Physics

The rapid growth of artificial intelligence computing has intensified the demand for energyefficient hardware accelerators capable of large-scale matrix-vector multiplication. Resistive random-access memory has attracted significant interest for such applications due to its analog weight storage capability and compatibility with crosspoint array architectures. However, the sneak-path current remains a critical challenge that limits the scalability and reliability of highdensity RRAM arrays. In this work, a palladium (Pd)-MoS 2 based self-rectifying RRAM device was fabricated and experimentally characterized, and a physics-informed compact model is developed to quantitatively evaluate its sneak-pass current suppression capability at the array level. The device exhibited asymmetric bipolar resistive switching originating from Schottkybarrier-controlled carrier injection at the metal/MoS 2 interface. To accurately capture this intrinsic rectifying behavior, a modulated thermionic-emission formulation based on the Richardson-Dushman equation was incorporated into the conventional Lehtonen-Laiho framework. This formulation preserved the essential Schottky barrier physics while ensuring numerical stability in circuit-level simulations. The proposed compact model reproduced the measured current-voltage characteristics, including a rectification ratio of approximately 60, a memory window on the order of 10 3 , and stable bipolar switching behavior. Furthermore, by systematically varying key physical parameters, such as metal work function, MoS 2 electron affinity, and Fermi-level pinning factor, the model enabled predictive estimation of Schottky barrier height and corresponding rectification characteristics for various metal/MoS 2 combinations.

Flame sensors are widely deployed in different fire monitoring scenarios. Identifying the origin of the flame, the fuel, often relies on the ultraviolet (UV) spectral signatures emitted by excited radicals during combustion. However, UV flame sensors capable of spectral discrimination typically require complex optical and material designs, resulting in high fabrication costs that hinder their application. To address this limitation, we proposed a multi-channel semiconductor UV flame sensor design based on an Al2O3-TiO2 double-layered nanostructure. This architecture was formed sequentially via anodization processes. By tuning the geometric parameters of the nanostructure, a seven-channel sensor array was designed to exhibit distinct wavelengthdependent responses within the spectral band of 280-320 nm, covering the • OH and NO• emissions. Simulations showed that the proposed structure achieved high responsivities and high internal quantum efficiencies in the target band. On this basis, a convolutional neural network (CNN) was trained to perform single-peak spectral discrimination, achieving a classification accuracy of 91% with a 0.1 nm label spacing, with a mean peak-position error of 0.32 nm. A U-Net-based network was further employed for dual-peak spectral reconstruction, yielding an average peak-intensity deviation ratio of 7.4% and high-fidelity recovery of the underlying spectra. These results demonstrate a compact UV flame sensing approach that combines Al2O3-TiO2 nanostructures with machine-learning-based spectral inference to enable high-resolution spectral discrimination for practical flame monitoring.

The escalating generation of urban lignocellulosic waste poses significant environmental and resource management challenges, necessitating sustainable valorization strategies. This article critically examines the conversion of urban lignocellulosic biomass into molecularly tailored nanomaterials for targeted soil and wastewater remediation. Emphasis is placed on the synthesis methodologies, molecular engineering approaches, and the intrinsic physicochemical properties governing their remediation performance. Key factors influencing material characteristics, including pyrolysis temperature, heating rate, residence time, and feedstock composition, are systematically analyzed. Tailored nanomaterials produced at elevated pyrolysis temperatures exhibit enhanced microporosity, increased specific surface area, and greater hydrophobicity, favoring the adsorption of non-polar organic contaminants.Conversely, low-temperature derived nanomaterials, enriched with oxygenated functional groups, demonstrate superior affinity towards polar organic and inorganic pollutants via surface complexation, electrostatic attraction, and precipitation mechanisms. The review further addresses critical challenges such as feedstock variability, process scalability, environmental risks, and regulatory considerations associated with field-scale applications.Future research directions emphasize the precision design of nanomaterials for contaminantspecific remediation, process optimization for large-scale deployment, and comprehensive environmental impact assessments. Overall, this study highlights the transformative potential of urban biomass-derived nanomaterials in advancing sustainable environmental remediation technologies and contributing to circular economy frameworks.

