum well (QW). The results suggest that the point defect density in the QW can be reduced by controlling the defect formation and diffusion mechanisms. The point defect that is both diffusing and acting as a non-radiative center is likely a native defect, more specifically, a nitrogen vacancy. The likely sources of the vacancies are primarily the nucleation layer and the GaN substrate, in the case of heteroepitaxy and homoepitaxy, respectively, and secondarily the growing surface of subsequent layers, depending on the growth conditions.

Numerical simulations are conducted to study the effects of wind gusts on the aerodynamic performance of a two-dimensional variable-pitch vertical-axis wind turbine. The influence of gust period, gust amplitude, and average tip speed ratio on the aerodynamic performance and the power coefficient of wind turbines is systematically analyzed. Results show that under gust conditions, the power coefficient of the wind turbine initially increases and then decreases as the gust period increases, reaching its maximum value at a gust period of 5. The maximum power coefficients for both standard gust and negative gust are achieved at a gust amplitude of 8 m/s. The power coefficient attains its maximum value at a mean tip speed ratio of 0.5, corresponding to values of 0.37 and 0.30 for the standard gust and negative gust, respectively. Proper orthogonal decomposition is employed to perform modal decomposition of the flow field under both gust and uniform flow conditions, which reveals that gust-induced unsteadiness increases flow complexity compared to uniform inflow.

Graphene has emerged as a promising material for next-generation electronic and thermal devices owing to its exceptional charge transport and thermal conductivity. However, high-quality samples are predominantly obtained via mechanical exfoliation from graphite crystals, a process that inherently lacks scalability. Despite extensive efforts toward large-area synthesis, cost-effective approaches for producing high-quality, large-area, single-crystalline graphene with fast turnaround time remain limited. Here, we report the design, fabrication, and performance benchmarking of a rapid thermal chemical vapor deposition system capable of synthesizing epitaxial monolayer graphene under atmospheric pressure. The entire growth process, from sample loading to unloading, is achieved within 25 min with a temperature ramp rate exceeding 23 °C/s. Growth at atmospheric pressure eliminates the need for vacuum components, thereby reducing both system complexity and operational costs. The structural and electronic quality of epitaxial graphene is comprehensively characterized using Raman spectroscopy, selected area electron diffraction, and magnetotransport measurements, which reveal signatures of the quantum Hall effect in synthesized graphene samples. Furthermore, we demonstrate van der Waals epitaxial growth of palladium thin films on graphene transferred to Si/SiO2 substrates, establishing its single-crystalline nature over a large area and its potential as a versatile platform for subsequent heteroepitaxial growth.

Circuit breakers in converter station filter fields are critical protection and control components, and their operating condition directly affects the safety and stability of power transmission systems. In practical condition assessment tasks, field operational data are characterized by a severe class imbalance, where normal samples dominate and fault samples are extremely scarce, significantly degrading model accuracy and robustness. To address this challenge, an anomaly data augmentation approach based on a Conditional Wasserstein Generative Adversarial Network with Gradient Penalty (cWGAN-GP) is proposed. Multidimensional key features, including closing time and auxiliary switch operation time, are utilized. A small set of anomaly seed samples is first constructed using normal operation data combined with expert knowledge and manufacturer-defined thresholds. By introducing conditional constraints, the cWGAN-GP effectively learns the feature distribution of fault samples and generates high-quality synthetic data, thereby alleviating the imbalance problem. Furthermore, a Probabilistic Neural Network (PNN) optimized by the Dung Beetle Optimizer (DBO) is developed for circuit breaker health status identification. The DBO algorithm adaptively optimizes the key parameters of the PNN, improving classification performance. Experimental results demonstrate that the proposed framework achieves a macro F1-score of 88.21%, significantly outperforming benchmark models including Random Forest, ECOC-SVM, and XGBoost. The proposed method provides an effective solution to fault sample scarcity and offers a practical reference for intelligent condition assessment and operation and maintenance of power equipment.

The Hugoniot equation of state, elastoplastic transition, and spall behavior of the Fe–36Ni Invar alloy were systematically investigated over a pressure range of 3–33 GPa. The Hugoniot elastic limit was determined to be between 0.8 and 1.0 GPa. Within the investigated pressure range, the shock velocity (Us)–particle velocity (Up) relation is linear, expressed as Us=3.703+1.888Up. The spall strength of Invar, determined using the acoustic method, is found to increase with shock stress, ranging from 2.5 to 3.7 GPa.

