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Physics Condensed Matter Materials Science

cond-mat.mtrl-sci Watch Materials Science

Sunday 14 June

Materials Science

Dimensional Crossover of Mass Anisotropy in Ta-doped WTe2

P. Das, D. Das, P. Kumar et al. (+2 more)

The observation of extremely large magnetoresistance in WTe2 has attracted considerable attention towards understanding its underlying origin. With its layered van der Waals structure, the question that remains largely unexplored is whether the three-dimensional anisotropic transport characteristics of WTe2 persists under chemical substitution. Here, we present a systematic angle-dependent magneto-transport study of single-crystalline TaxW1-xTe2 (x = 0, 0.05, 0.1). The results are analysed within a mass anisotropy scaling framework to extract the mass anisotropy parameter {\gamma} as a function of temperature and doping. It is observed that Ta substitution leads to monotonic increase of {\gamma} across all temperatures, indicating a progressive deepening of quasi-two-dimensional Fermi surface character. Ta doping also leads to a substantial improvement in crystalline quality, reflected in a pronounced increase in the residual resistivity ratio. Despite weakening electron-hole compensation, the magnetoresistance rises sharply to ~58,211% at x = 0.1, which is assigned to a substantial enhancement in carrier mobility. Rietveld refinement confirms a systematic c-axis contraction with Ta content, identifying the structural origin of the enhanced anisotropy. The mass anisotropy scaling that holds for x = 0 and x = 0.05 breaks down for x = 0.1, where the angular magneto-resistance anisotropy substantially exceeds single-ellipsoid predictions, pointing to a multi-pocket Fermi surface with distinct anisotropies. Nonlinear Hall resistivity provides independent evidence for the underlying multiband character of transport in this system. These findings demonstrate that Fermi surface anisotropy, carrier compensation, and mobility are independent parameters that can lead to tuneable control of large magnetoresistance in topological semimetal WTe2.
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All authors P. Das, D. Das, P. Kumar, Monika, S. Patnaik

Materials Science

Unveiling AlSb as a Promising Zincblende Semiconductor for Visible-Light Shift-Current Generation

César Castillo-Quevedo, Edgar Paredes-Sotelo, Peter L. Rodríguez-Kessler et al. (+2 more)

We use density functional theory to investigate the shift-current response in zincblende III–V (AlP, AlAs, AlSb, GaP, GaAs, InP, InAs, and InSb) and II–VI (ZnS, ZnSe, ZnTe, CdS, CdSe, and CdTe) semiconductors. Our main goal is to identify which material generates the largest shift-current under illumination and to examine the factors influencing this response. We find that aluminum-containing semiconductors, particularly AlSb, exhibit the highest shift-current responses, while CdSe shows the lowest. We analyze the contributions of specific band-to-band transitions to the shift-current in AlSb by selectively summing valence and conduction bands. Additionally, we calculate delocalization indices to investigate the electron delocalization, which correlates with the shift current. Hydrostatic pressure does not enhance the shift current in these materials. These findings have potential applications in optoelectronics and identify the most promising zincblende semiconductors for efficient shift-current generation under visible-light illumination
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All authors César Castillo-Quevedo, Edgar Paredes-Sotelo, Peter L. Rodríguez-Kessler, Gerardo Martínez-Guajardo, Jose Luis Cabellos

Materials Science

Switching Chern number by sliding and gating in alternately twisted tetralayer MoTe2

Xiao-Wei Zhang, Kaijie Yang, Xiaodong Xu et al. (+2 more)

Switching the bulk Chern number in topological materials is of central importance for the design of topological electronic devices. Motivated by recent observations of integer and fractional quantum anomalous Hall effects in twisted transition metal dichalcogenides (tTMDs), we realize the switching of valley Chern number through sliding and gating in alternately twisted tetralayer (ATT) MoTe$_{2}$. Using large-scale density functional theory (DFT) calculations, we show that the Chern number of the first $K$-valley moiré band evolves from $+1$ to $-1$ under the interlayer sliding. Furthermore, an applied electric field can switch the valley Chern number from $-1$ to $+1$. Based on the developed continuum model, we reveal that these switching behaviors are caused by the sliding- and gate-dependent intralayer moiré potential distributions across the layers. Our results establish ATT MoTe$_{2}$ as a promising platform for engineering moiré band topologies through the design of moiré potentials with sliding in multilayer moiré systems.
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All authors Xiao-Wei Zhang, Kaijie Yang, Xiaodong Xu, Ting Cao, Di Xiao

Materials Science

NIMO: A Software Platform for Closed-Loop Materials Exploration with Diverse AI Algorithms

Ryo Tamura, Naruki Yoshikawa, Koji Tsuda et al. (+1 more)

