Papers

The capabilities of a plug-flow fixed-bed cell for operando studies of heterogeneous catalysts are demonstrated using laboratory-based X-ray absorption spectroscopy (XAS) with a von Hamos spectrometer. The cell operates at temperatures up to 1000 deg C and pressures up to 10 bar, equipped with three mass flow controllers and two infrared lamps for rapid heating under inert/reactive gas atmospheres. Proof-of-principle studies include in situ MnO oxidation in 5% Ni/MnO and operando Ni nanoparticle evolution in 20-NiO/COK-12 (20.2% NiO on SiO2) during CO2 methanation before/after activation. Within 5-15 min per spectrum, oxidation state changes are resolved while catalytic activity is simultaneously quantified by online GC. Extended datasets and methods are available in the ancillary file SI.pdf (Supplementary Information file). A shortened version of this work has been published as a Technical Note in Journal of Analytical Atomic Spectrometry (2026, 41, 1208-1211, DOI: 10.1039/D6JA00027D). This manuscript provides an extended version including additional datasets, analysis, and methodological details beyond the published article.

We develop a microscopic quantum theory of surface plasmon polaritons valid for arbitrary metal-dielectric geometries. Our framework is based on the Power-Zienau-Woolley representation of quantum electrodynamics, which provides an optimal separation between electronic and photonic degrees of freedom and is therefore particularly well suited for constructing quantum descriptions of polaritonic excitations in strongly dispersive media. Within this formulation, the fundamental electronic oscillator is identified as the bulk plasmon mode, which is nonperturbatively coupled to the radiative continuum of free photon modes. This coupling induces a geometry-dependent renormalization of the bulk plasma frequency, giving rise to confined plasmonic resonances. As specific applications, we recover the localized surface plasmon modes of metallic nanoparticles, including radiative frequency shifts and decay, as well as the exact dispersion relation of propagating surface plasmon polaritons at planar interfaces. Our quantum treatment further reveals that light-matter interactions at metal-dielectric interfaces are inherently in the ultrastrong coupling regime. As a result, in the quasistatic limit, the system exhibits unconventional ground-state quantum fluctuations that can be controlled through the refractive index. These results open new intriguing perspectives in the field of quantum plasmonics.

Tungsten exhibits exceptional temperature and radiation resistance, making it well-suited for applications in extreme environments such as nuclear fusion reactors. Additive manufacturing offers geometrical design freedom and rapid prototyping capabilities for these applications, provided the intrinsic brittleness and low printability of tungsten can be overcome. Designing tungsten alloys with improved ductility, and thus printability in additive manufacturing, can be accelerated using a computationally derived performance predictor to screen out brittle compositions. Calculations of the Pugh ratio using density functional theory may serve this purpose, given its correlation with ductility. This process can be made more efficient through the use of machine learning interatomic potentials to accelerate density functional theory calculations. Here, we demonstrate that machine learning interatomic potentials can effectively identify optimal alloy compositions in the W-Ta-Nb system along the melting point-Pugh ratio Pareto front. The trend in Pugh ratio as a function of tungsten fraction is explained in terms of the electronic density of states at the Fermi level. Experimental validation reveals a strong correlation between the computed Pugh ratio and the observed crack fractions in additively manufactured alloys. Notably, the two alloys predicted to have the highest Pugh ratio values, W20Ta70Nb10 and W30Ta60Nb10, exhibit no intergranular microcracking in experiments.

With the growing interest in graphene field-effect transistors (GFETs) for biosensing applications, there is a strong demand for strategies enabling flexible and multiplexed biofunctionalization, as well as highly parallel, real-time electronic readout integrated with microfluidic control. Here we present a methodology that addresses these challenges by enabling real-time, parallel monitoring of multiple GFETs integrated on a single microfabricated chip within an automated electronic and microfluidic platform. We demonstrate the capabilities of this approach through ultrasensitive detection of the SARS-CoV-2 spike (S) and nucleocapsid (N) proteins. GFET chips are functionalized via van der Waals assembly using 1 nm-thick molecular two-dimensional (2D) materials - carbon nanomembranes - which enable multiplexed biofunctionalization. The chips are integrated into a custom-developed microelectronic and microfluidic system that allows parallel, real-time, and automated measurements of 15 GFETs. We present in situ biofunctionalization of the GFETs with antibodies, followed by highly specific detection of the S- and N-proteins with limits of detection down to 10 aM and a dynamic range spanning four orders of magnitude. Owing to its versatility, the presented methodology is readily adaptable for sensing a wide range of biological and chemical targets.

