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Physics Condensed Matter Materials Science

cond-mat.mtrl-sci Watch Materials Science

Tuesday 19 May

Materials Science

Adaptive Slater Koster Parameters: Crossing Oxidation States with Density Functional Tight Binding

Yihua Song, Artem Samtsevych, Anton Beiersdorfer et al. (+4 more)

We propose to adapt the confined pseudo-atomic orbitals underpinning the precalculated Slater-Koster (SK) interaction tables in Density Functional Tight Binding (DFTB) to local atomic environments. We demonstrate significant improvement in electronic structure and energetics in the application to a partially oxidized Ni surface and Li insertion into graphite, where we assign optimal SK parameters to metal atoms in different oxidation states. Further analysis reveals the smoothness of the SK integrals across the varying oxidation states. Exploiting this, we introduce a site-resolved machine-learning scheme for fully adaptive DFTB. Using atomic descriptors and simple regression architectures already established in the context of machine-learning interatomic potentials, our scheme achieves 95% band-structure accuracy across all Ni-O binary compositions in the Materials Project.
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All authors Yihua Song, Artem Samtsevych, Anton Beiersdorfer, Tobias Melson, Christoph Scheurer, Karsten Reuter, Chiara Panosetti

Materials Science

Realization of a parity-violating antiferromagnetic state in LaMnSi

Takuma Iwata, K. Shiraishi, T. Aoyama et al. (+12 more)

Spontaneous symmetry breaking underlies functional electronic phenomena in quantum materials. Breaking space-inversion ($\mathcal{P}$) or time-reversal ($\mathcal{T}$) symmetry can generate spin-split electronic bands central to modern spintronics. By contrast, parity-violating antiferromagnetic (AFM) order breaks both $\mathcal{P}$ and $\mathcal{T}$ while preserving the combined $\mathcal{PT}$ symmetry, enabling spin-degenerate yet momentum-asymmetric electronic bands. This momentum asymmetry has been proposed as a microscopic origin of unconventional nonreciprocal and nonlinear responses but its experimental verification has remained challenging because it requires establishing both the symmetry-breaking magnetic order and the associated electronic structure. Here we combine soft x-ray angle-resolved photoemission spectroscopy (ARPES) and polarization-resolved optical second-harmonic generation (SHG) microscopy to study LaMnSi, a candidate parity-violating AFM metal. Soft x-ray ARPES resolves the three-dimensional bulk band structures in agreement with density functional theory calculations for the AFM phase, whereas SHG microscopy detects sign-reversing nonlinear optical responses from opposite AFM domains that carry $\mathcal{T}$-odd parity-violating order. Together, these results provide direct evidence for parity-violating AFM state in LaMnSi, establish LaMnSi as a parity-violating AFM metal, and identify this class of AFMs as a promising platform for symmetry-controlled nonreciprocal and nonlinear electronic responses.
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All authors Takuma Iwata, K. Shiraishi, T. Aoyama, D. Senba, T. Takeda, Y. Fujisawa, M. Nurmamat, K. Nakanishi, K. Yamagami, M. Arita, T. Yamada, Y. Yanagi, A. Kimura, H. Tanida, Kenta Kuroda

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

Accelerated "on-the-fly" coupled-cluster path-integral molecular dynamics: Impact of nuclear quantum effects on an asymmetric proton

Thomas Spura, Hossam Elgabarty and Thomas D. Kühne

We present an accelerated “on-the-fly” coupled-cluster path-integral molecular dynamics (PIMD) method for finite-temperature simulations in which electron correlation and nuclear quantum effects are treated simultaneously. The approach is based on our quantum ring-polymer contraction (qRPC) technique, in which the inexpensive Hartree-Fock potential is evaluated on the full ring-polymer, while the expensive coupled-cluster correction is evaluated on the centroid only. This qRPC decomposition is combined with a second-generation Car-Parrinello-like dynamics of the Hartree-Fock reference and a basis-consistent extrapolation of the coupled-cluster and de-excitation amplitudes. The combination of all three acceleration layers is essential for making correlated PIMD calculations feasible. We apply the method to a proton shared by water and formaldehyde. Relative to classical nuclei, nuclear quantum effects broaden covalent X–H bond-length distributions, reduce the bias of the shared proton toward formaldehyde, and shift the mean proton-transfer coordinate from 0.206 to 0.135A. The probability of finding the proton closer to formaldehyde decreases from 81.7$\%$ to 61.1$\%$. The corresponding nuclear magnetic shielding tensors show that electron correlation and nuclear quantum effects are of comparable magnitude and can act in opposite directions. These results demonstrate that predictive simulations of asymmetric hydrogen bonds require a simultaneous treatment of correlated electronic structure and nuclear quantum fluctuations.
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Materials Science

Partially reactive force field for the UiO-66 metal-organic framework

Akanksha Nawani and Rocio Semino

UiO-66 is the most widely studied metal-organic framework, on account of its structural tunability given by its capacity of sustaining high amounts of point defects in its structure. Its synthesis mechanism is largely unknown, with only a few works mostly focused on the formation of the Zr-oxide cluster. In this work, a partially reactive force field to model UiO-66, nb-UiO-FF, is introduced. This force field incorporates node–ligand reactivity via a Morse potential and the introduction of dummy atoms to reproduce the anisotropic charge distribution of the Zr atoms in the node. nb-UiO-FF reproduces structural features of both UiO-66 and its isoreticular analog UiO-67 as well as framework stability with or without defects, activated or filled with N,N-dimethylformamide or ethanol. Defect generation and node–ligand binding energies are comparable with density functional theory values. The force field is further employed within a molecular dynamics scheme to study the early stages of solvothermal node–ligand binding. Species with structures corresponding to motifs present in UiO-66 are observed, along with other metastable species. This force field enables studying the self-assembly of UiO-66, as well as the formation of its point defects.
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Materials Science