Self-driving laboratories (SDLs), where artificial intelligence proposes subsequent experiments and robotic systems execute them, are rapidly becoming the vanguard of materials discovery. A critical bottleneck, however, lies in seamlessly bridging diverse AI algorithms tailored for specific exploration goals with the heterogeneous robotic hardware found across different laboratories. Here, we present NIMO, an open-source software platform designed to dissolve this barrier through three core paradigms: a modular AI-robot decoupling mediated via simple CSV file exchange, a discrete candidate-pool architecture that seamlessly absorbs domain knowledge, and a unified Python interface pre-loaded with twelve distinct AI algorithms. In this Perspective, we review the operational principles of each algorithm alongside six diverse SDL implementations driven by NIMO, covering electrolyte discovery, organic synthesis, thin-film exploration, fuel-cell process informatics, coffee-ring phase exploration, and legacy liquid-handling automation. One of these also demonstrates NIMO's seamless interoperability with the IvoryOS orchestration framework. To democratize autonomous science, we also introduce a no-code desktop application that enables intuitive, human-in-the-loop exploration for non-programmers. NIMO is freely available at https://github.com/NIMS-DA/nimo, offering a versatile, plug-and-play foundation to accelerate autonomous materials exploration across diverse experimental landscapes.
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All authors Ryo Tamura, Naruki Yoshikawa, Koji Tsuda, Shoichi Matsuda

Saturday 13 June

Materials Science · Cross-listed from cond-mat.soft

Cobalt-Catalysed Chain Transfer Polymerisation Enables Soft Methacrylate Nematic Elastomers for Switchable Pressure-Sensitive Adhesion

Noboru Koshimizu and Mohand O. Saed

Liquid crystal elastomers (LCEs) exhibit unique viscoelastic behavior arising from reversible liquid-crystalline ordering, making them attractive candidates for switchable pressure-sensitive adhesives (PSAs). However, methacrylate-based LCEs are typically highly crosslinked, leading to elevated glass-transition temperatures ($T_g$) and storage moduli ($E'$) that limit adhesive performance. Here, we demonstrate that catalytic chain-transfer polymerization provides an effective strategy for engineering soft methacrylate nematic elastomers through systematic control of network architecture. Incorporation of parts-per-million concentrations of bis(boron difluorodimethylglyoximate)cobalt(II) (CoBF) during photopolymerization reduced the effective crosslink density and increased the molecular weight between crosslinks, producing substantial decreases in $T_g$ and $E'$ while preserving nematic order. Dynamic mechanical analysis revealed that increasing CoBF concentration enhanced viscoelastic dissipation and broadened the accessible nematic temperature window. To further optimize rheological properties for pressure-sensitive adhesion, monofunctional methacrylates and flexible poly(ethylene glycol) dimethacrylate (PEGDMA) were incorporated into the network. The optimized formulation exhibited a $T_g$ near 0~$^\circ$C, a room-temperature storage modulus of approximately 0.3 MPa, and high damping behavior, approaching the Dahlquist criterion for pressure-sensitive adhesion. As a result, the resulting nematic elastomers displayed strong tack, peel, and lap-shear adhesion in the nematic state, together with rapid, reversible, and residue-free debonding upon heating above the nematic-to-isotropic transition temperature.
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Materials Science

A Unified Dielectric-Dependent Hybrid Functional for Accurate Band Gaps across Dimensions

Subrata Jana, Manoar Hossain, Arghya Ghosh et al. (+3 more)

Predicting fundamental band gaps across material classes and dimensionalities remains a central challenge in electronic-structure theory. Here, we show that intrinsic dielectric screening provides a unified control parameter for nonlocal exchange from bulk to low-dimensional and heterogeneous materials. We introduce a geometry-independent dielectric response and incorporate it self-consistently into a nonempirical screened-dielectric-dependent hybrid functional. Benchmarks for 100 materials spanning bulk, two-dimensional, one-dimensional, and mixed-dimensional systems show near-GW accuracy at the computational cost of generalized Kohn-Sham theory. These results reveal a screening-exchange-gap relation in which reduced dimensionality weakens intrinsic dielectric screening, strengthens nonlocal exchange, and drives the opening of fundamental gaps.
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All authors Subrata Jana, Manoar Hossain, Arghya Ghosh, Gabriel Chirchir, Prasanjit Samal, Szymon Smiga

Materials Science

Nonlocal Orbital-Free Kinetic Energy Functional from the Jellium-with-Gap Model for Finite Systems

Abhishek Bhattacharjee, Subrata Jana, Szymon Smiga et al. (+1 more)

The quasi-linear scaling of orbital-free density functional theory (OF-DFT) with system size makes it a computationally efficient alternative to conventional Kohn–Sham density functional theory for many condensed-matter applications. However, its applicability remains limited, particularly for finite systems such as molecular clusters, due to the lack of accurate kinetic energy density functionals. In this context, the development of nonlocal kinetic energy density functionals (NL-KEDFs) has significantly advanced the practical utility of OF-DFT. Here, following an alternative formulation based on the linear-response kernel derived from the jellium-with-gap model (JGM), we develop an NL-KEDF capable of accurately describing the diverse density regimes characteristic of finite systems, including molecular clusters. Benchmark calculations, together with an analysis of the corresponding Pauli potentials, demonstrate that the proposed functional achieves higher accuracy than state-of-the-art orbital-free approaches for finite systems. Furthermore, the optical properties computed using the present method show good agreement with reference results, highlighting its reliability. These results indicate that the proposed NL-KEDF provides a robust and efficient framework for extending OF-DFT to finite systems, with potential implications for nanomaterial design and a deeper understanding of nanoscale phenomena.
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All authors Abhishek Bhattacharjee, Subrata Jana, Szymon Smiga, Prasanjit Samal

Materials Science

Symmetry-aware generative design of flat-band materials beyond known crystal-net prototypes

Yihao Wei, Ivan Savochkin, Artem Mishchenko et al. (+2 more)