As process nodes scale to the nanosheet structure, the continuous reduction in device dimensions and the introduction of vertical stacking structures pose new challenges for single-event effect (SEE) sensitivity. This work uses calibrated TCAD simulations to systematically investigate the effects of four key parameters-gate length, number of nanosheet stacks, sheet spacing, and drain voltage-on the single-event transient (SET) response of n-type nanosheet devices. By extracting the electron current integrals at the source and drain cross-sections, the relative contributions of the funneling effect and parasitic bipolar junction transistor (BJT) amplification mechanisms are quantitatively distinguished across different transient stages. The results reveal that the SET response exhibits a two-stage behavior: a prompt peak dominated by the funneling effect and modulated by gate length, drain voltage, and sensitive volume, and a delayed tail governed by the parasitic bipolar amplification, which depends on the intrinsic properties of the device structure. Reducing the gate length renders the parasitic BJT effect in the peak stage non-negligible. Increasing the number of stacks induces a nonlinear BJT amplification effect in the tail stage. The impact of sheet spacing on SET response is found to be minor. Drain voltage modulates only the peak stage without altering the tail attenuation characteristics. The two-stage mechanism elucidated in this work provides a physical foundation for radiation-hardened design in gate-all-around (GAA) devices.

Periprosthetic joint infection (PJI), a challenging complication of arthroplasty, is usually treated/managed using antibiotic-loaded PMMA bone cement. However, this cement has many shortcomings, such as a low cumulative amount of the antibiotic released by the time the release is exhausted and ineffectiveness against some bacteria that are present in many PJI cases, such as methicillin-resistant Staphylococcus aureus (S. aureus). As such, there are many ongoing research programs focus on developing alternative cement formulations without compromising their mechanical and curing properties. The present study evaluates the antimicrobial, mechanical, and curing performance of PMMA bone cement loaded with 0.5, 1.0, or 1.5 wt.% Cu nanoparticles (Cu NPs) against Escherichia coli (E. coli) and S. aureus (concentration: 2.0 × 10⁶, 3.0 × 10⁶, and 7.1 × 10⁶ CFU/mL). Analysis of the nanoparticles using scanning electron microscopy (SEM), X-ray diffraction (XRD), and dynamic light scattering (DLS) found they were nanocrystalline and had a mean hydrodynamic diameter of 114 nm. Evaluations of the antimicrobial performance of the cement, using the Kirby-Bauer disc diffusion method, showed that, for a given combination of bacterial species and concentration, the diameter of the inhibition zone on cement specimens increased with an increase in Cu NPs loading of the cement. The compressive testing revealed that the incorporation of Cu NPs did not significantly affect the compressive strength or elastic modulus of the cement. In addition, a decrease in the maximum curing temperature was observed with an increase in Cu NPs loading, while the setting time remained without significant differences. These findings suggest that a PMMA bone cement loaded with either 1.0 or 1.5 wt.% Cu NPs may be suitable for the treatment and management of PJI. Future studies of this cement are warranted.

Thickness is a critical yet often overlooked degree of freedom governing both charge transport and surface reactivity in two-dimensional (2D) semiconductors. Here, we elucidate the thickness-dependent coupling between carrier transport and NH₃ sensing in multilayer MoS₂ field-effect transistors with controlled layer numbers. The field-effect mobility exhibits a pronounced nonmonotonic evolution, increasing from 0.13 cm² V⁻¹ s⁻¹ (6 layers) to a maximum of 20.1 cm² V⁻¹ s⁻¹ at ~21 layers before decreasing at larger thicknesses, reflecting the competition between interfacial Coulomb scattering, dielectric screening, and interlayer transport limitations. In stark contrast, the NH₃ sensing response shows a monotonic decrease with increasing thickness, with the 6-layer device delivering a response as high as 466.17% at 160 ppm. This inverse correlation arises from the progressive decoupling of surface adsorption from bulk transport due to enhanced electrostatic screening and reduced participation of inner layers. By directly linking thickness-dependent scattering physics with surface charge-transfer modulation, this work establishes a unified framework for understanding and engineering the trade-off between transport efficiency and sensing sensitivity in multilayer MoS₂. These findings highlight thickness as a key design parameter for optimizing 2D semiconductor devices across electronic and sensing.

