Materials Science
Efficient spectral Galerkin framework for nonlinear transient heat transfer in finite domains
Théo Andrieux, Andreas Ntinos and Manas V. Upadhyay
Accurately modelling the temporal
evolution of heterogeneous temperature fields requires resolving strong nonlinearities in the heat equation arising from temperature-dependent thermophysical properties, latent heats of transformation and any local heat sources/sinks. In this work, we present a spectral Galerkin (SG) framework to solve the fully nonlinear transient heat equation in finite domains to attain the accuracy of high-fidelity finite element (FE) simulations at considerably lower computational cost. The heat equation is reformulated into a linear reference problem with constant thermophysical properties and residual forcing terms. Solving the reference problem provides a complete three-dimensional orthonormal trigonometric basis, whose Galerkin projection reduces the heat equation to a set of modal ordinary differential equations (ODEs) in time; the reference operator is diagonal in the modal basis, and results in independent modal updates for a fixed nonlinear forcing. These ODEs can be integrated using exponential time differencing and iteratively corrected for nonlinearities. The SG method eliminates the global solve required by FE methods, and its use of structured grids allows efficient GPU parallelization. Applied to rapid
laser-metal interactions, the SG solver reproduces high-fidelity FE temperature fields with less than 1% relative error while achieving 227-fold faster GPU runtimes. Applied to a part-scale
laser scanning study [Ramani et al., Additive Manufacturing 52 (2022) 102643], the method shows that accounting for evaporation and latent heat more than halves their proposed processing metric. The source code of the SG heat solver and some worked examples are available at https://github.com/manasvupadhyay/spectral_galerkin_heat under the Apache 2.0 license.
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Materials Science
Crystallographic and Electronic Phase Changes in TiTe2 via Atmospheric and Electron Beam Exposure
Bishal Pokhrel, Joel Quarnstrom, Saraswati Shrestha et al. (+4 more)
In this study, we examine the surface sensitivity of a transition metal dichalcogenide (TiTe2) grown using the Chemical Vapor Transport (CVT) technique at high pressure and study the surface changes in the sample upon exposure to air as well as its crystallographic properties upon e-beam exposure. We examine the local density of States (LDOS) of the mechanically exfoliated sample surface before and after exposure using Scanning Tunneling Microscopy/Spectroscopy (STM/STS) and find a metal-to-
semiconductor transition at the surface. The STM analysis shows a clear change in surface roughness which indicates the formation of an adlayer on the surface of the sample. The
crystal structure was examined using X-ray Diffraction (XRD) and Transmission Electron Microscopy (TEM), indicating a phase transition from a single-crystalline hexagonal phase to a polycrystalline state via a distorted monoclinic phase. Furthermore, the presence of a possible superlattice suggests non-stoichiometric TixTey at the surface of the exposed layer.
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All authors Bishal Pokhrel, Joel Quarnstrom, Saraswati Shrestha, Halle Helfrich, Elena Echeverria, David N. McIlroy, Andrew J. Yost
Materials Science · Cross-listed from cs.CV
Symmetry-aware super-resolution of crystal orientation maps via invariant latent-space learning
Umang Garg, Warren Zamudio, McLean P. Echlin et al. (+3 more)
Crystal-orientation maps are physical fields defined only up to
crystal symmetry; electron backscatter diffraction (EBSD) resolves them experimentally, but acquisition-time constraints limit spatial resolution. Unlike conventional images, EBSD data lie on the quotient space $\mathrm{SO}(3)/G$, where $G$ is the
crystal-
symmetry group. Standard Euclidean interpolation can therefore mix
symmetry-equivalent representations and blur grain boundaries. We introduce the
Symmetry-Group-Aware Super-Resolution
Attention Network (SG-SRAN), which incorporates
crystal symmetry and boundary preservation by design. A frozen, locally isometric encoder maps equivalent orientations to a common latent representation in which Euclidean distance approximates misorientation. Super-resolution is performed in this space, with each high-resolution
token restricted to a feature-consistent local support to prevent cross-boundary mixing. A dictionary-based decoder then recovers valid orientations. Across FCC and HCP
benchmarks, SG-SRAN matches 15-16 million parameter backbones using only 27-49k trainable parameters, while achieving the lowest p68 errors, highest inverse-pole-figure fidelity, and zero-shot transfer to unseen
alloys.
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All authors Umang Garg, Warren Zamudio, McLean P. Echlin, Samantha H. Daly, Tresa M. Pollock, B.S. Manjunath
Materials Science · Cross-listed from physics.comp-ph
A new generation of effective core potentials: Selected heavy 5d and 6p elements
Omar Madany and Lubos Mitas
We expand the correlation-consistent effective core potentials (ccECPs) library by developing semi-local pseudopotentials and matching basis sets by heavy-elements from $5d$ (Hf, Os, Hg) and $6p$ (Tl, Po, At, Rn) blocks. In order to accurately capture scalar relativistic effects,
spin-orbit coupling, and electron-electron correlation, we implement a tiered core-valence partitioning strategy across three distinct resolutions. This includes a small 60-core (Hf, Os, Hg) that explicitly correlates subvalence shells, a large 78-core definition for the main-group elements that rigorously accounts for core polarization and relaxation effects in sparse valence environments, and an intermediate 68-core partition for Hg and Tl. This 68-core architecture represents a unique development in the ccECP library, optimizing the balance between accuracy and computational efficiency in a manner unexplored for ligther elements. Optimized against relativistic all-electron CCSD(T) references, the ccECPs deliver outstanding atomic precision, achieving a global average atomic low-lying states deviation of just 0.045 eV. This accuracy translates directly to robust molecular transferability, systematically restricting dissociation energy discrepancies to under 0.03 eV,
equilibrium bond lengths to within 0.005 Å. By enforcing a regularized, finite potential at the origin for enhanced numerical stability in
stochastic quantum Monte Carlo methods, this library removes a critical methodological bottleneck for predictive many-body simulations of heavy-element systems and materials.