Flat electronic bands underlie a range of strongly correlated and topological phenomena, whose design in real materials has so far relied on a small catalogue of named geometric motifs such as kagome, Lieb, and pyrochlore nets. This discrete catalogue is by no means to exhaust the geometries that support flat bands in real compounds, as band flatness is a property of network connectivity. Here we combine a continuous geometric representation of crystal sublattices, with a symmetry-constrained generative model, to access a broader design space for materials hosting flat bands. The key step is to choose sublattice motifs that are outside the known geometric clusters, ensuring the novelty of the generated structures. We then introduce SkeleGen, which pins these unconventional skeletons to symmetry-compatible Wyckoff positions while denoising the surrounding chemistry, resulting in 9,352 crystal candidates that survive stability and flatnessscreening. Band flatness is confirmed using high throughput full DFT calculations, which agree well also with the tight-binding spectra of the isolated skeletons, supporting a geometric origin of the band flatness. We demonstrate "out-of-distribution" motifs as a new design principle to dramatically expand geometric repertoire for materials discovery, potentially beyond flat bands.
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All authors Yihao Wei, Ivan Savochkin, Artem Mishchenko, Xiangwen Wang, Qian Yang

Materials Science

Impedance Matching and Absorption Enhancement in Helical Carbon Coil Microwave Absorbers via Tunable Anchoring Layer Thickness

Weihua Mu

Helical carbon coils exhibit unique three dimensional chiral architectures that can effectively interact with microwaves in the 2 to 18 GHz range. Inspired by recent experimental studies, we develop a coarse grained electrodynamic model for helical carbon coil arrays supported on quartz substrates, and examine their potential as microwave absorbers. Guided by the heuristic relation $f_{\mathrm{res}} = c / (n_{\mathrm{eff}} p)$, we compute absorption and reflection fractions for both bare helical carbon coil on substrate and helical carbon coil with anchoring layer on substrate configurations. The anchoring layer thickness is treated as a tunable parameter to improve absorption at selected frequencies. We find that the introduction of a carbon based anchoring layer of optimized thickness enhances impedance matching absorption. The parameters are chosen as representative values for demonstration purposes, and may vary within a certain range depending on preparation conditions. Our results serve to illustrate the potential of helical carbon coils as microwave absorbing devices, and to identify possible active tuning strategies. In the discussion section, we consider extensions of the present model to account for circular dichroism absorption, and examine the influence of actual interfacial reflection on microwave absorption and reflection.
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Materials Science · Cross-listed from cond-mat.soft

On the flow of electrically charged particles in an elastic solid

Jiashi Yang

This paper is a specialization of a broad and complicated continuum theory [arXiv:2403.07582] to a relatively simple and useful case so that it is more reader friendly. A continuum theory of the flow of charged particles in an elastic solid is presented. It can describe the behavior of soft solid electrolytes and elastic semiconductors. It is nonlinear and is valid for large deformation and strong fields. The theory is derived from a three-continuum mixture model including a charged lattice continuum, a bound charge continuum for electric polarization, and an ideal fluid for the flow of mobile charges. The basic electromechanical laws are applied systematically to the model. The electric fields are quasistatic and are in SI units.
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Materials Science

Ternary-composition tuning of the anomalous Nernst effect in amorphous-like Gd-Co-Pt films

Tomohiro Koizumi, Mojtaba Mohammadi, Hiroto Imaeda et al. (+2 more)

We report composition tuning of the anomalous Nernst effect in amorphous-like Gd-Co-Pt ternary films. Pt incorporation into Gd-Co films modifies the anomalous Nernst coefficient and induces a sign reversal of S_ANE, whereas Gd incorporation into Co-Pt films suppresses S_ANE but reduces thermal conductivity. Owing to the balance between transverse thermoelectric response and thermal transport, the heat-flux sensitivity reaches approximately 0.24 {\mu}m/A. Composition maps reveal that the magnitude and heat-flux sensitivity of the anomalous Nernst effect can be systematically tuned in the Gd-Co-Pt ternary composition space. This work extends ANE material design from binary-alloy optimization to ternary-composition engineering.
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All authors Tomohiro Koizumi, Mojtaba Mohammadi, Hiroto Imaeda, Hiroyuki Awano, Kenji Tanabe

Friday 12 June

Materials Science · Cross-listed from cs.AI

An Agentic Orchestration of Atomistic Simulations

Rahul Somasundaram, Adela Habib, Khanh Dang et al. (+12 more)

Atomistic simulations are central to materials design, but their execution involves complex, multi-step workflows that require significant human expertise. Here, we present an agent-based system embedded within the URSA (Universal Research and Scientific Agent) framework that automates the design, execution, and validation of atomistic simulations, demonstrated using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) tool. Our system autonomously selects interatomic potentials, constructs and runs simulations, and performs iterative error recovery within a closed-loop workflow. We evaluate the scientific reliability of the agent by benchmarking its outputs against LAVA, a high-throughput toolkit for LAMMPS and the Vienna Ab initio Simulation Package (VASP) calculations. Our framework reduces manual intervention and trial-and-error, thereby improving the rigor, reproducibility, and scalability of atomistic modeling.
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All authors Rahul Somasundaram, Adela Habib, Khanh Dang, Sachin Shivakumar, Ryley G. Hill, Golo Wimmer, Avanish Mishra, Aleksandra Pachalieva, Arthur Lui, Hari Viswanathan, Michael Grosskopf, Saryu Fensin, Russell Bent, Nathan DeBardeleben, Earl Lawrence