Using constrained-path quantum Monte Carlo, we map the ground-state phase diagram versus the nearest-neighbor (NN) attraction $V$ and spin-dependent hopping anisotropy $\alpha$ for the two-dimensional attractive $t$–$U$–$V$ Hubbard model at filling $n\simeq0.85$. We identify an onsite $s$-wave superfluid, a Cooper pair Bose metal with an uncondensed Bose surface, and an oriented equal-spin triplet $p$-wave pairing phase. The NN attraction activates the odd-parity channel, while hopping anisotropy suppresses the competing $s$-wave coherence and selects a $p_x/p_y$ polar axis, and thus lowers the critical $|V_c|$ for the onset of triplet-dominant $p$-wave pairing. A channel-resolved Landau analysis provides a criterion for the Landau $p$-wave scale $V_c^{\mathrm L}(\alpha)$, consistent with the observed anisotropy dependence of $|V_c|$. Our results establish how NN interaction and Fermi surface anisotropy cooperate to generate the oriented triplet $p$-wave pairing, and suggest that cold-atom and altermagnetic platforms could potentially realize this mechanism.

We have performed density functional theory (DFT) calculations to characterize the energetics, and the atomic and electronic structure, of stacking faults in GaN, both in the stable hexagonal wurtzite (wz) phase and in the metastable cubic zincblende (zb) phase. In wz GaN, SFs on the (0001) planes can be divided into three different intrinsic stacking faults (I1, I2, and I3) and oneextrinsic stacking fault (E). In zb GaN, SFs form along (111) directions, giving one type each of intrinsic, extrinsic and twin SFs. Based on the calculated formation energy, I1 is the most stable SF of wz GaN in agreement with experiment. For zb GaN, the intrinsic stacking fault is the most dominant planar defect. To characterize the effect of the stacking faults on the electronic structure of the material, we examined the band density. We found that the bands near the valence band maximum in wz GaN are localised on the Ga-polar side of the stacking fault (i.e. on the Ga side of the Ga-N bonds perpendicular to the SF), with the bands near the conduction band minimum more on the N-polar side, though somewhat delocalised. We found the opposite trend in zb GaN; this behaviour is caused by a redistribution of charge near the interface. We also show the band offsets for the stacking faults, finding that they are very sensitive to local conditions, but can all be described as type II interfaces, with the presence of a stacking fault reducing the gap locally.

Impact ionization probabilities were calculated in a CdHgTe quantum well, where the distance between electron subbands is close to the band gap energy. This band structure enables impact ionization with small momentum transfer for electrons in the second subband. The study demonstrates that such processes increase the impact ionization probability by approximately two orders of magnitude compared to the impact ionization probability for electrons in the first subband, for which transitions with small momentum changes are impossible. The probability of single impact ionization during the electron energy loss due to optical phonon emission is estimated. Experimental methods for detecting impact ionization in this structure are discussed.

We investigate the crystallization of crosslinked and entangled polymers under external deformation using a coarse-grained poly(vinyl alcohol) (CG-PVA) model and molecular dynamics simulations. Following uniaxial deformation, the systems are cooled at a constant rate to form semi-crystalline states and subsequently heated at a constant rate to induce melting. For unstretched systems, network junctions do not significantly affect the nucleation temperature but increase the amorphous fraction and reduce the melting temperature. Uniaxial deformation accelerates nucleation and markedly increases the crystallization temperature, with more strongly crosslinked polymers exhibiting larger shifts that correlate with an enhanced orientation order parameter. We further compare cooling and heating cycles under constant-strain and constant-stress conditions. Under constant stress, crystallization induces additional elongation beyond the initial pre-stretch and leads to pronounced mechanical hysteresis upon heating, a behavior characteristic of reversible shape-memory materials.

