Peer Revenue Now accepting positions

Papers

Fresh from arXiv, typeset properly. Highlighted words trade on the market.

Physics Condensed Matter Materials Science

cond-mat.mtrl-sci Watch Materials Science

Monday 29 June

Materials Science

Hidden Defect Chemistry in Ion-Irradiated MoS$_2$ Field-Effect Transistors Revealed by Photocurrent Loss

L. Daniel, D. Sutarma, L. Klieve et al. (+7 more)

Defect engineering in monolayer MoS$_2$ is a promising route to tune field-effect transistors (FETs), but the electronic response of defects in processed devices can be masked by contacts, substrate effects, adsorbates, and chemical passivation. Here, we irradiate MoS$_2$ FETs with low-energy 40~eV Ar$^+$ ions to preferentially create sulfur vacancies (V$_S$) in the channel while minimizing substrate damage. We compare dark and illuminated electrical characterization with surface analysis and first-principles calculations. Dark transfer characteristics show an apparent robustness against irradiation up to moderate fluences, with pronounced degradation only at the highest fluence. Under 532~nm illumination, however, the photocurrent and light-induced photodoping decrease systematically with increasing ion fluence, revealing irradiation-induced changes that are hidden in standard dark measurements. Atomic force microscopy and X-ray photoelectron spectroscopy show substantial carbon-containing residues on processed devices even after extended cleaning. We propose that such residues may provide a reservoir for hydrocarbon-mediated passivation of sulfur vacancies. Density-functional-theory calculations provide a microscopic model consistent with this scenario: unsaturated V$_S$ introduce in-gap states, H-C$_S$ configurations suppress these states, and carbon substitution without hydrogen leaves defect states in the band gap. Our results highlight carbon-containing surface contamination as a key factor in interpreting defect engineering experiments on MoS$_2$ and related TMDC devices.
Read the full abstract

All authors L. Daniel, D. Sutarma, L. Klieve, O. Kharsah, U. Hagemann, O. Altenhoff, S. Sleziona, L. Breuer, P. Kratzer, M. Schleberger

Materials Science

Bayesian model comparison of type-I and type-II ultrafast demagnetization dynamics

Hiroki Wadati and Tetsuro Ueno

Ultrafast demagnetization dynamics are often phenomenologically classified into type-I and type-II responses according to their temporal evolution following femtosecond laser excitation. However, finite experimental temporal resolution and noise can substantially obscure the intrinsic dynamics and complicate this classification. In this work, we investigate the distinguishability of type-I and type-II demagnetization dynamics using Gaussian-convolved phenomenological models and Bayesian information criterion-based statistical model comparison. Synthetic datasets with varying temporal resolution and noise levels are first analyzed to evaluate the conditions under which the two classes can be reliably discriminated. We show that convolution with the instrumental response function significantly reduces the observable differences between the intrinsic responses, thereby producing broad regimes in which model discrimination becomes statistically inconclusive. The applicability of the framework is further demonstrated through analysis of representative experimental ultrafast demagnetization data from NiCo2O4 thin films. These results suggest that the apparent classification of ultrafast demagnetization dynamics can be highly sensitive to experimental resolution, noise level, and analysis methodology.
Read the full abstract

Materials Science

Boron-assisted stabilization of low-resistivity mixed-valence Cu-O thin films prepared by reactive magnetron sputtering

Nirmal Kumar, Jemal Yimer Damte, Michal Procházka et al. (+5 more)

This study systematically investigated the influence of boron incorporation in Cu-O thin films and the effect of oxygen partial pressure ($p_{\rm ox}$) on the phase evolution, chemical bonding, and electrical characteristics of the prepared films. A phase transition from Cu$_2$O to Cu$_2$O/Cu$_4$O$_3$ to CuO was observed as oxygen partial pressure increased. Boron incorporation significantly broadened the stability window of the Cu$_2$O and Cu$_4$O$_3$ phases and delayed the transition to CuO at higher oxygen partial pressure. In the highly B-doped Cu-O films, Cu$_4$O$_3$ was stabilized even under oxygen-rich conditions along with the CuO phase, suggesting that boron significantly altered the oxidation pathway. The formation of B-O and possible B-O-Cu configurations altered the local oxygen chemistry and promoted mixed-valence copper oxide phases. Electrical measurements revealed that highly B-doped Cu-O films exhibited a delayed transition from a high-resistivity low-$p_{\rm ox}$ regime to a low-resistivity mixed-valence regime, ultimately reaching approximately 0.06 $\Omega$ cm, among the lowest reported resistivities for a CuO-like material. These findings demonstrate that boron doping is an effective approach for tailoring the phase stability, defect chemistry, and electrical characteristics of Cu-O thin films for optoelectronic and photovoltaic applications.
Read the full abstract

All authors Nirmal Kumar, Jemal Yimer Damte, Michal Procházka, Radomír Čerstvý, Jiří Houška, Pavel Baroch, Stanislav Haviar, Jiří Rezek

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

Rolling Two-Dimensional Collinear Magnets into Chiral Nanotubes with $p$-Wave Magnetism

Zhejunyu Jin, Robin R. Neumann, Rodrigo Jaeschke-Ubiergo et al. (+2 more)