Materials Science · Cross-listed from cs.LG

A Hybrid GNN-FEM Framework for Phase-Field Fracture Simulation. Physics-Preserving Hybridization for Generalizable Surrogate Modeling

Hyeonbin Moon, Yongjin Choi and Seunghwa Ryu

Scientific machine learning (SciML) has emerged as a promising approach for accelerating simulations of complex physical systems, yet achieving physically consistent and generalizable predictions for nonlinear, history-dependent problems remains a central challenge. In this study, we propose a hybrid GNN–FEM framework for efficient and generalizable phase-field fracture modeling. While phase-field approaches provide a robust variational framework for simulating complex crack evolution, their high computational cost limits practical applications because they require solving coupled, nonlinear, and history-dependent systems within an incremental finite element procedure. To address this challenge, a graph neural network surrogate is integrated into the conventional staggered scheme, replacing the phase-field update at each load increment while retaining the FEM-based displacement solver to enforce mechanical equilibrium and boundary conditions. By preserving the incremental solution structure, the framework remains consistent with history-dependent fracture evolution without requiring the surrogate to approximate the full solution trajectory. This selective surrogate strategy emphasizes the identification of a physically meaningful and incrementally structured learning target, rather than relying on brute-force data generation to learn the full fracture process. The proposed framework achieves strong generalization across varying geometries, loading conditions, material properties, and discretizations through dimensionless feature design, a graph-based formulation on mesh-based domains, and a physics-informed loss derived from the governing phase-field equation. Numerical experiments demonstrate that the hybrid approach reduces computational cost while maintaining accuracy compared with conventional FEM, and exhibits robust predictive performance across diverse problem settings.
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Materials Science · Cross-listed from cs.LG

Physics-Informed Discovery of Yield Functions in Plasticity via Convex Neural Representations

Hyeonbin Moon, Donghyuk Cho, Jecheon Yu et al. (+2 more)

Identifying anisotropic yield functions remains challenging since yielding is not directly observed in full-field mechanical measurements, directional calibration can require many loading directions, and selecting an appropriate analytical form is nontrivial. This study proposes a physics-informed framework for discovering yield functions from full-field displacement data and reaction force data, without stress observations, plastic strain measurements, direct yield surface data, or a prescribed parametric yield function. The framework identifies the yield function as a mechanically constrained constitutive component inside elastoplastic stress integration, rather than through direct stress-space supervision. The yield function is represented by a convex neural network that enforces convexity and positive homogeneity of degree one while imposing the assumed tension-compression symmetry, and this neural yield function is trained with a differentiable stress update and a physics-informed force equilibrium loss across multiple loading cases. The proposed framework is validated using finite element (FE) benchmark studies with von Mises, Hill 1948, and Yld2000-2d yield functions, assessing yield contour agreement, displacement-noise sensitivity, identifiability through plastically active stress states, epistemic uncertainty, and polynomial-surrogate deployment. This study provides a mechanics-constrained pathway for discovering anisotropic yield functions from displacement and force data while keeping the identified component within the structure of elastoplastic stress integration.
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All authors Hyeonbin Moon, Donghyuk Cho, Jecheon Yu, Jeong Whan Yoon, Seunghwa Ryu

Materials Science · Cross-listed from physics.flu-dyn

Impulsive Hydrodynamic Exfoliation into Monolayer Graphene and Nanofragments by Transonic Flow Focusing

A. Ponce-Torres, A. Rubio-González, J. M. Montanero et al. (+2 more)

We propose using Transonic Flow Focusing (TFF) to produce 2D and 0D nanomaterials. This technique focuses liquid suspensions into high-speed micrometer-scale jets, combining extremely high shear and elongational stresses in a confined, contact-free zone. For the Graphene Nanoplatelets suspensions and TFF operating conditions investigated here, the process promoted exfoliation without added surfactants or oxidative chemistry. Both graphene monolayer flakes ($\sim 300-400$ nm in lateral size) and monolayer graphene nanofragments with lateral sizes compatible with quantum dots ($\sim 10-15$ nm) were obtained in a single TFF step using isopropanol and pure water. Our theoretical analysis reveals that, during microsecond residence times at the meniscus-jet transition, shear and extensional stresses of the order of $10^6$ s$^{-1}$ act on the suspended particles, yielding viscous power densities of the order of $10^{10}$ $\mathrm{W/m^{3}}$. High-resolution transmission electron microscopy and atomic force microscopy show that the monolayer fraction exceeded 99% for isopropanol and 92.9% for water. These results suggest that TFF can combine solvent versatility with a high monolayer fraction in a purely mechanical top-down process.
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All authors A. Ponce-Torres, A. Rubio-González, J. M. Montanero, M. A. Herrada, F. J. Galindo-Rosales

Materials Science · Cross-listed from physics.comp-ph

Distilling latent electrostatics from foundation machine learning interatomic potentials

