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Physics Condensed Matter Materials Science

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Thursday 2 April

Materials Science

CARBON-2D Topological Descriptor (C2DTD): An Interpretable and Physics-Informed Representation for Two-Dimensional Carbon Networks

Felipe Hawthorne, Marcelo Lopes Pereira Junior, Fabiano Manoel de Andrade et al. (+2 more)

Two-dimensional (2D) carbon networks, from pristine graphene to defect-rich and amorphous monolayers, exhibit a complex structure-energy landscape governed not only by local bonding but also by medium-range order and network topology. Capturing these multi-scale effects in a compact, interpretable, and data-efficient manner remains a major challenge for machine learning (ML) in low-dimensional materials. In this work, we introduce the CARBON-2D Topological Descriptor (C2DTD), a physically informed structural representation specifically designed for 2D carbon systems. The descriptor integrates local geometric statistics, a compact radial structural signature, and explicit primitive ring topology into a fixed-length, invariant vector that is both computationally efficient and directly interpretable. Benchmarking on diverse datasets of 2D carbon allotropes and defect-engineered graphene sheets demonstrates that C2DTD achieves robust predictive performance in small-data regimes, outperforming generic high-dimensional featurization schemes while preserving physical transparency. Unsupervised manifold analysis reveals a smoother alignment between descriptor space and the DFT energy landscape, and feature-importance and ablation studies confirm that ring topology emerges as a dominant energetic driver, particularly under vacancy-induced reconstruction. Furthermore, controlled simulations with 5-15% random vacancies show that C2DTD naturally captures the progressive transition from hexagon-dominated graphene to topologically disordered networks, enabling both dataset-level and structure-specific interpretation. Owing to its compactness, interpretability, and strong physics-based inductive bias, C2DTD provides a fast and generalizable framework for data-driven modeling, defect analysis, and high-throughput screening of 2D carbon materials.
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All authors Felipe Hawthorne, Marcelo Lopes Pereira Junior, Fabiano Manoel de Andrade, Cristiano Francisco Woellner, Raphael Matozo Tromer

Materials Science

Loop-level surrogate modeling of dopant-distribution effects in Ba(Zr,Ti)O$_3$

Heiko Röthl, Elke Kraker, Julien Magnien et al. (+2 more)

Barium titanate-based perovskites are important candidates for lead-free dielectric and electromechanical technologies. In Zr-substituted BaTiO$_3$ (BZT), functional behavior is usually discussed in terms of the average Zr concentration, while the influence of dopant spatial distribution beyond average concentration is less understood and difficult to explore systematically. Here we present an accelerated materials-design workflow that links controlled dopant distributions to full field-driven response curves. We generate a broad set of Zr distributions spanning a continuum of nanoscale arrangements, with layers, rods, dots, and lamellae serving as representative end-member motifs, and encode each configuration using a compact, parametrized descriptor model. Effective-Hamiltonian molecular dynamics is used to compute polarization-electric-field and strain-field hysteresis loops, and we train a conditional autoencoder surrogate to predict complete loops directly from the distribution parameters. This surrogate enables rapid screening and dense, property-selective design maps at scales that are not feasible with direct simulations alone, and it supports targeted follow-up simulations in regions of interest. Using the predicted loop database, we screen the distribution space for multiple functional targets, including energy-storage performance, electromechanical response, and switching behavior, and identify the corresponding dopant distribution motif families. The resulting design maps show that dopant distribution is an independent tuning parameter that can strongly affect hysteresis behavior and loop-derived figures of merit: layer-like motifs, vertical lamellae, and nanoplate-like inclusions emerge in different performance regimes. More generally, predicting full response curves enables screening of other loop-derived targets and multi-objective design in substituted ferroelectrics.
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All authors Heiko Röthl, Elke Kraker, Julien Magnien, Manfred Mücke, Florian Mayer

Materials Science

AlloyVAE: A generative model for complex probabilistic field-to-field relationships in alloys

Ningyu Yan, Zhuocheng Xie, Kai Guo et al. (+3 more)

The inherent compositional heterogeneity of multi-principal element alloys (MPEAs) gives rise to complex, spatially varying mechanical fields that cannot be uniquely determined from coarse-grained composition descriptors. This non-uniqueness introduces intrinsically probabilistic structure-property relationships, posing a fundamental challenge to conventional deterministic modeling and machine learning approaches that collapse such mappings into average predictions. Here, we present AlloyVAE, a physics-informed generative framework that learns the full conditional distribution of mechanical fields from microstructural inputs. Built upon a conditional variational autoencoder architecture, the model incorporates learned smoothing operators to enhance functional regularity and a self-consistency mechanism to enforce physical plausibility. Trained on atomistic simulation data, AlloyVAE accurately predicts distributions of residual stress fields from composition and short-range order, and enables the generation of multiple physically consistent realizations under identical input conditions. Beyond forward prediction, the framework supports inverse design by optimizing composition fields to achieve targeted mechanical responses, and is extensible to coupled mappings involving eigenstrain. By capturing one-to-many structure-property relationships in heterogeneous materials, this work establishes a probabilistic paradigm for materials modeling and design, providing a scalable alternative to conventional simulations for navigating high-dimensional compositional spaces.
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All authors Ningyu Yan, Zhuocheng Xie, Kai Guo, Yejun Gu, Huajian Gao, Yang Xiang