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Materials Science
On the physical origins of switching diversity in Cu-embedded SiO$_x$ memristive devices
Sahitya Yarragolla, Rouven Lamprecht, Tobias Gergs et al. (+4 more)
Resistive switching devices with sub-stoichiometric SiO$_x$ and pancake-like Cu nanoparticles (Cu-PCs) exhibit distinct macroscopic current-voltage characteristics classified as capacitive or gradual (interface-type switching) and abrupt or resistive (filamentary-type switching), motivating an analysis of the microscopic processes underlying this diversity. It is proposed that the device defect landscape is largely shaped by two charged defect types, mobile oxygen vacancies and immobile Cu-related defects, whose distributions jointly govern interfacial and bulk transport. An effective one-dimensional cloud-in-a-
cell simulation framework is employed to reproduce the phenomenological picture of both interface-type and filamentary-type switching by incorporating the dominant coupled ionic and electronic processes underlying these mechanisms. The model includes oxygen-vacancy drift-
diffusion, Schottky-limited injection at the metal/oxide interfaces, and bulk trap-assisted transport via Poole-Frenkel conduction, with Cu-PCs near the top interface treated effectively. A simulation-based parametric study varying voltage stress, sweep rate, and oxide thickness is used to examine how these factors rebalance voltage partitioning and the spatiotemporal electric field distribution, thereby altering vacancy redistribution and the relative contributions of interface- and bulk-limited conduction. Using representative, physically motivated parameter sets informed by prior device-level studies, the simulations accurately reproduce the characteristic $I$-$V$ signatures of seven different experimentally observed switching responses. Overall, the findings help to link microscopic defect landscapes and transport processes to experimentally measured macroscopic responses within a single, self-consistent modeling framework.
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All authors Sahitya Yarragolla, Rouven Lamprecht, Tobias Gergs, Ole Gronenberg, Hermann Kohlstedt, Thomas Mussenbrock, Jan Trieschmann
Materials Science
Moiré Topology in Twisted Structures with Noncollinear Spin-Orbit Coupling
Xilong Xu, Liangtao Peng, Shaffique Adam et al. (+1 more)
Moiré superlattices provide a powerful platform for flat bands and correlated topological phases, yet most established examples rely on valley-contrasting Berry
curvature in hexagonal
lattices. Here, we propose a different route to achieve topological moiré minibands based on noncollinear
spin orbit coupling in centrosymmetric type II SOC bilayers. Interlayer hybridization opens local pseudogaps and produces sharply localized Berry
curvature, which twisting reconstructs into isolated topological minibands without requiring valley degrees of freedom or hexagonal
symmetry. We demonstrate this mechanism in tetragonal Dresselhaus-SOC HgI2, where a Lieb-like moiré potential yields topological flat bands. To improve miniband isolation, we develop a physics-informed machine-learning surrogate that identifies stronger SOC as a key design principle and guides the replacement of Hg by Pb. The resulting PbI2 minibands are narrower and better isolated, supporting correlation-driven magnetism and tunable
quantum spin Hall and Chern insulating phases, thereby providing an optimized material realization for experimental exploration.
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All authors Xilong Xu, Liangtao Peng, Shaffique Adam, Li Yang
Materials Science · Cross-listed from cond-mat.str-el
Geometric Ginzburg-Landau theory of charge ordering and commensurability
Aneesh Agarwal, Rutvij Gholap, Mohammad Saeed Bahramy et al. (+1 more)
The concept of
quantum geometry has recently led to reinvigorated insights in a wide range of fields including physical responses, superconductivity, and optical transitions, with effects most pronounced in systems with nearly flat dispersion. Here, we show that it plays an essential role in charge density wave formation (CDW) – an important physical phenomenon that is responsible for driving various sharp changes in material transport properties including metal-
insulator transitions. We derive an effective Ginzburg-Landau theory including uncharted contributions and, as a highlight, discover a general criterion for both CDW formation and commensurability transitions where underlying electron-
phonon interactions manifest purely as electronic
quantum geometric enhancements/suppressions. We
benchmark our framework in a class of transition-metal dichalcogenides and resolve a longstanding puzzle where well-established purely kinetic CDW criteria fail in describing the correct ordering wavevector. Besides rendering robust criteria and fundamental insights that are immediately relevant to several experimental charge ordering systems, our theory can also be applied directly to other
phonon-mediated phases such as superconductivity, and can be used as an important tool to explore the interplay between various such states. More generally, our framework provides a recipe for investigating the role of
quantum geometry in phase transitions.
