Materials Science · Cross-listed from cs.LG
Beyond Compression: Training Latent Representations for Stable Long-Horizon Rollout in Neural Surrogate Solvers
Andreas E. Robertson, Ashley T. Lenau, John D. Shimanek et al. (+5 more)
Latent neural surrogate solvers, or latent dynamics models, accelerate simulations of time-dependent physical systems by evolving a compressed latent space rather than resolving full-resolution fields directly. In principle this reduces computational cost and simplifies learning, but in practice errors often accumulate rapidly during long autoregressive rollouts, limiting predictive utility. We show that this instability does not stem from the latent representation itself, but arises when it is trained solely for reconstruction, producing representations poorly suited to long-horizon forecasting. We systematically evaluate training-level interventions that align latent representations with long-horizon rollout: Koopman operator learning and Hamming noise injection during autoencoder training to improve compression, together with noise injection and multi-step rollout fine-tuning to improve dynamics. Interventions that improve long-horizon rollout stability often degrade conventional training metrics, including reconstruction and one-step prediction accuracy. Collectively, these interventions reduce long-rollout error by approximately 40% and match or exceed the accuracy of full-resolution models on two physics
benchmarks, while requiring 2 orders of magnitude fewer floating point operations and half the GPU
memory. Applied to mesoscale
crystal-plasticity simulations of high-cycle fatigue, the resulting surrogate achieves stable extrapolation over horizons orders of magnitude beyond those observed during training. More broadly, these results show that neural compression should be designed not merely to reduce dimensionality, but to restructure the solution space for stable dynamical
evolution, a key requirement for reliable, efficient neural surrogates in scientific applications.
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All authors Andreas E. Robertson, Ashley T. Lenau, John D. Shimanek, Benjamin A. Jasperson, Vivek Oommen, David L. Damm, Krishna Garikipati, Remi Dingreville
Materials Science · Cross-listed from cond-mat.str-el
From dimensional reduction to tetramerization in mixed ferro-antiferro breathing pyrochlores
Sourin Chatterjee, Kelvin Salou-Smith, Benedikt Schneider et al. (+8 more)
We study the
spin-1/2 nearest-neighbor Heisenberg model on the breathing pyrochlore
lattice in the mixed ferro-antiferromagnetic regime, where one tetrahedral sublattice is antiferromagnetic and the other ferromagnetic. The classical ground-state
manifold is then that of the nearest-neighbor face-centered-cubic (fcc) antiferromagnet built from composite tetrahedral moments. Classical Monte Carlo simulations and the self-consistent Gaussian approximation show that thermal order-by-disorder lifts its subextensive degeneracy and selects the collinear Type-I state with wave vector $X=(1,0,0)$ through a strongly first-order transition. Pseudofermion functional renormalization group calculations for $S=1/2$ and $S=1$ reveal a nonmagnetic window adjacent to the decoupled antiferromagnetic-tetrahedron limit, beyond which $X$ order reappears. Density
matrix renormalization group calculations show that this window is not featureless: the antiferromagnetic tetrahedra develop nearly ideal tetramer correlations, with four bonds carrying $\langle\mathbf{S}_i\cdot\mathbf{S}_j\rangle\simeq-1/2$ and the two opposite bonds $\simeq+1/4$, while the structure factor retains broad maxima at $X$. A third-order effective
Hamiltonian in the tetrahedral-singlet
manifold explains this: reversing the sign of the inter-tetrahedron coupling converts Tsunetsugu's dimer selection into a uniform tetramer selection, as confirmed by exact diagonalization. A dynamic high-temperature expansion traces how local tetrahedral excitations give way to low-energy $X$-centered spectral weight. Finally, we place density-functional parameters for eight structures of
spin-3/2 breathing chromium thiospinels in the classical phase diagram. The mapping reproduces the $\mathbf{k}=(1,0,0)$ order of CuInCr$_4$S$_8$, accounts for the absence of order in LiGaCr$_4$S$_8$, and predicts Type-I order for LiInCr$_4$S$_8$.
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All authors Sourin Chatterjee, Kelvin Salou-Smith, Benedikt Schneider, Imre Hagymási, Arnaud Ralko, Johannes Reuther, Jeffrey G. Rau, Karlo Penc, Harald O. Jeschke, Ludovic D. C. Jaubert, Yasir Iqbal
Materials Science
AI-guided high-throughput discovery of iridium- and ruthenium-free palladium-oxide catalysts for durable acidic oxygen evolution
Ken J. Jenewein, Faezeh Habib Zadeh, Xiaoxiao Wang et al. (+19 more)
Catalyzing acidic oxygen
evolution at the
proton-exchange-membrane water electrolysis (PEMWE) anode relies almost entirely on iridium or ruthenium, drawn from concentrated supply chains that constrain gigawatt-scale deployment. We report an artificial intelligence (AI)-guided, human-supervised closed-loop platform (>90% automation) integrating combinatorial sputter synthesis, high-throughput screening, machine-learning composition-property models, adaptive multi-objective optimization, and context-aware large-
language-model
reasoning, where lead catalysts advanced to long-term validation in 1 M H2SO4 at 10 mA cm-2. Navigating a combinatorial metal oxide space, the platform iteratively evaluated the activity-stability trade-off of 2,942 catalysts across 53 material systems and 26 elements, surfacing Ir- and Ru-free complex oxides such as InMnPdOx and NiTaPdOx that conventional design logic, and off-the-shelf
language models, would not predict. In retrospective benchmarking, our sequential learning
agent advanced the activity-stability frontier faster than fixed-policy
Bayesian optimization or in-context
language-model selection. During long-term testing, NiTaPdOx operated at lower overpotential than PdOx, but both eventually exceeded 0.5 V: PdOx at ~200 h and NiTaPdOx at ~470 h. InMnPdOx showed a similar overpotential improvement in addition to a dramatic increase in operational stability, retaining overpotential below 0.5 V over 1,000 h of operation. The additive elements promote the formation of a nanostructure that is associated with catalytic activity while stabilizing Pd against corrosion. The results highlight the power of AI-driven science in addressing long-standing challenges in materials chemistry, and the greater availability of Pd relative to incumbent Ir and Ru offers a near-term option to ease supply constraints on scaled electrochemical H2 generation.