Xiaoyu Wang and Bingqing Cheng

Foundation machine learning interatomic potentials (MLIPs) have enabled atomistic simulations across broad regions of chemical and materials space, but many remain computationally expensive and lack explicit electrostatics, limiting their use for systems governed by long-range interactions and electrical response. Previously, we introduced Latent Ewald Summation (LES), which learns latent atomic charges and long-range electrostatics from density functional theory (DFT) energy and force labels alone. Here, we use LES to extract electrostatics that are latent in foundation models: energies and forces predicted by a teacher model are used to train a lightweight LES-augmented student MLIP, with optional fine-tuning on additional DFT data. The resulting models reduce computational cost while providing access to Born effective charge tensors, and infrared spectra. We benchmark student models distilled from a broad set of foundation MLIPs, including UMA, MACE, Orb, eSEN, GemNet-OC, PET, and EquiformerV2-based models, against experimental infrared spectra for liquid water, concentrated hydrochloric acid, and the anatase TiO2(101)-water interface. Across these systems, electrostatic response can be extracted from most foundation MLIPs. The benchmark further shows that the underlying DFT level and dataset used to train the teacher model play a larger role than architecture in determining electrostatic and spectroscopic accuracy. For the TiO2-water interface, fine-tuning with a modest amount of higher-level DFT data improves structural and infrared predictions. LES-based distillation therefore provides a practical route for converting foundation MLIPs into efficient, electrically responsive models, while also testing the physical fidelity encoded in foundation models.
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Materials Science

Complementary Thermodynamic Mechanisms of Boron and Carbon Segregation at Grain Boundaries in Nickel Alloys

Tyler D. Doležal, Rodrigo Freitas and Ju Li

Grain boundary stabilization by light interstitials is central to the performance of Ni-based superalloys, yet the thermodynamic mechanisms governing their interactions with substitutional chemistry remain poorly resolved. Here, we use hybrid Monte Carlo molecular dynamics simulations to quantify how boron and carbon modify the thermodynamic, structural, and chemical ordering of grain boundaries in Ni–Cr alloys. By analyzing interfacial state variables, site-resolved segregation spectra, local chemical ordering, and structural evolution, we show that boron and carbon stabilize grain boundaries through complementary pathways. Carbon drives saturation-controlled stabilization by recruiting Cr and conditioning boundary chemistry, while suppressing temperature-driven structural transformations of the boundary. In contrast, boron stabilizes grain boundaries through a selective mechanism that lowers the interfacial grand potential via localized ordering while permitting gradual structural evolution. These effects arise from coupled interactions between interstitial segregation and Cr redistribution, which together regulate site accessibility, chemical competition, and the range of accessible interfacial states. This work provides a thermodynamic framework for grain boundary engineering and suggests design principles for leveraging interstitial-substitutional interactions in alloys.
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Materials Science

Fermi-Level-Dependent Defect Chemistry and Oxygen Evolution Reaction Activity of Fe-Doped and Oxygen-Deficient \ce{SrTiO3}(001)

Amit Sehrawat and Jochen Rohrer

The oxygen evolution reaction (OER) on perovskite oxides is controlled by the interplay of dopant chemistry, defect charge states, and surface segregation, yet these factors are rarely treated on equal footing. Using first-principles density functional theory, we investigate how Fe dopants (\FeTi{}) and oxygen vacancies (\VO{}) in different charge states affect the OER on TiO$_2$-terminated \ce{SrTiO3}(001). We combine charge-dependent defect formation energies, segregation energies, and charge transition levels with OER free-energy profiles obtained in the computational hydrogen electrode framework. Neutral \FeTix{} preserves near-pristine activity, with overpotentials of $0.43$–$0.48$~V compared to $0.45$~V for the pristine surface, whereas the reduced states \FeTip{} and \FeTipp{} raise the overpotential to as much as $1.35$~V when intermediates bind to Ti sites adjacent to surface Fe. Oxygen vacancies segregate to the surface across the entire band gap ($\Delta E_\mathrm{seg} = -0.50$ to $-0.80$~eV) but do not improve the activity: \VOx{} and \VOp{} overstabilize oxygenated intermediates ($\eta$ up to $2.13$~V), and only \VOpp{} retains a balanced pathway ($\eta = 0.45$~V in the bulk-like region). Because the stable charge state and the segregation tendency of each defect are set by the Fermi level, the OER overpotential itself becomes a Fermi-level-dependent quantity. These results establish Fermi-level engineering as a framework for assessing and tuning defect-mediated OER activity in perovskite oxides.
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Materials Science

Precipitation strengthening as a collective multi-dislocation phenomenon

Mahmudul Islam, Jason Ogbebor, Nicolas Bertin et al. (+3 more)

Precipitation strengthening is a cornerstone of physical metallurgy, delivering otherwise unattainable combinations of strength and ductility. The approach relies on nanoscale precipitates that impede the motion of dislocations, the primary carriers of metal plasticity. Historically, precipitation strengthening has been rationalized via two idealized, limiting mechanisms: dislocations either cut through or bow around precipitates. However, under many technologically relevant conditions, multiple dislocations can interact with a precipitate at the same time, potentially giving rise to distinct precipitate-dislocation dynamics that in situ experiments are yet to fully resolve. Here, using large-scale atomistic simulations (100 million atoms) that capture these dynamics, we demonstrate that in this regime, the cutting-versus-bowing dichotomy is incomplete: strengthening arises as an emergent phenomenon driven by concurrent multi-dislocation interactions. These interactions simultaneously induce dislocation accumulation at interfaces, storage within precipitates, and precipitate-mediated multiplication inside the matrix. Our findings establish a distinct mechanistic regime of precipitation strengthening beyond traditional models and provide a quantitative foundation for predicting its behavior.
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All authors Mahmudul Islam, Jason Ogbebor, Nicolas Bertin, Sylvie Aubry, Vasily V. Bulatov, Rodrigo Freitas