Ciprofloxacin (CIP) was used as the target pollutant to examine its degradation by the Fe(II)/O2/sodium tripolyphosphate (TPP) system. Based on single-factor experiments, a central composite design combined with response surface methodology was employed to systematically investigate the effects of Fe(II) concentration, TPP/Fe(II) molar ratio, and pH on CIP removal efficiency, and a quadratic polynomial regression model was established. The results showed that the order of influence of the three factors on CIP removal efficiency was TPP/Fe(II) molar ratio > pH > Fe(II) concentration. The model exhibited a good fit (R2 = 0.9563) and, thus, demonstrated accurate predictive capability. The optimized conditions were determined as follows: a TPP/Fe(II) molar ratio of 2.45, a pH of 7.0, and a Fe(II) concentration of 15.8 mmol l−1. Under these conditions, a CIP removal rate of 91.7% was achieved after 20 min of reaction. The experimentally optimized TPP/Fe(II) molar ratio closely agreed with the theoretical stoichiometric ratio (2:1) required for the formation of the dominant complex [Fe(II)(TPP)2]4−. Quenching experiments indicated that the reaction follows a consecutive single-electron reduction pathway (O2 → ·O2− → H2O2 → ·OH), with ·OH being the dominant reactive species for CIP degradation, as evidenced by inhibition rates of 91.9%, 91.7%, and 96.9% upon addition of tert-butanol, benzoquinone, and catalase, respectively. This study provides both a theoretical basis and a technical reference for the treatment of CIP-containing wastewater using the Fe(II)/O2/TPP system.

The theoretical study of ion-acoustic solitary waves in collisionless unmagnetized plasma, which includes nonthermal electrons, nonthermal positrons, and warm relativistic positive ions, has been conducted considering relativistic effects γi≈Ovi6c6 using the reductive perturbation method. The relativistic effect γi≈Ovi6c6 shows a higher amplitude of solitons than that of the relativistic effect γi≈Ovi4c4. This study can be applied to astrophysical phenomena, such as pulsars and supernovae; plasma technology, including thrusters and fusion; and space exploration, involving solar wind and magnetospheres, thereby improving the comprehension of plasma dynamics.

Using a Green’s function approach, we present a thorough theoretical analysis of impurity band formation in wurtzite aluminum nitride (AlN) for the case of uncompensated n-type doping. A multiple-scattering approach is applied to the calculation of self-energies, correct to first order in the dopant concentration, from which electronic dispersion may be extracted. The unperturbed band structure of AlN is calculated according to a 4×4k·p Hamiltonian, which captures the anisotropy of all bands. Our findings demonstrate the influence of dopant concentration on impurity band dispersion, bandwidth, densities of state, and effective masses for n-type AlN. Without appreciable anisotropy in the conduction band, the observed donor band dispersion in AlN is itself nearly isotropic. To improve the design and functionality of AlN-based electrical and optoelectronic devices, this work offers a qualitative, conceptual foundation for further study of electrical contacting to n-type material and impurity band conduction.

Controlling the dielectric/semiconductor interfaces is essential for the development of semiconductor power devices. Gallium nitride (GaN) has attracted significant attention as a next-generation semiconductor owing to its superior properties; however, controlling the dielectric/GaN interface remains a critical challenge, unlike silicon (Si). In this study, we observed native oxides formed on both the c-face and m-face GaN surfaces after simple air exposure using scanning transmission electron microscopy. Oxygen diffusion into the Si crystal was significantly suppressed by the formation of a SiOx layer; on the other hand, gradual oxygen diffusion (Ga–N–O layer) with a depth of ∼2.0 nm into the GaN crystal was observed. Remarkably, a 1.5 times larger amount of oxygen was incorporated in the m-face GaN than in the c-face GaN. These findings provide key insights into the control of dielectric/GaN interfaces and may facilitate the development of GaN-based power devices.