$p$-wave magnets are noncollinear compensated magnetic systems that exhibit nonrelativistic antisymmetric spin splitting in momentum space. Their odd-parity spin symmetry enables unconventional spintronic functionalities, including highly efficient charge-to-spin conversion via the Edelstein effect. An outstanding question is whether such magnetic phases can emerge from simple and broadly accessible magnetic building blocks rather than from intrinsically noncollinear magnetic orders. Here, we show that rolling two-dimensional collinear magnets – ferromagnets, antiferromagnets, and altermagnets – into nanotubes generates a rich spin-symmetry landscape controlled by curvature, chirality, and magnetic order. Remarkably, chiral nanotubes hosting radial or tangential coplanar spin textures generically realize $p$-wave magnetism irrespective of the underlying collinear parent phase. The emergent odd-parity spin symmetry manifests itself in both electronic and magnonic spectra through antisymmetric $p$-wave spin splitting. Our results establish magnetic nanotubes as a versatile platform for engineering unconventional $p$-wave magnetism and predict a nonrelativistic Edelstein response that exceeds conventional spin-orbit-driven charge-to-spin conversion by more than an order of magnitude.
Read the full abstract

All authors Zhejunyu Jin, Robin R. Neumann, Rodrigo Jaeschke-Ubiergo, Jairo Sinova, Alexander Mook

Materials Science

Ferroelastic domain wall motion and collective domain switching in RbSCN

V. Soprunyuk, A. Tröster, J. Pils et al. (+4 more)

Low frequency (0.05 - 40 Hz) dynamic elastic measurements and resonant ultrasound spectroscopy measurements (100-600 kHz) of RbSCN have been performed in the temperature region of the order-disorder improper ferroelastic phase transition at T$_c \approx$ 435~K. Quite similar to KSCN, the low frequency data show - in addition to the intrinsic phase transition anomalies - superelastic softening in a- and b-directions, resulting from movements of ferroelastic domain walls under dynamic stress. However, in contrast to KSCN, a sudden discontinuous increase of Young's modulus appears in RbSCN at { T$^{\ast} < T_c $}, which is accompanied by a frequency dependent damping peak. This behaviour is reminiscent of a first order phase transition.\\ Heating RbSCN slightly above T$^{\ast}$, followed by subseqent cooling, removes all {signs of domain wall dynamics}. The results demonstrate, that the anomalies in RbSCN around $T^{\ast}$ result from collective domain switching events that are induced when the {temperature dependent critical pinning stress, $\sigma_c(T)$ falls below the applied external stress $\sigma$, implying that $T^{\ast}(\sigma=\sigma_c)$. This interpretation is supported by calculations of the temperature dependences of twin boundary widths $w$ and energies $F_w$, as well as the Peierls potential $V_0$ using a compressible pseudospin model, which leads to a critical pinning stress, $\sigma_c(T)$ that is in excellent agreement with experimental values of $T^{\ast}(\sigma_c)$. }
Read the full abstract

All authors V. Soprunyuk, A. Tröster, J. Pils, W. Schranz, I. Rychetsky, A. Klic, M.A. Carpenter

Materials Science

A parsimonious structure model for the icosahedral quasicrystal Cd5.7Yb

Michael Feuerbacher

A compact structure model for the icosahedral phase Cd5.7Yb is presented. The model is based on a higher-dimensional description and a cut-and-projection procedure to generate the atom distribution in three-dimensional physical space. It strictly employs only spherical or elliptical occupation domains, ensuring a low number of parameters and low calculation cost. In the presented form the model has seven adjustable parameters. Despite its minimalistic setting, the model reproduces available experimental data, such as chemical composition, mass density and electron density distribution, as well as the cluster structure in physical space very well. Nevertheless, the approximation of the occupation domains by spheres and ellipses evidently implies limitations in accuracy and universality. The model can be adapted for the description of other Tsai-type icosahedral phases.
Read the full abstract

Materials Science

Phonon-driven Floquet engineering for electronic states

Yu-Chan Tai, Chih-Wei Luo, Noriaki Takagi et al. (+3 more)

Controlling material excitations offers access to novel fundamental and technological properties. The paradigm of Floquet engineering, the manipulation of the electronic structure using a coherent and time-periodic driving source, has attracted significant attention. While most realizations rely on strong optical fields, coherent phonons provide an alternative route to realizing Floquet-Bloch states and are expected to enable substantially longer-lived Floquet-Bloch states. We show that laser-excited coherent phonons drive Floquet-Bloch states. Using time-resolved multiphoton photoemission combined with quantum beat spectroscopy on graphene-covered Ir(111), we track the coherent electronic dynamics of the image-potential states dressed by coherent phonons. The beat signal indicates the presence of sideband structure with the coherent-phonon frequency as its fundamental period, consistent with Floquet theory. Furthermore, an independent oscillation in intensity at the same frequency was observed, confirming excitation of the coherent phonon mode. Compared with conventional light-driven Floquet-Bloch states, the observed phonon-driven Floquet-Bloch states persist for one to two orders of magnitude longer. These results establish coherent phonons as a material-driven route to Floquet engineering and demonstrate the long-lived dressing of electronic states beyond the optical excitation window.
Read the full abstract

All authors Yu-Chan Tai, Chih-Wei Luo, Noriaki Takagi, Hiroshi Ishida, Chun-Liang Lin, Ryuichi Arafune

Materials Science

Analytical approximations of dispersion laws and ultra-complex conductivity diagrams