Building a Regional Data-Centric Materials Science Ecosystem for Processing-Rich Materials Innovation in the Great Plains

D.-M. Mei, K. Acharya, C. M. Adhikari et al. (+52 more)

Data-centric materials science is changing how materials are discovered, optimized, manufactured, and qualified, yet many deployment-limiting materials problems still depend on experimental, processing-rich, device-level, and field-relevant data that are difficult to capture in conventional materials databases. This perspective argues that the Great Plains and adjacent interior research corridor can make a distinctive national contribution by organizing distributed experimental assets into a trusted regional materials-data ecosystem. The proposed model emphasizes FAIR metadata, provenance, persistent sample identifiers, uncertainty-aware modeling, semi-closed-loop workflows, stackable workforce training, and tiered governance for academic, public, controlled-access, and industry-protected data. We identify five coupled barriers – fragmented data, weak algorithm–laboratory translation, uneven access to cyberinfrastructure and technical staff, workforce gaps at the materials–data interface, and insufficient incentives for sharing and reuse – and propose a staged roadmap for addressing them. A high-purity germanium pilot illustrates how regional strengths can be converted into reusable datasets, benchmark models, trained personnel, and decision-improving workflows. The broader message is that regional leadership in data-centric materials science will depend less on geographic concentration than on trustworthy data practices, interoperable infrastructure, cross-trained people, and application-driven materials challenges.
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All authors D.-M. Mei, K. Acharya, C. M. Adhikari, M. Adhikari, S. Aryal, B. V. Benson, K. Bhatta, S. Bhattarai, N. Budhathoki, A. M. Castillo, D. Chakraborty, S. Chhetri, S. Choudhury, T. A. Chowdhury, R. D. Cruz, B. Cui, S. Dhital, K.-M. Dong, R. Gapuz, A. Ghasemi, E. Z. Gnimpieba, B. D. S. Gurung, H. A. Hashim, R. I. Harry, K.-E. Hasin, M. K. Hassanzadeh, M. K. Jha, D. Kim, K.-C. Kong, B. Lama, A. Mahat, N. Maharjan, A. Majeed, J. Mammo, M. M. Masud, K. S. Moore, T. Mukherjee, A. Nawaz, H. Oli, S. A. Panamaldeniya, L. Pandey, R. Pandey, Z. Peng, A. Prem, M. M. Rana, K. Rana Magar, R. Rizk, C. S. Tadi, L.-W. Wang, Y. Yang, G.-L. Yin, C.-X. Yu, D. Zeng, M. Zhou, Q. Zhou

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

Function, Complexity and Thermodynamics in Adaptive and Intelligent Soft Matter Systems: An Information-Theoretical Framework

George S. Attard

The terms responsive, adaptive and intelligent are widely used in soft matter and materials science but remain qualitative, with no quantitative basis for comparing systems from different areas on a common axis. We address this by treating any stimulus-coupled material as an information channel. The three classes are distinguished by kernel conditioning: a memoryless map p(y|x) (responsive), a state-conditioned map p(y|x,s) (adaptive), and a feedback-modified channel with memory (intelligent). Three information-theoretic metrics follow: configurational diversity I1, functional selectivity I2, and stimulus-response information transfer I3. Because the kernel and substrate are the same object, a heuristic non-monotonic relationship arises between internal complexity and realised information transfer, with an optimal complexity N* set by transmission efficiency, stimulus energy and thermal noise. We propose two benchmarking planes: a dynamic plane (volumetric information rate I3/V versus power density P, referenced to the Landauer-Berut floor) and a static plane (I1, I2). Sixteen systems spanning synthetic soft matter, biology and hard matter separate into broad bands above the benchmark: ~10^18-10^20x for soft matter and shape-memory alloys, 10^10-10^16x for silicon and electromechanical devices, 10^9-10^10x for neuromorphic memristors, and 10^5-10^8x for evolved biology, with an ER lipid network near 10^11x. Each placement carries an uncertainty of one to two decades per axis; the band ordering nonetheless appears robust. The gap between synthetic soft matter and biology is tentatively attributed to the per-element substrate energy scale (1-10 kBT versus 10^4-10^5 kBT). The framework is offered as a foundation that may lead to validated design rules; three routes are proposed by which soft matter's separation from the Landauer benchmark might be reduced.
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Materials Science

Direct Simulation of LiNi0.8Mn0.1Co0.1O2 Transport Properties Using an Efficient and Accurate Machine Learning Potential

Jian He, Constantijn H. J. A. van de Wetering, Rolande W. Nolsen et al. (+1 more)

The rate capability of layered lithium nickel manganese cobalt oxide (NMC) cathode materials plays a decisive role in high-power applications such as fast charging, necessitating a detailed understanding of lithium-ion diffusion. However, the mechanisms governing lithium-ion transport in NMC remain insufficiently understood, both experimentally and computationally. In this study, we employ an advanced and efficient machine learning potential (MLP) to simulate lithium self-diffusion in LiNi0.8Mn0.1Co0.1O2 (NMC811), enabling direct large-scale molecular dynamics (MD) simulations. The workflow integrates a fine-tuned MACE (Message Passing Atomic Cluster Expansion) foundation model as a structural generator and leverages an active learning strategy applied to a near-ground-state dataset. This approach enables the construction of a reliable MLP for NMC811 in a data-efficient manner using a limited number of density functional theory (DFT) reference calculations. Based on this potential, we performed MD simulations to predict lithium diffusion coefficients. The MLP-based simulations preserve the accuracy of DFT while overcoming its time and length scale limitations, thereby allowing direct simulation of lithium self-diffusion in NMC811.
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All authors Jian He, Constantijn H. J. A. van de Wetering, Rolande W. Nolsen, Nongnuch Artrith

Materials Science

$G_0W_0$@HF and BSE methods in periodic systems from Hartree-Fock theory: gaussian orbital and density fitting approach