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All authors Aneesh Agarwal, Rutvij Gholap, Mohammad Saeed Bahramy, Robert-Jan Slager
Materials Science
Overcoming Transport Layer Bottlenecks to Quantify Ionic Parameters from Transient Ion Current Measurements of Perovskite Solar Cells
Shudi Jiao, Miguel Torre Cachafeiro, Huagui Lai et al. (+7 more)
In perovskite solar
cells (PSCs), voltage step-induced transient ion current (TIC) measurements, commonly referred to as bias-assisted charge extraction (BACE), are frequently used to quantify ion density. Drift-
diffusion simulations predict that the ion density computed from TIC saturates once mobile ions screen the electric field in the perovskite. However, experimental studies often report ion densities orders of magnitude above this limit, whose physical origin remains incompletely explained in terms of transport layer (TL) properties. In this work, the capacitance of the TLs is identified to be the fundamental bottleneck: the maximum quantifiable ion density is limited to the charge that can accumulate at the perovskite/TL interfaces, so that TIC most often depends more strongly on TL properties than on the ionic properties of the perovskite. Experiments with systematically varied C$_{\rm 60}$ electron-TL thickness (p-i-n) and Spiro-OMeTAD hole-TL doping (n-i-p) confirm this dependence across architectures. To overcome this limitation, the importance of a correction based on the average ionic displacement is discussed, and it is shown how extrapolating the TL-thickness trend towards the TL-free situation yields the actual ionic conductivity of the absorber, alongside density and mobility, depending on the assumed ionic model. Simulations are also examined in which ion penetration into the TLs or initial accumulation under forward bias raise the capacitive limit and extend TIC sensitivity to higher ion densities. The slow release of trapped carriers is also discussed as a potential source of current which can inflate the TIC signal. Overall, the presented analysis provides important practical considerations for interpreting TIC and quantifying ionic properties in PSCs.
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All authors Shudi Jiao, Miguel Torre Cachafeiro, Huagui Lai, Fuxiang Ji, Tristan Sachsenweger Ballantyne, Sharun Parayil Shaji, Matthias Diethelm, Fan Fu, Wei E.I. Sha, Wolfgang Tress
Materials Science · Cross-listed from cond-mat.mes-hall
WannierNLQG: A Julia package for nonlinear optical responses and quantum geometry from Wannier tight-binding models
Zhuocheng Lu, Zhichao Guo, Yuanyuan Xua et al. (+2 more)
Nonlinear optical responses and
quantum geometry are central to modern condensed matter physics and are deeply intertwined. We introduce WannierNLQG, an extensible Julia framework for computing nonlinear optical responses and
quantum geometric quantities from Wannier tight-binding models. Its gauge-consistent, degeneracy-aware architecture accommodates perturbative responses at arbitrary order and additional
quantum geometric quantities. The current release evaluates ordinary,
spin, and
photon-drag injection and shift currents, as Brillouin-zone integrals and on k slices. For shift current, a unified interface exposes four complementary formulations: the conventional method, projector trace, generalized Wilson loop, and a finite-momentum
geometric loop, with the last three explicitly accommodating degenerate subspaces. The framework also provides k-resolved Berry
curvature,
quantum metric, their multipoles, and additional
quantum geometric and mixed momentum-
spin quantities. Experimental
symmetry workflows additionally support
symmetry-adapted Wannier construction, symmetrization of tight-binding models and real-space operators, and reduction of spatially uniform response integrals to irreducible k-point orbits and invariant tensor components. The documentation covers formula conventions, the TaskConfig interface, and auditable output formats, with GeS and bilayer MoS2 case studies illustrating method comparison, degeneracy handling,
quantum geometric analysis, and
photon-drag responses. Together, these capabilities enable first-principles calculations of nonlinear response and
quantum geometry in realistic multiband materials, connecting
quantum geometry with quantitative materials modeling for optoelectronic, spintronic, and photovoltaic applications.
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All authors Zhuocheng Lu, Zhichao Guo, Yuanyuan Xua, Jiacheng Yao, Hua Wang
Materials Science · Cross-listed from cond-mat.stat-mech
Quantifying translational and bond-orientational order metrics in hyperuniform and nonhyperuniform many-particle systems
Anirban Mukherjee and Salvatore Torquato
Quantifying the degree of order/disorder in many-particle systems remains an outstanding problem in physics, materials science, and mathematics. To this end, we consider the translational order metric $\tau_T$, defined as the squared $L^2$ norm of the total correlation function $h(\mathbf{r})$, and introduce its bond-orientational analogue $\tau_O$, defined from the weighted total correlation function $h_{\mathbf{f}}(\mathbf{r})$ using local orientational weights (S. Torquato et al., Phys. Rev. X 16, 011042 (2026)). The pair $(\tau_T,\tau_O)$ places both forms of order on a common two-point statistical footing. We compute both metrics for two nonhyperuniform sphere-packing models in 2D and 3D as functions of packing fraction $\phi$: 1)
equilibrium hard particles and 2) nonequilibrium random sequential addition (RSA) packings. For the nonhyperuniform systems, bond-orientational order remains subdominant along the
equilibrium-fluid and RSA configurations; however, its magnitude relative to the translational metric increases near the upper end of the
equilibrium-fluid branches, much more strongly in 2D than in 3D, and the two metrics become comparable along the sampled
crystal branches. At common packing fractions,
equilibrium fluids and RSA packings trace distinct $(\tau_T,\tau_O)$ trajectories, revealing preparation-dependent differences in structural order. As a representative hyperuniform family, we study 2D disordered stealthy hyperuniform (SHU) ground states for $0<\chi<1/2$, where $\chi$ is the stealthiness parameter. Within the disordered SHU phase, bond-orientational order remains subdominant, but its magnitude relative to the translational metric increases toward the disorder-to-order threshold. In all three models, $\tau_T$ and $\tau_O$ are positively correlated beyond the Poisson-reference regime: $\tau_O$ increases monotonically with $\tau_T$ across the sampled state points.
