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Physics Condensed Matter Materials Science

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Saturday 25 July

Materials Science · Cross-listed from cs.AI

Harnessing agent memory to build lifelong AI partners for materials scientists

Siyu Liu, Bo Hu, Beilin Ye et al. (+3 more)

Materials research advances through accumulated experience - scripts that work, protocols that are trusted, warnings attached to failed calculations or experiments, and judgement that links a new question to an old result. This experience is essential for reproducibility and knowledge transfer, yet it is usually fragmented across notebooks, repositories, job logs and individual memory, and it is rarely portable across artificial-intelligence agents. Here we argue that a lifelong AI partner for materials science can be designed around persistent memory rather than around a particular agent implementation. We introduce a self-evolving memory framework that stores scientific experience as inspectable facts and executable skills, so that observations, failure boundaries, protocols and validation checks can be retrieved, revised and migrated across models. We evaluate the idea in three computational settings that expose different layers of materials-research competence. In 49 real-world materials-tool-use questions comprising 138 executable subtasks, memory nearly doubles GPT-5.2 task success without model-parameter updates. In elemental-solid equation-of-state calculations, memory converts a wavefunction-initialization failure into a pre-execution guardrail, improving outcomes from 22/1/4 to 25/2/0 Correct/Partial/Error and avoiding 92% of repeated errors. In 13 practical material simulation workflows, remembered skills and failure facts halve the aggregate trace burden (tokens) and reduce tool calls by over a factor of two by the third round, while preserving physically meaningful outputs in band-gap, phonon, vacancy and work-function analyses. These results show that agent memory can serve as a durable scientific asset; a portable, self-improving record of materials-research experience that outlives any single model or agent stack.
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All authors Siyu Liu, Bo Hu, Beilin Ye, He Cao, David J. Srolovitz, Tongqi Wen

Materials Science

Fermi-level mediated acceleration of flash sintering of oxide ceramics

Qin-Kun Li, Evgeni S. Penev and Boris I. Yakobson

The atomistic understanding of flash sintering (FS) remains speculative, despite its efficiency and versatility in materials processing. Employing first-principles calculations we demonstrate how charge compensation of a range of defects in the prototypical Y-stabilized cubic ZrO$_2$ (YSZ) shifts Fermi level E$_F$ up during FS, thereby accelerating cation migration for fast mass transport. The charge transition of Zr vacancy, V$_{Zr}^q$, reduces its bulk diffusion barrier in V$_{Zr}^{-4}$ during flash by 2 eV, relative to V$_{Zr}^0$ before flash, which is triggered by the charge equilibrium of nonstoichiometric defects. The substituent defect Y$_{Zr}$, released by annihilating O vacancy, V$_O$, in Y$_{Zr}$V$_O$Y$_{Zr}$ defect complex, acts as electron acceptor and favors V$_{Zr}^0$ before flash whereas excess V$_O$, as electron donor thermally generated at the FS onset, upshift E$_F$ and thus support V$_{Zr}^{-4}$. The proposed mechanism of Fermi-level mediated cation diffusion for YSZ is generalized to other flash-sintered ceramics and has considerable bearing on the general theory of FS techniques in oxide ceramics.
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Materials Science

Stoichiometric cluster learning for few-shot property prediction of multi-ionic integrated energetic materials

Ming-Yu Guo, Wei-Jia Zou, Yu Shang et al. (+1 more)

Multi-ionic materials pose a distinct representational challenge in machine learning-driven materials design. Different from single-molecule or composition-based materials, their properties arise from how charged building blocks aggregate into specific assemblies. Here, we show how pretrained machine-learned interatomic potentials (MLIPs) can bypass full crystal-structure prediction and support pre-synthesis screening from stoichiometric ionic clusters using multi-ionic integrated explosives (MIXs) as a synthesis-facing example. This strategy combines a stoichiometric ionic-cluster representation, which represents each candidate material by a non-periodic, stoichiometry-preserved formula-unit cluster, with multi-task fine-tuning (MT-FT), which adapts a pretrained atomistic backbone while retaining the energy–force objective as physical regularization for the sparse detonation-velocity labels. With the pretrained backbone regularized by MT-FT, this surrogate provides a cross-validated screen across only 25 structurally curated perovskite-type energetic materials (PEMs) with experimentally derived Kamlet–Jacobs (K–J) detonation velocities. Representation probes show that the learned descriptors implicitly retain site-aware ionic organization, density information, and coarse packing compatibility, implying why non-periodic clusters can remain predictive before full crystal structures are known. The surrogate extends known PEMs chemistry to three newly synthesized ABX$_4$ materials with both unseen ABX$_4$ stoichiometry and an unseen ethylenediammonium B-site cation, yielding three-point concordance with K–J reference velocities and a mean absolute error (MAE) of 92~m$\cdot$s$^{-1}$ without retraining. Together, these results establish stoichiometry-preserved cluster learning as a synthesis-facing screening strategy for data-scarce multi-ionic materials.
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All authors Ming-Yu Guo, Wei-Jia Zou, Yu Shang, Wei-Xiong Zhang

Materials Science

A DFT and Machine Learning-Assisted Study on the Lattice Thermal Conductivity of LiCdSb for Thermoelectric Applications