A.Ya. Maltsev

We study the probability of the emergence of ultra-complex conductivity diagrams in conductors that satisfy the tight-binding approximation and have the simple or body-centered cubic lattice. The presence of ultra-complex conductivity diagrams allows us to observe a number of highly nontrivial effects in strong magnetic fields, however, the probability of their emergence in a given substance is quite low. In the case of the simple or body-centered cubic lattice, the leading tight-binding approximation does not allow us to estimate this probability due to the peculiarities of the spectra in this situation. To estimate this probability, we use higher-order corrections to the leading approximation, which yield more accurate analytical expressions for the electron spectra.
Read the full abstract

Materials Science · Cross-listed from physics.optics

Dynamic Topological Light Control in Reconfigurable Non-Hermitian Metastacks

Ryan Hogan, Zihan Lu, Han Peng et al. (+4 more)

Metasurfaces often require complex lithography for dynamic optical control. To overcome this, we utilize a lithography-free, non-Hermitian planar metastack comprising a distributed Bragg reflector and a vanadium dioxide (VO2) thin film. By virtue of temperature and thermal hysteresis as an active synthetic dimension and exploiting the VO2 insulator-to-metal transition, we actively tune topological interface states to achieve polarization-sensitive spectral control. Notably, our system hosts path-dependent exceptional points (EPs); the intermediate hysteretic states generate a continuum of hot and cold EP pairs that ultimately converge into a single, degenerate EP. Furthermore, we experimentally observe wide-range dynamic optical control, comprising reversible 8% spectral shifts with near-unity reflectance modulation, alongside potential for ultrafast dynamics. Ultimately, our CMOS-compatible design provides a scalable, simple platform for active and topological photonics.
Read the full abstract

All authors Ryan Hogan, Zihan Lu, Han Peng, Jie Zhou, Yanling Xiao, Shining Zhu, Hui Liu

Materials Science · Cross-listed from cs.LG

Atompack: A Storage and Distribution Layer for Read-Heavy Atomistic ML Training Datasets

Ali Ramlaoui, Daniel T. Speckhard, Sagar Pal et al. (+3 more)

Atomistic machine learning datasets are increasingly used for training: large immutable snapshots are read repeatedly, shuffled across epochs, staged across clusters' storage systems, and republished as reusable scientific artifacts. This workload differs from interactive scientific curation, where mutable records and ad hoc inspection are often more important than random indexed throughput. We present Atompack, an append-oriented storage format and distribution layer designed around a simple workload: training pipelines usually consume complete molecular records, while the order of records is randomized by the learning algorithm. Atompack appends records efficiently during dataset construction, then commits an immutable index and serves records through a memory-mapped read path optimized for training. We compare Atompack with HDF5, LMDB, and ASE baselines representing array stores, key-value records, serialized records, and object-oriented databases. The benchmarks measure sequential reads, shuffled reads, shared-filesystem behavior, write throughput, and artifact size. On a representative 64-atom workload, Atompack is 96x faster than ASE LMDB on shuffled training-style reads while producing artifacts about 79% smaller. The results indicate that serving complete molecule records, rather than field chunks or reconstructed objects, improves shuffled training throughput while keeping artifacts compact enough for public distribution.
Read the full abstract

All authors Ali Ramlaoui, Daniel T. Speckhard, Sagar Pal, Fragkiskos D. Malliaros, Alexandre Duval, Victor Schmidt

Materials Science

Consistent transition model for Bi0.5Na0.5TiO3 from temperature-dependent structural and electrical properties

Thomas Fourgassie, Omar Ibder, Cosme Milesi-Brault et al. (+5 more)

BNT based solid solutions are promising parent materials for lead free dielectric capacitors, thanks to their high recoverable energy densities and breakdown strengths. However, the ambient temperature symmetry and high temperature phase evolution of BNT remain unclear. Crucially, structural transformations and electrical ordering are most often considered independently, hindering a coherent understanding of the BNT phase transition. In this work, we combine X ray diffraction, transmission electron microscopy, Raman spectroscopy, impedance spectroscopy, and high field polarization cycling to establish a unified picture of the structural and dielectric response of BNT. Based on these results, we propose a consistent transition model for BNT that reconciles previously conflicting interpretations. This integrated structure property study provides a rationale for developing high performance, lead free energy storage materials.
Read the full abstract

All authors Thomas Fourgassie, Omar Ibder, Cosme Milesi-Brault, Anna Katharina Ott, Eric Bourhis, Pascal Andreazza, Pierre-Eymeric Janolin, Cécile Autret-Lambert

Materials Science

Field-induced topological Hall effect and butterfly-shaped magnetoresistance in the centrosymmetric antiferromagnet EuAuAs

Yu Zhang, Junfa Lin, Huan Wang et al. (+6 more)

The coupling between magnetic and electronic degrees of freedom gives rise to a variety of intriguing transport phenomena. Among them, the topological Hall effect, originating from the real-space Berry phase associated with nontrivial magnetic textures, has attracted considerable attention. Here, we systematically investigate the magnetic and transport properties of antiferromagnet EuAuAs. Magnetic characterizations reveal antiferromagnetic transition at 5.7 K and 6.3 K for $H \parallel ab$ and $H \parallel c$, accompanied by metamagnetic transition and small hysteresis for $H \parallel ab$. Electrical transport measurements reveal a pronounced topological Hall effct in the antiferromagnetic state with $H \parallel ab$ and $I \parallel c$, which may be attributed to finite scalar spin chirality. Furthermore, the magnetoresistance exhibits butterfly-shaped hysteresis and strong angular dependence, which are likely associated with spin-dependent electron scattering, magnetic-domain evolution, and domain-wall pinning. Our results suggest that field-induced spin textures play an important role in the magnetotransport properties and provide insights into the interplay between magnetic textures and electronic transport in centrosymmetric antiferromagnets.
Read the full abstract