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Materials Science
Spectroscopic signatures of mode-selective electron-phonon coupling in transient reflectivity change on charge-density-wave TiSe$_2$
Yu Mizukoshi and Muneaki Hase
We report on time- and spectrally resolved pump-probe spectroscopy measurement on the charge-density wave (CDW) state of TiSe$_2$ at helium temperatures. The non-oscillatory component of the spectrally resolved signals exhibit a sign reversal near 1.5 eV, which was interpreted as a
redshift of the optical transition energy originated from the interband transition between the Se $p$-based valence band to the Ti $d$-derived conduction band. Furthermore, the oscillatory components exhibit distinct spectral dependences between the optical
phonons and the CDW-derived modes, suggesting the mode-selective coupling.
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Materials Science
Constrained Optimization of Higher-Order Cluster-Expansion Hamiltonians for Alloys Using Simulated Bifurcation
Kazuhide Ichikawa, Satoru Ohuchi, Tomoyasu Yokoyama et al. (+2 more)
Identifying ground-state and low-energy atomic configurations is a central problem in
alloy design. The cluster-expansion (CE) method represents configurational energetics on a fixed
lattice as an effective
Hamiltonian; for binary
alloys, higher-order CE models become
polynomial Ising
Hamiltonians. Using Au-Cu as a model binary
alloy, we formulate cubic and quartic cluster-expansion
Hamiltonians as penalty-augmented
polynomial unconstrained binary optimization (PUBO) problems under fixed-composition constraints. We optimize these PUBO problems using SQBM+, a simulated-bifurcation-based solver that can treat higher-order
polynomial binary objectives directly. This direct PUBO treatment avoids the need to construct an explicit quadratic reformulation with auxiliary variables. Composition constraints are imposed through quadratic penalty terms, whose weights are estimated from derivative coefficients of the continuous relaxation of the CE objective.
Benchmark calculations for systems up to 2048 atoms show that SQBM+ robustly obtains low-energy feasible configurations for cubic CE models and remains effective for many quartic instances. Formation-energy convex hulls constructed from the optimized configurations recover the CuAu and Cu3Au ordering trends and reveal finite-size effects at off-stoichiometric compositions. These results demonstrate simulated bifurcation as a practical route to constrained higher-order CE optimization for
alloy configuration search.
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All authors Kazuhide Ichikawa, Satoru Ohuchi, Tomoyasu Yokoyama, Takuma Saito, Yoshiki Matsuda
Materials Science
Structural and Electronic Properties of Bulk $\beta$(2H)-GaSe from First-Principles DFT Calculations with van der Waals Corrections
Julián A. Aros-González, Camilo A. Huertas-Archila and Miguel J. Espitia-Rico
Gallium selenide (GaSe) is a layered III-VI
semiconductor whose bulk
crystal serves as the essential energetic reference for modeling the isolated monolayer. We present a systematic density-functional-theory (DFT) study of the centrosymmetric $\beta$(2H)-GaSe polymorph, employing the GGA-PBE functional supplemented with a semiempirical Grimme DFT-D2 dispersion correction to accurately capture the weak van der Waals interlayer coupling. The optimized in-plane
lattice parameter agrees well with experimental values (within about 1.3%), while the out-of-plane parameter c is overestimated by the DFT-D2 correction relative to experiment, a known limitation of this dispersion scheme when the pairwise $C_6$ coefficients are not specifically fitted for the compound class under study. Electronic structure calculations confirm a non-
magnetic, direct-gap profile (1.12 eV). Although this magnitude reflects the well-known underestimation of semilocal functionals, the qualitative band
topology accurately captures the intrinsic two-dimensional carrier confinement within the bulk material. Consequently, this optimized three-dimensional framework provides a consistent energetic baseline for quantifying exfoliation processes, offering a reliable starting point for future theoretical explorations of the two-dimensional limit, such as surface functionalization for potential spintronic applications.
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Materials Science
Beyond Impedance Additivity: A Systematic Nonlinear Perspective on Memristor Associations
Luiz A. Meneghetti Jr., Leonardo K. Castelano, Antônio Sérgio dos Santos et al. (+5 more)
We investigate the validity of the superposition principle and impedance additivity in AC
circuits containing a memristive device connected in series with a resistor, capacitor, or inductor. While the series association of impedances is a cornerstone of linear
circuit theory, its applicability to
memory-bearing nonlinear systems remains largely unexplored. Using a state-dependent memristive model, we numerically analyze the stationary current response under sinusoidal excitation and characterize the resulting harmonic spectra, Bode diagrams, and Nyquist plots. To assess whether the fundamental response can still be interpreted through an equivalent-
circuit framework, we introduce the concept of an apparent memristor, whose effective parameters are extracted directly from the composite impedance. We show that, although the fundamental harmonic can be accurately reproduced by an apparent equivalent
circuit over selected parameter ranges, the effective parameters differ substantially from those of the isolated memristor, revealing a renormalization induced by the coupling to the passive element. More importantly, we identify parameter regimes in which the apparent-
circuit description breaks down altogether, particularly for capacitor and inductor-coupled systems, demonstrating that the composite impedance cannot generally be expressed as the sum of independent impedances. These results establish boundaries for the use of equivalent-
circuit models in
memory-enabled electronic systems and provide practical guidelines for the interpretation of impedance spectroscopy in nonlinear devices exhibiting
memory.