Materials Science

Terahertz optical activity near crystal field transitions of Tm3+ ions in magnetoelectric alumoborates

A.M. Kuzmenko, V.Yu. Ivanov, S.V. Garnov et al. (+5 more)

Crystal field (CF) excitations in the ground multiplet $^3H_6$ of Tm$^{3+}$ ions were investigated using terahertz transmission spectra of magnetoelectric TmAl$_3$(BO$_3$)$_4$ and Tm$_{0.05}$Yb$_{0.1}$Y$_{0.85}$Al$_3$(BO$_3$)$_4$. These excitations were identified as mainly magnetic dipole transitions from the ground singlet A$_1$ to the next excited doublet E, split by the crystal field of the D$_3$ symmetry. The fine structure of the modes was resolved at low temperatures. It manifested differently in lightly doped and in pure Tm borates, consistent with different distortions of the local crystal field with the D$_3$ symmetry. Strong natural optical activity was observed near the CF transitions resulting in a polarization plane rotation up to 25 degrees. The optical activity is quantitatively described by contributions of magnetic and electric dipole transitions to dynamic magnetoelectric susceptibility and taking into account the classification of local distortions.
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All authors A.M. Kuzmenko, V.Yu. Ivanov, S.V. Garnov, A. Shuvaev, A. Pimenov, K.N. Boldyrev, I. A. Gudim, A.A. Mukhin

Materials Science

Altermagnetism and Room-Temperature Metal-to-Insulator Transition in CsCr$_2$S$_2$O

Yi Liu, Chen-Chao Xu, Jin-Ke Bao et al. (+14 more)

Metal-to-insulator transitions (MITs), particularly near room temperature, have been extensively studied in nonmagnetic and conventional ferromagnetic and antiferromagnetic systems, yet the co-emergence of MIT and altermagnetism (AM) remains unexplored. Here, a layered chromium-based compound CsCr$_2$S$_2$O that realizes this coexistence was synthesized. It crystalizes in CeCr$_2$Si$_2$C-type structure with Cr moments orders in a C-type antiferromagnetic configuration below $T_\mathrm{N}$ = 326 K, constituting a room-temperature d-wave altermagnet. In the altermagnetic state, a subsequent Verwey-type MIT appears at $T_\mathrm{MI}$ = 305 K, driven by a tetragonal-to-orthorhombic structural distortion and stripe charge ordering of Cr$^{+2}$/Cr$^{+3}$ ions, while maintaining its altermagnetic character. First-principles calculations show moment-dependent spin-split electronic structures with maximum splitting energies of ~0.6 eV and ~0.3 eV in the metallic and insulating states, respectively. Our work links the two prominent phenomena, MIT and AM, in a single material, establishing a new platform for potential spintronic applications.
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All authors Yi Liu, Chen-Chao Xu, Jin-Ke Bao, Bai-Jiang Lv, Hao Li, Jing Li, Yi-Qiang Lin, Hua-Xun Li, Yi-Ming Lu, Xin-Yu Zhao, Wu-Zhang Yang, Zhen-Yi Zhang, Xian-Yan Chen, Wen-he Jiao, Ji-Yong Liu, Bai-Ren Zhu, Guang-Han Cao

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

Moiré Mott correlated mosaics in twisted bilayer 1T-TaS$_2$

Ana Vera Montoto, Jose L. Lado and Adolfo O. Fumega

The tunability and twist engineering of van der Waals materials enable the emergence of electronic states not present in individual monolayers. Among them, monolayer 1T-TaS$_2$ is a well-known Mott insulating system, whose star-of-David charge density wave reconstruction realizes an emergent triangular lattice of local magnetic moments. Interestingly, in its bulk form, the insulating gap is not correlation-driven, but stems from interlayer coupling. Here, we exploit the stacking-dependent nature of the insulating gap to show that in twisted 1T-TaS$_2$ bilayers, the spatially dependent competition between many-body and single-particle gaps creates Mott-trivial mosaic superlattices, featuring regions with local magnetic moments and non-magnetic insulating regions. We further demonstrate the tunability of the mosaic correlated state with an interlayer bias, giving rise to controllable charge transfer and quenching of correlations. Our results establish twisted 1T-TaS$_2$ as a flexible platform to engineer mixed spatially modulated correlated insulating phases, arising from the moiré profile.
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Materials Science

Lead-free antiperovskite derivatives Ba$_3$MA$_3$ (M = P, As, Sb, Bi; A = Cl, Br, I): Next-gen materials for optoelectronics