R. Zosiamliana, Lalhriat Zuala, N. T. Tien et al. (+3 more)

By using first-principles density functional theory (DFT) and the Boltzmann transport equation, we have calculated the corresponding electronic and thermoelectric properties of LiCdSb. For calculating electron transport properties, accurate band-structure estimation is crucial. Hence, for the precise band gap calculation, we have implemented a hybrid functional HSE06, which is widely known for its high accuracy. To evaluate the thermoelectric performance of a material, the calculation of lattice thermal conductivity (Kl) is a key parameter. However, from a theoretical perspective, the calculation of lattice thermal conductivity is very complex and demands huge computational resources. Therefore, in this work, we have opted for an alternative method of machine-learning interatomic potentials (MLIPs) for the calculation of Kl. Our result of Kl=0.24 Wm^-1K^-1 at room temperature is in qualitative agreement with the available theoretical and experimental data. The figure of merit (ZT) with Kl estimated from Slack+TDEC ZT is 0.18 at 300 K, and machine learning (ML) models ZT is 0.17 at 300K, combining with HSE06-based electronic transport properties agreed well with the available experimentally reported value of ZT is 0.10 at 300K. However, we report the ZT value well above the benchmark value of 1 beyond 600K. The ZT value exceeding 1 at higher temperatures makes LiCdSb a promising material for high-temperature energy conversion.
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All authors R. Zosiamliana, Lalhriat Zuala, N. T. Tien, Vo Khuong Dien, A. Laref, D. P. Rai

Materials Science · Cross-listed from cond-mat.stat-mech

Quantum fluctuation-driven transport crossover between two liquid states in distinguishable helium-4

Mika Tanabe, Momoko Tsujimoto and Kenichi Kinugawa

We show the emergence of a quantum fluctuation-driven transport crossover between two liquid states in distinguishable helium-4 obeying Boltzmann statistics, in the absence of atomic exchange. Using path integral centroid molecular dynamics simulations over 0.1-3.3 K and 1-60 bar, we investigate the transport properties of two distinct liquid states: the low quantum-dispersion liquid (LQDL) and the high quantum-dispersion liquid (HQDL). While LQDL exhibits conventional liquid behavior consistent with the Stokes-Einstein (SE) relation, HQDL emerges at lower temperatures and displays anomalous gas-like transport characterized by superdiffusion and ultralow viscosity, accompanied by a breakdown of the SE relation. This counterintuitive emergence of gas-like dynamics upon cooling reflects the dominant role of nuclear quantum fluctuations, in contrast to thermal fluctuations at higher temperatures. Across the LQDL-HQDL boundary, we identify a transport crossover marked by a qualitative change in the velocity autocorrelation function (VAF), a transition in the Prandtl number, and the emergence of transport minima in shear and kinematic viscosities, thermal conductivity, and thermal diffusivity. These minima reflect a crossover from liquid-like to gas-like transport upon cooling in the low-temperature subcritical region, in addition to the universal transport minima observed in the supercritical regime. The transition from oscillatory to monotonic VAF defines a second Frenkel line, distinct from the conventional Frenkel line observed in the supercritical region. LQDL is a heat-transport-dominated dissipative fluid, whereas HQDL is a momentum-dominated inertial fluid. These results demonstrate that nuclear quantum fluctuations alone induce gas-like liquid behavior and provide a unified picture of transport phenomena in distinguishable helium-4 without superfluidity.
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Materials Science · Cross-listed from cond-mat.mes-hall

Janus-induced atomic reconstruction amplifies twist-angle modulation of interlayer thermal transport in moiré bilayers

Bin Xu, Rulei Guo, Jie Sun et al. (+8 more)

In two-dimensional moiré bilayers, atomic reconstruction, the spontaneous structural relaxation toward energy-minimizing stacking registries in the near-commensurate regime, can strongly modify local stacking and interlayer coupling, providing a possibility to significantly control phonon-mediated properties. Here we show that the twist-angle dependence of interlayer thermal conductance can be modified by introducing Janus-induced mirror-symmetry breaking into bilayer MoS2. The intrinsic out-of-plane dipole in MoSSe/MoS2 bilayers leads to frictionless interface, and reduces the lattice deformation energy, thereby promoting atomic-reconstruction into locally distorted aperiodic moiré patterns. These features weaken interlayer coupling and suppress phonon transmission across the interface, leading to an anomalously strong twist-angle dependence of thermal conductance, with a pronounced minimum at small twist angles and a reduction rate nearly one order of magnitude larger than that of twisted bilayer MoS2. Our results demonstrate that interlayer thermal transport is modified by atomic reconstruction, highlighting Janus-induced mirror-symmetry breaking as an effective way to promoting phonon engineering in two-dimensional moiré structures.
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All authors Bin Xu, Rulei Guo, Jie Sun, Hiroo Suzuki, Takuma Yoshida, Ichiro Nakaya, Koki Sawasaki, Yasuhiko Hayashi, Shohei Chiashi, Tomoki Machida, Junichiro Shiomi

Materials Science

Imaging of van der Waals Materials via Standing-Wave Photoemission Microscopy: Depth-Resolved Electronic Structure of WS2

J. R. Paudel, R. Muzzio, M. E. Matzelle et al. (+13 more)

Two-dimensional van der Waals materials promise electronic, optoelectronic, and quantum technologies, yet depth-resolved characterization remains challenging. Here, we demonstrate standing-wave photoemission electron microscopy (SW-PEEM) for Angstrom-scale spectromicroscopy of monolayer WS2 on a W/C multilayer substrate. Tuning the X-ray standing wave through the monolayer yields a chemical depth profile and valence-band modulation with enhanced sensitivity to the top and bottom sulfur layers. X-ray optical modeling determines the structure and field distribution. The measurements reveal an ~0.2 eV shift in sulfur-derived valence-band spectral weight between measurements with enhanced sensitivity to the top and bottom sulfur layers. This shift is unlikely to arise from strong direct substrate hybridization and is instead consistent with sulfur-related surface species, as supported by calculations using a representative elemental-sulfur model. These results establish SW-PEEM as a non-destructive depth-resolved probe, highlighting its potential to probe interfacial coupling, chemical reconstruction, and emergent states in van der Waals and moiré systems.
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All authors J. R. Paudel, R. Muzzio, M. E. Matzelle, S. Sheikh, A. Fadul, A. Tiwari, F. Salmassi, E. Gullikson, K. M. McCreary, B. T. Jonker, J. Nieminen, C. M. Schneider, F. Kronast, A. Bansil, J. Katoch, A. X. Gray