We investigate the formation of three-body bound states in the continuum by tracing pole trajectories in the complex energy plane under variation of system parameters. Using a one-dimensional model of two identical bosons and a distinguishable particle interacting via Gaussian potentials, we systematically vary the interaction strength, interaction range, and mass ratio. Our results confirm the parametric nature of few-body bound states in a continuum (BIC) and extend this characterization to a broader set of system parameters. Specifically, we find that variations of both interaction parameters and the mass ratio can lead to the formation of at least one three-body BIC. However, the exact shape of trajectories differs, and for the mass ratio variation we find a more regular pattern with multiple BIC locations. These results suggest that the mechanism of few-body BIC formation is more sensitive to the kinematic structure of the problem than to the specific details of the two-body interaction.

The strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation (meta-GGA) functional is a milestone achievement of electronic structure theory. Recently, a revised and restored form (r$^2$SCAN) has been suggested as a replacement for SCAN in high-throughput applications. Here, we assess the accuracy and reliability of the r$^2$SCAN meta-GGA functional for the group-IV elemental solids carbon (C), silicon (Si), germanium (Ge), and tin (Sn). We show that the r$^2$SCAN functional agrees closely with its parent functional SCAN for elastic constants, bulk moduli, and phonon dispersions, but the numerical stability of r$^2$SCAN is superior. Both meta-GGA functionals outperform standard GGA (Perdew-Burke-Ernzerhof) in terms of accuracy and approach the level of common hybrid functionals (Heyd-Scuseria-Ernzerhof). However, we find that r$^2$SCAN performs much worse than SCAN for the $\alpha\leftrightarrow \beta$ phase transition of both Ge and Sn, yielding larger phase energy differences and transition pressures.

The dynamic strength of concrete under complex loading conditions is a key consideration in the design and maintenance of infrastructures. To assess this mechanical property, Split Hopkinson Pressure Bar (SHPB) tests are typically adopted across a wide range of loading and confining conditions. In this study, mesoscale modelling based on the finite element method (FEM) is employed to simulate SHPB tests on three-phase concrete with realistic aggregate shape, in order to investigate the effects of loading ramp rate, internal friction, and confining pressure on the dynamic increase factor (DIF). Microscopic evidence to explain these effects is explored through analysing the distributions of the internal strain rate and local damage. As key results, increasing loading ramp rates, internal friction, and confining pressure can generally leads to higher DIF values. Only a higher loading ramp rate significantly amplifies the strain-rate effect on the DIF, as evidenced by pronounced increases in both internal strain rate and damage in the mortar and aggregate phases. In contrast, higher internal friction and confining pressure weaken the strain-rate effect on the DIF. Both can be attributed to the mortar phase, which shows a less pronounced increase in damage with increasing strain rate. This study enriches the understanding of the dynamic fracture of concrete toward complex loading scenarios.

In this work, we report that Bi2Ta3S6-family superconductors exhibit nontrivial band topology. They possess a natural quantum-well structure consisting of alternating stacks of TaS2 and honeycomb Bi layers, which contribute superconducting and topological properties, respectively. Symmetry-based indicators $(\mathbb{Z}_4;\mathbb{Z}_{2}\mathbb{Z}_{2}\mathbb{Z}_{2})=(2;000)$ reveal that the topological nature arises entirely from the Bi layers, which belong to a quantum spin Hall phase characterized by a $p_x-p_y$ model on a honeycomb lattice. The topological zigzag (ZZ) and armchair (AC) edge states are obtained. Using VASP2KP, the in-plane $g$ factors of these topological edge states are computed from the ab initio calculations: $g_{x/y}^{\mathrm{ZZ}}=2.07/1.60$ and $g_{x/y}^{\mathrm{AC}}=0.50/0.06$. The strong anisotropy of the edge-state $g$ factors allows us to explore Majorana zero modes in the Bi monolayer on a superconductor, which can be obtained by exfoliation or molecular beam epitaxy. The relaxed structures of the Bi2Ta3Se6, Bi2Nb3S6 and Bi2Nb3Se6 are obtained. Their superconducting transition temperature $T_c$ are estimated based on the electron-phonon coupling and the McMillan formula. Furthermore, using the experimental superconducting gap $\Delta$ and the computed $g$ factors, we obtain the phase diagram, which shows that the in-plane field $B_y>2.62\mathrm{ T}$ can generate corner Majorana zero modes in the Bi monolayer of the superconductor Bi2Ta3S6. A similar paradigm also applies to the Bi2Ta3S6 bulk with the emergence of Majorana hinge states. These natural quantum-well superconductors therefore offer ideal platforms for exploring topological superconductivity and Majorana zero modes.