Materials Science

Atomistic insights into the structural, thermal, and mechanical evolution of $Zr_{47.5}Cu_{47.5}Ag_{5}$ bulk metallic glass

N. Mendez, S. Jaroszewicz, M. P. Beccar-Varela et al. (+1 more)

Bulk metallic glasses (BMGs) are distinguished by amorphous atomic structures that confer superior mechanical performance; however, the evolution of these properties in ternary bulk configurations remains insufficiently explored. In this study, we employed large-scale molecular dynamics simulations to investigate the structural, thermal, and mechanical properties of $Zr_{47.5}Cu_{47.5}Ag_{5}$ BMGs. Our thermodynamic and topological analyses, utilizing potential energy regression and the Modified Wendt-Abraham parameter, identified a glass transition temperature ($T_g$) of approximately $692\text{ K}$. Structural characterization via Voronoi tessellation and partial radial distribution functions reveals that the amorphous matrix is stabilized by icosahedral clusters, with Ag atoms inducing significant chemical heterogeneity through localized nano-clustering. Thermal transport properties, computed via the Green-Kubo formalism, demonstrate a monotonic decrease in conductivity with temperature, consistent with structural scattering saturation in disordered lattices. Mechanical tensile testing reveals that the material exhibits robust rate- and temperature-dependent behavior, with yield strengths reaching $\approx 2.3\text{ GPa}$ at room temperature. We show that macroscopic strain-softening is intrinsically linked to the thermally induced collapse of rigid icosahedral motifs, which facilitates shear band percolation. These findings provide a structural rationale for the beneficial role of Ag dopants in enhancing the resilience of multicomponent metallic glasses.
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All authors N. Mendez, S. Jaroszewicz, M. P. Beccar-Varela, M. C. Mariani

Materials Science · Cross-listed from cond-mat.mes-hall

Dominant spin Hall torque and negligible orbital Hall torque in {\alpha}-W/ferromagnet heterostructures with artifacts-free angular momentum detectors

Taiyang Zhang, Lujun Zhu, Qianbiao Liu et al. (+1 more)

{\alpha}-phased W was theoretically predicted to have a negative spin Hall conductivity and a positive orbital Hall conductivity at the same time, leaving the physical origin of the current-induced torque a critical open question. Here, we develop two angular momentum detectors of Cu/Ni/Cu and Cu/Fe60Co20B20/Cu that are free of artifacts torques (e.g., self-induced torque and spin-vorticity torque) and clarify that the spin-orbit torque contributed by {\alpha}-W remains negative and predominantly from the spin Hall effect in the entire thickness regime. The damping-like torque exhibits a monotonic decay as the W thickness increases above 5 nm likely due to the thickness-dependent structural evolution and resistivity reduction of the W layer. The negative torque in the entire thickness regime suggests negligible orbital Hall torque from {\alpha}-W. This result is consistent with the theory that the orbital Hall effect from simplified band structure calculations is not a non-local angular momentum source.
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All authors Taiyang Zhang, Lujun Zhu, Qianbiao Liu, Lijun Zhu

Materials Science

Absence of orbital current torque in a magnetic metal/Pt/CuOx trilayer

Zhihao Yan, Lujun Zhu, Xiangrui Qin et al. (+2 more)

Naturally oxidized copper (CuOx) was cited as an exceptionally strong orbital-current source despite the keen debate over the concept of orbital current. Here, we report unambiguous experimental evidence for the absence of a detectable orbital-current torque in the Fe/Pt/CuOx trilayers. Using a magnetic metal detector of Fe thin film with a negligible self-induced torque, the damping-like torque due to Pt/CuOx bilayers is clarified to entirely arise from the spin Hall spin current of the Pt. As the Pt thickness increases, the torque for Fe/Pt/CuOx and Fe/Pt/MgO increases coherently and monotonically, as exactly expected from the spin Hall effect of Pt and the drift-diffusion model of spin angular momentum. These findings suggest poor generality or even universal absence of orbital current torque.
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All authors Zhihao Yan, Lujun Zhu, Xiangrui Qin, Zhengxiao Li, Lijun Zhu

Materials Science

Designing Strong and Broadband Nonreciprocal Thermal Radiation in Magnetic Topological Materials

Yiyang Jiang, Yufei Zhao, Linxiao Zhu et al. (+1 more)

Breaking reciprocity in thermal radiation opens opportunities for energy harvesting, sensing, and thermal management. Traditional nonreciprocal radiative semiconductor devices need external magnetic field. In this work, we predict a series of magnetic topological materials for magnetic-field-free nonreciprocal thermal radiation in the infrared regime, by combining first-principles calculations with Maxwell electrodynamics. We find strong and broadband nonreciprocity in magnetic Weyl semimetals (e.g., Co$_3$Sn$_2$S$_2$), outperforming the conventional semiconductor such as InAs. Furthermore, we propose universal material design recipes: strong nonreciprocity requires a large anomalous Hall response relative to the optical loss, whereas the broadband response favors large optical loss and small dielectric dispersion. Our work establishes a predictive materials-discovery framework and quantitative design rules for next-generation magnet-free nonreciprocal thermal devices.
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All authors Yiyang Jiang, Yufei Zhao, Linxiao Zhu, Binghai Yan