Charles H. Patterson

The $GW$ method for calculating quasi-particle energies of solids commonly begin from a DFT Hamiltonian and Kohn-Sham orbitals in a plane wave basis. Screening of the coulomb interaction is implemented using the inverse dielectric function in the random phase approximation (RPA). We present $G_0W_0$ calculations which begin from the Hartree-Fock method in a basis of gaussian orbitals. The screened coulomb interaction, $W$, is obtained using a $W$ = $v$ + $v\Pi v$ approach without invoking a plasmon pole approximation. The polarizability, $\Pi$, in $W$ is treated at the RPA level. RPA polarizabilities require solution of Bethe-Salpeter equations (BSE) for each unique $\textbf{Q}$ point. A strategy for obtaining self-energies which are converged with respect to number of virtual states is employed in which $G_0W_0$ yields the majority of the self-energy and the remaining part from high energy virtual levels is evaluated at second-order. The methods are evaluated by applying them to elemental semiconductors (C, Si) and oxides (MgO and anatase and rutile TiO$_2$). Common errors of HF theory applied to materials include overestimation of both the band gap and valence band widths. These are corrected in the approach employed here. Typically, the RPA screened interaction results in overestimation of band gaps while the $G_0W_0$ self-energy band width renormalization yields band widths for diamond and Si which are in good agreement with experiment. HF calculations are performed in gaussian orbital basis sets and $G_0W_0$ and BSE calculations are performed using density fitting with a coulomb metric.
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Materials Science

Impacts of annealing on structural and photophysical properties of zinc phthalocyanine adsorbed on graphene

Gautier Creutzer, Quentin Fernez, Nataliya Kalashnyk et al. (+5 more)

We report the demonstration and analysis by combined scanning-tunneling-microscopy and optical microspectroscopy of a 2D phase change experienced by a self-assembled zinc phthalocyanine (ZnPc) monolayer adsorbed on graphene. To probe the intrinsic properties of individual ZnPc molecules, they are spatially confined within the pores of a self-assembled 2D matrix. This confinement allows us to track a phase change induced by annealing, which we discuss in terms of a planar-square to shuttlecock molecular transition. We show that after annealing of the adsorbed ZnPc, the exposition of Zn atoms to reactants in a supernatant solution is improved, for example, for metal-ligand formation towards 3D self-assembly.
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All authors Gautier Creutzer, Quentin Fernez, Nataliya Kalashnyk, Zohreh Safarzadeh, Lydia Sosa Vargas, Céline Fiorini-Debuisschert, Nicolas Fabre, Fabrice Charra

Materials Science

Predicting Organic Solar Cell Performance and Stability from Fast, Morphology-aware Current-Voltage Modeling

Yasin Ameslon, Larry Lüer, Jens Harting et al. (+2 more)

Understanding the relationship between morphology and performance in organic solar cells is essential for developing devices that are both high performing and resilient to aging. This work introduces a unique method capable of calculating the current-voltage (JV) curve of complex heterojunction morphologies containing up to five phases (donor amorphous, donor crystalline, acceptor amorphous, acceptor crystalline, mixed amorphous) with a very low computation time using morphology-aware descriptors of light absorption, exciton dissociation, non-geminate recombination and free charge carrier mobilities. The method is validated against Monte Carlo and 3D drift-diffusion simulations and applied to P3HT:PCBM and PM6:Y6 systems, shedding light on the physical compromises encountered to optimize device performance and lifetime. Finally, we show that the morphology-performance relationship is dependent on the materials system studied.
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All authors Yasin Ameslon, Larry Lüer, Jens Harting, Olga Wodo, Olivier J.J. Ronsin

Materials Science

Impact of the Lattice Constant on the Polymorphism of Organic/Inorganic Interfaces

Christoph Wachter and Oliver T. Hofmann

The polymorphism of organic/metal interfaces influences many of their properties. As a result, a host of contemporary research focuses on analyzing the factors which are pertinent for modifying polymorphism. In this work, we elucidate how the lattice constant of the underlying lattice affects the energetic landscape of adsorbate monolayers for the model system of tetracyanoquinodimethane (TCNQ) on coinage metal surfaces with varying lattice constants. In particular, we focus on how the adsorbateadsorbate and the adsorbate-substrate interaction are affected when increasing the lattice constant and changing the surface chemistry. Based on these investigations, we show that the adsorbate-substrate interaction for some adsorption geometries can change significantly with the lattice constant. In addition, due to a transition from repulsive to attractive adsorbate-adsorbate interactions, polymorphs with tight packing become more favorable, if the lattice constant is increased, resulting in a lattice-constant-based phase transition.
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Materials Science

Nanoscale Thermal Imaging of Dislocation-Mediated Heat Transport

Ruilin Mao, Bingyao Liu, Jiaxin Liu et al. (+7 more)

Dislocations in crystalline materials are widely exploited to tailor the thermal conductivity of semiconductors and thermoelectrics, yet a critical gap persists: direct measurement of local thermal resistance at individual buried dislocations, along with its spatial extent, remains elusive due to the limitations of conventional thermal probes. Here, we use in situ scanning transmission electron microscopy-electron energy-loss spectroscopy to map nanoscale temperature distributions across a low-angle SrTiO3 grain boundary with periodic dislocation arrays. Our results reveal a temperature drop of 47 K across the dislocation array. The associated temperature-field distortions are concentrated near the dislocation cores, consistent with stronger local thermal resistance at these discrete sites rather than a uniformly distributed resistance along the array. We further identify a distinct two-scale heat transport characteristic near the dislocation array: core-dominated effects over approximately 4.8-6.2 nm and extended inter-core influences over approximately 10.3-14.3 nm. Atomic-scale structural and vibrational analyses further reveal core-associated atomic reconstruction and localized optical-phonon perturbations, providing a microscopic basis for the stronger local thermal resistance inferred near dislocation cores. These findings quantitatively resolve spatial heterogeneity of dislocation-mediated heat transport, uncover its atomic-scale mechanism, and provide a quantitative basis for defect engineering, guiding the design of high-performance thermoelectrics, semiconductors, high-temperature structural alloys, and other functional crystalline materials.
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All authors Ruilin Mao, Bingyao Liu, Jiaxin Liu, Xiaoyue Gao, Junping Luo, Fachen Liu, Ruochen Shi, Jiade Li, Jinlong Du, Peng Gao