Materials Science

Hydrogen-Induced Sign Reversal in Magnetic Hysteresis Evolution of CoPd Alloys and Co/Pd Multilayers

S. S. Das and A. Gerber

Hydrogen absorption in magnetic thin film nanostructures can modulate their electronic, magnetic, and transport properties by modifying the electronic structure and lattice strain. However, the influence of composition and nanostructuring on these two competing effects is not well understood. We systematically investigate hydrogen-induced magnetic hysteresis in Co$_x$Pd$_{100-x}$ alloys, [Co(0.1 nm)/Pd(d)]$_{15}$, and [Co(0.2 nm)/Pd(d)]$_{15}$ multilayers, using extraordinary Hall effect characterizations (EHE) in air and 4% H$_2$/N$_2$ mixture. We show that the hydrogen-induced response is not universal, but depends strongly on composition and layer thickness. This reflects competition between Pd-related electronic effects and magnetoelastic anisotropy. In Pd-rich CoPd alloys and Co(0.2 nm)/Pd multilayers, hydrogen initially contracts the hysteresis loops at low Co fractions, followed by loop expansion above x ~ 40%. This contrast results from competition between suppression of Pd-induced magnetization through Pd-4d band filling and hydrogen-driven anisotropic strain that strengthens magnetoelastic anisotropy in Co-rich samples. In contrast, in ultrathin [Co(0.1 nm)/Pd(d)]$_{15}$ multilayers, hydrogen induces a weak, non-monotonic but generally expanding loop behaviour across x = 15-60%, indicating a dominant role of interfacial magnetic connectivity and strain-mediated magnetoelastic anisotropy in the ultrathin limit. Furthermore, we observe a hydrogen-induced reversal of the EHE loop polarity near the crossover regime, reflecting a change in the dominant EHE scattering mechanisms, thus providing an additional degree of magnetic tunability by hydrogen. These results demonstrate that hydrogen can selectively tune the magnetism of CoPd nanostructures via composition-controlled electronic and magnetoelastic effects, offering insights for hydrogen-responsive spintronic and sensing devices.
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Materials Science

Ferroelastic exciton splitting in hybrid perovskite nanowalls

Afreen, J. Delgado-Alvarez, H. Krishna Mishra et al. (+9 more)

Hybrid metal-halide perovskites are soft semiconductors in which electronic excitations are strongly influenced by lattice distortions and structural phase transitions. An important open question is whether ferroelastic symmetry breaking merely broadens optical resonances or instead modifies excitonic states through exciton-lattice coupling. Here, we address this question using highly aligned MAPbI3 nanowalls fabricated by glancing-angle deposition, enabling symmetry-selective coupling between ferroelastic texture, structural anisotropy, and a well-defined optical axis. Combining temperature-dependent photoluminescence, X-ray diffraction and polarization-resolved ultrafast transient absorption spectroscopy, we observe a polarization-selective excitonic splitting in the orthorhombic phase at 5 K, characterized by orthogonal optical selection rules and a 45 meV energy separation. Near 160 K, where orthorhombic and tetragonal phases coexist, a lower-energy lattice-coupled excitation emerges 58 meV below the centre of the anisotropically split excitonic structure, consistent with coupling between excitonic and lattice-dressed states. At higher temperatures, these excitations progressively acquire lattice-dressed character accompanied by reduced optical anisotropy. A symmetry-guided effective Hamiltonian captures the evolution from anisotropically split excitons to coupled excitonic and lattice-dressed states across the structural transition. Our results show that ferroelastic texture and phase coexistence can modify exciton-lattice coupling, providing a route to symmetry-selective optical responses in soft polar semiconductors.
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All authors Afreen, J. Delgado-Alvarez, H. Krishna Mishra, J. Castillo-Seoane, Koustav Maiti, Pravrati Taank, A. Borras, A. Barranco, Surajit Saha, Priya Mahadevan, J. R. Sanchez-Valencia, K. V. Adarsh

Materials Science · Cross-listed from cs.IR

VecTree-RAG: An Agentic Retrieval-Augmented Generation Framework Combining Vector and Tree Retrieval for Efficiency and Accuracy

Xinyan Zhong, Yuwei Shi, Yuqi Wei et al. (+3 more)

Scientific question answering requires a retrieval system to solve two distinct problems: identifying which papers are relevant and locating the supporting evidence within those papers. Conventional retrieval-augmented generation typically addresses both through similarity search over fixed-length passages, flattening document structure and separating scientific claims from their methodological and argumentative context. We present VecTree-RAG, an agentic framework that assigns these tasks to complementary retrieval mechanisms. Vector search ranks compact document and section representations across the corpus, whereas reasoning-guided traversal of source-verified section trees localizes evidence within shortlisted papers. Full text is retained in a page store and exposed progressively only after structural localization. We evaluate VecTree-RAG on 300 QASPER questions, an open-access subset of 54 LitQA2 questions, and 49 multi-document MOSAIC questions. Compared with Dense RAG, reranked Dense RAG, RAPTOR, and Search-o1, VecTree-RAG obtained the highest observed answer score on all three benchmarks, reaching 0.800 LLM-judge correctness on QASPER, 0.925 accuracy on LitQA2, and a 0.547 composite score on MOSAIC. On QASPER, its evidence-page precision was 0.274, compared with 0.046–0.071 for the baselines. LitQA2 ablations further showed that the complete vector–tree architecture required fewer inference tokens than variants without tree navigation or corpus-level vector routing. These results indicate that vector retrieval narrows the corpus-level search space and tree navigation concentrates reading on structurally relevant evidence. Although multi-turn inference remains more expensive than single-call retrieval, VecTree-RAG provides a structure-aware and traceable architecture for scientific literature question answering.
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All authors Xinyan Zhong, Yuwei Shi, Yuqi Wei, Chen Shen, Tianhang Zhou, Zhenghao Wu