Surajit Adhikari, Aftab Alam and Priya Johari

Antiperovskite derivatives have recently emerged as promising lead-free alternatives to halide perovskites for optoelectronic applications. Here, using a comprehensive first-principles calculations including density functional perturbation theory and many-body perturbation theory (involving GW and Bethe-Salpeter equation (BSE)), we investigate the stability, excitonic, polaronic, and optoelectronic properties of cubic Ba$_3$MA$_3$ (M = P, As, Sb, Bi; A = Cl, Br, I). These compounds are found to be dynamically and thermodynamically stable direct-gap semiconductors with G$_0$W$_0$@PBE+SOC band gaps spanning 1.23-2.17 eV. BSE calculations reveal moderate exciton binding energies (0.254-0.352 eV) and intermediate-radius excitons, while Fröhlich polaron analysis indicates intermediate carrier-phonon coupling and mobilities up to $\sim$ 75 cm$^{2}$V$^{-1}$s$^{-1}$. The resulting spectroscopic limited maximum efficiencies reach $\sim$ 19-32%, surpassing several lead-based perovskites. Our results establish Ba-based antiperovskite derivatives as a robust, eco-friendly platform for next-generation optoelectronic devices.
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Materials Science

Phonon Thermal Hall Effect in quartz and its absence in silica

Yu Ling, Benoît Fauqué and Kamran Behnia

The observation of a misalignment between the applied heat flux and the measured temperature gradient in insulating solids induced by magnetic field has become a subject of experimental investigation, theoretical speculation, and unsettled controversy. To identify the origin of this phonon thermal Hall effect, we performed a comparative study of longitudinal and transverse heat transport in crystalline (quartz) and vitreous (silica) SiO$_2$ using identical experimental set-ups and thermometers. A finite signal was detected in the crystalline samples and none in the amorphous sample, within our resolution. The cleaner crystal exhibited a larger thermal Hall conductivity than the dirtier one, ruling out disorder as the driver of the effect. On the other hand, the amplitude of the transverse thermal resistivity is almost identical in the two crystalline samples (W$_{\perp}$/B$\approx 10^{-6}$ m.K.W$^{-1}$.T$^{-1}$). We show that in a phonon gas, as in a molecular gas displaying the Senftleben-Beenakker effect, heat is conducted through two channels, and argue that a thermal Hall response is unavoidable whenever these channels differ both in entropy production and in their coupling to the magnetic field. Under such conditions, the conserved energy current and the non-conserved entropy current cease to be parallel. Finally, the magnitude of the transverse thermal resistivity can be accounted for by a surprisingly simple picture. The heat flux induces a tiny drift velocity of the lattice nuclei, the magnetic field exerts a transverse Berry force on this drift, and this force is balanced by an entropic restoring force.
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Materials Science

Atomistic theory of the phonon angular momentum Hall effect

Daniel A. Bustamante Lopez, Verena Brehm and Dominik M. Juraschek

The spin and orbital Hall effects convert longitudinal charge currents into transverse flows of electronic angular momentum. Here we develop an atomistic theory of the recently proposed lattice-vibrational analogue, in which a longitudinal heat current driven by a thermal gradient is converted into a transverse current of phonon angular momentum. We derive a microscopic real-space expression for this current and show that it originates from thermally induced mixing of polarized vibrational motion, leading to a characteristic edge accumulation of phonon angular momentum. We demonstrate the effect in minimal square- and honeycomb-lattice models and compute the resulting phonon angular momentum accumulations for a range of example materials using input from first-principles calculations. Our results confirm that the phonon angular momentum Hall effect is a universal response of crystalline solids and our framework is generically applicable to all materials.
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Materials Science

Switching between Antiferromagnetic and Ferromagnetic Skyrmions in Two-Dimensional Magnets

Xinyang Jiang, Jian Wu and Weiyi Pan

Antiferromagnetic (AFM) and ferromagnetic (FM) skyrmions possess unique advantages for spintronic applications. AFM skyrmions eliminate the skyrmion Hall effect and exhibit fast dynamics, whereas FM skyrmions are easier to nucleate and manipulate. However, realizing a transition between AFM and FM skyrmions within the same two-dimensional (2D) material has remained elusive. Here, using first-principles calculations and atomistic spin simulations on the Janus monolayer Cr2Ge2Te3S3, we demonstrate that strain-driven modulation of magnetic interactions enables switching between AFM and FM skyrmion phases. A compressive strain of $-3\%$ induces an AFM ground state hosting AFM skyrmions, while a tensile strain of $+2\%$ drives the system into a FM skyrmion phase. Moreover, under an out-of-plane magnetic field, FM skyrmions are rapidly transformed into a uniform FM phase, while AFM skyrmions transform into AFM bimerons under stronger fields. These findings establish a framework for controllable transitions between topological magnetic states in a single 2D material.
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Materials Science

Elastic softening and fracture in randomly perforated solids

Tero Mäkinen, Alessandro Taloni, Giulio Costantini et al. (+3 more)