All authors Yu Zhang, Junfa Lin, Huan Wang, Kun Han, Yiting Wang, Xue Dong, Zhenfeng Guan, Shengdi Xi, Tian-Long Xia

Materials Science

Ferron Hall effect: Transverse accumulation of polarization driven by thermal gradients in ferroelectrics

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

The phonon Hall effect describes the generation of a transverse heat current in response to a longitudinal thermal gradient in a magnetic field. Here, we theoretically demonstrate that, when the lattice excitations deflected by the Hall effect carry electric dipole moments, their transverse motion produces an accumulation of electric polarization in ferroelectric materials. This accumulation is driven by lattice excitations that carry polarization, known as ferrons, and we therefore call the mechanism the ferron Hall effect. Using atomistic lattice dynamics with parameters obtained from density functional theory, we illustrate the effect in the prototypical ferroelectric BaTiO3. Our results identify ferrons as the electric-polarization analogues of magnons in transverse transport and provide a route toward thermal and magnetic manipulation of ferroic order.
Read the full abstract

Materials Science

The substitutional atomic distance model for predicting lattice thermal conductivity in alloys

Zhicheng Zong, Tianhao Li, Shixian Liu et al. (+2 more)

Understanding phonon transport in alloys is crucial for the design of high-performance electronic and thermoelectric devices. However, conventional theoretical models fail to provide a clear physical picture of phonon scattering caused by atomic disorder in alloys, and their prediction accuracy is limited. In this work, a new substitutional atomic distance model for alloys is proposed, providing an intuitive physical picture. SiGe and InGaAs alloys are taken as representative systems, and their thermal conductivities are calculated, showing good agreement with previous experimental measurements. The results indicate that alloy scattering plays a dominant role in reducing thermal conductivity. This study provides new insights into phonon transport in alloys and offers guidance for tailoring thermal properties through compositional engineering.
Read the full abstract

All authors Zhicheng Zong, Tianhao Li, Shixian Liu, Haisheng Fang, Nuo Yang

Materials Science

Atomically Thin Amorphous Carbon with an Ultralow Dielectric Constant

Chee-Tat Toh, Artem K. Grebenko, Ugur Karadeniz et al. (+17 more)

Two-dimensional (2D) materials exhibit excellent properties at monolayer thickness and are viable replacements for various microelectronic components as scaling gradually approaches the atomic limit. Despite significant advancements in the ongoing 2D revolution of integrated circuits, one crucial building block, namely a 2D ultralow-k (ULK) dielectric, remains unreported. The challenge lies in achieving a dielectric constant less than 3, as traditional low-k dielectrics are inherently unstable at the 2D limit due to their amorphous or porous nature. The realisation of ultrathin dielectrics with low-k is also needed to address current bottlenecks in integrated circuits scaling. Specifically, low-k materials are necessary to minimise parasitic capacitances as the distance between conductive elements shrinks below 10 nm. Moreover, advanced architectures like gate-all-around field effect transistors (GAA FET) require even lower dielectric constants (k<2) at sub-3nm thickness. Here, we show that layer-by-layer grown multilayer amorphous carbon (ML-AC), as thin as 0.8 nm, is a mechanically robust 2D ULK dielectric with k of 1.35 and dielectric strength of 28-31 MV cm-1. The lack of any long-range order, its intrinsic 2D nature, sp2 carbon character and low density are all essential for minimising dielectric permittivity. Moreover, ML-AC overcomes the vulnerability of existing dielectrics to ion diffusion degradation with a record metal ion diffusion time to failure (TTF) of 10^10 s for even a single layer. Therefore, otherwise necessary additional layers occupying up to 3 nm can be eliminated, which is especially significant as metal line widths approach 10 nm. Combined with its low-temperature, direct and conformal growth even on a dielectric, these critical features enable substantial improvements in silicon-based semiconductor electronics and ensure compatibility with future 2D electronics.
Read the full abstract

All authors Chee-Tat Toh, Artem K. Grebenko, Ugur Karadeniz, Usha Bhat, Ya He, Hongji Zhang, Denis V. Vyalikh, Anna Makarova, Alexander Fedorov, Alena A. Alekseeva, Kostya Iakoubovskii, Lu Shi, Andrei Starkov, Chuan Chu Tee, Lucas M. Sassi, Michel Bosman, Naoto Kamiuchi, Yuta Sato, Kazutomo Suenaga, Barbaros Oezyilmaz

Materials Science

Optimizing Expert-Designed Crystal Graph Networks for Band-Gap Prediction with an Autonomous LLM Research Loop

Chenmu Zhang and Boris I. Yakobson

Predicting a material's properties from its structure is a central, fast-advancing problem in computational materials science. A decade of work has produced standard public benchmarks and many published machine-learning models for the task (Dunn et al., 2020). The task's fixed metric and these baselines make it a natural setting for autonomous agent research (Karpathy, 2026). On the MatBench band-gap benchmark ($>$100k crystals), a general-purpose coding agent autonomously built the most accurate model trained without external pretraining, ahead of all seventeen expert-designed models reported for the task. A closer analysis shows it reached this by implementing known methods: either already standard in crystal neural-network models, or borrowed from other areas of machine learning. The contributing implementations include element-pair features on each message-passing edge and a crystal space-group embedding. The work not only demonstrates that LLM-agent autonomous research can optimize an expert-designed machine learning model for material property prediction, but also investigates the limitations of such autonomous research.
Read the full abstract