Materials Science

Uncertainty-quantified $J$-integral computation for quasicontinuum and finite element methods

Sai Harshith Badi, Stephen M. Whalen, Ronald E. Miller et al. (+1 more)

The $J$-integral is a fundamental concept in fracture mechanics, quantifying the energy release rate that drives crack propagation. While extensively implemented in finite element (FE) codes and adapted for atomistic calculations, its application within multiscale frameworks bridging atomistic and continuum formulations remains unexplored. This work presents a rigorous implementation and validation of the $J$-integral within the three-dimensional quasicontinuum (QC3D) method, computed under plane strain assumptions, using continuum fields (stress, strain energy density) derived from the interatomic potential via the Cauchy-Born rule. The implementation is validated against linear elastic fracture mechanics (LEFM) theory and the virtual crack extension (VCE) method across three regimes: (1) small-strain linear elasticity, with a prescribed anisotropic $K$-field displacement applied throughout; (2) the same field evaluated through the nonlinear Cauchy-Born constitutive relation, without atomic relaxation; and (3) the same relation with atomic relaxation enabled, allowing the crack-tip region to equilibrate. Excellent agreement is shown throughout. We further introduce a Markov chain Monte Carlo framework to statistically quantify the uncertainty of $J$-integral results for a given mesh and integration domain, applicable to conventional FE methods as well. Predictive capability is demonstrated via a QC3D simulation of a three-point bending test of silicon, where the computed critical energy release rate agrees closely with the Griffith criterion. This work establishes a reliable framework for evaluating crack driving forces in multiscale fracture simulations with quantified uncertainty, enabling large-scale fracture simulations while resolving atomistic mechanisms at the crack tip.
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All authors Sai Harshith Badi, Stephen M. Whalen, Ronald E. Miller, Ellad B. Tadmor

Materials Science

Role of $p$-$d$ Hybridization on Optical Properties of Chalcopyrite Semiconductors

Neunghee Han, Harang Kim, Minjae Kim et al. (+1 more)

Designing quantum materials for coherent optical properties is a central agenda in quantum technology. Semiconductor quantum dots are an emerging approach for controlling coherent optical properties via confinement effects, tunable band gaps, and exciton binding energies, yet their inherent structural and compositional inhomogeneity degrades the coherence of the optical spectra, posing a major obstacle. We show that, for chalcopyrite semiconductors, hybridization between transition-metal $d$ and ligand $p$ electrons in the valence band is key to the coherence of the quantum dot optical spectrum. We demonstrate this using first-principles electronic-structure calculations and optical spectroscopy. The strong $p$-$d$ hybridization in CuInS$_{2}$ induces the Cu($d$) Coulomb scattering channel, giving rise to the incoherent photodoped hole carrier, while the weak $p$-$d$ hybridization in AgInS$_{2}$ induces the delocalized photodoped hole carrier having a predominant S($p$) orbital character. Our experimental results on optical spectra suggest that when the Cu ratio is enhanced in the Ag$_{1-x}$Cu$_{x}$In$_{1-y}$Ga$_{y}$S$_{2}$ quantum dot, Cu atoms at both Ag sites and defect sites experience enhanced $p$-$d$ hybridization, and a coupling begins to develop between the electrons in the quantum dot and the defect electrons at a small Cu ratio. This coupling activates Cu($d$) Coulomb scattering for photodoped holes traversing the defect sites, producing an incoherent optical response that naturally explains the long-standing absence of band-edge spectral signatures in CuIn$_{1-y}$Ga$_y$S$_2$ quantum dots. These results serve as a guideline for designing semiconductor quantum dots. To achieve a coherent optical spectrum, avoid $p$-$d$-hybridized orbital character in the photo-doped carrier.
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All authors Neunghee Han, Harang Kim, Minjae Kim, Woonhyuk Baek

Materials Science

AEcroscopyWave: Towards Self-Driving Characterization Platforms for Agentic AI

Yongtao Liu, Jawad Chowdhury, Ganesh Narasimha et al. (+8 more)

The characterization of electronic materials has traditionally been stratified into two distinct regimens: industry-scale automated systems to inspect materials for defects and ensure quality (such as in the semiconductor industry), and highly customized, operator-driven systems requiring human experts. The former offers high throughput but limited flexibility, whereas the latter is heavily bandwidth-limited but provides research-grade discovery capabilities. Recent advances in "self-driving" characterization tools offer the potential to bridge the two stratified regimes, by the creation of application program interfaces (APIs) that can control hardware, and the integration of AI methods to incorporate autonomy into the process. Here, we discuss our latest developments in AEcroscopyWave, a custom-built characterization platform for the agentic-AI era, that provides unified control of scanning probe microscopes with programmable peripheral instrumentation, highlighting the design choices that are necessary for maximizing the capability of the system and the ease of use for both human and AI agents. The benefits of making heterogeneous scientific instruments accessible, composable and usable by agents is demonstrated by test cases.
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All authors Yongtao Liu, Jawad Chowdhury, Ganesh Narasimha, Ralph Bulanadi, Liam Collins, Ruben Millan Solsona, Marti Checa, Asraful Haque, Sumner B. Harris, Stephen Jesse, Rama Vasudevan