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All authors Ken J. Jenewein, Faezeh Habib Zadeh, Xiaoxiao Wang, Gustavo Malkomes, Huafan Zhang, Natalie Page, Jae Jin Bang, Peter J. Santiago, Karla V. Contreras, Katherine K. Li, Allison Perna, Lorena M. Britton, Fahrettin Kilic, Kevin J. Cruse, Armin Taheri, Krishnanand Mallayya, Harley Quinn, Rebecca A. Durr, Peter A. Beaucage, Santiago Miret, John M. Gregoire, Rafael Gómez-Bombarelli
Materials Science · Cross-listed from cond-mat.mes-hall
Pomeranchuk-like electronic localization above 100 K in twisted MoS$_{2}$
Zhiren Xiong, Jianqi Huang, Ruyue Han et al. (+8 more)
Twisted transition-metal dichalcogenides (TMDs) have manifested a rich variety of emerging physical phenomena, yet experimental studies have so far been largely limited in their valence bands (p-doped). Here, we show correlated electronic states in the conduction bands (n-doped) of near-AA-twisted bilayer MoS$_2$ with twist angles ranging from $\sim2.3^\circ$ to $\sim3.5^\circ$, down to the mK temperature regime. A strongly reconstructed correlated phase diagram as a function of twist-angle has been observed - correlated gaps persist to temperatures approaching $160$ K at small twist angles, but collapse to only $\sim20$ K at intermediate angles, where a richer landscape of interaction-driven states emerges. At the largest twist-angle $\sim 3.5\,^{\circ}$, correlated resistance at 1 electron per moiré unit
cell is enhanced upon heating, consistent with thermally assisted localization, or, a Pomeranchuk-like behaviour. Its
magnetic-field response, however, is highly anisotropic, which differs markedly from that of canonical isospin moiré Pomeranchuk effect in
graphene systems. Strikingly, such signature can persist even above 100 K around a filling of 2 electrons per moiré, despite of its weak resistive nature. Our results establish the twisted MoS$_2$ as a platform for studying the complexity of charge localization, internal flavour degrees of freedom, and band
topology in conduction bands of semiconducting moiré systems.
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All authors Zhiren Xiong, Jianqi Huang, Ruyue Han, Hanwen Wang, Hui Ding, Jianming Lu, Jianpeng Liu, Zheng Vitto Han, Xingdan Sun, Siwen Zhao, Baojuan Dong
Materials Science
Ultrafast Electron Microscopy: A Quantitative Platform for Nonequilibrium Materials Research
David J. Flannigan and Swarit Ahmed Shadman
Macroscopic materials function is determined not merely by
equilibrium structure, but by how carriers,
phonons, fields, defects, interfaces, and collective order dynamically evolve after perturbation. Ultrafast electron microscopy (UEM) uniquely bridges this gap, coupling femtosecond-to-nanosecond timing with real-space, reciprocal-space, and energy-resolved contrast. Here, we review how these integrated capabilities now quantitatively map energy flow and conversion in electronic materials, decode electronic-structural coupling in
quantum and correlated systems, and isolate the localized propagation of carriers, polaritons, strain, and
phonons across optoelectronic and nanomechanical architectures. We emphasize the predictive design rules now emerging from direct metrology of carrier-
lattice coupling, momentum-resolved
phonon thermalization, defect-controlled phase transformations, and authentic operando switching. We critically assess UEM's ongoing maturation from a qualitative, proof-of-concept experiment into a rigorous, quantitative materials platform. This paradigm shift is actively driven by integrated
multimodal detection, advanced energy-resolved spectroscopy, high-repetition-rate sources, multidimensional (4D and 5D) acquisition, and physically constrained forward modeling. Ultimately, the central opportunity lies in establishing a complete, causal link from initial excitation to localized energy flow, transient structure, and macroscopic device function. By prioritizing quantitative reproducibility and robust mechanistic interpretation, UEM is positioned to engineer materials in functional states that
equilibrium thermodynamics simply cannot describe.
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Materials Science
From Processing to Functionality: Engineering Accessible Material States in Cu-Embedded SiO$_x$ Memristive Devices
Tobias Gergs, Rouven Lamprecht, Sahitya Yarragolla et al. (+5 more)
Resistive switching in oxide-based devices is widely governed by
stochastic defect processes, yet a predictive link between fabrication conditions and functional behavior remains elusive. Here, we establish a multiscale framework connecting
plasma-defined deposition conditions to macroscopic device functionality in sputtered SiO$_x$/Cu/SiO$_x$-based systems. By combining large-scale statistical analysis of more than 50,000 experimentally characterized devices with physics-based
plasma and atomistic simulations, we show that device behavior does not emerge from deterministic process-to-performance mappings, but from a probabilistic cascade spanning defect formation, defect-state
evolution, and functional-regime emergence. Data-driven clustering reveals a continuous functional state space composed of operational switching types, while inverse modeling identifies the reconstructed oxygen-vacancy density as an effective latent descriptor capturing the combined influence of structural disorder and defect
topology. This latent descriptor is strongly coupled to both Cu redistribution and electrical response, linking otherwise hidden material properties to observable device characteristics. Furthermore, macroscopic switching behavior is argued to arise from ensemble integration across spatially heterogeneous subdomains, providing a physical explanation for the pronounced variability of large-area devices. These findings shift the perspective from deterministic defect engineering toward probabilistic defect-state design and establish a physically grounded framework for understanding and controlling functional variability in such oxide-based systems, such as memristive or resistive-switching devices.