Materials Science

High-Throughput Bayesian Optimization of Cement-Salt Hydrates Composites for Seasonal Thermochemical Energy Storage

Alessio Mondello, Giulio Barletta, Luca Lavagna et al. (+3 more)

Thermochemical energy storage (TCES) based on salt hydrates is a promising route for seasonal heat storage; however, the design of practical sorbent materials remains challenging due to a non-trivial coupling between composition, synthesis feasibility, performance, and cost. Here, focusing on salt-into-matrix cement-based composites, we demonstrate that a high-throughput experimental framework based on Bayesian optimization (BO) can be used to orchestrate the optimization process of composite materials for low-temperature TCES. The explored design space is defined by salt type, salt concentration, water-to-cement ratio, and additive-to-cement ratio, while two competing objectives are pursued in parallel, namely the specific energy and the specific energy cost. The BO-guided campaign identified Pareto-optimal composites based on CaCl$_2$, Zn(NO$_3$)$_2$, and LiCl, highlighting the promise of cement-salt combinations that have been only marginally explored, or not previously reported, in cement-based TCES systems. The best-performing formulation (LiCl-based), achieved an average specific energy of about $\SI{458}{\kilo\joule\per\kilo\gram}$, whereas CaCl$_2$- and Zn(NO$_3$)$_2$-based composites showed lower but still competitive specific energy values combined with more favorable specific energy cost. Overall, the optimized formulations improved the specific energy of previously developed cement-based materials by up to a factor of five, although it remains below that of state-of-the-art composites based on silica gel and expanded vermiculite. Nonetheless, the present materials, notably CaCl$_2$- and Zn(NO$_3$)$_2$-based composites, offer an attractive cost-to-performance balance, highlighting BO as an effective strategy for accelerated TCES materials discovery.
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All authors Alessio Mondello, Giulio Barletta, Luca Lavagna, Matteo Fasano, Matteo Pavese, Eliodoro Chiavazzo

Materials Science

Zero-net-magnetization hybrid magnet

San-Dong Guo and Shi-Hao Zhang

Zero-net-magnetization magnets possess ultradense and ultrafast application potential, benefiting from their intrinsic zero stray field and terahertz dynamics characteristics. Herein, we propose the concept of zero-net-magnetization hybrid magnet, in which magnetic atoms with opposite spin polarization are partially coupled via spatial inversion ($P$) symmetry, partially via rotation/mirror ($C/M$) symmetry or partially without any symmetry correlation. From a local perspective and neglecting the interactions between local regions, hybrid magnet can be regarded as being composed of $PT$-antiferromagnet (possessing the combined symmetry ($PT$) of $P$ and time-reversal ($T$)), altermagnet, or fully compensated ferrimagnet. To realize hybrid magnet, we propose that such system can be constructed by forming heterojunction with three types of zero-net-magnetization magnetic monolayers. We mainly investigate the heterojunction composed of two kinds of zero-net-magnetization magnets, among which one type corresponds to fully compensated ferrimagnet. When heterojunction hybrid magnet exhibits a type-II band alignment, only one of electron doping and hole doping can induce a net magnetic moment, while the other hardly generates any net magnetization. Taking the heterojunction constructed by $PT$-antiferromagnet and fully compensated ferrimagnet as an example, we verify our proposal by means of the tight-binding (TB) model. Finally, taking the $\mathrm{Cr_2C_2S_6}$/$\mathrm{CrMoC_2S_6}$ heterojunction as an example, we perform first-principles calculations combined with electric field modulation to validate our TB model and theoretical proposal.
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Materials Science

Evaluation of External Magnetic Flux Density in Piezo-Flexomagnetic Nanobeams Using a Hybrid 1D-2D Finite Element Framework

Lala Samprit Ray and Bishweshwar Babu

This study numerically evaluates the external magnetic flux density generated in air by the bending of a piezo-flexomagnetic nanobeam. In several classes of non-contact sensors, the magnetic field induced in the surrounding medium is often more useful than the internal magnetic response. However, most theoretical studies on piezo-flexomagnetic nanostructures neglect the external magnetic domain. The proposed framework employs a coupled hybrid finite element formulation combining a 1D Timoshenko beam model with a 2D magnetostatic problem encompassing both the beam body and the surrounding air domain. The formulation is verified against analytical solutions of magnetically isolated piezo-flexomagnetic beams. The results demonstrate the presence of a significant external magnetic flux distribution in free-standing structures, even in the absence of piezomagnetic coupling. A systematic sensitivity analysis further identifies the material parameters most strongly influencing the external transverse magnetic flux density. These findings provide insight into the design of nanoscale non-contact magnetoelastic sensing systems.
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Materials Science

Octahedral Tilting in Halide Double Perovskites: Disentangling Lone-Pair Chemistry and Geometric Effects

Mehmet Baskurt, Erik Fransson, Madeleine Lindvik et al. (+2 more)