Materials Science

A Multi-Level Architecture for Reusable Materials Ontologies – The OntoCrafter Ceramics Ontology (OCO) as Reference Implementation

Thomas Pannek and Wolfgang Grond

The Materials Science and Engineering ontology landscape is fragmented along multiple axes simultaneously. Horizontally: a recent survey identified 94 ontologies of which over 40 are structurally incompatible; each new application domain – ceramics, polymers, batteries, smart materials – typically restarts ontology design from scratch. Vertically: EU regulation (CSRD, CSDDD, PPWR, CBAM, R2R, AI Act, ESPR) forces material, manufacturing, supply-chain, and lifecycle data into integrated digital product passports, leaving ontologies that only address horizontal fragmentation incomplete for any contemporary consumer. And mechanistically: a vocabulary that records that BNT-BT has $d_{33} \approx 580$ pC/N stores a fact but cannot surface why – Bi-6s$^2$ lone-pair stereo-activity, anomalous Born effective charges, soft modes, defect chemistry – without a systematic explanation skeleton. We propose a multi-level modular architecture with two independent classification axes – level of abstraction (L0 bridges, L1 material-agnostic laboratory-notebook, L2 material-class-specific, L3 categorical reasoning) and consumer audience (material vs. compliance) – in which the material-specific level is internally organised by a seven-tier mechanistic-explanation skeleton (Symmetry, Energy/DFT, Thermo/CALPHAD, Kinetics, Microstructure, Defect chemistry, Bonding) applicable to any crystalline ionic oxide. The level-and-audience modularity dissolves the horizontal fragmentation, the compliance audience absorbs the vertical regulation pressure, and the seven-tier organisation of Level 2 delivers the mechanistic explanation depth. We instantiate the architecture as the OntoCrafter Ceramics Ontology (OCO v0.94): 5,196 classes across 44 modules; 167,348 OWL axioms (40,454 logical); 1,674 properties; 829 cross-ontology bridge mappings; 1,172 SHACL shapes; 163 published competency questions.
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Materials Science · Cross-listed from physics.comp-ph

Spin disorder competing with positional symmetry breaking governs the metal-insulator behavior in oxide paramagnets

Jia-Xin Xiong, Xiuwen Zhang and Alex Zunger

Numerous transition-metal oxides have low-temperature, long-range-ordered antiferromagnetic (AFM) states that are generally insulating, and high-temperature, disordered paramagnetic (PM) phases. The latter can be either insulating (predicted here for NaFeO3), or metallic (predicted here and previously observed in NaOsO3). Similar distinctions have been traditionally affected in strongly correlated models by the value used for Coulomb repulsion U. Here we show an alternative, strong-correlation-free (U=0) view suggesting that the distinction between insulating and metallic PM phases is governed by the competition between local magnetic moment disorder and the polymorphous distribution of off-center atomic displacements. Such parameter-free, energy-lowering symmetry breaking density functional calculations provide a framework for understanding metal-insulator behaviors across different quantum materials in terms of measurable local structural and magnetic parameters.
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Materials Science

Lattice dynamics and the spectroscopic signatures of H-bond disorder in $\delta$-AlOOH

Chenxing Luo, Sangjoon Lee, Hongjin Wang et al. (+2 more)

Raman and infrared anomalies associated with H-bond symmetrization in $\delta$-AlOOH, including mode softening and linewidth broadening at 5-10 GPa, occur at significantly lower pressures than predicted by static harmonic theory. To resolve this discrepancy, we combine harmonic phonon calculations with strongly constrained and appropriately normed (SCAN)-based deep-potential molecular dynamics and phonon quasiparticle analysis at 300 K. This framework extracts temperature- and pressure-dependent frequencies and lifetimes from long-time trajectories, capturing the branch reorganization and rapid linewidth growth characteristic of the disordering regime. Incorporating quasiparticle renormalization and directional longitudinal-optical-transverse-optical (LO-TO) splitting further yields near-quantitative agreement with the ambient-pressure OH-stretching Raman multiplet. These results identify finite-temperature dynamical effects and the progressive loss of spectral coherence as the origin of the spectroscopic signatures of H-bond symmetrization.
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All authors Chenxing Luo, Sangjoon Lee, Hongjin Wang, Zhen Zhang, Renata Wentzcovitch

Materials Science · Cross-listed from cond-mat.supr-con

Tailoring the properties of YBa$_{2}$Cu$_{3}$O$_{7-\delta}$ thin films by 30 keV He$^+$ irradiation: An enabling route to superconducting device nanopatterning

Bernd Aichner, Simon Koch, Philipp A. Korner et al. (+8 more)