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All authors Tobias Gergs, Rouven Lamprecht, Sahitya Yarragolla, Ole Gronenberg, Luca Vialetto, Hermann Kohlstedt, Thomas Mussenbrock, Jan Trieschmann
Materials Science · Cross-listed from physics.app-ph
Topological-Insulator Heterophase Gate Stacks for Transistor Electrostatics
Minuk Song, Jiwan Kim, MD Gius Uddin et al. (+25 more)
Conventional gate-stack scaling reduces dielectric thickness and increases permittivity while largely treating the position and electronic character of the gate-side screening boundary as fixed. Here we show that this boundary can be engineered by converting the surface of the topological
insulator Bi\textsubscript{2}Se\textsubscript{3} into insulating high-$\kappa$ BiF\textsubscript{3}. Position-resolved calculations reveal a gap-opened immediate amorphous-BiF\textsubscript{3}/crystalline-Bi\textsubscript{2}Se\textsubscript{3} interface and a reconstructed gap-closed Bi\textsubscript{2}Se\textsubscript{3}-derived state in the adjacent subinterface layer, accompanied by a localized interfacial dipole. Capacitor measurements independently resolve a finite series response consistent with electronic compressibility at this boundary; this response lowers the nominal stack capacitance. Despite this capacitance penalty, MoS\textsubscript{2} transistors with closely matched BiF\textsubscript{3} thicknesses and a common BiF\textsubscript{3}/MoS\textsubscript{2} channel-side material interface exhibit near-thermionic-limit switching, negligible hysteresis and substantially weaker subthreshold drain-bias dependence than BiF\textsubscript{3}-only controls. These results identify the position and electronic character of the gate-side screening boundary as additional design variables for transistor electrostatics beyond nominal dielectric capacitance.
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All authors Minuk Song, Jiwan Kim, MD Gius Uddin, Wonseok Kim, Jihun Park, Han Uk Lee, Dong Won Jeon, Dohyung Lee, Lide Yao, Jouko Lahtinen, Gyunghyun Jang, Soohyun Min, Yonas Tsegaye Megra, Xiaoqi Cui, Seungwoo Choi, Yunyun Dai, Sang Hoon Chae, Keun Su Kim, Dong-Ho Kang, Hyeon-Jin Shin, Wooseok Song, Seth Ariel Tongay, Chul-Ho Lee, Manish Chhowalla, Sung Beom Cho, Zhipei Sun, Kibog Park, Hoon Hahn Yoon
Materials Science
Crystal symmetry predicts unconventional magnetism
Ziyin Song, Zhong Fang, Chen Fang et al. (+1 more)
Unconventional compensated magnets combine zero net magnetization with momentum-dependent
spin polarization, but identifying them usually requires knowledge of their
magnetic order. Here we show that
crystal symmetry can constrain unconventional
magnetic character before the
magnetic ground state is known. Starting from a non-
magnetic crystal structure and a specified
magnetic sublattice, we generate
symmetry-compatible compensated orders and classify their
spin textures using
spin-space-group
symmetry. We identify materials whose generated candidates are all unconventional, either across a defined search space or after restricting the
magnetic-
cell size. Within the experimental
benchmark, 68% of the prioritized materials are unconventional, compared with 9% of the remaining materials. Screening the Materials Project yields thousands of promising candidates for unconventional compensated magnetism. First-principles calculations for $\mathrm{VGe_3}$ and tetragonal $\mathrm{Fe_2SiO_4}$ connect these
symmetry predictions to the energetics and
spin textures of competing
magnetic orders. In $\mathrm{VGe_3}$, a noncoplanar candidate permits mixed-wave
spin polarization along a fixed axis without
spin-orbit coupling, combining components that are odd and even under momentum reversal. This framework enables crystallography-guided searches for unconventional compensated magnets without first determining their
magnetic ground states.
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All authors Ziyin Song, Zhong Fang, Chen Fang, Hongming Weng
Materials Science
Atom-Resolved Machine Learning of Dielectric and Piezoelectric Response
Jinyu Liu, Yingwei Chen, Liyang Ma et al. (+2 more)
Predicting dielectric and piezoelectric responses in structurally complex materials requires large simulation
cells, for which density-functional perturbation theory (DFPT) calculations scale as $\mathcal{O}(N^4)$ and become computationally prohibitive. However, machine-learning approaches have remained challenging, limited either by the large amounts of expensive DFPT data required for direct regression or by the cubic cost of reconstruction. We here propose a machine-learning framework that learns the ionic response as an atom-indexed field: DART (Direct Atom-Resolved response-Tensor learning) learns these fields directly and achieves high accuracy from small training sets, whereas LARS (Linear-scaling Atom-Resolved Response Solver) reconstructs them from learned microscopic ingredients through sparse linear solves and requires no DFPT labels for the ionic dielectric or piezoelectric tensors. Using DART, we extrapolate to 314 stackings of AlN/ScN superlattices absent from training and identify a high-response polar candidate, for which DFPT gives a laterally clamped piezoelectric strain coefficient $d_{33,f}=14.511$ pC/N and $k_t^2=20.46\%$, exceeding the ordered 1AlN/1ScN reference by 63% and 66%.
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All authors Jinyu Liu, Yingwei Chen, Liyang Ma, Hongyu Yu, Hongjun Xiang
Materials Science
Subnanometer thermodynamic overlayers on bimetallic nanoparticles
Caitlin A. McCandler, Xianzhuo Lao, Jie Liu et al. (+3 more)
Nanoparticle properties are governed by their surfaces, yet their atomic-scale surface structures remain challenging to predict. Here, we report that bimetallic nanoparticles can form a thermodynamically controlled "shell-dimer" architecture in which one metal forms an overlayer only a few atomic layers thick on another. Using Au-Rh as a model system, atomic-resolution imaging and molecular dynamics show that an ultrathin Au overlayer forms on Rh, stabilized by competition among surface, interfacial, and strain energies. Anisotropic strain limits its growth to the subnanometer scale, and changes in surface chemistry can destabilize the overlayer altogether. Across a range of bimetallic nanoparticles, we found that overlayer formation is associated with elemental immiscibility and
lattice mismatch. These findings provide a basis for understanding and controlling surface structures in multimetallic nanoparticles.