Halide double perovskites (HDPs) have emerged as promising alternatives to their lead-based counterparts. However, their structural dynamics is less explored than that of conventional halide perovskites. In this work, we investigate octahedral tilting at 0 K and the relative stability of tetragonal and cubic phases of a set of 57 halide double perovskites (HDPs). By combining structural and energetic descriptors with simple geometric metrics, we identify the main trends controlling the stabilization of one-tilt tetragonal phases across this family. We find that both the magnitude of the tilt angles and the energetic preference for tilted phases correlate primarily with the Goldschmidt tolerance factor $t$. The presence of stereochemically active lone-pair cations also correlates with enhanced tilting; however, this trend largely reflects that lone-pair chemistries in HDPs occur together with ionic sizes that shift $t$ away from unity. Consistent with this picture, we observe several compounds without lone pairs that nonetheless exhibit strong octahedral tilting. Finally, using machine-learned interatomic potentials, we connect the 0 K tilting energetics to finite-temperature behavior: compounds with more strongly stabilized tilt phases exhibit higher transition temperatures, and phonon spectra at 350 K reveal soft and broad modes that are consistent with the trends in tolerance factors, tilt angles, and tilt energies at 0 K. Our results provide a systematic reference for structure-stability relationships in HDPs and clarify when lone-pair chemistry is correlated with, rather than the primary cause of, octahedral tilting.
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All authors Mehmet Baskurt, Erik Fransson, Madeleine Lindvik, Paul Erhart, Julia Wiktor

Materials Science

Charge Symmetry Beyond Space-Group Equivalence

Qiu-Shi Huang, Xin-Gao Gong and Su-Huai Wei

Crystallographic space-group symmetry $G_{\rm lat}$, determined by atomic species and their spatial arrangement, is one of the most important descriptors in solid-state physics, underlying the classification of electronic states, spectral degeneracies, order parameters, and phase transitions. Yet the symmetry $G$ of a crystal also depends on the electronic coupling network between atomic sites, including electron hopping, Coulomb interactions, and orbital hybridization. This raises a fundamental question: must $G$ reproduce every equivalence relation imposed by $G_{\rm lat}$? Equivalently, must symmetry-related atoms at the same Wyckoff position be electronically identical, while atoms at inequivalent Wyckoff positions are electronically distinct? We develop a systematic theory of interaction-controlled electronic equivalence, with site charge imbalance as an order parameter whose stability is governed by the competition between onsite charging cost and intersite Coulomb gain. Group-theoretical analysis identifies the site-exchange operations lost from or added to $G_{\rm lat}$. Sites identified as equivalent by $G_{\rm lat}$ can spontaneously develop charge imbalance, lowering the realized symmetry to $G\subset G_{\rm lat}$. Conversely, sites identified as inequivalent by $G_{\rm lat}$ can remain equivalent through a hidden low-energy gauge symmetry. Within the low-energy $(s,p_z)$ manifold, this realizes $G\supset G_{\rm lat}$ and protects near-Fermi degeneracies that appear accidental in a $G_{\rm lat}$-based analysis. First-principles calculations verify both scenarios and establish pressure as a control parameter: it destabilizes the charge-equivalent state in Type I, whereas in Type II it destroys the hidden equivalence, splits the near-Fermi doublets, and can drive a metal-insulator transition.
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Materials Science

Cryogenically Enhanced Laser-Induced Amorphous Phase Transitions in Crystalline Silicon

Conrad Kuz, Andy Lee, Shashu Tomar et al. (+6 more)

Amorphization of silicon is crucial to applications in photonics, microelectronics and solar cell technologies. Ultrafast lasers have been used to generate amorphous silicon from crystalline silicon using rapid nonthermal melting and solidification in room temperature. As material temperature can affect cooling rates significantly, adding temperature control in ultrafast laser modification of silicon may allow a new degree of freedom in ultrafast laser modification. In this work, we investigate the role of cryogenic temperature in governing ultrafast damage pathways via single-shot femtosecond laser irradiation of silicon from room temperature down to 24K at 1030nm. Across this temperature range, we observe a pronounced enhancement of amorphization at lower temperatures, revealed through optical microscopy, Raman spectroscopy, and Kelvin probe force microscopy (KPFM). Raman analysis identifies this ring as an amorphous surface layer, while complementary AFM and SEM imaging show temperature-dependent changes in surface morphology, including localized melt redistribution and refrozen material. To elucidate the physical origins of this behavior, we implement a carrier dependent two-temperature model (nTTM). The simulations reproduce the experimentally observed trends and indicate that reduced phonon population, modified absorption pathways, and altered lattice relaxation dynamics at cryogenic temperatures collectively promote amorphous freezing over recrystallization. This study represents the first detailed examination of silicon under ultrafast irradiation below the liquid-nitrogen regime and reveals temperature-governed mechanisms relevant for advanced silicon microstructuring.
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All authors Conrad Kuz, Andy Lee, Shashu Tomar, Ravleen Kaur, Mohamed Yaseen Noor, Justin Twardowski, Liam Clink, Roberto C. Myers, Enam Chowdhury

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

Nearly perfect Fermi surface nesting in hole-doped La$_3$Ni$_2$O$_7$ enables bulk superconductivity without pressure or strain

Chengliang Xia, Jiale Chen, Hongquan Liu et al. (+1 more)

The discovery of high-temperature superconductivity in Ruddlesden-Popper nickelates has drawn great attention. However, unlike cuprates and iron-based superconductors, Ruddlesden-Popper nickelates exhibit superconductivity either under high pressure in bulk samples or under compressive strain in thin films. Genuine bulk superconductivity under ambient pressure has remained elusive in these materials, precluding key measurements such as specific heat and superfluid density. In this work, we combine density-functional-theory, dynamical-mean-field-theory, and random-phase-approximation to solve the superconducting gap equation for bulk hole-doped bilayer nickelate La$_{3-x}$Sr$_x$Ni$_2$O$_7$ at ambient pressure. We find that hole doping induces a Ni-$d_{3z^2-r^2}$-derived $\gamma$ pocket on the Fermi surface, and serves as a tuning parameter for both its size and shape. As $x$ approaches 0.4, the $\gamma$ pocket evolves from circular to diamond-shaped and expands to span half of the Brillouin zone, resulting in nearly perfect Fermi surface nesting with the optimal nesting vector $\textbf{Q} = (\pi, \pi)$. This, in turn, strongly enhances antiferromagnetic spin fluctuations and substantially increases the leading superconducting eigenvalue to a level at which superconductivity becomes experimentally observable. Our work provides both a robust mechanism and an experimentally feasible route to inducing the long-sought bulk superconductivity in La$_3$Ni$_2$O$_7$ without pressure or strain.
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All authors Chengliang Xia, Jiale Chen, Hongquan Liu, Hanghui Chen