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All authors Luiz A. Meneghetti Jr., Leonardo K. Castelano, Antônio Sérgio dos Santos, Soumen Pradhan, Fabian Hartmann, Ovidiu Lipan, Sven Höfling, Victor Lopez-Richard
Materials Science
pyeCE: A Python Implementation of the Embedded Cluster Expansion
Yann L. Müller, Claire A. Paetsch and Anirudh Raju Natarajan
The cluster expansion is a widely used approach for predicting the finite-temperature thermodynamics of
alloys from zero-kelvin first-principles calculations, but its conventional formulation becomes intractable for materials with more than three or four chemical species. High-
entropy alloys have therefore remained largely out of reach. We present pyeCE, an open-source Python library that implements the embedded cluster expansion (eCE), in which machine learning maps many chemical species onto a smaller set of effective species and thereby limits the growth in the number of cluster functions. pyeCE provides the complete modeling workflow, including the construction of
symmetry-adapted descriptors with a learnable per-sublattice chemical
embedding, a neural-network energy model, ladder-based training, uncertainty quantification, and finite-temperature simulations through Monte Carlo sampling. Built on the PyTorch and pymatgen libraries, it supports systems with multiple species on multiple sublattices and runs on graphics processing units. We demonstrate the package on two material systems. In the first, a single model spanning the full composition space of a 9-component refractory
alloy resolves short-range order and order–disorder behavior. This model enables rapid screening for compositions with strong Cr clustering, a feature linked to the formation of a continuous, corrosion-resistant oxide scale. In the second, a model of hydrogen dissolution in a Mo–Nb–W
alloy reproduces the composition dependence of hydrogen uptake and resolves the interstitial environments that hydrogen occupies. The modular design of pyeCE allows it to be extended to problems beyond
alloy thermodynamics, including kinetics, defect energetics, and the coupling of chemical order to
magnetic and vibrational degrees of freedom.
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Materials Science · Cross-listed from cond-mat.str-el
Fast, Accurate, and Scalable Fermionic Neural Networks via Translation Equivariance
David D. Dai, Yen-Ting Lin and Marin Soljačić
We demonstrate that designing a neural
quantum state to be an exact eigenstate of the
Hamiltonian's
symmetries significantly improves both training speed and final variational energy. For the 2D electron gas, we design TorFormer, a neural network wavefunction which is an exact eigenstate of the total momentum. TorFormer describes both the Fermi
liquid and Wigner
crystal with no supervision and significantly outperforms Psiformer-based references up to large system sizes. For $r_s = 30.0$ and $40.0$ at $N=91$, we compare TorFormer trained for $8\mathrm{K}$ steps against the previous best NQS, which required $100\mathrm{K}$ training steps. Our improvement to the total energy at $r_s = 40.0$, excluding the trivial Madelung part, is $0.12\%$—enormous compared to the tiny differences separating phases. Relative to Slater-Jastrow-backflow
diffusion Monte Carlo, TorFormer's energy decrease is roughly $9.8$ times that of the previous best NQS. Our work demonstrates that neural
quantum states can both accurately and efficiently solve large-scale problems.
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Materials Science
Observation of Magnetic-Anisotropy Crossover and High-Temperature Skyrmions in the Dirac Magnet Fe3Ge with a Distorted Kagome Lattice
Yalei Huang, Xiaowei Lv, Bin Li et al. (+13 more)
Topological materials that simultaneously host robust high-temperature skyrmions and nontrivial electronic band structures have attracted tremendous interest owing to their distinctive advantages for both fundamental research and prospective technological applications. Here, we report the observation of robust skyrmions in the Dirac kagome magnet Fe3Ge, which exhibits a high Curie temperature of ~ 650 K. At room temperature, Fe3Ge shows a large intrinsic anomalous Hall conductivity of ~ 380 {\Omega}-1cm-1, originating from its nontrivial electronic band
topology. Systematic magnetization measurements reveal a
spin reorientation transition at ~ 375 K, indicating a crossover from easy-plane to easy-axis
magnetic anisotropy. Below the
spin reorientation temperature, a large topological Hall effect is observed, arising from microscopic noncoplanar
spin structures. Lorentz transmission electron microscopy shows that mesoscopic skyrmions are stabilized in the easy-axis
magnetic anisotropy regime and persist over an exceptionally wide temperature window of 375-650 K, far exceeding that of most previously reported skyrmion-hosting materials. These results establish Fe3Ge as a promising platform for exploring diverse topological properties, with strong potential for advancing future high-temperature spintronic applications, ranging from next-generation information storage to logic computing devices.