Two-dimensional Janus structures have garnered rapidly growing attention across multidisciplinary fields. However, despite extensive theoretical and experimental efforts, a principle for designing intrinsic Janus materials remains elusive. Here, we propose a first-principles alloy theory based on cluster expansion, incorporating a strong repulsive interaction of a cation-mediated anion-pair cluster and refined short-range cluster-cluster competitions, to unravel the formation mechanism of intrinsic Janus structures with a distorted 1T phase among numerous competing phases. Our theory not only explains why intrinsic Janus structures are accidentally observed in RhSeCl and BiTeI which are composed of alloyed elements from different groups, but also accurately predicts a wide range of 1T-like intrinsic Janus materials that are ready for synthesis. Intriguingly, as demonstrated in the case of RhSeCl, we reveal that intrinsic Janus materials can exhibit anomalous second-harmonic generation (SHG) with a distinct quantum geometric effect, originating from strong lattice and chemical-potential mirror asymmetry. Furthermore, a novel skin effect unexpectedly emerges in finite-thickness RhSeCl, accompanied by a hidden SHG effect within the bulk region. Our theory paves the way for the ab initio design of intrinsic Janus materials, significantly accelerating progress in Janus science.

Controlling the photonic environment of emitters is essential to the design of classical and quantum light sources. We study the case of a dipole-like emitter in a cylindrical pillar etched into a planar Bragg microcavity, which is a common design of quantum-dot single photon source. In addition to the well-known cavity modes created by the high-reflectivity of the Bragg mirrors at small in-plane wavevectors, we show the presence of broad spectral features that play a key role in controlling photon collection efficiency and Purcell enhancement. These non-cavity modes are insensitive to the periodic index modulation of the Bragg reflectors, but arise from the cylindrical pillar geometry, as we show by comparison with simulations of uniform pillars, which reproduce the non-cavity modes. This approach provides a tool for understanding and modelling these often-disregarded decay channels as a function of source height, cavity dimensions and surface layers.

Recent studies have shown that certain antiferromagnetic (AFM) materials with the same symmetry breaking as ferromagnets can generate sufficiently large ferromagnetic (FM) responses. Here, we report that the new AFM material NbMnAs exhibits a large anomalous Hall effect (AHE) at zero field and at room temperature, despite having only a small net magnetization. A polycrystalline sample of NbMnAs, likely close to stoichiometric composition, exhibited an AFM state with a small spontaneous magnetization of approximately $6 \times 10^{-3} \mu_{\rm B}$/Mn and the AHE below $T_{\rm N}=354\,{\rm K}$. In contrast, single crystals of NbMnAs obtained by a flux method exhibited a deficiency at the As site, {which resulted} in a decrease in $T_{\rm N}$ and an increase in spontaneous magnetization. Although improvement of the single-crystal growth is still required, our study reveals that NbMnAs is a novel material capable of exhibiting significant FM responses derived from antiferromagnetism at room temperature.

We investigate how the coherence and spatial dressing of a single impurity evolve in the two-dimensional Bose-Hubbard model when the impurity couples attractively to the bath. Using large-scale, sign-problem-free worm-algorithm quantum Monte Carlo, we measure the impurity winding, bath superfluid response and compressibility, and impurity-bath density correlations. In a compressible superfluid bath ($U_{\mathrm{b}}/t=13.3$), strengthening attraction drives an interaction-controlled winding-collapse self-trapping crossover: a mobile light polaron evolves continuously into a heavy polaron and ultimately into a bound cluster with vanishing winding, while the bath remains globally superfluid. In incompressible Mott-insulating baths, by contrast, extended density rearrangements are suppressed and the dressing cloud collapses; we compare the resulting short-range deformation patterns for both attractive and repulsive couplings. Across the SF-MI transition at fixed moderate attraction ($U_{\mathrm{ib}}/t=-8.0$), the impurity crosses over from a mobile polaron with an extended deformation cloud to a nearly free defect with minimal dressing in the Mott background; for this coupling it does not lock into a fully self-trapped defect even deep in the insulator. Together with our companion Letter [Impurity Self-Trapping in Lattice Bose systems] on repulsive couplings, these results provide a unified microscopic picture of impurity self-trapping in correlated lattice bosons, connecting interaction-driven winding collapse in the superfluid to compressibility-controlled undressing across the SF-MI transition.