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

Thermal Fundamental Gap Predictions in DFT via Optimally Tuned Hybrids

Tim Gould, Leeor Kronik, Gil Amoyal et al. (+1 more)

Predicting electronic fundamental gaps at finite temperature has remained conceptually and practically challenging. We address this in three connected steps. First, we extend generalized Kohn–Sham hybrid density functional theory to thermal ensembles, deriving a Mermin generalized Kohn–Sham framework from a thermal one-particle auxiliary system and an exact density-functional remainder. Second, via an extension of Janak's theorem that holds rigorously in this framework, we recast Hirata's thermal-quasiparticle picture as a thermal orbital gap estimator and derive a closed low-temperature form, the error of which is controlled by the derivative discontinuity. Third, because optimal tuning eliminates this error, the auxiliary orbital gap matches the interacting gap at low temperature, upgrading optimal tuning from a ground-state strategy to the governing principle – mandatory, not optional – for accurate finite-temperature gap predictions obtained from gaps of orbital eigenvalues within a hybrid functional framework. We present applications that validate the theory and demonstrate its consequences.
Read the full abstract

All authors Tim Gould, Leeor Kronik, Gil Amoyal, Stefano Pittalis

Materials Science · Cross-listed from cs.CV

MatMMExtract: An Open-Source Pipeline for Panel-Level Extraction of Grounded Image-Text Pairs from Materials Science Literature

Subham Ghosh, Shubham Tiwari, Mohammad Ibrahim et al. (+1 more)

The materials science literature encodes decades of experimental knowledge in figures, yet this visual record remains locked away and inaccessible to AI at scale. The core difficulty is structural: most scientific figures are compound, with a single caption describing multiple sub-panels simultaneously, making direct image-text pairing unreliable. We present MatMMExtract, an end-to-end open-source pipeline that resolves this by decomposing compound figures into individual sub-panels and generating structured, grounded annotations using a large language model guided by a curated materials science taxonomy. Applied to 14,810 open-access articles, MatMMExtract produces MatSciFig; 391,606 panel-level image-text pairs from 180,571 figures, each annotated with a sub-caption, a two-level visualisation category spanning 19 classes and over 100 subtypes, and a scientific summary. To enable accurate panel localisation, we introduce MaterialScope, a domain-specific detection dataset of 2,811 manually annotated materials science figures, on which a fine-tuned YOLO12-m detector achieves mAP_50 of 0.9227. Among six benchmarked language models, Gemini 3.1 Flash Lite delivers the best cost-quality trade-off for annotation generation, with 82% of outputs rated good and a hallucination rate of 4.8%. A dual-encoder retrieval baseline on MatSciFig achieves a 4.4 times improvement in R@1 over zero-shot CLIP, demonstrating the dataset's immediate utility for vision-language learning. All resources are released openly to the community.
Read the full abstract

All authors Subham Ghosh, Shubham Tiwari, Mohammad Ibrahim, Abhishek Tewari

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

Length–Velocity Gauge Equivalence of Quantum Geometric Nonlinear Conductivity in the Adiabatic DC Limit

Shakeel Ahmad and Fei Xue

Nonlinear transport has emerged as a sensitive probe of quantum geometry beyond the Berry-curvature physics of linear response. However, the intrinsic second-order dc response remains conceptually subtle: different quantum and semiclassical formulations can appear to give different static limits, with different assignments of Fermi sea and Fermi surface contributions. Here we resolve this ambiguity by developing a gauge-consistent density-matrix theory of intrinsic nonlinear conductivity in both the length gauge, where the electric field couples through the position operator, and the velocity gauge, where it enters through the vector potential. We show that the two gauges give the same adiabatic dc response when the same retarded continuation is used for all external frequencies and when the velocity gauge current includes all field-dependent vertices. The apparent Fermi sea terms cancel in the full expression, leaving a Fermi surface quantum geometric contribution determined by the band-normalized quantum metric. This result implies that a fully gapped insulator has no residual dc nonlinear Hall current in the adiabatic clean limit. The reactive part of the Fermi surface term agrees with the original semiclassical Berry-connection-polarizability response, while the dissipative Ohmic sector requires a more careful treatment of relaxation and impurity scattering. Our work establishes the length-velocity gauge equivalence for quantum geometric nonlinear response and provides a foundation for using nonlinear transport to probe magnetic quantum geometry, especially in PT-symmetric antiferromagnets.
Read the full abstract

Sunday 28 June

Materials Science · Cross-listed from cs.LG

STEMGym: Benchmarking Sequential Decision-Making under Dose Budgets in Autonomous Electron Microscopy

Can Polat, Erchin Serpedin, Mustafa Kurban et al. (+1 more)