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All authors Yalei Huang, Xiaowei Lv, Bin Li, Chunqiang Xu, Dhanarajagopal Alltrin, Xiaoxuan Ma, Wanting Yang, Wei Zhou, Xiangzhuo Xing, Wen-Chin Lin, Raman Sankar, Michael Smidman, Shixun Cao, Dong Qian, Renchao Che, Xiaofeng Xu
Materials Science · Cross-listed from cs.LG
An Explainable Machine Learning Framework for Predicting Blood-Brain Barrier Permeability Using Molecular Descriptors
Fatemeh Mahmoudi
Blood-
brain barrier (BBB) permeability is a critical determinant in the development of central nervous system therapeutics because it directly influences the ability of drug candidates to reach their target sites within the
brain. In this study, an explainable machine learning framework was developed to predict BBB permeability using molecular descriptors generated from the MoleculeNet BBBP
dataset with the RDKit cheminformatics toolkit. Fifteen physicochemical descriptors extracted from 2,039 compounds were used to train four supervised machine learning
algorithms, including Logistic Regression, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost). Hyperparameter optimization was performed using GridSearchCV, while model interpretability was investigated using SHapley Additive exPlanations (SHAP). Among the evaluated models, the optimized XGBoost classifier achieved the best predictive performance, with an accuracy of 88.97%, a precision of 88.92%, a recall of 97.76%, an F1-score of 93.13%, and a ROC-AUC of 0.9282. Stratified five-fold cross-validation further demonstrated the robustness of the proposed model, yielding a mean ROC-AUC of 0.8982 +/- 0.0130. Feature importance and SHAP analyses consistently identified TPSA, HBD, and LogP as the most influential molecular descriptors governing BBB permeability prediction. Overall, the proposed framework provides an accurate, interpretable, and computationally efficient approach for BBB permeability prediction and may serve as a valuable tool for the early-stage screening of CNS drug candidates.
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Materials Science
Strong Impact of Halide Ordering on Structural Phase Transitions in Mixed Perovskites
Felix Uddén, Erik Fransson, Julia Wiktor et al. (+3 more)
Mixed halide perovskites are highly versatile
semiconductors with applications in photovoltaics, light-emitting diodes, and photodetectors. Understanding their thermodynamic phase behavior is central to guiding compositional design and improving device stability. Here, we train machine-learned interatomic potentials (MLIPs) on density functional theory reference data for CsxRb1-xPbBr3yI3-3y, CsxRb1-xPbBr3yCl3-3y, and CsxRb1-xPbCl3yI3-3y halide perovskites, enabling large-scale hybrid Monte Carlo-molecular dynamics simulations that sample both configurational and vibrational degrees of freedom. All three binary halide systems exhibit a miscibility gap, the extent of which correlates with halide ion size mismatch. The gaps in Br-Cl and Br-I close at low temperatures, while the Cl-I gap extends above room temperature. At temperatures above the miscibility gap (200 K to 500 K), all systems show a tendency toward layered halide ordering, with halide species preferentially occupying apical or equatorial octahedral sites. In CsPbBr3yI3-3y, this ordering occurs in a device-relevant temperature regime and is linked to the structural phase transitions, shifting transition temperatures by up to 100 K relative to randomly mixed structures. We attribute the strongly non-linear composition dependence of the orthorhombic-tetragonal phase boundary observed experimentally (a linear decrease followed by a plateau) to halide ordering. Introducing Rb on the A-site weakens halide ordering and eliminates the non-linear behavior, while narrowing the miscibility gap in both the Br-I and Br-Cl systems. These results establish halide ordering as a key determinant of structural phase stability in mixed-halide perovskites.
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All authors Felix Uddén, Erik Fransson, Julia Wiktor, Benjamin M. Gallant, Dominik J. Kubicki, Paul Erhart
Materials Science
Dimensional Control of Excitonic Interactions in Exfoliated 2D Molecular Crystals
Jonghyun Son, Seonghyun Koo, Daniel Yim et al. (+17 more)
Two-dimensional (2D) materials provide unique opportunities to tailor excited-state properties through reduced dimensionality, altered dielectric screening and layer-dependent structural reconstruction. While such effects have been widely explored in norganic systems, their realization in molecular
crystals has been limited by the difficulty of controlling thickness at the atomic scale while preserving crystalline order. Here we show that tetracene and three other molecular
crystals can be mechanically exfoliated into mono-, few- or multilayer flakes, while retaining crystalline order. This capability enables new studies of molecular
crystals across a well defined thickness range within the same structural organization. Thickness-dependent spectra of these samples reveal how out-of-plane confinement modifies the excited-state energy landscape of tetracene: With decreasing thickness, the Davydov splitting diminishes, the Stokes shift increases, and signatures of more delocalized
excitons emerge. Electron diffraction and
exciton model-based analyses correlate these trends to changes in molecular packing, intermolecular coupling and dielectric screening. Our results also demonstrate that key features of molecular
excitons can be systematically tuned by layer number, extending dimensional control from inorganic 2D materials to molecular
crystals.