We develop a four-band tight-binding model for monolayer 1T'-MoS 2 under a perpendicular electric field (PEF), which reproduces the non-parabolic band dispersion, field effects, and spin texture in agreement with first-principles calculations. Using this model, we show that charge carriers in nanoribbons exhibit net spin polarization solely along the s x direction, with the s y and s z components canceled by mirror symmetry σ yz h . The spin conductance of 1T'-MoS 2 nanoribbons is calculated using the non-equilibrium Green's function (NEGF) method combined with the tight-binding model, revealing that the s x -polarized spin conductance induced by the PEF remains robust against impurities when the Fermi level is located within the topological band gap.

In the era of digital transformation characterized by the deep integration of artificial intelligence and the Internet of Things, human-machine interaction systems have become ubiquitous in smart architecture and urban security. As the primary security interface, intelligent access control systems face unprecedented challenges. Traditional biometric technologies, such as facial recognition and fingerprint scanning, not only rely heavily on external power sources but also encounter critical limitations regarding privacy risks and environmental sensitivity. To address these issues, this study develops a self-powered bimodal sensor based on a single-electrode triboelectric nanogenerator, providing a low-power, high-security, and multidimensional sensing solution. The core of the sensor lies in its sophisticated functional structural design, featuring a polydimethylsiloxane triboelectric layer patterned with a micro-pyramid array, integrated with a copper foil electrode and a polyethylene terephthalate substrate. The device leverages the coupled effects of contact electrification and electrostatic induction to convert mechanical stimuli into characteristic electrical signals rich in material electronegativity and human kinetic information. To extract latent features from these complex waveforms, a deep learning framework based on a convolutional neural network is implemented to analyze and decouple the signals. Experimental results demonstrate that the system exhibits superior recognition performance in complex environments: in single-dimensional tasks, the accuracies for material identification and user authentication reach 99.83% and 98.88%, respectively. Even under a challenging scenario, the system maintains a high recognition accuracy of 96.15%. This work provides a robust technological foundation for future smart security, flexible electronic skins, and personalized healthcare monitoring.

Counterfeiting of integrated circuits is a major problem because of its potential to compromise the performance of critical infrastructure from healthcare devices to defence equipment and aerospace hardware. Therefore strong track-and-trace security features boards based on reliable light-responsive encryption security patterns are attracting great attention to be integrated into electronic boards and components. Here we present NaYF 4 and NaYbF 4 nano- and micro- particles synthesized by the solvothermal method, with different combinations of rare-earth doping ions (Yb 3+ , Er 3+ and Tm 3+ ), which give rise to tailored upconversion emission as a function of their composition and crystalline structure. An extensive structural and spectroscopic study by means of electron microscopy, X-ray diffraction and emission luminescence spectra of synthesized nanoparticles has been carried out. We also present proof-of-concept developments laser micromachined luminescent tags with unique upconversion luminescence patterns acting as “lightkeys”, more difficult to mimic by ever increasing sophisticated counterfeiters, to disregard non-original electronic components and chips.