We study the mechanical response of quasi-brittle polymethyl methacrylate (PMMA) specimens containing controlled random distributions of laser-cut holes. Tensile tests combined with digital image correlation reveal a nearly linear decrease of the Young's modulus with porosity, but with a softening rate far exceeding classical effective medium theory and the Hashin-Shtrikman bound. The extrapolated critical porosity at which the modulus vanishes is well below the 2D percolation threshold, indicating that ideal cylindrical void models fail to capture the observed behavior. Microscopy shows irregular pore geometries and frequent coalescence, which effectively act as crack-like defects and strongly enhance compliance. The rupture stress distributions are well described by a Weibull model accounting for both load-bearing area reduction and stress concentration at hole edges. Digital image correlation reveals heterogeneous but non-localized deformation, with strain increasingly correlated with the hole pattern, indicating a growing influence of defect-induced stress concentrations. These results highlight the dominant role of defect morphology in governing stiffness degradation and fracture statistics in porous quasi-brittle materials.
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All authors Tero Mäkinen, Alessandro Taloni, Giulio Costantini, Davide Della Torre, Riccardo Donnini, Stefano Zapperi

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

Bond-Length-Driven Magnetic Transition in Quasi-One-Dimensional CrSb$X_3$ ($X$=S, Se)

Kang Lee, Hong-Suk Choi and K.-W. Lee

Using ab initio calculations, we investigate the magnetic ground states of quasi-one-dimensional insulating CrSb$X_3$ ($X$ = S, Se) with infinite double-rutile chains. Within conventional band theory, without explicit Coulomb correlations ($U$), we obtain band gaps in close agreement with experiment. Remarkably, we find that the magnetic order is highly sensitive to the Cr-Cr bond length $d_{\rm Cr-Cr}$: increasing the bond length induces a transition from antiferromagnetic to ferromagnetic order at a critical distance $d^c_{\rm Cr-Cr} \approx 3.53 (\pm 0.05)$ Å. Accordingly, CrSbS$_3$ lies near the transition boundary, whereas CrSbSe$_3$ is robustly ferromagnetic, in good agreement with experiment. Analysis of the exchange interactions reveals that the first-order phase transition is dominated by a sign reversal of the intrachain nearest-neighbor superexchange $J_1$ mediated by chalcogen ions, while the intrachain direct exchange $J_2$ remains ferromagnetic and changes only gradually. This behavior reflects an emergent Bethe-Slater-like behavior driven by competing exchange pathways in a quasi-1D transition-metal system, where the competition between $J_1$ and $J_2$ dictates the magnetic ground state. Besides, the electronic structures of the ground states of each compound are investigated.
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Materials Science

Understanding ultrafast x-ray 'echoes' diffracted from single crystals

Angel Rodriguez-Fernandez, Dmitry Karpov, Steven Leake et al. (+2 more)

Multiple x-ray beams generated by interference processes in perfect crystals were imaged with a resolution of about 100nm using tele-ptychography in the diffraction direction. These multiple wave-fields, also known as x-ray diffraction echoes, are related to the process known as the Pendelloesung effect and are described by dynamical diffraction theory. The echoes are produced by the constructive interference of diffracted x-rays at the exit surface of the crystal sample. In the imaged diffraction peak, we observed 10 echoes maxima with a total signal length of 78 um. Which translates into a total temporal delay in the signal of less than 108 fs.This makes the echoes of high importance for x-ray optics at x-ray Free Electron Laser sources, as the effect could be used for future ultrafast x-ray beam splitters. In addition to this application, echoes can be exploited to follow ultrafast processes in single crystal micro-structures such as melting or strain propagation.
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All authors Angel Rodriguez-Fernandez, Dmitry Karpov, Steven Leake, Dina Carbone, Ana Diaz

Materials Science

Electrochemical doping in H-terminated diamond films: Impact of O-functionalization and insights from in-situ Raman spectro electrochemistry

N. Mohasin Sulthana, P.K. Ajikumar and K. Ganesan

The p-type surface conductivity of H-terminated diamond (HD, H-diamond) has created new path ways for developing diamond based electronic devices as well as chemical and bio-sensors. However, the hydrophobic nature of the HD surface can negatively impact device performance due to its low wettability. Herein, we report the study on polymer electrolyte-gated field effect transistors (EGFETs) fabricated using pristine and partially O-terminated HD films. The HD surface is transformed from hydrophobic to moderate hydrophilic by partial O-termination. Also, the sheet resistance of the HD surface increases from 7.6 to 18.7 k-Ohms per sq. while the sheet hole density decreases from 10.5 to 4.8 x 10^12 cm^-2 upon partial O-termination. Consequently, the ON - OFF ratio of the EGFET devices decreases from ~ 40 to 14 and the maximum transconductance declines from of -150 to -7.9 micro-seimens per V, but the areal capacitance increases from ~ 7.8 to 27.1 microFarad per cm^2 with partial ozonation on HD surface. In addition the in situ Raman measurements in HD EGFET provide direct experimental evidence of a gating-induced blue shift and linewidth broadening of the diamond Raman band which are associated with strong electron phonon coupling. This work highlights the significant impact of the partial O-termination on the performance of the HD EGFET devices and effect of electrochemical gating on the phonon behaviour of the H-diamond.
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Materials Science

Quantum-Information Measure of Electron Localization

Stefano Pittalis, Filippo Troiani, Celestino Angeli et al. (+2 more)