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All authors Caitlin A. McCandler, Xianzhuo Lao, Jie Liu, Huipu Liu, Kristin A. Persson, Peng-Cheng Chen
Materials Science · Cross-listed from cond-mat.soft
Extracting hydrogel properties by watching hydrogel particles moving through solid ice
Yanxia Feng, Se-Hyeong Jung, Camillo Sirvinski et al. (+4 more)
Strikingly, when hydrogel particles are embedded in ice in a temperature gradient, they move through the solid ice towards warmer temperatures, while swelling as they warm up. This motion comes from a flow of unfrozen water through the hydrogel mesh, driven by a process known as `cryosuction'. Here, we show how one can use this behavior to measure – with extremely high resolution – a range of different hydrogel transport properties, and how these change as a hydrogel deswells. These properties include permeability, compressibility, and poroelastic diffusivity: all of which are challenging to measure, but widely important for phenomena involving swelling, dehydration, transpiration and filtration. We demonstrate the measurement technique using poly(ethylene glycol) diacrylate (PEGDA) hydrogels. The technique uses picoliter-scale hydrogel volumes, and yields measurements of hydrogel properties that are consistent with existing literature data. The high resolution of our measurements also allows us to test commonly-used, classical predictions for hydrogel properties (derived assuming an idealized, homogeneous
polymer network in the hydrogel). We show that these classical predictions do not work well, highlighting the need for new models that can accurately describe real hydrogels.
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All authors Yanxia Feng, Se-Hyeong Jung, Camillo Sirvinski, Dan Balkanyi, Federico Paratore, Lucio Isa, Robert W. Style
Materials Science
Local order in natural sanidine disentangled via single crystal diffuse scattering
Christin Wiggers, Daniel A. Chaney and Ella M. Schmidt
Natural sanidine commonly preserves metastable chemical disorder at ambient conditions, but the local structural correlations associated with this disorder remain poorly understood due to a reliance on average-structure analysis alone. Here, we investigate single-
crystal diffuse scattering in a natural sanidine from Drachenfels, Germany, with consistent observations across additional samples from Laacher See, Germany, and Vesuvio, Italy. The diffraction data reveal pronounced anisotropic diffuse features, including characteristic bowtie-like intensity distributions in reciprocal space. To resolve the origin of these features, we combine three-dimensional difference pair distribution function (3D-$\Delta$PDF) analysis with force-field calculations and Monte Carlo modelling. The 3D-$\Delta$PDF shows correlated deviations from the average structure and indicates a strong coupling between occupational and displacive disorder. Force-field calculations demonstrate that the aluminosilicate framework responds strongly to the local alkali occupancy, with the largest structural variation occurring along the $a$ direction. Guided by these observations, we construct a disorder model in which K/Na occupational short-range order is combined with chemically constrained Al/Si distributions and local framework relaxations. The model reproduces the main experimental diffuse-scattering features and shows that the bowtie-like diffuse scattering arises from correlated framework distortions driven primarily by local K/Na order.
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Materials Science · Cross-listed from cond-mat.mes-hall
Spin-Polarized Magnetic Metal Electrodes for Magnetic Tunnel Junctions
Zhiyuan Duan, Peixin Qin, Li Liu et al. (+7 more)
Magnetic tunnel junctions are foundational components of spintronic
memory, sensing, and computing, and their performance depends critically on the
magnetic metallic electrodes. This Perspective examines electrode materials through the lens of
magnetic order and the distinct microscopic mechanisms that generate
spin-selective tunneling. Conventional ferromagnets, including CoFeB and half-metallic Heusler
alloys, support exchange-split electronic states and
symmetry-filtered tunneling, whereas compensated collinear and noncollinear antiferromagnets exploit sublattice selectivity,
spin-orbit anisotropy, vector
spin textures, and
magnetic multipoles. Altermagnets provide a collinear, zero-net-moment route based on
symmetry-allowed momentum-dependent
spin splitting. Across these material classes, we compare the origins of tunneling polarization, the roles of barrier evanescent states and interface termination, and strategies for electrically writing and reading the relevant
magnetic order. This comparison reveals a broader design principle: effective electrode polarization is not a scalar bulk quantity, but a momentum-, orbital-,
symmetry-, and interface-resolved transport property. Beyond the pursuit of ever larger tunneling magnetoresistance, future progress will depend on converting the unconventional
spin polarization of emerging
magnetic metals into electrically addressable, thermally robust, and reproducible tunneling functionality at realistic interfaces.
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All authors Zhiyuan Duan, Peixin Qin, Li Liu, Guojian Zhao, Sixu Jiang, Xiaoyang Tan, Jingyu Li, Xiaoning Wang, Ziang Meng, Zhiqi Liu
Materials Science
Radiation-technological processes under intense irradiation of a complex fractal medium
Zatsepin Anatoly Fedorovich, Oksengendler Boris Leonidovich, Suleymanov Sultan Khamidovich et al. (+2 more)
A fracton model of a complex medium has been constructed to study physicochemical processes for radiation-technological purposes that occur under intense irradiation. The possibility of shock-wave generation, as well as of percolation phenomena involving fractal aggregates, has been studied in the search for an ideal thermal
insulator.