Friday 24 July

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

CP2K: An electronic structure and molecular dynamics software package - Dynamics, Transport, and Spectroscopic Response

Jan Wilhelm, Anna-Sophia Hehn, Hossam Elgabarty et al. (+39 more)

One of the distinguishing aspects of CP2K is its seamless integration of diverse structural and transition-state optimization techniques with advanced sampling approaches including Monte Carlo, molecular dynamics, and metadynamics, enabling the efficient exploration of complex potential- and free-energy landscapes, including rare events. These capabilities are combined with a broad hierarchy of energy and force evaluation methods, ranging from classical and machine-learned interaction potentials and mixed quantum-classical multiscale and semiempirical schemes, to highly accurate quantum-mechanical electronic-structure approaches. At the heart of the latter lies the Gaussian and plane-wave framework, along with its augmented all-electron generalization, which have been described in detail in our previous code review [T. D. Kühne et al., J. Chem. Phys. 152, 194103 (2020)]. Building on this foundation, the present work revisits the methods within CP2K that turn electronic structure into dynamics, transport, and spectroscopic response. Particular emphasis is placed on the coupling between static response calculations and nuclear motion: spectra may be evaluated at optimized structures, averaged over thermally sampled configurations, obtained from time-correlation functions along ab-initio or path integral molecular trajectories, or followed in real time together with electronic and nuclear dynamics. The same modular structure also enables equilibrium and biased transport simulations, from Kubo-type linear response to open-boundary approaches under external potentials, highlighting CP2K's unique capability to unify quantum chemistry with quantum and statistical mechanics within a versatile, holistic simulation environment.
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All authors Jan Wilhelm, Anna-Sophia Hehn, Hossam Elgabarty, Beliz Sertcan Gökmen, Maximilian Graml, Stepan Marek, Ritaj Tyagi, Frederick Stein, Johann V. Potoschnig, Augustin Bussy, Christian S. Ahart, Zehua Chen, Linnea Andersson, Zdenek Futera, Filip Ivanovic, Margherita Buraschi, Christoph Schran, Remi Pasquier, Leonard Prokisch, Bibek Samal, Jelena Schmitz, Shridhar Sanjay Shanbhag, Harald Forbert, Ole Schütt, Franz Pöschl, Sebastian Ehlert, Stefano Battaglia, Michele Nottoli, Benjamin Stamm, Vamsee Voora, Rustam Z. Khaliullin, Sergey K. Chulkov, Matt B. Watkins, Clotilde S. Cucinotta, Jochen Blumberger, Chao Zhang, Yang Yang, Dominik Marx, Matthias Krack, Jürg Hutter, Marcella Iannuzzi, Thomas D. Kühne

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

New class of exactly flat topological bands - compact localised states protected by local graph topology

Tamaghna Hazra

Strongly correlated quantum matter is fundamentally defined by the tension between non-commuting quantum operators. Hamiltonians exhibiting macroscopic degeneracies are of general interest in this field because they imply an infinite susceptibility to any non-commuting perturbation. In moiré heterostructures, engineering such extensive degeneracies in the kinetic Hamiltonian creates a fertile garden for exotic strongly correlated phases of matter to emerge from the resulting flat bands. Here, we introduce a prescription to construct an infinite family of exact flat band Hamiltonians supported on the faces of arbitrary graphs. We demonstrate this algorithm on the faces of four Bravais lattices. Using a discrete graph generalization of the Atiyah-Singer index theorem, we prove that the extensive degeneracies of such face-graph Hamiltonians are protected by the local topology of the face-graph connectivity. The resulting macroscopic null spaces yield compact localised states that remain localised over time due to frustration in hopping pathways. We discuss the broad implications of such non-dispersing quantum modes in diverse settings, from arrested dynamics in quantum networks and quantum machine learning algorithms to Majorana-free topological quantum computation.
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Materials Science · Cross-listed from cond-mat.mes-hall

Supermoiré-trapped quadrupolar exciton

Anish Kumar, Suman Chatterjee, Kenji Watanabe et al. (+2 more)

Moiré-trapped dipolar interlayer exciton in heterobilayers offers a rich platform to explore interaction-driven phenomena. Extending the number of layers to three and beyond leads to highly intriguing multipolar exciton - a superposition state of vertically aligned phase-coherent excitons. However, in experiments, unintentional twist-angle mismatch among layers may degrade the strength and homogeneity of the vertical Coulomb coupling. Here we propose that the supermoiré effect in a heterotrilayer comes to the rescue by creating periodic pockets of vertically aligned atomic registries that facilitate the formation of quadrupolar excitons trapped in such pockets. Using WS$_2$/WSe$_2$/WS$_2$ stack, we show interaction between multiple confined levels of the top and bottom moiré interfaces, creating electric field tunable multi-level hybridized bright (symmetric) and dark (anti-symmetric) quadrupolar states. Our work underscores the critical role of supermoiré effect in quadrupolar excitons. The discovery of reduced sensitivity on precise angle-alignment will ignite exploration of complex excitonic states in multi-layered heterostructures.
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All authors Anish Kumar, Suman Chatterjee, Kenji Watanabe, Takashi Taniguchi, Kausik Majumdar

Materials Science

Machine Learning Inference Limits of Routine Cement Characterization for CEM I Performance: Evidence From a Multi-Producer Dataset