Understanding electron localization in molecules and materials plays a central role in electronic structure theory, and will increase in importance with the rise of data-driven approaches. The electron localization function (ELF) is widely used to visualize electron organization in molecules and materials, and it remains a central ingredient in modern density-functional approximations. Yet its formulation retains highly empirical elements. Here we introduce a quantum-information measure of electron localization derived from the concurrence of a correlated two-spin mixed state. This construction yields a genuine two-point localization indicator grounded in quantum-information theory, avoiding the heuristic normalization and chosen nonlinear remapping of the ELF. We show that atomic shells, covalent and ionic bonds, lone pairs, molecular dissociation, and charge-transfer processes are captured. The method is straightforward to evaluate numerically.
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All authors Stefano Pittalis, Filippo Troiani, Celestino Angeli, Irene D'Amico, Tim Gould

Materials Science

Benchmarking Chemically Scalable Machine-Learning Interatomic Potentials for Large-Scale Simulations of Multicomponent Alloys

Fei Shuang, Penghua Ying, Kai Liu et al. (+5 more)

Machine learning interatomic potentials (MLIPs) with broad chemical flexibility are essential for atomistic simulations of compositionally complex alloys, but their deployment in large-scale molecular dynamics requires a balance among accuracy, efficiency, stability, transferability, and uncertainty quantification. Here, we benchmark two chemically scalable MLIP frameworks, neuroevolution potential (NEP) and graph atomic cluster expansion (GRACE), for 16 elemental metals and their multicomponent alloys. GRACE-FS shows higher training efficiency and generally better average accuracy, chemical transferability, and finite-temperature robustness, whereas UNEP-v1 provides substantially higher inference speed and remains competitive in selected stress and large-error metrics. We further show that chemical transferability is closely linked to high-temperature MD stability in highly multicomponent environments and that ensemble-based uncertainty provides a more reliable error indicator than D-optimality for the heterogeneous systems considered here. Finally, three-million-atom shock simulations demonstrate that UNEP-v1, combined with ensemble uncertainty, enables uncertainty-aware simulations under extreme dynamic conditions, yielding robust global spall-strength predictions while revealing model sensitivity in local damage pathways. These results provide practical guidelines for selecting and deploying MLIPs in large-scale simulations of multicomponent alloys.
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All authors Fei Shuang, Penghua Ying, Kai Liu, Zixiong Wei, Fengxian Liu, Zheyong Fan, Minqiang Jiang, Poulumi Dey

Materials Science

Abrupt crystallization from shock-compressed CaSiO3 glass

A. Amouretti, K. Nonaka, X. Liu et al. (+13 more)

We have performed in situ time-resolved X-ray diffraction at ~100 GPa on laser-shocked CaSiO3 glass to investigate the glass-to-crystal transition. At this extreme pressure, we observe the ultrafast crystallization of the CaSiO3 perovskite structure from the compressed amorphous phase, with a typical nucleation time of 1.69 +/- 0.10 ns and a final grainsize of ~20 nm. The grain size temporal evolution suggest a diffusion controlled transformation. Moreover, the observed concomitant explosive grain growth together with the release wave arrival into shocked CaSiO3 also suggests a role of the release in the nucleation process.
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All authors A. Amouretti, K. Nonaka, X. Liu, Y. Hironaka, H. Huang, R. Kodama, K. Lawler, K. Miyanishi, H. Nakamura, C. Schwartz, Y. Seto, K. Sueda, Y. Wu, M. Yabashi, T. Yabuuchi, N. Ozaki

Materials Science

Magnetoelectric Coupling in Nickel-Cobalt Ferrite and Lanthanum Ferrite Heterostructure Composites: Experimental Evidence and Simulation-Driven Insights

Manjeet Seth

A material that reveals two or more ferroelectric properties at the same time is called multiferroic materials. The most commonly multiferroic materials shows ferroelectricity and ferromagnetism property within a single phase. Accordingly such materials can possess both spontaneous magnetization and electric polarization and which can be individually controlled through external electric or magnetic fields. The unique coexistence of ferroelectric properties opens up possibilities for innovative applications, including memory devices, sensors, and actuators that are responsive to both electrical and magneticstimuli. Multiferroics gives a valuable foundation for generating cutting edge multifunctional devices, exhibiting their versatility across broad area technological fields. Applications include sensors, transducers, spintronics, terahertz emitters, miniature antennas, energy harvesting, multiple state memory storage, electric field controlled ferromagnetic resonance devices, and nanoscale electronics. Researchers are continually work to discovering new materials exploring the fundamental mechanisms involved, and optimizing their performance for various application. Multiferroic materials has a promising area for innovation and exploration the field of advance technologies this type of materials contributing not only to device development but also enhancing the understanding of the interactions between ferroelectric and magnetic orders. Additionally, magnetoelectric composites is a type of multifunctional material showing strong coupling between magnetic and electric properties for further technological applications. Magnetoelectric (ME) composites are synthesis by combining separate magnetic and electric materials to produce unique functionalities through their interactions. This coupling enables the control of magnetic properties by an electric field and vice versa.
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Materials Science