We map out the global phase diagram of a single mobile impurity in the two-dimensional Bose-Hubbard model, spanning the bath evolution from a compressible superfluid (SF) to an incompressible Mott insulator (MI) and the full range of impurity-bath coupling. Using sign-problem-free worm-algorithm quantum Monte Carlo, we identify two distinct self-trapping mechanisms that organize the entire diagram. In the compressible SF, increasing impurity-bath coupling $|U_{\mathrm{ib}}|$ drives an interaction-driven self-trapping crossover signaled by a collapse of the impurity winding number: a light, extended polaron evolves continuously into a heavy polaron and ultimately into a self-trapped state – a repulsive saturated bubble or an attractive bound cluster – even while the bath remains globally superfluid, demonstrating self-trapping without any bath phase transition. By contrast, when the bath is tuned across the SF-MI transition at fixed $U_{\mathrm{ib}}$, localization is compressibility controlled. The vanishing bath compressibility quenches long-wavelength density redistribution and suppresses polaronic dressing, converting the SF polaron into a weakly dressed, nearly free defect upon entering the MI when $|U_{\mathrm{ib}}| \le 8.0$. Then increasing $|U_{\mathrm{ib}}|$ triggers a distinct Mott-specific route: the impurity binds a quantized vacancy or particle excitation, manifested by discrete changes $\Delta N_b=\pm1$ in the total bath occupation. Together, our results provide a unified microscopic picture of impurity self-trapping in correlated lattice bosons, governed by winding collapse in the SF and by compressibility loss and defect quantization across the SF-MI boundary.

We present an extension to the two-dimensional functional renormalization group to efficiently treat interactions on the surface or at interfaces of three-dimensional systems. As an application, we consider a semi-infinite stack of two-dimensional square lattices, including a Hubbard interaction on the surface layer and an alternating interlayer coupling. We investigate how strongly correlated states of the decoupled two-dimensional Hubbard model on the surface evolve under inclusion of such an SSH-like interlayer coupling. For large parts of the phase diagram as a function of the interlayer hopping parameters, the physics of the two-dimensional system prevails, with antiferromagnetic, superconducting $d$-wave, and ferromagnetic correlations taking center stage. However, for intermediate interlayer couplings the superconducting state at intermediate interaction strengths separates into two regimes by a small region of incommensurate spin-density-wave and spin-bond order, enabling the potential realization of chiral spin-bond order.

Electrogenerated gas nanobubbles strongly influence the performance of electrochemical energy-conversion systems, yet their nucleation and early evolution remain poorly understood due to limitations of existing experimental and computational approaches. Operando imaging lacks the temporal resolution required to capture nucleation events, while molecular dynamics simulations are restricted to nanometer-scale domains containing at most a few bubbles. Here, we develop a thermodynamically consistent phase-field framework that unifies dissolved gas transport, curvature dependent interfacial thermodynamics, and implicit bubble nucleation within a single continuum description. Using hydrogen nanobubble formation during electrocatalysis as a canonical test case, the model captures nucleation without prescribing nuclei, resolves diffusion-controlled growth under curvature effects, and remains computationally tractable despite hydrogen's extremely low solubility. Simulations reveal how nanobubble nucleation occurs once a local supersaturation threshold is exceeded, triggering a reorganization of the chemical-potential field that focuses dissolved gas toward the nascent bubble. In multi-catalyst systems, overlapping diffusion fields lead to strong bubble-bubble interactions, including competitive growth, Ostwald ripening, and source occlusion. Extending the framework to dispersed catalyst populations shows that nanobubble survival is governed not only by catalyst size but also by spatial arrangement and diffusive competition, such that only a subset of bubbles persist while others dissolve and act as feeders. These results reframe electrogenerated nanobubbles as emergent, spatially organized features rather than unavoidable parasitic byproducts, and point toward electrode designs that deliberately control where bubbles nucleate and grow to preserve active area and mitigate transport losses.