Marchellino Ghorayeb, Christiane Rößler, Horst-Michael Ludwig et al. (+2 more)

Routine cement performance characterization provides continuous quality control data, but its information content for performance inference and transferability across independent producers remains uncertain. This study analyzes 476 cement records from 23 European producers, collected in one laboratory over 27 years, to determine what can be inferred from routine measurements. The analysis focuses on CEM I and combines oxide chemistry, Blaine fineness, particle-size distribution descriptors, physical properties, and derived Bogue and equivalent-alkali descriptors with machine learning attribution and producer-transfer tests. For CEM I, fineness is the strongest descriptor family for strength class and water demand, but oxide chemistry contributes a comparable signal when evaluated jointly. Blaine and compact particle-size distribution representations are largely interchangeable within the descriptor space, indicating that the dominant recoverable fineness information is captured by routine measurements. Equivalent alkali shows a consistent negative association with 28-day strength, through K$_2$O in this dataset. Strength class and water demand can be recovered from routine cement characterization data. The early-strength designation is recovered only as a population-level tendency, not a physically separable class, because early-strength development can arise from combinations of fineness, sulfate–alkali chemistry, phase assemblage, and plant practice. Producer-holdout tests show that absolute prediction errors remain comparable across the held-out producers in this dataset, whereas recovery of within-producer strength variation is producer-dependent. Routine CEM I characterization therefore supports useful performance inference across producers, while exposing producer-specific variation whose recovery may require additional speciation.
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All authors Marchellino Ghorayeb, Christiane Rößler, Horst-Michael Ludwig, Leon Herrmann, Stefan Kollmannsberger

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

Quasiparticle interference as a tool to study quantum materials

Luke C. Rhodes, Yuhki Kohsaka, Tetsuo Hanaguri et al. (+2 more)

To understand the properties of quantum materials a detailed knowledge of the material's low energy electronic structure is key. Details of the electronic structure drive the ground state through electronic instabilities, electronic correlation effects, new electronic orders or just the absence of electronic states near the Fermi energy - making a realistic and detailed understanding crucial to be able to control and design properties of quantum materials. The past 25 years have seen a significant improvement in experimental techniques to observe the true electronic structure, in particular in techniques such as Angle resolved photoemission spectroscopy (ARPES) where energy resolutions of 2meV are routinely achievable now, which however is limited to zero magnetic field and only provides information about the occupied states. Scanning tunneling microscopy (STM) achieves a significantly better energy resolution <100${\mu}$eV and can operate at temperatures well below 50mK and in magnetic fields. While per se a real-space technique, by imaging quasiparticle interference (QPI) STM can also provide information about the electronic structure. This technique has been used over the past decades to study a wide range of quantum materials to understand correlated electron behaviour. Recent theoretical progress now enables routine modelling of QPI, a key requirement to interpret the complex data. Here, we review the principles of QPI, its origin, experimental detection, and the physical insight gained from the study of QPI and possible future directions for this technique.
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All authors Luke C. Rhodes, Yuhki Kohsaka, Tetsuo Hanaguri, Carolina de Almeida Marques, Peter Wahl

Materials Science

Reversible photo-switching optical functionality in two-dimensional mixed-halide hybrid perovskites

Enamul Haque, Wenxin Mao and Javier Cerrillo

Ion migration in halide perovskites is often associated with defects, irreversible processes, and structural instability, making them largely impractical for photo-switching applications. Here, we demonstrate a physical mechanism for reversible, defect-free light-induced halide-ion swapping in two-dimensional mixed-halide perovskites. We find that the halide-ion swapping process arises from strong light-lattice coupling rather than defects. By combining nudged elastic band and photo-force calculations, we show that photo-induced forces perform non-equilibrium work that drives halide ions along the halide-exchange path without reaching the fully swapped configuration. Thus, the cumulative light-induced work can only partially overcome the ground-state activation energy barrier in the presence of light. Analysis of lattice dynamics identifies a few soft phonon modes, two of which are IR-active with oscillator strength $\approx -0.14$ e/(amu)$^{1/2}$, which may be considered the microscopic origin of light-induced halide-ion swapping. This microscopic origin is further supported by band-edge-selective electron-phonon coupling, which amplifies interactions among excited carriers under illumination and with halide-ion motion without inducing a uniform dynamical instability. Using GW (G-Green's function and W-screened Coulomb interaction) calculations, we accurately reproduce the experimentally observed optical absorption spectra in the absence of light, enabling us to describe the light-induced excited state reliably. We demonstrate a clear redshift in the optical spectra in the presence of light, which is due to light-induced bandgap renormalization. Overall, these findings not only establish an intrinsic, defect-free mechanism for photoswitchable optical functionality in 2D mixed-halide perovskites but also demonstrate an intrinsic self-resetting feature in the absence of light.
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Materials Science

Mechanisms of Microstructural Evolution and Degradation in Aluminum under High-Damage Irradiation

Alhassan S. Issaka, Sadie Wicks, Vishal Yadav et al. (+3 more)

Aluminum alloys are widely used in research reactor systems, yet the mechanisms governing irradiation-induced degradation remain poorly understood. Here we combine conventional cascade-overlap molecular dynamics simulations with an accelerated Iterative Kinetic Approach (IKA) to investigate defect evolution in single-crystal Al subjected to 50 keV He irradiation. Benchmarking shows that IKA reproduces the essential defect kinetics of cascade simulations while enabling access to substantially higher accumulated damage. By extending the IKA to higher damage levels, we identified three distinct regimes governing radiation-induced degradation in Al: recombination-driven annihilation, defect accumulation, and sink-controlled absorption. At higher damage, Frank loops dissociate into Shockley partials and stair-rod loops, ultimately driving the nucleation and growth of stacking-fault tetrahedra (SFTs). These transformations progressively convert mobile defects into SFTs. Ultimately, the synergistic effect of interstitial and vacancy loops and SFTs increases irradiation hardening in Al at 300 K. This work provides insight into irradiation-induced degradation in aluminum reactor materials.
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All authors Alhassan S. Issaka, Sadie Wicks, Vishal Yadav, Assel Aitkaliyeva, Michael R. Tonks, Simon R. Phillpot