A central premise of autonomous scientific imaging is that smarter navigation, whether Bayesian, RL-based, or otherwise adaptive, is the principal lever for sample-efficient acquisition. We present evidence to the contrary in scanning transmission electron microscopy (STEM), an atomic-resolution imaging modality whose every measurement deposits damaging electron dose. We introduce STEMGym, an open-source Gymnasium benchmark of 15 physics-simulated STEM worlds spanning five materials, three difficulty levels, and four characterisation tasks, scored by the Dose-Efficiency Curve area (DEC-AUC), a single scalar capturing the information-vs-dose Pareto frontier. Across 33 agent configurations under realistic dose budgets, the dominant determinant of dose efficiency is the analyst (perception) pipeline, not the navigator: pairing a trained CNN analyst with naïve raster scanning raises DEC-AUC by 5.5x over a CNN-free raster baseline (0.287 vs.\ 0.052), while substituting Bayesian or adaptive finite-state-machine navigation for raster yields no statistically significant further gain. Production-tier vision-language models further underperform task-specific CNNs by {\sim}13x on crystallographic defect analysis. By decoupling perception, navigation, and planning under a unified dose budget, STEMGym reframes where ML effort should be invested in autonomous electron microscopy and provides the measurement infrastructure to test it.
Read the full abstract

All authors Can Polat, Erchin Serpedin, Mustafa Kurban, Hasan Kurban

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

Geometric Algebra Meets Cartesian Tensors: Higher-Order Equivariance for Interatomic Potentials

Can Polat, Erchin Serpedin, Mustafa Kurban et al. (+1 more)

$\mathrm{Cl}(3,0)$ interatomic potentials, despite their algebraic elegance, predict force magnitudes accurately but force directions poorly. Across ten rMD17 molecules, every $L \leq 1$ baseline in our twelve-model study attains aggregate force-cosine similarity below $0.25$. The cause is structural. The geometric product of two vectors in $\mathbb{R}^3$ realises only the $L=0$ and $L=1$ components of its irreducible representation content, leaving the symmetric-traceless rank-2 component absent from the per-edge bilinear that drives each message-passing layer. We address this with CliffordSTF, which couples the Clifford multivector to closed-form symmetric-traceless tensor tracks at ranks two and three through bilinear cross-track contractions, using a single learned bilinear and no Clebsch–Gordan tables, Wigner-$D$ matrices, or e3nn calls. On rMD17, CliffordSTF raises aggregate force-cosine similarity from $0.055$ (base Clifford) to $0.551$, an order-of-magnitude relative directional gain, alongside improved magnitude accuracy (force MAE $15.8\%$ lower; energy MAE $10.9\%$ lower). It outperforms all CG-free or body-ordered baselines in our study (all $\leq 0.17$). On catalysis benchmarks, CliffordSTF achieves the best out-of-distribution S2EF energy MAE on OC22 in our experiments, and the best in-distribution energy MAE among $L \geq 2$ methods on OC22 IS2RE. An eleven-variant ablation shows the two tracks are complementary: neither alone matches the combined model.
Read the full abstract

All authors Can Polat, Erchin Serpedin, Mustafa Kurban, Hasan Kurban

Materials Science · Cross-listed from cs.LG

Interpretable Inverse Design of Metal-Organic Frameworks with Large Language Model Agents

Kyungmin Nam, Seunghee Han and Jihan Kim

Inverse design of metal-organic frameworks (MOFs) requires navigating combinatorial spaces with costly property labels and opaque machine-learning models. We introduce LLM4MOF, a closed-loop multi-agent framework that converts a natural-language target into chemical hypotheses, constraints, diagnostic tests, and feedback. One agent proposes interpretable hypotheses over metal nodes, linkers, pore geometry, and functionality. Another converts them into constraints selecting MOFs defined by a node, linker, and topology. The Matchmaker forms four beams to attribute gains to geometry, chemistry, or metal choice: full hypothesis, chemistry, metal only, and random baseline. Blind to database landscapes, LLM4MOF enriches top performers across six adsorption, separation, and electronic-structure tasks within 400 evaluations. It also designs and live-simulates de novo MOFs spanning H2 storage, SF6 capture, and C2H6/C2H4 separation, deriving a distinct design rule for each objective. Under an identical nominal evaluation budget it consistently outperforms random search, Bayesian optimization, and genetic algorithms, and the outcome is insensitive to the language-model backend. All of this uses not a single property-labeled training structure, whereas generative alternatives train on thousands to hundreds of thousands. A new objective requires only a natural-language request: interpretable inverse design at a fraction of the data cost of existing approaches.
Read the full abstract

Materials Science

Bilinear Flexo-Antiferrodistortive Coupling in Ferroelastics: Polar Twins, Antiphase Boundaries and Fingerprints of Alterelectricity

Eugene A. Eliseev, Anna N. Morozovska, Akash Saha et al. (+1 more)

Using the Landau-Ginsburg-Devonshire approach we show that the linear gradient-type coupling between the electric polarization vector and antiferrodistortive long-range order parameter pseudovector, that has the form of Lifshitz invariant and named "bilinear flexo-antiferrodistortive coupling", can emerge in all antiferrodistortive ferroelastics, since it is symmetry-allowed. Using the four sublattices model we reveal that the bilinear flexo-antiferrodistortive coupling can induce the sublattice-sensitive polarization at the twin walls and antiphase boundaries in antiferrodistortive ferroelastics without any ferroelectric or antiferroelectric ordering. Since the induced polarization is perpendicular to the antiferrodistortive long-range order parameter and counter-directed in neighboring sublattices with checkerboard-type direction of antiferrodistortive long-range order parameter, such structure of polarization may correspond to the alterelectric-type quadrupolar electric order. However, physical manifestations of the bilinear flexo-antiferrodistortive coupling are invisible in most nanostructured antiferrodistortive ferroelectrics and antiferroelectrics due to the domination of piezoelectric and/or omnipresent linear flexoelectric couplings.
Read the full abstract