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All authors Zatsepin Anatoly Fedorovich, Oksengendler Boris Leonidovich, Suleymanov Sultan Khamidovich, Ibrokhimov Rakhmatullo, Nigora Turaeva
Materials Science · Cross-listed from physics.hist-ph
Piezoelectricity: A Brief History of its Discovery and Physical Principles Using the Example of Low Quartz
Ruediger G. Ballas and Nataliya Koev
Piezoelectricity is a key phenomenon in solid-state physics and has significant technological relevance. In teaching, however, it is often treated either without a historical context or an explicit link to the microscopic
crystal structure, meaning that a crucial level of understanding remains untapped. This study combines the history of the discovery of piezoelectricity with its physical description within a didactically coherent framework. Building on the work of the brothers, Jacques and Pierre Curie (1880 - 1882), it demonstrated how investigations into pyroelectricity led to the identification of polarization induced by mechanical compression in hemihedral
crystals such as tourmaline and quartz. The development from early qualitative experiments towards the first quantitative determination of piezoelectric constants is traced in a structured manner. Using low quartz as an example, the microscopic cause of piezoelectricity was attributed to the asymmetric displacements of silicon and oxygen ions within the orthosilicate ion tetrahedral network. This leads to the formation of macroscopic polarization owing to uncompensated dipole moments in the
crystal lattice. The direct and reciprocal piezoelectric effects are qualitatively distinguished and discussed in the context of mechanical-electrical coupling. The article is aimed at students in physics and engineering as well as lecturers. It was conceived as a didactic review article (tutorial article) and serves as a structured introduction to the physical and historical foundations of piezoelectricity.
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Materials Science
Anisotropic Magnetic and Transport Properties of RAlGe (R = Y, Gd-Tm, Lu)
Tyler J. Slade, Lin-Lin Wang, Sergey L. Bud'ko et al. (+1 more)
We grew single
crystals of the RAlGe family for R = Y, Gd-Tm, Lu and characterized them with powder X-ray diffraction, temperature dependent specific heat measurements as well as temperature and field dependent resistance and magnetization measurements. These RAlGe materials crystallize in an orthorhombic Cmcm
crystal structure in which the R atoms occupy a position with $m$2$m$ point
symmetry. We find that when R is a moment bearing rare earth atom, the RAlGe materials order antifferomagnetically at $T_{\text{N}}$ ranging from 5 K (TmAlGe) to 39 K (TbAlGe). A second, lower temperature antiferromagnetic transition is also detected in the range 6-8 K for R = Tb-Ho, but no lower transition is observed (for T above 1.8 K) for R = Er, Tm. The R = Tb-Tm members show evidence for strong
crystal field effects influencing the physical properties, where the
crystal field favors an easy $a$-axis for R = Tb-Ho and an easy $b$-axis for R = Er, Tm. Of these compounds, strongly uniaxial behavior is observed for DyAlGe and TmAlGe. At T = 2 K, rich metamagnetism is observed when the external field is applied along the $a$-axis for R = Tb–Ho, whereas a single metamagnetic transition is observed (up to 70 kOe) with the field along the $b$-axis when R = Er and Tm. All RAlGe materials show metallic transport behavior and have moderate positive magnetoresistance up to 60-150 % at 2 K superimposed on top of metamagnetic features. The field dependent magnetization measurements on non-moment bearing YAlGe show clear de Haas-van Alphen oscillations, indicating the Fermi surface includes small, high mobility pockets.
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All authors Tyler J. Slade, Lin-Lin Wang, Sergey L. Bud'ko, Paul C. Canfield
Materials Science
Unified description of exciton, phonon and plasmon dispersions in 2D materials from an optical conductivity approximation
Alberto Guandalini, Andrea Ferretti, Daniele Varsano et al. (+2 more)
The modified Coulomb interaction in two-dimensional (2D) materials gives rise to unique, non-analytic low-momentum dispersions of
excitons,
phonons, and plasmons. Here, we describe the 2D dispersion of longitudinal excitations by introducing the optical conductivity approximation (OCA), a unified framework that evaluates the finite-q longitudinal response probed by electron energy-loss spectroscopy (q-EELS) by only using the q = 0 optical conductivity. By doing so, the approach demonstrates that the linear dispersion of all the above mentioned excitations is mainly due to the form of the 2D macroscopic Coulomb interaction rather than to the dispersion of the underlying band structure. Applying this approach to hexagonal boron nitride and
graphene we accurately reproduce the energy and intensity dispersions of the hBN longitudinal-optical
phonon and low-energy bright
excitons, along with the
graphene pi-plasmon. Our work also provides an efficient computational scheme to describe low momentum EELS data without the need to calculate the response functions at dense moment
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All authors Alberto Guandalini, Andrea Ferretti, Daniele Varsano, Paolo Barone, Francesco Mauri
Materials Science
X2SBench: an open benchmark for evaluating crystal structure determination from powder diffraction
Zhiyuan Gao, Juncheng Xiao, Shuchen Pu et al. (+7 more)
Progress towards practical powder X-ray diffraction (PXRD) structure determination requires evaluation beyond small
crystals and idealized patterns. X2SBench combines 152,587 simulated structure-pattern pairs with 591 curated measurements, extending evaluation to larger
cells, lower-
symmetry structures and diverse compositions. Fixed splits, defined inputs and common structural metrics support comparisons by
crystal system, atom count and element count. Joint stratification locates weaknesses within these groups. On 558 paired targets, an X2SBench-fine-tuned model improves recovery from simulated patterns but loses accuracy on measured inputs, revealing a gap in experimental transfer. Background subtraction and smoothing improve recovery for one tested checkpoint, while augmentation and reference-
lattice comparisons identify further opportunities for measurement adaptation and reliable
cell estimation. An open platform provides data access and standardized result submission, establishing a shared basis for community evaluation and progress towards practical PXRD analysis.