Semiflexible polymers are ubiquitous in natural and artificial systems, where their intermediate rigidity gives rise to rich structural and dynamical behavior. Confinement plays a central role in these behaviors, as spatial restrictions can promote chain alignment, induce structural rearrangements, and enable complex self-assembly. While the organization of semiflexible polymers under rigid confinement has been extensively investigated, their behavior within deformable and dynamically evolving microenvironments, such as drying droplets or intracellular compartments, remains poorly understood. In this study, we use dissipative particle dynamics simulations to investigate the self-assembly of crowded semiflexible polymers confined within a deformable droplet, whose size may also change over time. By systematically varying polymer contour length, concentration, and degree of confinement, we identify distinct assembly regimes. Increasing polymer concentration promotes the formation of ordered fibrillar domains, with orientational alignment strongest near the droplet interface. Chain length critically dictates the morphology of assembled structures: short chains remain largely disordered, chains with intermediate lengths form linear fibrillar structures with maximal nematic order, and long chains assemble into circular bundles. Dynamic confinement further modulates the assembly through the competition between the rate of confinement change and polymer mobility. Slow increase in the degree of confinement allows polymers to reorganize into highly ordered structures, while rapid crowding kinetically traps the system in disordered states. Our findings elucidate how polymer mechanics and time-dependent confinement jointly govern the organization of semiflexible polymers in deformable, dynamic, and crowded environments.

Anomalous Hall effect studies on ultrathin Si(50Angstrom)/Fe(t_Fe) bilayers were performed at 300 K. Giant enhancements of about 60 times in saturation anomalous Hall resistivity and 265 times in anomalous Hall coefficient (R_s) were observed upon decreasing the Fe layer thickness t_Fe from 200 to 10 Angstrom. The R_s observed for t_Fe = 10 Angstrom is about three orders of magnitude larger than that of bulk Fe. The scaling law between R_s and longitudinal electrical resistivity (Rho) suggests that the side jump is the dominant mechanism of the anomalous Hall effect. The observed largest Hall sensitivity of 433 Ohm/T surpasses that of the semiconducting GaAs and InAs Hall sensors already reported.

A continuous route from a disordered soup of simple chemical feedstocks to a functional protocell – a compartment that metabolizes, grows, and propagates – remains elusive. Here, we show that a homogeneous aqueous chemical mixture containing phosphorus, iron, molybdenum salts and formaldehyde spontaneously self-organizes into compartments that couple robust non-equilibrium chemical dynamics to their own growth. These structures mature to a sustained, dissipative steady state and support an organic synthetic engine, producing diverse molecular species including many core biomolecular classes. Internal spherules that are themselves growth-competent are produced within the protocells, establishing a rudimentary mode of self-perpetuation. The chemical dynamics we observe in controlled laboratory conditions also occur in reaction mixtures exposed to natural day-night cycles. Strikingly, the morphology and chemical composition of the protocells in our experiments closely resemble molybdenum-rich microspheres recently discovered in current oceanic environments. Our work establishes a robust, testable route to de novo protocell formation. The emergence of life-like spatiotemporal organization and chemical dynamics from minimal initial conditions is more facile than previously thought and could be a recurring natural phenomenon.