Materials Science

Frequency-dependent stress response under thermal cycle: A thermal-crystal plasticity and dynamic mode decomposition study

Haruki Ohashi and Yoshiteru Aoyagi

Thermal cycle environments involving repeated temperature changes are common conditions observed in modern engineering processes. Under such conditions, materials undergo repeated thermal expansion and contraction, forming complex thermal stress fields. Thermal-crystal plasticity simulations that account for stress fields and thermal conduction at the polycrystalline microstructure scale are an effective method for numerically reproducing thermal cycle environments. However, the influence of thermal cycle frequency on the temporal behavior of the stress field and plastic response has not yet been fully understood, partly because a systematic analysis method capable of simultaneously capturing spatial heterogeneity and temporal evolution remains limited. In this study, we predicted the thermal stress field generated under different thermal cycle frequencies using thermal-crystal plasticity simulations and investigated the effect of frequency on the spatiotemporal structure of the stress response. The present framework illustrates that the resulting thermal-mechanical response can be represented as a superposition of multiple effective temporal components, reflecting the increased complexity of the system behavior. By employing dynamic mode decomposition (DMD) as a diagnostic and post-processing technique, we demonstrate that the spatiotemporal structure of the stress field under thermal cycle conditions can be systematically extracted and compactly represented. This approach enables a quantitative characterization of frequency-dependent changes in the thermal stress response beyond conventional averaging or snapshot-based analyses. The results highlight the utility of DMD as a framework for organizing complex simulation data and for interpreting the temporal structure of plastic response under cyclic thermal loading.
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Materials Science · Cross-listed from cond-mat.mes-hall

Transconductance as a Probe of Valley Thermodynamics in Multilayer WSe$_2$

Katsunori Wakabayashi, Souren Adhikary and Tomoaki Kameda

Transconductance is a central figure of merit in field-effect transistors, typically governed by charge accumulation and carrier mobility. In multilayer WSe$_2$ transistors, however, it is shown to carry a nonlinear transport signature of inter-valley carrier redistribution between the $K$ and $\Gamma$ valleys. This valley-crossover contribution suppresses transconductance in bilayer WSe$_2$ and reverses sign in trilayer, while remaining absent in single-valley systems. Unlike extrinsic mechanisms such as trap-state filling or contact resistance, the anomaly leaves the subthreshold swing unchanged and cannot be reproduced within conventional single-valley transport models. Introducing the valley susceptibility $\chi_v \equiv \partial f_\Gamma/\partial V_{\rm GS}$, bounded by an intrinsic thermodynamic limit $(4k_BT)^{-1}$, we quantify this response and show that it reaches ${\sim}0.20\,\mathrm{V}^{-1}$ in bilayer WSe$_2$ near threshold at room temperature. The sign, magnitude, and temperature dependence of the anomaly provide directly measurable fingerprints of valley thermodynamics, establishing transconductance as an electrical probe of internal electronic degrees of freedom and revealing a previously hidden nonlinear response in standard transistor measurements.
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Monday 18 May

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

Harnessing AtomisticSkills for Agentic Atomistic Research

Bowen Deng, Bohan Li, Matthew Cox et al. (+20 more)

Computational materials science and chemistry span vast knowledge domains and fractured software ecosystems. Although large language models (LLMs) have demonstrated research capabilities, scaling monolithic agents to manage the rigor and complexity of atomistic research remains a challenge. Here, we introduce AtomisticSkills, an open-source harness framework that empowers general-purpose AI coding agents to conduct atomistic research across materials science, chemistry, and drug discovery. By hierarchically decomposing scientific workflows into agent skills and tools, AtomisticSkills provides agents with modular, extensible, and plug-and-play research capabilities. The framework integrates more than 100 human-curated multidisciplinary skills, including database access, thermodynamics and kinetics modeling, and diverse simulation engines employing machine learning interatomic potentials (MLIPs) and density functional theory (DFT). We validate its functional coverage against scientific literature and demonstrate robust orchestration capabilities across diverse scientific campaigns: generative design of Li-ion solid-state electrolytes, high-throughput screening of metal-organic frameworks for CO2 capture, autonomous MLIP benchmarking and fine-tuning, multi-stage structure-based virtual screening for drug design, multimodal X-ray diffraction pattern analysis, and screening of Fe-oxide catalysts for oxygen evolution reaction. AtomisticSkills provides a critical agent infrastructure towards building fully autonomous AI scientists.
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All authors Bowen Deng, Bohan Li, Matthew Cox, Hoje Chun, Juno Nam, Artur Lyssenko, Sathya Edamadaka, Jurgis Ruza, Xiaochen Du, Nofit Segal, Jesus Diaz Sanchez, Mingrou Xie, Ty Perez, Yu Yao, Miguel Steiner, Sauradeep Majumdar, Charles B. Musgrave III, Anirban Chandra, Abhirup Patra, Detlef Hohl, Connor W. Coley, Ju Li, Rafael Gómez-Bombarelli

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

Modelling the photocatalytic oxidation of methane and other air pollutants for applications in ventilation systems

Samuel D. Tomlinson, Aliki Marina Tsopelakou, Tzia Ming Onn et al. (+3 more)