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All authors Zhiyuan Gao, Juncheng Xiao, Shuchen Pu, Qi Li, Weida Wang, Shufei Zhang, Yong Yang, Shifeng Jin, Yunqi Cai, Hongming Weng
Materials Science · Cross-listed from cond-mat.soft
Microscopic origin of the Baumgärtel-Schausberger-Winter Relaxation Spectrum in Polymer Melts and Particle Rafts
Dario Nichetti, H. Henning Winter and Alessio Zaccone
Entangled
polymer melts exhibit the robust two-branch Baumgärtel-Schausberger-Winter (BSW) relaxation spectrum, while related spectra occur in nonpolymeric monodisperse disordered systems. In spite of the successful application of BSW to many different materials, a molecular derivation of these spectra is lacking. We construct a molecular theory in which a chain segment moves relative to a screened, dynamically responding multichain environment. Gaussian-chain preaveraging gives $M_{\rm seg}(\Delta m)\sim(\Delta m)^{-1/2}$, hence $\lambda_p\sim p^{3/2}$ and, after stress projection, $H(\tau)\sim\tau^{-2/3}$. Independently, longitudinal primitive-path
diffusion gives contour-length fluctuations with $H(\tau)\sim\tau^{1/4}$. A molecular-weight-constrained implementation is tested simultaneously against experimental $G'(\omega)$ and $G''(\omega)$ data for four monodisperse polybutadiene (PBD) melts, without fitting spectral exponents or individual modal weights. The resulting BSW spectrum exhibits a continuous transfer from the fast cooperative to the slow constraint-renewal cascade before a finite-chain terminal edge. A common two-sector caged dynamics then connects
polymers to particle rafts without assuming identical microscopic mechanisms.
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Materials Science · Cross-listed from cond-mat.mes-hall
Nodal-Line Semimetals with Non-Quantized Berry Phase
Zhi-Xia Li, Liangliang Huang, Min-Xue Yang et al. (+3 more)
Nodal-line semimetals (NLSMs) are topological materials characterized by one-dimensional band crossings in momentum space, which typically carry a Berry phase quantized to integer multiples of $\pi$. Here, we extend the conventional paradigm to a class of NLSMs in which the Berry phase can take arbitrary fractional or even irrational multiples of $\pi$. This non-quantized Berry phase leads to a splitting of Landau levels when a
magnetic field is applied parallel to the nodal ring, an effect that can be detected via Shubnikov-de Haas oscillations in the magnetoconductivity. Despite the absence of a quantized topological invariant, drumhead-like surface states with weak dispersion persist at open boundaries. Notably, two identical surface states localize on the same boundary, in contrast to conventional NLSMs, where they reside on opposite boundaries. A systematic
symmetry analysis shows that such NLSMs can be realized in a broad range of
magnetic space groups. Our work opens a new avenue for exploring NLSMs beyond the conventional framework of a quantized Berry phase.
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All authors Zhi-Xia Li, Liangliang Huang, Min-Xue Yang, Feng Tang, D. Y. Xing, Wei Chen
Materials Science
Selective strain tuning of nonequilibrium multiferroic dynamics in BiFeO$_\text3$
Chenhang Xu, Patrick Liu, Bo Zhang et al. (+11 more)
Quantum materials are characterized by intertwined orders, and a fundamental goal in condensed matter physics is to achieve their selective control in such a way that one order parameter can be tuned while leaving others largely unaffected. Although significant progress has been made in thermal
equilibrium, realizing such control out of
equilibrium remains highly challenging. Here we employed in-situ tensile strain to selectively manipulate the photoinduced
lattice dynamics associated with ferroelectric and
magnetic orders in multiferroic BiFeO$_3$. By applying MeV ultrafast electron diffraction to freestanding BiFeO$_3$ membranes under tunable strain, we showed that tensile strain markedly suppresses the ultrafast photoinduced reduction of the ferroelectric displacement. By contrast, the photoinduced dynamics of the antiferrodistortive rotation of the oxygen octahedra, which modulates the
magnetic order, remains insensitive to strain. Not only do these findings reveal distinct microscopic pathways underlying nonequilibrium multiferroic dynamics, they also establish tunable strain as an effective route for engineering ultrafast phase control in correlated materials.
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All authors Chenhang Xu, Patrick Liu, Bo Zhang, Minyong Han, Henry G. Bell, Cameron J. R. Duncan, Yusong Liu, Patrick L. Kramer, Randy Lemons, Jake D. Koralek, Alexander H. Reid, Dong Qian, Harold Y. Hwang, Alfred Zong
Materials Science · Cross-listed from physics.plasm-ph
Equation of state and transport coefficients of warm dense aluminum from mixed deterministic-stochastic density functional theory
Zi Li, Weijie Li, Cong Wang et al. (+2 more)
Aluminum is a reference standard in high-energy-density research and serves as a liner material in megampere Z-pinch facilities. Using mixed deterministic-
stochastic finite-temperature density functional theory, we compute the equation of state and transport coefficients of
liquid aluminum up to temperatures of 1000 eV and compare the results with model-based approaches. We find that for T<200 eV the density-functional results differ from the models by more than 10% at high density, with a maximum deviation of over 30% (at T = 10 eV), leading to significant discrepancies in the Hugoniot curve at high compression; the calculated electrical and thermal conductivities deviate from model predictions by 26% to 63% at T~100 eV. We further employ the Drude model and the Epperlein-Haines framework to examine the
magnetic-field dependence of the conductivities. These results can provide valuable input data for radiation-hydrodynamics codes.