Precipitate-Induced Dynamic Strain Aging and Its Effect on the Strain Rate Sensitivity of Precipitation Hardened Aluminum Alloys

Sahar Choukir and Derek Warner

We examine precipitate-induced dynamic strain aging in precipitation-hardened Al-Cu alloys by combining atomistic simulations, kinetic Monte Carlo, and analytical rate theory. Atomistic simulations were used to characterize (1) the energetics of nearest neighbour Cu<->Al exchanges at dislocation - precipitate junctions and (2) the subsequent change in obstacle strength. For robustness, the simulations were performed with two distinct interatomic potentials. The resulting catalog of local Cu-Al exchange events was used as input for a kinetic Monte Carlo model of the time-dependent evolution of obstacle strength during dislocation pinning at the precipitate. The predicted strengthening kinetics were then embedded in an analytical dynamic strain aging model to predict the strain-rate sensitivity parameter. On the whole, the modeling predicts a low strain-rate sensitivity across a broad range of intermediate quasi-static strain rates, consistent with experimental observations for precipitate-strengthened alloys. The results therefore identify a mechanistic origin of the low strain-rate sensitivity in precipitation hardened aluminum alloys, emerging directly from the kinetics of dislocation-precipitate interactions when nearest neighbour Cu<->Al exchanges are considered.
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Materials Science

Insulator-to-Metal Transitions Driven by Quantized Formal Polarization Mismatch

Hongsheng Pang and Lixin He

We propose a mechanism for insulator-to-metal (IM) transitions driven by the mismatch of quantized formal polarization (QFP), a symmetry-protected bulk invariant. For a material with a low-symmetry insulating phase and a high-symmetry phase that allow distinct QFPs, any continuous path connecting them while preserving the symmetry of the low-symmetry phase must inevitably pass through an IM transition. The reason is that QFP remains invariant along any gapped symmetry-preserving evolution, whereas the high-symmetry phase requires a different QFP, which can only be accommodated by gap closing. First-principles calculations on two representative systems, two-dimensional InPS$_3$ and three-dimensional CdBiO$_3$, confirm this mechanism. Our results establish QFP mismatch as a general symmetry constraint on phase evolution and reveal a new route to symmetry-driven IM transitions in high-symmetry materials.
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Materials Science · Cross-listed from physics.ins-det

Electrostatic transfer of sub-micron magnetic particles onto cantilevers using a focused ion beam system

Peter Sun, George R. Du Laney, Tim M. Fuchs et al. (+3 more)

In this paper, we present a focused-ion-beam-assisted method for preparing magnet tips for magnetic resonance force microscopy measurements. The method electrostatically transfers prefabricated magnetic nanoparticles to microcantilevers, achieving precise control over the magnet overhang past the cantilever leading edge while minimizing the fabrication damage to the leading edge of the tip magnet. We demonstrate successful fabrication of magnets ranging in size from 460 nm to 2.8 um. These magnets were affixed to two types of cantilevers: silicon cantilevers with a spring constant of 800 uN/m, and single-crystal silicon cantilevers with a spring constant of 30 uN/m. We show that the electrostatic transfer method enables a wide variety of tip shapes, sizes, and materials that were previously not possible with conventional fabrication methods. The transfer procedure allows us to prefabricate the desired particle geometry with minimal ion-beam damage, as confirmed by Monte Carlo simulations. We show that the technique is versatile and can be used to fabricate custom-tipped cantilevers for a broader range of scanning probe techniques.
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All authors Peter Sun, George R. Du Laney, Tim M. Fuchs, Tjerk H. Oosterkamp, Malcolm G. Thomas, John A. Marohn

Wednesday 1 April

Materials Science · Cross-listed from cs.AI

From Data to Theory: Autonomous Large Language Model Agents for Materials Science

Samuel Onimpa Alfred and Veera Sundararaghavan

We present an autonomous large language model (LLM) agent for end-to-end, data-driven materials theory development. The model can choose an equation form, generate and run its own code, and test how well the theory matches the data without human intervention. The framework combines step-by-step reasoning with expert-supplied tools, allowing the agent to adjust its approach as needed while keeping a clear record of its decisions. For well-established materials relationships such as the Hall-Petch equation and Paris law, the agent correctly identifies the governing equation and makes reliable predictions on new datasets. For more specialized relationships, such as Kuhn's equation for the HOMO-LUMO gap of conjugated molecules as a function of length, performance depends more strongly on the underlying model, with GPT-5 showing better recovery of the correct equation. Beyond known theories, the agent can also suggest new predictive relationships, illustrated here by a strain-dependent law for changes in the HOMO-LUMO gap. At the same time, the results show that careful validation remains essential, because the agent can still return incorrect, incomplete, or inconsistent equations even when the numerical fit appears strong. Overall, these results highlight both the promise and the current limitations of autonomous LLM agents for AI-assisted scientific modeling and discovery.
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Materials Science · Cross-listed from cond-mat.supr-con

Electronic-Structure Correlations Governing Superconductivity in Nb-Based High-Entropy Alloys