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All authors Jonghyun Son, Seonghyun Koo, Daniel Yim, Sangjin Han, Dong-Hwan Yang, Gi-Yeop Kim, Kihyun Lee, Jieun Yeon, Hye Soo Kim, Eunbeen Jeon, Minji Ko, Minhee Choe, Kenji Watanabe, Takashi Taniguchi, Hee Cheul Choi, Kwanpyo Kim, Si-Young Choi, Seogjoo J. Jang, Hyungjun Kim, Sunmin Ryu
Materials Science
uFlowCSP: Crystal Structure Prediction using Mean flow generative models
Sourin Dey, Dipannoy Das Gupta, Lai Wei et al. (+2 more)
Crystal structure prediction (CSP) is fundamental to computational materials discovery. Generative models including CDVAE, DiffCSP, FlowMM, and CrystalFlow learn stable-
crystal distributions directly, but
diffusion and flow-matching inference requires tens to thousands of sequential network evaluations per candidate. We introduce uFlowCSP, a MeanFlow-based CSP model that learns the average, rather than instantaneous, probability-flow velocity. It generates a complete structure in one to five evaluations, delivering 5x-58x faster inference with equal or better performance. A chemistry- and
symmetry-aware
Transformer uses canonical atom ordering, global composition, and per-
token chemistry
embeddings. A coarse
crystal-system
token is used only during training; it provides additive gains, particularly improving space-group agreement despite being absent at inference, which remains formula-only. On MP-20 with 20 candidates per target, one step matches CrystalFlow (78.38% vs. 78.34%) with 100x fewer evaluations and about 10x lower wall-clock time. Five steps reach 83.64%, exceeding CrystalFlow (78.34% at 2,000 evaluations) and DiffCSP (77.93% at about 20,000), while using 20x fewer evaluations. uFlowCSP generates 10,000 structures in 0.39-1.31 minutes, versus 6.5 for CrystalFlow and 76.1 for DiffCSP. Under CSPBench's energy-ranked top-five structure-and-space-group criterion, five-step uFlowCSP reaches 72%/72%/65% structure, space-group, and consensus match rates. CrystalFlow reaches 78%/73%/68% at 100 steps but falls to 49%/32%/31% at five. Thus, uFlowCSP improves accuracy per network evaluation, not merely peak accuracy.
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All authors Sourin Dey, Dipannoy Das Gupta, Lai Wei, Sadman Sadeed Omee, Jianjun Hu
Materials Science
Facile hBN-hBN Interfacial Overlap Engineering for Enhanced Quantum Emitter Formation
Nhat Minh Nguyen, Trung Vuong Doan, Md Shakhawath Hossain et al. (+12 more)
Quantum emitters in two-dimensional materials, particularly hBN, are promising platforms for
quantum technologies. However, achieving high-density emitters at predetermined locations while preserving optical quality remains challenging. Here, we introduce a facile, cost-effective double-layer all-dry transfer approach to deterministically create overlap regions between hBN flakes. These pre-defined capped regions exhibit a significantly enhanced emitter density, with up to a 15-fold increase compared to uncapped areas. Importantly, this method does not compromise emitter quality: emitters within overlap regions demonstrate excellent optical performance, including high signal-to-background and signal-to-noise ratios, large Debye-Waller factors, high brightness, and strong spectral stability. Possible defect configurations are also discussed to contextualize the observed emission characteristics. This scalable strategy enables preferential formation of
quantum emitters in targeted regions, achieving higher densities than simple treatments such as
plasma irradiation while avoiding the complexity of advanced fabrication techniques. The approach provides a practical pathway for integrating high-quality
quantum emitters into scalable
quantum photonic platforms.
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All authors Nhat Minh Nguyen, Trung Vuong Doan, Md Shakhawath Hossain, Akila Elangasinghe, Duc Anh Ngo, Ha Ngoc Duy Huynh, Thi Ngoc Anh Mai, Yongliang Chen, Kenji Watanabe, Takashi Taniguchi, Michael G. Ruppert, Chaohao Chen, Xiaoxue Xu, Toan Dinh, Toan Trong Tran
Materials Science
Morphology and depletion force-based large-scale self-assembly of nanocubes on surface
Yeonhee Lee, Seungsang Cha, Yuna Kwak et al. (+3 more)
Self-assembling nanoparticles is a highly efficient and facile way to form functional nano-, micro- and macrostructures. However, currently available methods lack precision and controllability in size, shape and composition, suffer from poor reproducibility and scalability, and require complex steps and expensive materials. Here, we present the uniform morphology-induced and depletion force-directed nanoparticle assembly on surface (MIDAS) method with gold nanocubes (AuNCs). Using this approach, morphology-sensitive depletion forces trigger shape-selective flocculation and assembly of the AuNCs with uniform size and shape. Importantly, the surface roughness-controlled substrate drives the large-scale formation of AuNC-assembled monolayers (2D AuNAMs) or three-dimensional AuNC-assembled multilayers (3D AuNAMs) in a highly specific manner without any complex ligand modification or preparation steps.
Lattice-gas modeling and kinetic Monte Carlo simulations show the depletion force is the key parameter determining supercrystal morphology and corroborate the experimental findings. This work establishes a generalizable nanoparticle assembly mechanism and demonstrates the broad applicability of the MIDAS strategy for scalable fabrication and patterning of 2D and 3D nanoparticle architectures.