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All authors Zi Li, Weijie Li, Cong Wang, Ping Zhang, Xianjue Peng
Materials Science
Hamiltonian learning reveals optoelectronic mechanisms across thermodynamic state space in soft semiconductors
Frederik Vonhoff, Jesper R. Pedersen, Frederico P. Delgado et al. (+5 more)
Predicting optoelectronic response across thermodynamic state space requires coupling finite-temperature nuclear dynamics to electronic structure at scales where direct first-principles calculations are impractical. Machine-learning force fields and
Hamiltonian-learning models provide scalable predictions, but integrating them into reliable and interpretable workflows remains challenging. Here, we introduce FLOW-OTTER, a modular, model-agnostic framework that automates molecular dynamics,
Hamiltonian prediction, observable extraction, reliability assessment, and
Hamiltonian-level interpretation. We demonstrate FLOW-OTTER in halide perovskites, soft
semiconductors whose anharmonic fluctuations strongly modulate electronic response. Using FLOW-OTTER, we show that independently learned nuclear and electronic models remain predictive when composed end-to-end, reproducing experimental temperature- and pressure-dependent band-gap trends using models trained only on first-principles targets at zero pressure. By resolving the nonlinear
evolution of Pb-$s$/Br-$p$ antibonding at the valence-band maximum, it identifies the microscopic origin of the asymmetric pressure response. FLOW-OTTER thus establishes
Hamiltonian learning as a general route from thermodynamic trajectories to experimentally grounded optoelectronic mechanisms.
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All authors Frederik Vonhoff, Jesper R. Pedersen, Frederico P. Delgado, Martin Schwade, Peter Beck, Jonas A. Oldenstaedt, Ivano E. Castelli, David A. Egger
Materials Science
Combining physical models with dynamically acquired experimental information for the optimization of multicomponent NASICON fast ionic conductors in a self-driving laboratory
Bernardus Rendy, Yuxing Fei, Tanjin He et al. (+9 more)
Elemental substitution within existing structural frameworks is a widely applied strategy for developing advanced materials. Yet, optimizing target properties while maintaining phase purity usually demands extensive trial-and-error, which becomes substantially inefficient when navigating a complex design space. Here, we introduce a strategy that simultaneously and dynamically assesses composition-dependent synthetic accessibility and target properties via aggregated cost functions that guide autonomous experimentation in a truly self-driving and self-learning mode. Specifically, we developed a cost-guided autonomous solid-state synthesis (CASS) framework and demonstrate its application in the discovery of Na superionic conductor (NASICON) solid electrolytes. CASS successfully optimizes ionic conductivity and phase purity, leading to the identification of 18 promising compositions in 78 trials conducted in an autonomous laboratory, the A-Lab. Among these, we identified two fast-conducting NASICONs yielding total (bulk) ionic conductivity of 0.7 (3.96) and 0.3 (3.17) mS/cm. The successful deployment of CASS reinforces the potential of coupling self-driving autonomous laboratories with physics-informed generative models to accelerate materials discovery. Moreover, the interpretability of the design factors, informed by outcomes from both successful and failed syntheses, enables model refinement and generation of new chemical insights.
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All authors Bernardus Rendy, Yuxing Fei, Tanjin He, Xiaochen Yang, Andrea Giunto, Lauren N. Walters, David Milsted, Hao Qiu, Matthew J. McDermott, Bin Ouyang, Yan Zeng, Gerbrand Ceder
Materials Science
Rational Design of Low-Dimensional Hybrid Organic/Inorganic Interfaces for Enhanced Second-Harmonic Generation
Michele Guerrini, Muhammad Sufyan Ramzan and Caterina Cocchi
Hybrid interfaces formed by push-pull organic molecules physisorbed on two-dimensional (2D)
semiconductors provide a structurally tunable platform for engineering second-harmonic generation (SHG). However, predicting and optimizing their macroscopic response remains a formidable challenge due to the phase-sensitive interference between the nonlinear responses of the adlayer and substrate. Here, we develop a physics-informed computational screening framework that decomposes the effective second-order susceptibility into its constituent substrate, molecular, and electric-field-induced SHG channels. Validated by fully atomistic first-principles calculations across representative interface structures, this model maps the complete orientation-resolved tensor landscape of chemically modulated carbon-conjugated polar molecules on 2D substrates with distinct
symmetry. Crucially, our findings dismantle the conventional reliance on static polar descriptors, demonstrating that the ground-state permanent dipole magnitude is a fundamentally unreliable proxy for macroscopic nonlinear response. Instead, we show that the ultimate criterion for SHG maximization is encoded in the phase-resolved projection of the full anisotropic molecular hyperpolarizability tensor. On non-centrosymmetric substrates, the coherent interference between the physisorbed adlayer and the underlying 2D
matrix induces a characteristic Fano-like asymmetry and ranking reversals that are entirely absent on centrosymmetric platforms. By establishing that functionalization
topology, dynamic spatial orientation, and substrate point-group
symmetry constitute a single, non-separable parameter space, this work provides a systematic blueprint for the rational assembly, predictive discovery, and non-invasive characterization of next-generation low-dimensional hybrid materials for nonlinear optoelectronics.
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Materials Science · Cross-listed from cond-mat.mes-hall
Valley Berry curvature dipole induced nonlinear valley Hall effect
Lulu Xiong, Xue-Jin Zhang, Zeying Zhang et al. (+4 more)
Valley Hall effect is a signature effect in the field of valleytronics, and recent studies have pushed this effect into the nonlinear regime. Here, we reveal a previously unexplored type of nonlinear valley Hall effect which arises from a valley Berry
curvature dipole (vBCD) mechanism. We show this nonlinear valley Hall effect is forbidden for conventional time-reversal-connected valleys, but is supported in the class of valleytronic systems featuring time-reversal-invariant valleys. The candidate layer groups and detailed
symmetry constraints on vBCD are obtained. It shows the nonlinear valley Hall response, as well as the nonlinear charge Hall response, can be well controlled by tuning the driving field direction. We demonstrate our proposal in an effective model study and in a concrete material example, strained Nb$_{3}$SBr$_{7}$, by first-principles calculations. The nonlocal transport signature of this vBCD induced nonlinear valley Hall effect is also discussed.