Due to the large variety of different optical glasses with partially complex chemical composition on the one hand and the complexity of the polishing process applied for glass surface smoothing on the other hand, glass polishing is not yet understood in its entirety. Against this background, the impact of polishing on distinctly different glasses – fused silica, lanthanum crown glass, boron crown glass, and heavy flint glass – was investigated in this work. Manufacturing-induced surface contamination was detected using laser-induced breakdown spectroscopy and X-ray photoelectron spectroscopy. This includes minerals from the water used for suspension preparation as for example iron, calcium, and magnesium, wear debris from the polishing pad, i.e., zinc, nitrogen and carbon, as well as polishing agent material, namely cerium and lanthanum. It was observed that glasses with low alkali resistance suffer from a notably higher number and degree of impurities than glasses with high alkali resistance. This observation can be attributed to differences in interactions between the glass surface and the slightly alkaline polishing suspension. The results moreover indicate that as a trend, lower contamination occur for higher hardness and softening point of the particular glass. The observed effects suggest a dual-pathway model for manufacturing-induced contamination, either mainly governed by thermo-mechanical glass properties or driven by chemical reactions.

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Thermal transport in superlattices is particularly rich because it can exhibit three distinct transport regimes: coherent wave-like, ballistic incoherent, and diffusive propagation, each governed by different physical mechanisms. Coherent transport is especially promising for technological applications because it enables control of heat flow through band-structure engineering, interference effects, and phononic filtering in ways that are not accessible in purely diffusive materials. In this work, we investigate thermal transport across AlN/GaN heterostructure interfaces and superlattices using molecular dynamics simulations and the Atomistic Green's Function method in combination with a machine-learned force field potential. Our results are compared with analytical models and previous literature. For AlN/GaN interfaces, we find that inelastic phonon transmission contributes a significant fraction of the thermal boundary conductance, and we develop an inelastic extension of the diffuse mismatch model that accounts for all possible three-phonon processes. In the superlattice thermal conductivity, we observe a minimum at a period of approximately 2 nm, together with multiple signatures of partially coherent acoustic transport persisting even at room temperature. The results further reveal a fundamental contrast in the role of anharmonicity between isolated interfaces and periodic superlattices, where it enhances interfacial conductance in the former while suppressing thermal transport in the latter.

This study introduces benzoic acid (BA) as an unhomologous, O-donor modulator for the morphological engineering of the N-donor ZIF-67 framework. By systematically varying BA and linker concentrations, tunable crystal sizes (500–4000 nm) and distinct habit transitions were achieved while preserving the underlying sodalite topology. UV–vis spectroscopy, DFT calculations, and molecular dynamics (MD) simulations reveal that benzoate competitively coordinates to Co 2+ sites, regulating nucleation kinetics despite the chemical antagonism between carboxylate and imidazolate species. These structural modifications were tested for performance in the cycloaddition of CO 2 using epichlorohydrin, with the optimized catalyst exhibiting high conversion of CO 2 . This work establishes a robust structure–property relationship for modulator-directed MOF synthesis, demonstrating that nonconventional modulators are alternative tools for tailoring material functionality in carbon utilization.

Microbially induced calcium carbonate precipitation is a widespread natural phenomenon with numerous technical applications. Recent advances have shown that bacterial calcium carbonates (BCC) form nonclassically via amorphous calcium carbonate (ACC) precursors in the presence of organics, but the role of organics in the formation and nanostructural features of BCCs is not fully understood. Here we show that two bacterial strains produce BCCs with diverse textural and structural features at the macroscale but similar at the micro and nanoscale. We show that bacterial organics guide precipitation of calcite, stabilizing ACC to produce nanogranular crystals and these organics are then trapped within the crystal, rather than being released as previously suggested. These organics are N-rich and create regions of low Z-contrast aligned perpendicular to the c -axis of the bacterial calcite crystal, yielding a “Swiss-cheese-like” mesostructure. Moreover, it is these occluded organics that lead to the distinctive biosignatures observed in BCC. Finally, we also observe crystalline 2D films, possibly proteins, templating the oriented crystallization of bacterial calcite. These ultrastructural features help to disclose how microbial CaCO 3 biomineralization takes place leading to improved technical applications and may provide fingerprints for their identification in nature.