Md Sabbir Hossen Bijoy, Vladislav Korostelev, Deva Prasaad Neelakandan et al. (+10 more)

Superconducting high-entropy alloys have recently emerged as a new platform for exploring superconductivity in highly disordered metallic systems and may offer advantages for applications requiring mechanical robustness and tolerance to extreme environments. Yet the mechanisms that govern their superconductivity, particularly the roles of lattice distortion and complex local order, both inherent to high-entropy alloys, remain unclear. The conventional valence-electron-concentration rule fails to reliably predict superconducting behavior, motivating a correlation analysis that links performance to electronic structure and lattice disorder. Here, we study a systematic series of niobium-based body-centered-cubic high-entropy alloys, from binary to quinary compositions, designed to investigate the electronic and structural effects and identify the dominant factors controlling superconductivity. Our experimental results reveal that the superconducting critical properties evolve non-monotonically with alloy complexity. Interestingly, alloys with greater lattice distortion can still achieve higher critical temperature and upper critical field. These observations are corroborated by first-principles and Eliashberg analyses, which identify the position of the niobium d-band relative to the Fermi level as the primary driver of electron-phonon coupling, critical temperature, and upper critical field, with lattice distortion serving as a secondary modifier that generally weakens coupling. We consolidate these findings into a detailed correlation map linking superconducting properties to electronic-structure fingerprints and vibrational signatures, establishing a mechanism-informed design strategy for superconducting high-entropy alloys with enhanced critical temperature and field.
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All authors Md Sabbir Hossen Bijoy, Vladislav Korostelev, Deva Prasaad Neelakandan, Harshil Goyal, Steven E. Porterfield, Youming Xu, Shuchen Li, Xi Chen, Mark Adams, Barton C. Prorok, Konstantin Klyukin, Chanho Lee, Fariborz Kargar

Materials Science

Revealing Strain and Disorder in Transition-Metal Dichalcogenides Using Hyperspectral Photoluminescence Imaging

Adam Alfrey, Cole Tait, Takashi Taniguchi et al. (+2 more)

Hyperspectral photoluminescence (HSPL) imaging provides spatially resolved spectral information for monolayer transition-metal dichalcogenides (TMDs), enabling the detection of subtle variations in excitonic features that are not accessible with conventional optical or photoluminescence intensity imaging. We employ HSPL to map the microscopic spatial distribution of strain and disorder in hBN-encapsulated MoSe$_2$ and WSe$_2$ samples. Quantitative extraction of exciton, trion, and biexciton energies and linewidths reveals strain gradients and localized deformations, such as wrinkles and ripples. The technique allows for characterization of regions with uniform optical properties and identification of areas affected by micro-scale disorder, which may be missed by optical microscopy. Measurements on samples with different device architectures and fabrication processes demonstrate the general utility of hyperspectral PL imaging for assessing spatial heterogeneity and optoelectronic quality in two-dimensional materials.
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All authors Adam Alfrey, Cole Tait, Takashi Taniguchi, Kenji Watanabe, Steven T. Cundiff

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

A New Paradigm for Computational Chemistry

Raphael T. Husistein and Markus Reiher

Computational chemistry has become an indispensable tool for generating data and insights, pervading all branches of experimental chemistry. Its most central concept is the potential energy hypersurface, key to all chemistry and materials science, as it assigns an energy to a molecular structure, the necessary ingredient for reaction mechanism elucidation and reaction rate calculation. Density functional theory (DFT) has been the most important method in practice for obtaining such energies, which is mirrored in the use of high-performance computing hardware. In the last two decades, a new class of surrogate potential energy functions has been evolving with remarkable properties: quantum accuracy combined with force-field speed. Until very recently, their application was hampered by the fact that they needed to be trained on truly large system-specific data sets, generated before a computational chemistry study could be started (in sharp contrast to DFT, which, as a first-principles method, works out of the box, but at a far higher price of computational cost). Very recently, this roadblock has been overcome by so-called foundation machine learning interatomic potentials, which are poised to completely change the way we do computational chemistry, likely prompting us to abandon DFT as the prime method of choice for this purpose in less than a decade.
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Materials Science

Enantiopurity-Controlled Magnetism in a Two-Dimensional Organic-Inorganic Material

P. Garrett Hegel, Oscar Gonzalez, Mingrui Li et al. (+6 more)

Extended solids that combine unpaired electron spin and structural chirality can host unconventional magnetic behaviors with potential for electronic technologies. A versatile strategy for creating chiral solids is incorporation of chiral organic molecules into inorganic crystals. However, such hybrid organic-inorganic materials have so far been examined through the lens of absolute chirality, leaving enantiomeric excess (ee) underexplored as a tuning parameter. Here, we report two-dimensional (2D) intercalation compounds with controllable ee produced by cation exchange of MnPS$_3$ with chiral organic molecules. We show that these materials' magnetism is determined by intercalant ee rather than absolute chirality. Moreover, low-ee materials display thermally activated dynamic magnetism absent from enantiopure analogs. These ee-dependent magnetic behaviors are explained by local ordering of Mn vacancies, directed by correlated vacancy-intercalant electrostatics and confined molecular packing. Together, these results demonstrate a distinctive tuning strategy for molecule-material hybrids and establish design principles for 2D chiral and magnetically dynamic materials.
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All authors P. Garrett Hegel, Oscar Gonzalez, Mingrui Li, Shannon S. Fender, Harishankar Jayakumar, Archana Raja, Ariana Ray, Isaac M. Craig, D. Kwabena Bediako