All authors Eugene A. Eliseev, Anna N. Morozovska, Akash Saha, Venkatraman Gopalan

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

Electron Delocalization versus Emission Coherence of Quantum Dot Superlattices

Lanfang Hou, Zijian He, Kexin Wang et al. (+3 more)

Cooperative emission is a collective quantum optical process that requires macroscopic phase coherence among coupled emitters. Recent observations of cooperative emission in QD superlattices have renewed interest in how such coherence emerges in nanostructured solids. Meanwhile, theoretical studies have long discussed the relationship between electronic delocalization and coherence, particularly whether delocalized states necessarily give rise to cooperative emission. This study addresses this question through power-dependent steady-state PL and time-resolved PL decay measurements. The findings indicate that, although the quantum resonance peak exhibits delocalized excitonic characteristics, it shows no signatures of cooperative radiation. In particular, neither superlinear intensity scaling nor power-dependent emission delay was observed, indicating the absence of cooperative-radiation signatures. This can be understood from two disorder-related aspects. Temperature-dependent spectroscopy reveals pronounced inhomogeneous broadening and low-temperature dark-exciton participation, pointing to intra-domain static disorder and exciton-state mixing. These effects collectively hinder the establishment of macroscopic coherence. The temperature dependence of the quantum resonance peak decay lifetime is consistent with two-dimensional exciton dynamics. This work provides direct experimental evidence that electronic delocalization can be decoupled from cooperative coherence in CdSe quantum dot superlattices.
Read the full abstract

All authors Lanfang Hou, Zijian He, Kexin Wang, Kai Wang, Shun Wang, Butian Zhang

Materials Science

Strain-Driven Domain Walls in Antiferromagnets

Diego De Gusem, Arnaud Nizet and Bartel Van Waeyenberge

We derive an equation describing domain wall motion in antiferromagnets under the influence of normal strain. From this equation, we find that the domain wall moves towards positions where $\varepsilon_{xx}$ is high and $\varepsilon_{zz}$ is low. Furthermore, each strain component leads to a different terminal velocity for the same strain profile. This difference arises because both strains affect the domain wall width in opposite ways: $\varepsilon_{xx}$ reduces the width, whereas $\varepsilon_{zz}$ increases it. The model is then compared with mumax$^+$ simulations for various strain profiles, including a strain gradient, an oscillating strain, and a Rayleigh wave. The comparison shows good agreement between the analytical and numerical results. Finally, we demonstrate the potential of standing surface acoustic waves as an error correction method in racetrack memory.
Read the full abstract

Materials Science

Multiphysical impedance spectroscopy of porous electrodes based on linear irreversible thermodynamics

Junning Jiao and Juner Zhu

Porous electrodes couple electrical, chemical, mechanical, hydraulic, and thermal fields, yet conventional frequency-domain diagnostics interrogate only one of them: electrochemical impedance spectroscopy (EIS) the electrical response and dynamic mechanical analysis (DMA) the mechanical. Each reads a diagonal entry of the multiphysical constitutive matrix and is blind to the cross-couplings that govern structural evolution and degradation. Starting from linear irreversible thermodynamics, we formulate a general theory of multiphysical impedance spectroscopy, in which perturbing one field and measuring the conjugate response of another probes an off-diagonal entry of the constitutive matrix, recovering the static coupling coefficient and resolving its relaxation dynamics across frequency. Specializing to the electro-chemo-mechanical pathway yields a closed-form theory of mechano-electrochemical impedance spectroscopy (MEIS), in which a small harmonic current is applied and the stack stress is measured; the impedance factorizes into a chemical-accumulation term multiplying the sum of a chemo-mechanical and a poro-mechanical kernel. The porosity-accommodation bridge function is derived from a Helmholtz free energy – following from a microstructural stiffness and viscosity rather than a fitted form – and a three-phase (solid-fluid-void) closure interpolates continuously between unsaturated and Biot-saturated limits through a void-accommodation fraction. Non-dimensionalization reduces the spectrum to five groups, identifies the phase angle as the discriminator of the chemo-mechanical parameters, and locates the onset of second-quadrant behavior, which in a full cell arises from the competition between an expanding and a contracting electrode. MEIS emerges as one member of a family of cross-coupled spectroscopies the same framework brings within reach.
Read the full abstract

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

Latent Genetic Algorithm for Crystal Structure Prediction

Kaixin Zheng, Wanjian Yin, Hongyu Yu et al. (+1 more)

Predicting crystal structures requires navigating rugged energy landscapes in which favorable local motifs must be inherited across candidates with incompatible cells, densities, and symmetries. Conventional real-space crossover often destroys these motifs when parent structures are geometrically mismatched. Here we show that latent representations learned by pretrained universal interatomic potentials can serve as continuous evolutionary coordinates for crystal structure prediction. In the Latent Genetic Algorithm (LGA), offspring are generated by inverse optimization of atomic positions and lattice vectors to match a target latent representation, which is constructed via interpolation of the parent latent vectors. LGA suppresses high-energy and short-contact offspring, increases the HfO$_2$ ground-state recovery rate from 20-35% to 60-95%, and enables a unified variable-supercell search over 16 perovskites with a nearly tenfold reduction in search cost. Applied to (PbTiO$_3$)$_n$/(PbZrO$_3$)$_n$ superlattices, LGA reveals $\sqrt{2} \times 3\sqrt{2} \times 1$ long-period ground-state structures characterized by a common in-plane finite-$q$ modulation $q{_\parallel} = (1/6,1/6)$ and layer-coupled sidebands. To our knowledge, this in-plane periodicity has not been reported in any related oxide perovskite superlattice studies. Altogether, LGA offers a powerful representation-guided paradigm for ground-state structure prediction and provides a practical, decoder-free route toward materials inverse design.
Read the full abstract