Focused helium ion beam (He-FIB) irradiation with 30 keV ions is a key tool for nanoscale patterning and defect engineering in high transition temperature (Tc) cuprate superconducting devices, yet its usable fluence window is constrained by the competing requirements of reliable superconductivity suppression and minimal structural degradation. In this work, we provide a comprehensive dataset on the effects of large-area 30 keV He+ ion exposure on the electric transport and superconducting properties of epitaxial YBa2Cu3O7 (YBCO) thin films. X-ray diffraction shows a fluence-driven loss of crystalline order accompanied by an out-of-plane lattice expansion and an orthorhombic-to-tetragonal transition, culminating at predominant amorphization at the highest fluence of 1 x 10^16 cm^-2. Raman spectra exhibit increasing disorder while lacking signatures of oxygen depletion, indicating that irradiation mainly generates oxygen-related Frenkel defects rather than changing the carrier concentration. Consistently, with increasing fluence, the normal-state resistivity \rho_N(T) at temperature T above Tc increases strongly, while d \rho_N/d T remains nearly unchanged at moderate fluence. The suppression of Tc is accurately described by Abrikosov-Gor'kov pair breaking and reaches complete quenching of superconductivity at 4.5 x 10^15 cm^-2. The anisotropic upper critical fields decrease approximately exponentially with increasing fluence, the vortex activation energy is reduced, and the anisotropy drops, in contrast to oxygen-depleted YBCO. Hall-angle analysis confirms a nearly constant carrier density but a systematic increase in defect scattering and reduced mobility, consistent with a crossover toward the dirty limit at high fluence. These results establish quantitative fluence thresholds and a practical operational window for He-FIB nanopatterning of YBCO quantum circuits.
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All authors Bernd Aichner, Simon Koch, Philipp A. Korner, Max Karrer, Katja Wurster, Christoph Schmid, Ulrich Kentsch, Reinhold Kleiner, Edward Goldobin, Dieter Koelle, Wolfgang Lang

Materials Science

First-principles calculations of internal conversion processes in spin defects

Stefano Paolo Villani, Yu Jin and Giulia Galli

Optically active spin defects are foundational for quantum technologies, yet common approximations underestimate their internal conversion (IC) rates by orders of magnitude. We propose a broad, predictive framework to compute IC rates that incorporates multi-configurational effects via many-body wavefunctions in TDDFT, and includes all-phonon-mode contributions via analytical non-adiabatic couplings. Our approach resolves discrepancies with experiment, achieving quantitative agreement for the NV$^-$ center in diamond, and identifying a previously overlooked non-radiative channel in the divacancy triplet lifetime in SiC.
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Materials Science

Modifying Electrochemical Doping in Light-Emitting Electrochemical Cells with Gold Nanoparticles

Ajay K. Poonia, Anton Kirch, Joan Ràfols-Ribé et al. (+8 more)

Electrochemical doping offers dynamic control of the electronic properties of organic semiconductors, and it is the enabling feature of a range of technologies, including electrochemical transistors, energy-storage devices, light-emitting electrochemical cells (LECs), and bioelectronics. Electrochemical doping is commonly controlled by the selection of the constituents in the active material of the device or the applied voltage bias, but herein we report that the incorporation of Au nanoparticles (Au-NPs) at an electrode interface can constitute an alternative control parameter. The LEC features balanced p- and n-type electrochemical doping that forms a p-n junction doping structure in its active material, and we find that it is possible to reshape this doping profile by incorporating Au-NPs at an electrode interface. Specifically, we establish that the inclusion of neat non-capped Au-NPs at the anodic interface shifts the p-n junction (i.e., the emission zone) away from the anode. In contrast, the inclusion of Au-NPs capped with sodium citrate is found to reverse this behavior, so that the emission zone is instead moved towards the anode. We utilize this control parameter to shift the emission zone towards a position of constructive (destructive) interference, as manifested in a strong increase (decrease) of the LEC emission efficiency. Our findings establish an interfacial strategy for modulating the spatial profile of electrochemical doping and tuning device performance without altering the chemistry of the active material, relying instead on the surface modification of one electrode. This approach is important because it provides a versatile and minimally invasive route to optimize electrochemical devices while preserving the intrinsic properties and formulation of the active material.
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All authors Ajay K. Poonia, Anton Kirch, Joan Ràfols-Ribé, Lucrezia Catanzaro, Anish Rao, Karol Kołątaj, Vittorio Scardaci, Giuseppe Compagnini, Guillermo P. Acuna, Ludvig Edman, Nicolò Maccaferri

Materials Science

The Future of Computing for Materials Science Challenges

Phalgun Lolur, Richard P. Padbury, George H. Booth et al. (+10 more)

Materials discovery increasingly relies on the coordinated use of theory, computation, experiment, data-driven methods, and emerging quantum technologies, yet the full potential of these tools is realised only when they operate within workflows that reflect the complexity of real systems. This perspective summarises current capabilities, limitations, and opportunities across these domains, drawing on contributions from academia, industry, and national laboratories to identify the scientific and structural requirements for more reliable and efficient discovery. Classical simulations provide broad coverage across design spaces, while experimental measurements reveal degradation, heterogeneity, and kinetic processes that determine performance under realistic conditions. Machine learning accelerates exploration when supported by well-curated datasets with clear provenance and uncertainty quantification, and quantum computing offers promising routes into correlated electronic behaviour when aligned with properties that influence engineering decisions. Collectively, these insights highlight the need for reproducible workflows, shared data standards, realistic benchmarks, and a research culture that prepares scientists to work across paradigms. By integrating these methodological and organisational elements, the community can move toward discovery processes that deliver robust predictions, support confident decision making, and shorten the path from conceptual design to deployable materials.
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All authors Phalgun Lolur, Richard P. Padbury, George H. Booth, Katherine Inzani, Nicole Holzmann, Thomas W. Keal, Joseph Montaya, Daniel F. Urban, Thomas Eckl, Emanuele Marsili, Wibe A. de Jong, Jonathan R. Owens, Julian van Velzen