Permanent magnet synchronous motors are widely used in various industrial applications due to their high efficiency and reliable torque generation. However, the permanent magnets in the rotor are highly sensitive to temperature, and continuous thermal stress can cause demagnetization, which leads to performance degradation and a shortened operational lifetime. Therefore, an accurate temperature prediction algorithm is essential for maintaining motor reliability and preventing irreversible magnetic loss. In this work, we propose novel methods for permanent magnet temperature prediction based on a sequence-to-sequence learning architecture. Unlike prior approaches that rely on extensive feature engineering or external environmental variables, the proposed methods employ only control-related electrical inputs together with past temperature values, which improves interpretability and facilitates the design of effective control strategies. Moreover, we incorporate probabilistic teacher forcing and attention mechanisms to further improve the stability and accuracy of long-horizon prediction. Through comprehensive evaluation under realistic operating conditions, we demonstrate that the proposed methods can achieve low prediction error and maintain valid prediction performance over a relatively long forecast horizon.

Chiral molecular magnets are attractive for next-generation sensing, information storage, and spintronic technologies. Here, we report the synthesis and characterization of the zero-dimensional enantiomeric copper halides (R/S-PPA)2CuX4 (X = Cl, Br) (PPA = phenylpropylamine), prepared via a slow solvent evaporation crystallization method. These materials consist of isolated [CuX4]2– tetrahedra embedded in chiral organic frameworks and exhibit intense and opposite circular dichroism signals with amplitudes up to ±100 mdeg. Although the inorganic lattice is structurally zero-dimensional with isolated [CuX4]2– units, effective three-dimensional magnetic connectivity is established via supramolecular superexchange pathways. The bromide analogue displays clear low-temperature ferromagnetic ordering, with a saturation magnetization of 8.72 emu g–1 (1.02 ± 0.03 μB/f.u.) and a Curie temperature of 9.7 ± 0.2 K. These lead-free 0D copper halides provide a low-temperature platform for chirality-magnetism and spin-dependent studies, and offer design guidelines toward higher ordering temperatures.

Esophageal squamous cell carcinoma (ESCC) remains a challenging malignancy due to limited therapeutic efficacy of conventional chemotherapy, which is often hampered by drug resistance and systemic toxicity. Ferroptosis, an iron-dependent regulated cell death mechanism, has emerged as a promising strategy for cancer treatment. Curcumin, a natural compound with demonstrated anticancer properties, faces significant clinical translation barriers due to its poor solubility and bioavailability. To address these challenges, we developed a tumor microenvironment-responsive nanogel microsphere (MCCH) system using DNA hydrogel and metal-organic framework (MOF) technology for codelivery of curcumin and cisplatin. We comprehensively evaluated the MCCH system's physicochemical properties, drug release profiles, and cytotoxicity. In vitro and in vivo experiments were conducted to assess its capacity for ferroptosis induction, malignant phenotype suppression, and tumor growth inhibition. The MCCH system demonstrated ATP-triggered drug release and potent ferroptosis induction in ESCC cells, as evidenced by glutathione depletion, accumulation of lipid peroxidation, and modulation of GPX4/ACSL4 expression pathways. In vivo studies showed significant reduction of tumor volume and inflammatory markers while maintaining low systemic toxicity. The MCCH system not only enhances curcumin's delivery efficiency but also synergizes with cisplatin to trigger ferroptosis through dual modulation of GPX4/ACSL4 pathways. This innovative approach represents a promising targeted therapy for ESCC with substantial clinical translational potential.

Achieving robust human-machine interaction in noisy, constrained, or speech-impaired environments remains a significant challenge for conventional voice-based systems. Here, we present a wearable, flexible, and multichannel piezoresistive interface capable of decoding laryngeal and submandibular motion during complex speech behaviors. The system integrates a micropyramid polydimethylsiloxane (PDMS) sensing layer coated with conductive polypyrrole (PPy) onto a multichannel electrode array supported by a flexible polyimide (PI) substrate, providing superior skin conformity, high strain sensitivity, and robust long-term stability. We developed a fully integrated hardware platform enabling four-channel synchronous data acquisition, wireless transmission, and real-time on-device processing. A modified Audio Spectrogram Transformer (AST) combined with a multichannel fusion mechanism enables end-to-end semantic recognition. Using a 14-word core English vocabulary, we constructed two structured datasets─Microphone and Vocal─comprising a total of 3,840 samples. The system achieved classification accuracies of 99.6% and 96.4%, respectively, highlighting strong generalizability, semantic clarity, and robustness against signal variability. Real-world evaluations confirm stable performance under motion, facial expressions, and background noise. By unifying soft materials engineering, flexible circuit integration, and multimodal deep learning, this work advances speech recognition in complex environments and offers a scalable solution for assistive communication, wearable AI, and silent interaction under extreme conditions.