Materials Science · Cross-listed from cs.LG

Bridging the Simulation-to-Experiment Gap with Generative Models using Adversarial Distribution Alignment

Kai Nelson, Tobias Kreiman, Sergey Levine et al. (+1 more)

A fundamental challenge in science and engineering is the simulation-to-experiment gap. While we often possess prior knowledge of physical laws, these physical laws can be too difficult to solve exactly for complex systems. Such systems are commonly modeled using simulators, which impose computational approximations. Meanwhile, experimental measurements more faithfully represent the real world, but experimental data typically consists of observations that only partially reflect the system's full underlying state. We propose a data-driven distribution alignment framework that bridges this simulation-to-experiment gap by pre-training a generative model on fully observed (but imperfect) simulation data, then aligning it with partial (but real) observations of experimental data. While our method is domain-agnostic, we ground our approach in the physical sciences by introducing Adversarial Distribution Alignment (ADA). This method aligns a generative model of atomic positions – initially trained on a simulated Boltzmann distribution – with the distribution of experimental observations. We prove that our method recovers the target observable distribution, even with multiple, potentially correlated observables. We also empirically validate our framework on synthetic, molecular, and experimental protein data, demonstrating that it can align generative models with diverse observables. Our code is available at https://kaityrusnelson.com/ada/.
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All authors Kai Nelson, Tobias Kreiman, Sergey Levine, Aditi S. Krishnapriyan

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

A multiphysics model for triboelectric nanogenerator design with explicit surface roughness representation

MD Tanzib Ehsan Sanglap, Jack Perris, Rudra Mukherjee et al. (+5 more)

The design of triboelectric nanogenerators (TENGs) for efficient energy harvesting requires predictive models that capture the interplay between surface roughness, real contact area, and electrostatic behaviour across diverse tribolayer materials and roughness levels. To address this demand, this paper presents a multiphysics finite element framework that couples mechanical contact analysis with electrostatic simulations, considering exact surface roughness representations rather than idealised statistical approximations. Compared with optical interference microscopy measurements, the framework predicts the real contact area ratio more accurately than analytical models. The proposed approach captures the electrostatic behaviour by scaling the TENG surface charge density with the real contact area ratio between the rough tribolayers, computed for a given mechanical load. This method improves agreement with experiments for open-circuit voltage and capacitance relative to approximate analytical models. To represent the TENG circuit, a time-dependent ordinary differential equation is integrated, enabling evaluation of electrical responses under varying load conditions and elucidating the roles of surface roughness, mechanical load, contact-separation frequency, and resistive load. The framework provides a robust, scalable tool for performance optimisation across dielectric materials, mechanical behaviours, and operating conditions and is readily extendable to other surface-dependent energy-harvesting devices.
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All authors MD Tanzib Ehsan Sanglap, Jack Perris, Rudra Mukherjee, Charchit Kumar, Lukasz Kaczmarczyk, Chris J. Pearce, Daniel M. Mulvihill, Andrei G. Shvarts

Materials Science

Parameter-Efficient Fine-Tuning of Machine-Learning Interatomic Potentials for Phonon and Thermal Properties

Jonas Grandel, Philipp Benner and Janine George

Machine-learning interatomic potentials are widely used as computationally efficient surrogates for density functional theory in atomistic simulations, enabling large-scale, long-time modeling of materials systems. We investigate how different fine-tuning strategies influence the prediction of harmonic phonon band structures, thermal properties, and the potential energy surface along imaginary phonon modes. We achieve substantial accuracy improvements with minimal additional data, with as few as 10 additional training structures already yielding significant gains. In addition to existing approaches, we introduce Equitrain, a finetuning framework that implements LoRA-based adaptation. Across 53 materials systems, we show that fine-tuned models consistently outperform both the underlying pretrained model and models trained from scratch. Equitrain achieves the best overall performance, and our results demonstrate that fine-tuning enables accurate phonon predictions.
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Materials Science

Observation of acoustic magneto-chiral anisotropy in $\alpha$-quartz

M. Altangerel, S. Badoux, C. Proust et al. (+2 more)

We report the experimental observation of magneto-chiral anisotropy in the longitudinal and transverse ultrasound propagation in $\alpha$-quartz. To perform such measurement, we have built an ultrasound spectrometer with unprecedented experimental resolution of the order of $\Delta v/v \sim 10^{-8}$. We present a simple macroscopic Becquerel-like analytical model that accounts for the magnitude of the observed effect and its frequency dependence.
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All authors M. Altangerel, S. Badoux, C. Proust, D. Vignolles, G. L. J. A. Rikken