Materials Science

Magnetic proximity-induced non-relativistic valley polarization

Weifeng Xie, Yongqi Chen, Yiboyang Sun et al. (+3 more)

The magnetic proximity effect in van der Waals (vdW) heterostructures exerts a significant impact on the electronic and magnetic properties of adjacent materials. Here, we propose vdW heterostructures composed of monolayers ferromagnets (FM) and altermagnets (AM), in which the magnetic proximity effect from the FM induces pronounced non-relativistic valley polarization in the AM. Furthermore, by flipping the magnetization of the FM and the direction of Néel vector of the AM, four independent valley-polarized states can be realized in the FM/AM vdW heterostructures, exhibiting strong magneto-valley coupling. The phenomenon is qualitatively elucidated by a tight-binding model and demonstrated to be generalizable. These findings suggest that FM/AM vdW heterostructures hold potential application in the field of valleytronics-based information storage.
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All authors Weifeng Xie, Yongqi Chen, Yiboyang Sun, Xiong Xu, Yunliang Yue, Hui Wang

Materials Science

Charge-Density-Wave Phase Transitions in Monolayer 1T-TaS2 from Universal Machine Learning Molecular Dynamics

Valentina Nesterova, Tribhuwan Pandey, Tom Berlijn et al. (+3 more)

Charge-density-wave (CDW) phases in 1T transition-metal dichalcogenides arise from strong electron-phonon coupling and accompanying lattice instabilities. Capturing their temperature-dependent structural evolution using conventional first-principles molecular dynamics (MD) remains challenging because of the large supercells and extensive finite-temperature sampling required. Here, we combine density functional theory (DFT), universal machine-learning interatomic potentials (MLIPs), MD, and temperature-dependent effective potential phonon calculations to investigate the structural and vibrational signatures of CDW transitions in monolayer 1T-TaS2. Benchmarking against DFT displacement energies identifies UMA-s-1p1 universal machine learning potentials with sufficient accuracy for subsequent finite-temperature simulations. Our results show that large-scale MD simulations reproduce the experimentally observed phase transition sequence from the low-temperature Star-of-David (SoD) distorted structure to the high-temperature primitive hexagonal structure, as quantified by the number of Ta atoms attributed to SoDs. Heating-cooling cycles exhibit thermal hysteresis, and upon cooling, the system freezes into a multi-domain state in which {\alpha} and e̱ta} CDW chiralities nucleate independently and persist to the lowest temperatures. These findings demonstrate that carefully benchmarked universal MLIPs can provide a scalable framework for finite-temperature studies of CDW materials.
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All authors Valentina Nesterova, Tribhuwan Pandey, Tom Berlijn, Fariborz Kargar, Lucas Lindsay, Konstantin Klyukin

Materials Science

Hidden Truchet Architecture in Zinc $p$-Hydroxybenzoate

Hunter J. Windsor, Guy Greenbaum, Tristan N. Dolling et al. (+2 more)

We redetermine the structure of the disordered metal-organic framework Zn(hba) (hba$^{2-}$ = the dianion of 4-hydroxybenzoic acid). Using single-crystal X-ray diffraction measurements, we characterise the structured diffuse scattering that is experimentally observed for this material and which is characteristic of strongly correlated disorder. We use geometric and crystal chemical arguments to propose a general model for correlated disorder in Zn(hba), and then relate this model to a specific realisation of so-called Truchet tilings. Using Monte Carlo simulations, we proceed to show that the model so developed is simultaneously consistent with both the average crystal structure solution described previously, and the structured diffuse scattering reported here. The existence of ordered analogues with different, but related, chemistry suggests scope for control over correlated disorder in this family of metal-organic frameworks. Our study illustrates the potential for a Truchet-tile formalism to help describe and understand more generally the correlated disorder that occurs in framework materials - even amongst those that are chemically and crystallographically dissimilar.
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All authors Hunter J. Windsor, Guy Greenbaum, Tristan N. Dolling, Yevheniia Kholina, Andrew L. Goodwin

Materials Science

Substrate-metal interface engineering enhances TaN/Ta thin film superconducting resonator performance

Moritz Singer, Harsh Gupta, Benedikt Schoof et al. (+6 more)

Tantalum has been demonstrated as a promising material for superconducting qubits. However, comparatively little attention has been given to its nitrides. Tantalum nitride exhibits a range of stoichiometries, resulting in a variety of material properties, including both superconducting and non-superconducting phases. Owing to this versatility, tantalum nitrides can serve multiple purposes in superconducting qubits: as seed layers for alpha-Ta growth, as a superconducting base material and as a non-superconducting barrier in the Josephson junction. In this study, we explore the performance of superconducting TaN and Ta thin film combinations on silicon substrates in terms of internal quality factor Qi. We find that standalone TaN films exhibit Qi values of about 1.5x10^5 at 100mK in the single-photon regime. Surprisingly, a resonator made from Ta grown on a few-nanometers-thick TaN seed layer yields largely the same performance. However, adding an additional, few-nanometers-thick Ta buffer layer between the Si substrate and this TaN seed layer enhances Qi significantly up to 5.9x10^5. Supporting transmission electron microscopy measurements reveal nitrogen accumulation and structural disorder at the TaN-Si interface, while this interfacial modification is suppressed when the Ta buffer layer is introduced. The observed improvement in resonator performance is consistent with a reduction of interface-related two-level system losses and strongly supports the hypothesis that controlling the substrate-metal interface is pivotal for the performance of superconducting qubit circuitry.
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All authors Moritz Singer, Harsh Gupta, Benedikt Schoof, Elena Willinger, Anton Orekhov, Alexandra Schewski, Samuil Kostadinov, Philip Constantin Schneider, Marc Tornow