Reducing Ir loadings in proton exchange membrane water electrolyzer anodes is critical for lowering capital expenses. Loading reduction could be achieved by improving the Ir activity via doping/alloying and/or the development of advanced microstructures. However, the anode porous transport layer (PTL) is a comparatively simple component whose properties also impact Ir utilization. Therefore, well-designed PTLs may also enable reduced Ir loadings. In this work, we survey eight PTLs from various manufacturers to observe their impact on cell performance at low (0.4 mg_Ir cm^-2) and ultralow (0.1 mg_Ir cm^-2) Ir loadings. The PTLs were characterized by their microstructural properties, including porosity, particle size distribution, and pore size distribution. Electrochemical cell performance was correlated to PTL morphology, and it was found that PTLs with lower porosities and smaller particle and pore radii enabled good performance even at ultralow Ir loadings. 1000-h durability testing indicated that using lower porosity PTLs can significantly improve durability behavior. A runaway voltage phenomenon was observed during durability testing of cells with ultralow Ir loadings, which was caused by increases in both anode and cathode overpotentials. Furthermore, we observed that the beginning of test performance of 0.1 mg_Ir cm^-2 cells correlates to the 1000-h degradation rates of 0.4 mg_Ir cm^-2 cells, suggesting that for the Ir catalyst used in this work, short-term testing at ultralow loadings can be used as an indicator of long-term degradation at higher loadings.

Rare-earth oxide-supported Ru metal catalysts are promising for NH₃ synthesis owing to a strong metal-support interaction. Modifying rare-earth oxides with a second metal offers an effective approach to tuning support properties, while systematic support engineering to enhance NH₃ synthesis performance remains scarce. In this work, a series of Ru/Ce_1-aLa_aO_<i>x</i> catalysts with varying Ce-to-La molar ratios were synthesized and evaluated for NH₃ synthesis. The NH₃ synthesis rate of Ru/Ce_1-aLa_aO_<i>x</i> exhibits a volcano relationship with an increase in the La content. The optimal Ru/Ce_0.7La_0.3O<i>_x</i> catalyst exhibits a remarkable NH₃ synthesis rate of 34.13 mmol_NH3 g_cat^-1 h^-1 with over 500 h long-term stability at 400 °C and 1 MPa, which is 1.65-fold that of Ru/CeO₂. Various characterizations reveal that La doping is beneficial to increase the charge density of Ru sites via facilitation of oxygen vacancy formation, which consequently ensures fast N₂ cleavage. In addition, the La doping can avoid hydrogen poisoning more effectively through enhanced hydrogen spillover, which together with promoted N₂ activation are responsible for high-performance NH₃ synthesis over Ru/Ce_0.7La_0.3O<i>_x</i> catalyst under mild conditions.

In this paper, we describe highly sensitive plasmonic hydrogen sensors that are based on plasmonic nanohole arrays in gold films coated with a thin layer of palladium. These plasmonic hydrogen sensors operate at room temperature, which is very important for hydrogen sensing, as sensing at higher temperatures can lead to possible fires or explosions, as hydrogen is a highly flammable and potentially explosive gas above a certain concentration. We describe low-cost compact hydrogen sensors that are fabricated over a large area using nanosphere lithography. These compact hydrogen sensor chips are integrated into miniaturized capsules along with small LEDs and photodetectors such that these capsules can easily be attached to flexible conductive wires and threads or can be attached to an electronic textile fabric. The plasmonic hydrogen sensors being proposed in this paper are not only highly specific to hydrogen but also have a low limit of detection in the low ppm range. We also demonstrate a textile fabric based plasmonic gas sensing system, having multiple plasmonic hydrogen sensors attached to conductive threads embroidered on an electronic textile fabric, which has not been carried out previously. In this article, we also demonstrate a wearable textile jacket with multiple embedded plasmonic hydrogen sensors. Moreover, we demonstrate a wearable jacket with embedded plasmonic gas sensors such that light sources (LEDs) of different wavelengths are employed for sensing, providing multiwavelength sensing results. Sensing in different spectral regimes can also allow verification of the sensing results with those obtained by using a spectrometer, possibly alleviating the need for employing a spectrometer for carrying out the gas sensing work.