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All authors Yeonhee Lee, Seungsang Cha, Yuna Kwak, Nicholas Juntunen, Grant M. Rotskoff, Jwa-Min Nam
Materials Science
First-principles investigation of structural, mechanical, vibrational, thermal, electronic and optical properties of Na3Bi: a topological Dirac semimetal
Maisha Fahmida, Syed Shovon Mahbub Mahin, Suptajoy Barua et al. (+1 more)
Exploring the properties of topological materials has remained an active area of research in condensed matter physics for the past few decades. Here, we present a first-principles investigation of the structural, elasto-mechanical, thermal, electronic, and optical properties of Na3Bi, one of the earliest discovered topological Dirac semimetals, using density functional theory. The hexagonal phase of Na3Bi is found to be both mechanically and dynamically stable, exhibiting moderate elastic anisotropy with a universal anisotropy index of 0.832. The compound displays a moderate machinability index of 2.386 alongside a low hardness value of 2.005, consistent with its predominantly brittle, covalently bonded character accompanied by a slight metallic contribution. Its comparatively low Debye temperature of 181.39K points to a mechanically soft
lattice with loosely bound atoms. Electronic structure calculations confirm semimetallic behavior, with well-defined Dirac points pinned at the Fermi level and a Fermi surface composed of point-like pockets. Optical analysis across a wide spectral range reveals non-selective, moderate reflectivity of 40 to 45% and, in the visible region, an unusually high refractive index reaching between 2 and 4.5. Na3Bi is additionally found to be an efficient absorber of ultraviolet radiation. Together, these findings establish a comprehensive baseline for the mechanical, thermal, and optical behavior of hexagonal Na3Bi and point to its potential relevance for acoustic damping, UV-sensing, and optoelectronic applications
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All authors Maisha Fahmida, Syed Shovon Mahbub Mahin, Suptajoy Barua, Ishtiaque M. Syed
Materials Science · Cross-listed from quant-ph
Cascade-induced high-performance nonreciprocal quantum batteries
Niaz Ali Khan and Dahai He
Nonreciprocal
quantum batteries harness reservoir engineering for controlled energy transfer, heralding a paradigm shift for
quantum energy storage. A prior study utilizing the Metelmann-Clerk formalism reported a fourfold enhancement in nonreciprocal energy accumulation over reciprocal counterparts. This fourfold enhancement, however, appears to stem from a Lindblad master equation that exhibits fundamental inconsistencies, which may systematically understate the actual nonreciprocal advantage. Our approach is rooted in the rigorously established cascaded open
quantum systems formalism, which ensures both mathematical consistency and physical fidelity. Remarkably, we surpass the previously reported fourfold
benchmark, attaining a regime-independent sixteenfold steady-state nonreciprocal energy advantage over reciprocal systems. We further uncover a dissipation-dependent battery-to-charger efficiency, fourfold under symmetric damping, surpassing this
benchmark when the battery is less dissipative, and lower otherwise. This work establishes the cascaded formalism as a mathematically rigorous and experimentally viable foundation for high-performance
quantum energy storage.
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Materials Science
Automated Generation of Commensurate Magnetic Structures based on Spin Space Groups and Graph Theory
Yifan Wang, Boyang Deng, John Robertson et al. (+3 more)
Magnetic structures with
symmetry constraints are candidates for energetically favorable configurations. Enumerating these structures is essential for identifying experimental observations and provides unbiased, linearly stable, and optimally sampled reference configurations for energy fitting when extracting
spin interactions. We present SpinGraph, an automated workflow generating
symmetry-distinct
magnetic configurations. SpinGraph is not only compatible with the more general
spin space groups, but also allows precise control of the prescribed single- or multi-Q states superposition. For finite groups, we enumerate compatible subgroups directly. For
spin space groups with a continuous or special
spin-only part, the finite component is enumerated first and then combined with the compatible exact
spin-only constraints. These actions are translated into graph constraints in real or
Fourier space. The
symmetry of every generated structure is re-evaluated after construction. Finally, we integrate SpinGraph with the
magnetic analysis code AMATIS to perform a thorough calculation for the
spin interactions of the insulating monolayer CrI3. SpinGraph complements the last part of AMATIS and realizes the fully automated workflow for the
spin Hamiltonian construction, which is essential for studying phase transitions,
spin textures,
magnons, and
spin dynamics.
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All authors Yifan Wang, Boyang Deng, John Robertson, Weisheng Zhao, Stefan Blügel, Haichang Lu
Materials Science
Twist and strain identification in moiré heterostructures
Zhen Zhan, Federico Escudero, Dong Wang et al. (+4 more)
The geometrical and electronic properties of moiré materials are highly sensitive to the twist and strain in the samples due to the moiré magnifying effect. Accurate identification of twist and strain in moiré materials is therefore essential. In this work, we establish a general framework to extract the twist and strain configurations from moiré images with either atomic or moiré scale resolution. With only moiré-wavelength information, we show that there is a continuous family of possible twist and strain configurations, each one accounting for different orientations of the moiré pattern. To estimate the most likely twist-strain configuration, we discuss additional constraints and methods involving the minimum elastic energy and the electronic spectra. The minimum elastic energy, in particular, reflects that shear configurations become much more favorable as the strain increases. As an example of the developed methodology, we discuss the formation and identification of strained triangular moiré patterns. Our framework provides a comprehensive approach to identify the twist and strain configurations in systems with moiré-scale resolution.
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All authors Zhen Zhan, Federico Escudero, Dong Wang, Yiwen Liu, Ambikesh Gupta, Pierre A. Pantaleón, Francisco Guinea