SiO2/Fe/SiO2 sandwich structure films fabricated by sputtering were studied by varying the Fe layer thickness (t_Fe). The structural and microstructural studies on the samples showed that the Fe layer has grown in nanocrystalline form with (110) texture and that the two SiO2 layers are amorphous. Magnetic measurements performed with the applied field in in-plane and perpendicular direction to the film plane confirmed that the samples are soft ferromagnetic having strong in-plane magnetic anisotropy. The temperature dependence of magnetization shows complex behavior with the coexistence of both ferromagnetic and superparamagnetic properties. The transport properties of the samples as studied through Hall effect measurements show anomalous Hall effect (AHE). An enhancement of about 14 times in the saturation anomalous Hall resistance (R_Ahs) was observed upon reducing the t_Fe from 300 to 50 Angstrom. The maximum value of R_Ahs = 2.3 Ohm observed for tFe = 50 Angstrom sample is about 4 orders of magnitude larger than that reported for bulk Fe. When compared with the single Fe film, a maximum increase of about 56% in the R_Ahs was observed in sandwiched Fe (50 Angstrom) film. Scaling law suggests that the R_s follows the longitudinal resistivity (Rho) as, R_s proportional to (Rho)^1.9, suggesting side jump as the dominant mechanism of the AHE. A maximum enhancement of about 156% in the sensitivity S was observed.

Solid-state electrolytes (SSEs) are attractive for next-generation lithium-ion batteries due to improved safety and stability but their low room-temperature ionic conductivity hinders practical application. Experimental synthesis and testing of new SSEs remain time-consuming and resource intensive. Machine learning (ML) offers an accelerated route for SSE discovery; however, composition-only models neglect structural factors important for ion transport while graph neural networks (GNNs) are challenged by the scarcity of structure-labeled conductivity data and the prevalence of crystallographic disorder in CIFs. Here, we train two complementary predictors on the same room-temperature, structure-labeled dataset (n = 499). A gradient-boosted tree regressor (GBR) combining stoichiometric and geometric descriptors achieves best performance (MAE = 0.543 in log(S cm-1)), and Shapley Additive exPlanations (SHAP) identifies probe-occupiable volume (POAV) and lattice parameters as key correlations for conductivity. In parallel, we fine-tune large language models (LLMs) using compact text prompts derived from CIF metadata (formula with optional symmetry and disorder tags), avoiding direct use of raw atomic coordinates. Notably, Llama-3.1-8B-Instruct achieves high accuracy (MAE = 0.657 in log(S cm-1)) using formula and symmetry information, eliminating the need for numerical feature extraction from CIF files. Together, these results show that global geometric descriptors improve tree-based predictions and enable interpretable structure-property analysis, while LLMs provide a competitive low-preprocessing alternative for rapid SSE screening.

Anomalous Hall effect studies were performed at 300 K on Si/Fe multilayers prepared by dc magnetron sputtering. About 60 times enhancement in the saturation Hall resistance and 80 times enhancement in anomalous Hall coefficient are obtained in [Si(50 angstrom)/Fe(tFe)]_20 multilayers when decreasing the Fe layer thickness from 100 Angstrom to 20 Angstrom. The largest anomalous Hall coefficient (Rs) of 1.4 x 10^-7 Ohm m/T was found for t_Fe=20 Angstrom, which is about three orders of magnitude larger than that of pure Fe and Fe/Cr, Al/Fe, Cu/Fe, SiO2/FePt/SiO2 multilayers. The ordinary Hall coefficient R_0 was about two orders of magnitude larger than that of pure Fe. The R_s was found to vary with the longitudinal electronic resistivity, Rho as R_s proportional to (Rho)^2.2, indicating the role of interfaces for the enhancement of the anomalous Hall effect in the multilayers. An increase of Hall sensitivity from 9 mOhm/T to 1.2 Ohm/T is observed on decreasing tFe from 100 Angstrom to 10 Angstrom. The high Hall sensitivity obtained is about three orders of magnitude larger than that of Al/Fe and Cu/Fe multilayers, showing it as an emerging candidate for Hall element for potential applications.

Soft, stretchable organic field-effect transistors (OFETs) can provide powerful on-skin signal conditioning, but current fabrication methods are often material-specific: each new polymer semiconductor (PSC) requires a tailored process. The challenge is even greater for complementary OFET circuits, where two PSCs must be patterned sequentially, which often leads to device degradation. Here, we introduce a universal, monolithic photolithography process that enables high-yield, high-resolution stretchable complementary OFETs and circuits. This approach is enabled by a process-design framework that includes (i) a direct, photopatternable, solvent-resistant, crosslinked dielectric/semiconductor interface, (ii) broadly applicable crosslinked PSC blends that preserve high mobility, and (iii) a patterning strategy that provides simultaneous etch masking and encapsulation. Using this platform, we achieve record integration density for stretchable OTFTs (55,000 cm^-2), channel lengths down to 2 um, and low-voltage operation at 5 V. We demonstrate photopatterning across multiple PSC types and realize complementary circuits, including 3 kHz stretchable ring oscillators, the first to exceed 1 kHz and representing more than a 60-fold increase in stage switching speed over the state of the art. Finally, we demonstrate the first stretchable complementary OTFT neuron circuit, where the output frequency is modulated by the input current to mimic neuronal signal processing. This scalable approach can be readily extended to diverse high-performance stretchable materials, accelerating the development and manufacturing of skin-like electronics.