Developing infrared nonlinear optical (NLO) crystals with practical application potential remains a great challenge. Here, by harnessing a hybrid supertetrahedral assembly strategy, we discovered a new infrared nonlinear optical material, Ba 5 Zn 3 Ga 2 Sn 2 Se 15, which crystallizes in the orthorhombic space group Ama 2. Its structure is based on the assembly of hybrid T2-type supertetrahedral clusters, forming a three-dimensional anionic framework built from one-dimensional hybrid [SnZn 3 Se 9 ] supertetrahedral chains and two-dimensional [SnGa 2 Se 8 ] anionic layers. This multicationic framework gives rise to the following properties: a phase-matchable SHG response of 1.3 × AgGaS 2, an experimental band gap of 2.27 eV, and a birefringence of 0.1055 at 1064 nm, which is sufficient for phase matching. Theoretical calculations indicate that the SHG response originates from distorted hybrid supertetrahedral units and asymmetric charge transfer along the M–Se bonds (M = Zn, Ga, Sn). The compound also exhibits congruent melting behavior, a prerequisite for growing large single crystals. This work suggests that hybrid supertetrahedral architectures are a viable platform for mid-infrared NLO materials.

Balancing large birefringence with ultraviolet (UV) transparency remains a central challenge in the development of birefringent crystals. Herein, we report two Sb(III)-based hypophosphites, Sb(H 2 PO 2 ) 2 Cl and Sb(H 2 PO 2 ) 2 F, and comparatively investigate their crystal structures and optical properties. Single-crystal X-ray diffraction analysis shows that Sb(H 2 PO 2 ) 2 Cl crystallizes in a wave-like two-dimensional (2D) layered structure, whereas Sb(H 2 PO 2 ) 2 F adopts a 1D chain structure. Optical measurements reveal that Sb(H 2 PO 2 ) 2 F exhibits a markedly enhanced birefringence of 0.205 at 546 nm, compared with 0.055 for Sb(H 2 PO 2 ) 2 Cl, in good agreement with DFT-calculated values of 0.211 and 0.041, respectively. Meanwhile, Sb(H 2 PO 2 ) 2 F retains a wide band gap of 4.81 eV and a short UV cutoff edge of 258 nm, indicating a favorable balance between optical anisotropy and UV transparency. Further structure–property analysis suggests that the enhanced birefringence of the fluoride is closely associated with the more favorable orientational efficiency of the stereochemically active lone pair on Sb 3+ . These results demonstrate that halogen substitution is an effective approach for tuning optical anisotropy in UV-transparent Sb(III)-based hypophosphites.

A method based on COSMO-SAC models for predicting the solvent effect on crystal morphology is developed in ADDICT, providing an efficient design and screening tool to study the morphologies of organic crystals in various solvents. Solvation free energies are estimated based on activity coefficients calculated by the COSMO-SAC models, and solvent-modified bond energies between growth units in the crystal surface can be obtained from the COSMO calculations. Application of the approach to mechanistic growth modeling of four crystal systems including olanzapine, rubrene, adipic acid, and ibuprofen provides evidence of the reliability of the proposed method, since all of the predicted morphologies are in good agreement with experimental results. This method in ADDICT can be used to rapidly screen crystallization solvents in the fields of pharmaceuticals, organic semiconductors, etc.

This work reports a dual-modulus microcone array for graded tactile sensing and intelligent slip detection. The asymmetric microstructure─comprising hollow and solid polydimethylsiloxane/carbon nanotube (PDMS/CNT) microneedle arrays with distinct Young’s moduli (460.8 kPa vs 581.2 kPa)─produces a hierarchical mechanical response fundamentally different from conventional single-modulus designs. This structural design yields high sensitivity (9.55 kPa –1 ) over a broad pressure range (0.1–450 kPa), fast response/recovery (68/51 ms), and durability exceeding 10000 cycles. The superhydrophobic surface (contact angle 156.5 ± 1.0°, sliding angle <2°) ensures stable operation in wet and variable-temperature environments (10–70 °C). Integrated with a one-dimensional convolutional neural network for slip detection and adaptive feedback control, the sensor enables real-time grip force regulation during delicate object manipulation, minimizing mechanical damage and contamination. This work establishes a materials platform that couples interfacial engineering with machine learning-enhanced perception, with implications for soft robotics, wearable electronics, and intelligent human-machine interfaces.