All authors Kaixin Zheng, Wanjian Yin, Hongyu Yu, Hongjun Xiang

Materials Science

Silicon-compatible ideal antiferroelectricity with large digital electromechanical responses enabled by thermal-strain domain engineering

Hao Xiong, Huazhang Zhang, Liang Shu et al. (+16 more)

Antiferroelectrics exhibit reversible antipolar-polar transformations, offering a compelling platform for multiple functionalities in modern nanoelectronics, yet deterministic control of antiferroelectric domains and switching pathways remain elusive. Moreover, their integration with ubiquitous silicon-based electronic devices has been limited by the structural and chemical incompatibilities of conventional oxide platforms. Here, we convert the conventional drawback of thermal mismatch into a functional advantage and realize ideal antiferroelectricity in epitaxial PbZrO3 thin films on silicon through thermal tensile-strain engineering, a strain regime unattainable on conventional perovskite substrates. Combined theoretical and experimental studies show that tensile strain stabilizes the (004)o domain, enabling a direct one-step switching, whereas compressive-strain-stabilized (240)o domains switch through intermediate ferrielectric states. The resulting films exhibit near-zero remanent polarization, square double hysteresis, nanosecond switching (~75ns), large reversible electrostrain (~0.6%) and robust operation windows. These findings provide key insights into domain-engineered ideal antiferroelectricity on silicon, opening a viable route toward high-performance antiferroelectric nano-electronic devices.
Read the full abstract

All authors Hao Xiong, Huazhang Zhang, Liang Shu, Yangyang Si, Jiaqi Liu, Chao Zhou, Rui Zhang, Jingxuan Li, Jinyang Li, Chhavi Rastogi, Hao Pan, Bin Xu, Er-Jia Guo, Yunlong Tang, Sujit Das, Philippe Ghosez, Qian Li, Jing-Feng Li, Zuhuang Chen

Materials Science

Kinetically Controlled Condensation Boundary Governing Indium Incorporation in InGaN Metal Organic Vapor Phase Epitaxy

Qihui Lin, Junlin Wu, Erqi Xu et al. (+10 more)

We combine in situ synchrotron X-ray crystal truncation rod measurements with a binary Burton-Cabrera-Frank model to quantify indium incorporation during InGaN growth by metal-organic vapor phase epitaxy (MOVPE) on GaN(0001). By distinguishing In adatoms from condensed droplets and incorporating coupled Ga-In incorporation kinetics, the model captures the intrinsically nonlinear dependence of indium composition on precursor flux and growth temperature. The critical In coverage corresponding to the maximum attainable In composition at a given temperature is determined by a kinetic balance between In adatom supply and incorporation capacity, defining a kinetically controlled condensation boundary that shifts with temperature and Ga flux. The model quantitatively predicts this boundary, in agreement with independent measurements, and provides a predictive framework for optimizing high-In-content InGaN growth while avoiding droplet formation.
Read the full abstract

All authors Qihui Lin, Junlin Wu, Erqi Xu, Jiaqing Yue, Jiale Wang, Zihao Xu, Haixin Qi, Liyi Luo, Haitao Wang, Jia Wang, Hiroshi Amano, Bo Shen, Guangxu Ju

Materials Science

Real-space identification of distinct magnetic configurations in a candidate d-wave altermagnet

Jin-Cheng Gu, Mingzhe Hu, Ziyin Song et al. (+11 more)

Altermagnetism is an emerging class of magnetic order characterized by momentum-dependent spin-split electronic structures despite vanishing net magnetization. Although momentum-space signatures consistent with altermagnetism have been reported in a growing number of materials, their relationship to the underlying real-space magnetic configurations remains incompletely understood, because similar spin-split electronic structures can arise from distinct magnetic orders. In the candidate d-wave altermagnet KV2Se2O, the magnetic origin of the observed momentum-dependent spin splitting has remained controversial. Here, we employ spin-polarized scanning tunnelling microscopy combined with magnetic-field-dependent quasiparticle interference imaging to determine the magnetic configuration of KV2Se2O at the atomic scale. Spin-resolved quasiparticle interference reveals a checkerboard-like antiparallel spin texture within the V2O layer and determines its interlayer spin arrangement across unit-cell step edges. Remarkably, we identify both C-type and G-type magnetic configurations, both of which generate similar spin-split electronic structures at the single-layer level but correspond to d-wave altermagnetic and conventional antiferromagnetic orders, respectively. These observations reveal a complex magnetic landscape arising from nearly degenerate magnetic states. Our results establish a direct connection between momentum-space spin splitting and real-space magnetic order, providing a framework for identifying the microscopic origin of spin-split electronic structures in altermagnetic materials.
Read the full abstract

All authors Jin-Cheng Gu, Mingzhe Hu, Ziyin Song, Lihan Wang, Lihong Wang, Junming Zhang, Jiali Zhao, Hang Li, Shifeng Jin, Xin-Ding Zhang, Genfu Chen, Hongming Weng, Zhongxu Wei, Tian Qian