Photocatalytic oxidation (PCO) is a promising strategy for indoor air purification and outdoor pollutant abatement, potentially offering treatment for climate- and health-relevant pollutants such as methane (CH$_4$), nitrogen oxides (NO$_\text{x}$) and volatile organic compounds (VOCs). In this work, we present experiments evaluating the PCO of CH$_4$ (2 to 10 ppm) under varying UV-C light intensities (4 to 59 W/m$^2$), using titanium dioxide (TiO$_2$) as the photocatalyst. At 2 ppm CH$_4$, TiO$_2$ achieves a maximum conversion efficiency of 24.4% and a maximum apparent quantum yield of $0.013$% over the tested UV-C light intensities, demonstrating activity at environmentally relevant concentrations. We develop a model to interpret the experimental results and assess the potential of PCO for ventilation applications. The model is validated against our CH$_4$ data and literature results for formaldehyde (HCHO) and NO$_\text{x}$. While laboratory-scale configurations achieve high conversions (e.g., 24.4% for CH$_4$), ventilation-scale performance is predicted to be limited by thin concentration boundary layers and short residence times, with conversion efficiencies dropping to around $0.017$%. Finally, we estimate the climate impact of CH$_4$ removal in terms of CO$_2$e emission rates, demonstrating that TiO$_2$-based PCO in ventilation applications can yield a net climate benefit (i.e., a net-negative CO$_2$e emissions rate) when the modelled CO$_2$e removal rate exceeds the emissions from catalyst material production and UV operation, particularly when pre-existing UV-C irradiation is leveraged.
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All authors Samuel D. Tomlinson, Aliki Marina Tsopelakou, Tzia Ming Onn, Steven R. H. Barrett, Adam M. Boies, Shaun Fitzgerald

Materials Science

Dominant vibronic relaxation channels in a europium-based molecular qubit

Neil Iyer

Molecular spin qubits offer a versatile platform for quantum information processing due to their synthetic tunability and well-defined electronic structure. Here, a fitted-parameter-free computational framework combining density functional theory (DFT), time-dependent DFT (TD-DFT), and Redfield theory is applied to investigate the longitudinal spin-lattice relaxation time $T_1$ of the Eu nuclear spin qubit Eu(dpphen)(NO3)3. Using a single-molecule gas-phase model, the experimental long relaxation component $T_{1,\mathrm{long}} = 41.39$ s is reproduced within a factor of 1.4 (calculated: 55.88 s at 4.2 K), indicating that the slow relaxation channel is governed by intramolecular vibronic coupling. In contrast, the calculated $T_{1,\mathrm{short}}$ deviates by a factor of 66, highlighting the importance of crystal lattice and intermolecular effects absent from the model. The experimental $^5D_0 \rightarrow {}^7F_0$ optical transition is reproduced to within 1.1%, supporting the accuracy of the electronic structure description. Vibrational analysis identifies a large-amplitude dpphen rocking mode at a frequency of $332.02~\mathrm{cm}^{-1}$ as the dominant vibronic coupling channel, while electric field gradient (EFG) derivative analysis independently identifies another nitrate-rocking mode at $180.57~\mathrm{cm}^{-1}$ as the primary modulator of the nuclear spin environment via nitrate motion. These results are consistent with a near-maximal quadrupole asymmetry parameter $\eta = 0.941$, which creates state mixing through off-diagonal quadrupolar terms. Overall, the results establish a single-molecule relaxation baseline and suggest targeted ligand rigidification and substitution strategies to suppress decoherence.
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Materials Science · Cross-listed from cs.LG

LEAP: A closed-loop framework for perovskite precursor additive discovery

Xin-De Wang, Zhi-Rui Chen, Ze-Feng Gao et al. (+3 more)

Efficient discovery of precursor additives is essential for improving the performance of perovskite solar cells, yet the large chemical space makes conventional trial-and-error screening inefficient. We develop LEAP(LLM-driven Exploration via Active Learning for Perovskites), an expert-in-the-loop closed framework that couples a domain-specialized large language model(LLM) with active learning for iterative additive prioritization. The LLM is trained to extract mechanism-relevant knowledge from the perovskite additive literature and to represent candidate molecules through interpretable descriptors, which are further integrated into a Bayesian optimization workflow for uncertainty-aware prioritization under low-data conditions. Benchmark results on unseen literature show that the domain-specialized model outperforms general-purpose models in mechanism-consistent reasoning. Experimental validation in an expert-in-the-loop proof-of-concept study suggests improved additive prioritization across three screening rounds, leading to average device PCEs of 20.13% and 20.87% for the later-round 6-CDQ- and 2-CNA-treated devices, respectively, compared with 19.25% for the control, with a champion PCE of 21.32%. These results provide preliminary evidence that literature-grounded mechanistic descriptors, when coupled with Bayesian optimization and expert feasibility review, can support mechanism-aware additive prioritization in perovskite photovoltaics.
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All authors Xin-De Wang, Zhi-Rui Chen, Ze-Feng Gao, Peng-Jie Guo, Cheng Mu, Zhong-Yi Lu

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

Floquet-Engineered Odd-Parity Altermagnetic Higher-Order Topology in a Two-Dimensional Antiferromagnet Cr$_2$CH$_2$

Xiaorong Zou, Hyeon Suk Shin, Baibiao Huang et al. (+5 more)