The investigation of dyes in perovskite solar cells (PSCs) is an emerging field, since dyes may introduce a range of effects beyond conventional light harvesting. However, the large number of possible materials and processing combinations make systematic investigation challenging. This study presents a hybrid and transferable strategy combining automated workflows and supporting manual evaluation to gain insights into the effects of dyes in PSCs. Using a near-infrared (NIR) dye and a typical lead halide perovskite, an automated synthesis-characterization workflow is demonstrated to be suitable for the evaluation of the effects of a dye either as a precursor additive or as a post-treatment material using photoluminescence as the key performance parameter. In addition, the automated synthesis-device fabrication-evaluation workflow can provide guidance for identifying a suitable concentration range of dye additives in precursor solutions. Computational results at density-functional theory (DFT) level and manually performed experiments suggest that the dye MK245 interacts with the perovskite and modifies its local or interfacial electronic environment. Integration of MK245 can significantly improve the device stability both in mesoscopic triple-layer perovskite solar cells and in conventional thin-film solar cells.

Image-guided thermal ablation has been included in the National Comprehensive Cancer Network (NCCN) guidelines of multiple solid tumors. However, insufficient ablation of larger lesions and thermal injury adjacent to major organs and tissues limit its clinical application. Besides, sublethal hyperthermia at the margin of ablation can induce an immunosuppressive tumor microenvironment and increases recurrence risk. These physical and biological limitations are linked to each other. We developed an injectable hydrogel MR@CaP@HA with in situ thermal insulation and dual-responsive (pH/GSH) chemo-immunomodulatory delivery. MR@CaP@HA hydrogel can create a thermal insulation area with a thickness of about 5-10 mm after injection in situ, keeping the surrounding tissues under 45 °C during ablation. The disulfide-cross-linked hyaluronic acid (HA) network degrades in a glutathione (GSH)-dependent manner, inducing gel-liquid transition and controlled nanoparticle release. The released MR@CaP (calcium phosphate co-loaded with MIT and R848) nanoparticles disassemble in an acidic environment, delivering mitoxantrone (MIT) and resiquimod (R848) in a dual-responsive manner. This dual-responsive delivery system induces robust immunogenic cell death and dendritic cell maturation and achieves macrophage M1 rate of 95% in vitro and 35% in vivo. With coordinated thermal modulation and programmable drug release, the integrated therapy sterilizes residual tumor cells and achieves complete tumor eradication in 50% of animals. This work establishes a material-driven platform that overcomes thermal safety and immune resistance barriers, offering a translational strategy to enhance procedural safety and long-term efficacy.

The widespread application of advanced multispectral detectors in surveillance and reconnaissance poses a serious threat to military equipment and personal safety. However, achieving comprehensive and effective camouflage across the visible (VIS) to infrared spectra and specific laser wavelengths, while maintaining efficient thermal management, remains a significant challenge. Herein, we propose a wavelength-selective thermal regulator (WSTR) that achieves excellent camouflage performance across a wide spectrum, including VIS, midwave infrared (MWIR, ε 3–5μm = 0.21), long-wave infrared (LWIR, ε 8–14μm = 0.17), and laser wavelengths (ε 1.06μm = 0.99, ε 1.55μm = 0.94, and ε 10.6μm = 0.91). The regulator emits a radiative intensity of 725.2 W/m 2 at high temperatures and 95.7 W/m 2 at relatively low temperatures. It achieves efficient thermal regulation through radiative heat dissipation via two nonatmospheric windows (ε 5–8μm = 0.60, ε 14–20μm = 0.63). Additionally, by varying the thickness of the ZnS film, a range of structural colors suitable for camouflage against different backgrounds can be achieved. Besides, this regulator employs a multilayer structural design that maintains stable spectral emissivity across a wide range of incident angles, thereby further enhancing the stability of its infrared camouflage performance. This study provides valuable insights and feasible solutions for the development of multispectral camouflage technology.