Stochastic gradient descent (SGD) is central to deep learning, yet the dynamical origin of its preference for flatter, more generalizable solutions remains unclear. Here, by analyzing SGD learning dynamics, we identify a nonequilibrium mechanism that governs solution selection during training. Numerical experiments reveal a transient exploratory phase in which SGD trajectories repeatedly escape sharp valleys and migrate toward flatter regions of the loss landscape before becoming confined to a final basin. Using a tractable physical model, we show that SGD noise reshapes the loss landscape into an effective potential that preferentially stabilizes flat solutions. We further uncover a transient freezing mechanism: as training progresses, the flattening landscape suppresses transitions between competing valleys. Stronger SGD noise delays this freezing transition, prolonging the exploratory phase and thereby increasing the probability of convergence to flatter minima. Together, these results provide a unified physical framework connecting learning dynamics, loss-landscape geometry, and generalization, and suggest guiding principles for the design of more effective optimization algorithms.

Electronic nematic and smectic liquid crystals are spontaneous symmetry-breaking phases that are seen to precede or coexist with enigmatic unconventional superconducting states in multiple classes of materials. In this Letter we describe scanning tunneling microscopy observations of a short ranged charge stripe (smectic) order in NaAlSi, whose superconductivity is speculated to have an unconventional origin. As well as this we resolve a clear spatial modulation of the superconducting gap amplitude, which arises due to the intertwined superconducting and smectic orders. Numerical calculations help to understand the possible driving mechanism as a suppression of kinetic energy on the Fermi surface formed in part by two large, flat-topped hole pockets of p-orbital character.

Accelerating alkali-ion battery discovery requires accurate modeling of atomic-scale kinetics, yet the reliability of universal machine learning interatomic potentials (uMLIPs) in capturing these high-energy landscapes remains uncertain. Here, we systematically benchmark state-of-the-art uMLIPs, including M3GNet, CHGNet, MACE, SevenNet, GRACE, and Orb, against DFT baselines for cathodes and solid electrolytes. We find that the Orb-v3 family excels in static migration barrier predictions (MAE $\approx$ 75–111 meV), driven primarily by architectural refinements. Conversely, for dynamic transport, the GRACE model trained on the OMat24 dataset demonstrates superior fidelity in reproducing ion diffusivities and structural correlations. Our results reveal that while architectural sophistication (e.g., equivariance) is beneficial, the inclusion of high-temperature, non-equilibrium training data is the dominant driver of kinetic accuracy. These findings establish that modern uMLIPs are sufficiently robust to serve as zero-shot surrogates for high-throughput kinetic screening of next-generation energy storage materials.

Compared to the study of graphene itself, the study of nano-structured graphene is rather limited because it is difficult to prepare atomically ordered edges. In this study, we have fabricated a periodically patterned mesh structure of graphene with atomically precise zigzag edges (zGNM: zigzag graphene nanomesh) and studied its thermal conductivity ($\kappa$) by opto-thermal Raman measurement. Unintuitively, it is found that the $\kappa$ of zGNM of 2,3 monolayers (MLs) thick is inversely proportional to the nanoribbon width ($W$), while that of zGNM of 5$\sim$10 MLs thick is independent of $W$ down to 30 nm. Since the $\kappa$ of suspended zigzag graphene nanoribbons (zGNRs) is suppressed by decreasing $W$, this nonclassical behavior of zGNM is due to the mesh structure. In addition, zGNRs show a higher $\kappa$ than GNRs with atomically rough edges. This is probably due to the atomically ordered zigzag edges.