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All authors Lulu Xiong, Xue-Jin Zhang, Zeying Zhang, Yinning Zhou, Jin Cao, Cong Xiao, Shengyuan A. Yang
Materials Science
Superconductivity and Band Topology in Functionalized 2D Hexagonal MBenes
Mohammad Keivanloo, Shashi B. Mishra, Amirreza Shariatmanesh et al. (+5 more)
Recently, two-dimensional transition-metal borides (MBenes) have attracted substantial interest due to their promising properties for electrocatalytic applications. Here, we explore their potential as novel two-dimensional
superconductors and topological materials through first-principles calculations on both pristine and surface-functionalized hexagonal MBenes. We conduct a thorough examination of the structural, electronic, phononic, superconducting, and topological properties of 36 compounds with formulas M$_{2}$B$_{2}$ and M$_{2}$B$_{2}$T$_{2}$ (M = Sc, Ti, V, Zr, Nb, Hf, Ta, Mo, W; T = F, O, OH). Our analysis identifies 21 superconducting MBenes, including four with critical temperatures (T$_{c}$) exceeding 10 K, with Ti$_{2}$B$_{2}$O$_{2}$ exhibiting the highest predicted T$_{c}$ of 24 K based on the McMillan formalism. For the two most promising compounds, Ti$_{2}$B$_{2}$O$_{2}$ and V$_{2}$B$_{2}$(OH)$_{2}$, we further solve the anisotropic Migdal-Eliashberg equations, obtaining zero-temperature superconducting gaps of 6.1 and 3.6 meV and anisotropic T$_{c}$ values of approximately 32 and 25 K, respectively.
Symmetry-indicator-based analysis further reveals nontrivial normal-state band
topology in several superconducting MBenes. These results indicate the coexistence of
phonon-mediated superconductivity and nontrivial normal-state band
topology within this material family, making MBenes promising platforms for future investigations of the possible emergence of topological superconductivity.
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All authors Mohammad Keivanloo, Shashi B. Mishra, Amirreza Shariatmanesh, Mohammad Sandoghchi, Kenta Hongo, Ryo Maezono, Elena R. Margine, Mohammad Khazaei
Materials Science
Electric Current-Driven Microstructural Evolution in SrTiO3
Jingjing Yang and Jian Luo
Polycrystalline SrTiO3 is employed as a model system to investigate microstructural
evolution under applied electric currents. Under a substantial current density, well-aligned, elongated abnormal grains develop near the anode following a flash event, in contrast to previously reported cathode-side enhanced grain growth under negligible currents. The equivalent diameter of the abnormal grains increases linearly with time, deviating from classical parabolic grain growth kinetics. The applied current drives elemental redistribution near the anode, producing a Ti-rich region adjacent to a Sr-rich belt that migrates toward the cathode, from which the abnormal grains nucleate. Aberration-corrected scanning transmission electron microscopy and electron energy-loss spectroscopy reveal that the fast-moving grain boundaries (GBs) within the Ti-rich bulk region are Sr-enriched, O-depleted, and Ti-reduced. An analysis based on the Brouwer diagram suggests the formation of p-i-n regions under the applied electric field. Conversion between electronic and ionic currents at the p-i and i-n junctions, field-driven precipitation and dissolution of the Sr-rich Ruddlesden-Popper phase, and field-driven migration of Sr and O vacancies collectively explain the elemental redistribution and redox-modulated migration of the Sr-rich belt. Incomplete redox reactions at the moving junctions create the moving Sr-rich belt and generate a locally reducing environment, consequently producing fast-moving, Sr-rich, reduced GBs. These findings reveal new mechanisms of electric current-driven defect-mediated microstructural
evolution.
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Materials Science
Frustrated junctions in interfacial networks
Håkan Hallberg, Vasily V. Bulatov, Bryan W. Reed et al. (+1 more)
Networks of interfaces in materials and living systems evolve through motion and rearrangement of interfaces and junctions. Local
equilibrium at a junction requires interfacial force balance. We show that in three dimensions the classical Herring condition for triple lines is necessary but insufficient: four triple lines meeting at a quadruple node may each satisfy Herring
equilibrium, while the four conditions remain mutually incompatible. Such a frustrated node has no admissible local
equilibrium geometry. In the semi-isotropic limit, the six interfacial energies must form the edge lengths of a non-degenerate tetrahedron, with constructibility determined by the Cayley-Menger determinant. This hidden compatibility constraint arises from three-dimensional geometry and applies broadly to foams, polycrystals, tissues and other interfacial networks.
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All authors Håkan Hallberg, Vasily V. Bulatov, Bryan W. Reed, Mukul Kumar
Materials Science · Cross-listed from cs.LG
Growth-Inspired Graph Generation and Inverse Design of Mechanical Lattices via Dot Matrices Database Augmentation and GCNN
Weiyun Xu and Jiamu Liu
Natural load-bearing and transport networks are not assembled in a single step; they emerge through a temporally ordered process of growth, branching, reinforcement, and loop formation. Inspired by this developmental logic, this work introduces a morphogenetic graph-generation framework for mechanical
lattices in which a discrete dot
matrix provides potential nodes and the final architecture is created by sequential cross-layer and intra-layer growth. The same rule is visualized in two dimensions as a leaf-vein-like developmental sequence and implemented in three dimensions on a 3x3x3 nodal
matrix containing 27 candidate nodes. A
dataset of distinct three-dimensional
lattices was evaluated by beam-based finite element analysis and represented directly as graphs. A graph convolutional neural network (GCNN) with three graph-convolution layers and dual global pooling learns the
topology-property mapping and predicts effective compressive stiffness. Coupling the GCNN surrogate with rapid structural sampling enables inverse design: for a target stiffness of 1000 MPa, the selected design was predicted at 1042.43 MPa and validated by finite element analysis at 1027.49 MPa. Beyond straight members, the framework has also been extended to parameterized horseshoe-shaped curved beams made of nonlinear materials, enabling
topology-geometry design toward prescribed deformation shapes. Our work provides a paradigm for augmenting the database of mechanical metamaterials, and the resulting perspective links biological morphogenesis, graph learning, and nonlinear shape programming in a unified generative design framework for architected materials.
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