Periodic driving provides a platform to dynamically tailor quantum states of matter, yet its impact on symmetry-protected topological phases remains incompletely understood. Here, we demonstrate that periodic driving enables the realization of an odd-parity altermagnetic (AM) higher-order topological insulator (HOTI) phase in the Cr$_2$CH$_2$ monolayer. In equilibrium, Cr$_2$CH$_2$ is a 2D antiferromagnetic (AFM) HOTI protected by $\mathcal C_3$ rotational symmetry, characterized by a symmetry indicator $\chi^{(3)}$ = $\{-2,1\}$ and robust corner states. Under circularly polarized light (CPL), the system develops a f-wave altermagnetic state governed by the symmetry $[C_{2}||\overline{3}_{001}]$ with odd-parity spin splitting. Despite substantial Floquet-induced band renormalization, the $\mathcal C_3$-protected corner states remain intact over a broad range of driving strengths, highlighting the altermagnetic higher-order topology under Floquet driving. As the light intensity increases, the system gradually evolves into an altermagnetic semimetallic state. These results establish a direct connection between magnetism and topology in a periodically driven AFM system, offering a route toward the control of coupled spin and topological transport.
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All authors Xiaorong Zou, Hyeon Suk Shin, Baibiao Huang, Yanmei Zang, Ying Dai, Chengwang Niu, Chang-Jong Kang, Chang Woo Myung

Materials Science · Cross-listed from cond-mat.str-el

Electronic and Magnonic Properties of $g$-Wave Altermagnetism in Intercalated Transition Metal Dichalcogenides

Shuyi Li, Adrian Bahri and Chunjing Jia

Altermagnetism is a recently identified class of magnetic order characterized by unconventional momentum-dependent spin splitting in the absence of net magnetization, and understanding its electronic and magnetic properties is essential for revealing its fundamental physics and potential applications. In this work we investigate two intercalated transition-metal dichalcogenides, Fe$_{1/4}$NbS$_2$ and V$_{1/3}$NbS$_2$, as candidate altermagnetic materials by using effective tight-binding and spin models complemented by first-principles calculations. We show that the $g$-wave electronic spin splitting originates from bond-dependent hopping anisotropy, leading to material-dependent nodal structures. For the magnetic excitations, the emergence of chiral splitting in the magnon dispersion is controlled by single-ion anisotropy, which manifests as altermagnetic-like nodal structures when spins are oriented along an easy-axis. Conversely, this altermagnetic signature disappears when the spins are aligned in an easy-plane. Beyond linear spin-wave theory, we find that $1/S$ corrections from magnon–magnon interactions preserve the symmetry and nodal structure of the band splitting while generally reducing its magnitude, with strong antiferromagnetic exchange leading to a non-negligible renormalization of the chiral splitting. Our findings establish intercalated transition-metal dichalcogenides as promising platforms for understanding the interplay between crystal symmetry, non-relativistic spin splitting, and magnetic properties in altermagnets.
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Materials Science · Cross-listed from math-ph

On the single field formulation in magnetostatics

Stefan Krömer and Giuseppe Tomassetti

We systematically discuss the equivalence of two variational formulations of magnetostatics, in terms of magnetization and magnetic field on the one hand and the single field formulation using only magnetic induction. To demonstrate that this link is stable also when the magnetic laws are coupled with other variational static models, elasticity is included in the models as well. Interestingly, despite the fact that the corresponding magnetoelastic energy densities in the material can be computed via Legendre-Fenchel transform in the magnetic state variables, the two formulations are not linked by standard convex duality on the level of the functionals. In addition, convexity and coercivity of the given functional are neither required for the transformation nor always preserved by it.
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Materials Science

Atomistic Modeling of Chemical Disorder in Materials: Bridging Conventional Methods and AI-Assisted Approaches

Jiayu Peng and Peichen Zhong

Chemical disorder, originating from the mixed occupation of crystallographic sites by multiple elements, is widespread in alloys, ceramics, and compositionally complex materials, where short- and long-range orderings strongly influence properties. A central obstacle is the representation gap between experiments and simulations: experiments often report disorder as partial occupancies and ensemble-averaged behaviors, whereas atomistic simulations and AI workflows usually require fully specified configurations. Tackling this gap requires computational methods that convert averaged disorder descriptions into representative configurational ensembles while balancing cost, bias, and fidelity. This challenge has become more urgent in AI-driven computational discovery, where ignoring disorder may cause AI workflows to misrank stability, misjudge novelty, and misdirect experiments with too-idealized representations. This Review highlights how conventional and AI-driven methods can bridge this representation gap. We assess the strengths and limitations of approaches spanning mean-field theories, cluster expansion, quasi-random approximations, Monte Carlo, and emerging schemes powered by universal interatomic potentials and generative models. We further highlight how AI can accelerate various computational schemes by lowering the cost of microstate evaluation, configurational exploration, and atomistic-to-thermodynamic closure. We also emphasize how AI can enable disorder-native capabilities, including workflow triage, ordering-sensitive and alchemical representations, generative models of disordered structures and distributions, and kinetics-aware disorder prediction. Together, this framework outlines a practical roadmap toward disorder-native AI, which can transform chemical disorder from a representational obstacle into a controllable variable for realistic AI-accelerated materials discovery.
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Materials Science · Cross-listed from cond-mat.str-el

The analysis of heat capacity of MnGe metallic helimagnet

M.A. Anisimov, A.V. Bokov, A.V. Semeno et al. (+2 more)

Zero-field heat capacity of metallic helimagnet MnGe was analyzed based on the results of resistivity decomposition published previously by our group for the same crystal. Current procedure allowed identifying along with ($i$) electronic ($\tilde{\gamma}$ $\approx$ 7 mJ/mol$\cdot$K$^2$) and ($ii$) phononic ($\Theta_D$ $\approx$ 350 K) components ($iii$) the additional term, caused by the presence of spin fluctuations (SFs). The last contribution was found to exist in a wide range of temperatures in both paramagnetic (PM) and magnetically ordered states. However, its amplitude appears to be significantly lower in comparison with phononic component. The obtained value of spin fluctuation temperature $\theta_{sf}$(MnGe) $\approx$ 330 K correlates well with previous estimations, as well as with results of various experiments, which predict the existence of SFs in MnGe at least up to 250 $-$ 300 K.
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All authors M.A. Anisimov, A.V. Bokov, A.V. Semeno, V.A. Sidorov, A.V. Tsvyashchenko