Materials Science

Unbiased Diffusion Monte Carlo for non local operators

Carlos Rodriguez Perez, Valerio Olevano, Francesco Sottile et al. (+1 more)

We propose a new mathematically exact method for computing unbiased Diffusion Monte Carlo (DMC) estimates of non-local operators. We demonstrate that the current state-of- the-art technique, Forward Walking, is only exact for local quantities and fails to yield unbiased results for the non-local components of reduced density matrices (RDMs). Our method significantly outperforms Forward Walking, as shown in two systems: in the symmetric Hubbard dimer it yields a pure 1RDM; while in the Helium atom it will give an unbiased 1RDM in the limits of zero time step and infinite walkers.
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All authors Carlos Rodriguez Perez, Valerio Olevano, Francesco Sottile, Vitaly Gorelov

Materials Science

SAGE-Net: Semantics-Augmented Geometric Encoder for Material Property Prediction

Guanghui Zhang, Yuxuan Yao, Kieran B. Spooner et al. (+4 more)

Reliable structure-property modeling is crucial for accelerating materials discovery, where crystal graphs and structure-derived crystallographic descriptions provide complementary geometric and semantic information. Existing multimodal materials models primarily incorporate textual information through post-encoding fusion, latent-space alignment, or attention-based representation interaction mechanisms. However, in most cases, crystallographic semantics are introduced after structural encoding and therefore cannot directly guide the formation of atom-level crystal-graph representations. Here, we present Semantics-Augmented Geometric Encoder Network (SAGE-Net), a flexible multimodal framework that injects description-derived chemical and crystallographic semantics into geometric message passing. SAGE-Net introduces Semantic-Guided Message Passing (SGMP), which gates atom-level updates and enables crystallographic semantics to directly modulate local geometric interactions across multiple graph neural network (GNN) backbones. Across benchmarks covering bandgap, mechanical, transport-related properties, and synthesizability assessment, the SAGE-Net instantiated with different GNN backbones achieves the lowest MAE on eight out of ten JARVIS-DFT regression targets and delivers strong or highly competitive performance against both structure-based and multimodal baselines. For synthesizability assessment, the SAGE-Net demonstrate outstanding classification performance and high recall rates. Interpretability analysis unravels that SAGE-Net effectively captures physically interpretable crystallographic features, viz. space group, dimensionality, polyhedral environments, among others. Together, these results demonstrate SGMP-based SAGE-Net as a general and transferable framework for deeply integrated multimodal materials learning.
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All authors Guanghui Zhang, Yuxuan Yao, Kieran B. Spooner, Jun Yin, Dan Han, David O. Scanlon, Lijun Zhang

Materials Science

Composition Anisotropy Drives Large Bulk Photovoltaic Fields Along the Non-polar Vertical Direction in 2D Hybrid Perovskite Ferroelectrics

Yuzhong Hu, Andrii Shcherbakov, Jonathan Zerhoch et al. (+7 more)

The photovoltaic electric field of the bulk photovoltaic effect (BPE) reflects the intrinsic ability of ferroelectrics to separate photoexcited excitons into electrons and holes, and are essential parameters for applications such as voltage-readout photodetectors. Because polarization defines the cation-anion displacement and noncentrosymmetric axis, the polar direction is generally one of the orientations exhibiting strong bulk photovoltaic field (EBPE). Here, we report emergent BPE behavior in 2D hybrid perovskite ferroelectrics (HPFs), where EBPE can be two orders of magnitude higher along the vertical nonpolar direction than along the polar in-plane direction. Its magnitude is up to orders of magnitude higher than that of benchmark photoferroelectrics across different material systems and is the highest among 2D HPFs reported so far. This strong BPE response with emergent directional anisotropy originates from the unique coupling among the shift-current BPE mechanism, an efficient photocarrier-generating inorganic part, and an insulator-like organic part, a combination that is conflicting or inaccessible in traditional photoferroelectrics. This composition and anisotropy also produce basic BPE behavior distinct from that of typical photoferroelectrics, including a laser intensity dependent photovoltage and a nonlinear scaling of photovoltage with material dimension. We analyze and develop a series of formulas to describe the emergent photovoltage phenomena, which should be applicable to this novel 2D ferroelectrics family and to polar systems with similar anisotropy and robust photoelectric response.
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All authors Yuzhong Hu, Andrii Shcherbakov, Jonathan Zerhoch, Lars Schneider, Shangpu Liu, Xitao Liu, Fangping Zhuo, Lovro Fulanovic, Felix Deschler, Martijn Kemerink

Materials Science · Cross-listed from physics.optics

Counterdirectional Exciton and Trion Motion in Applied Electric Field

Daniel Vaz, Yuanjun Guan, Qiaochu Wan et al. (+13 more)

Charged excitonic complexes are central to the optoelectronic and many-body properties of semiconductors, yet their real-space transport dynamics remain largely unexplored. Here, we report the direct optical observation of trion motion under an applied electric field. The trions exhibit electrically driven drift with velocities approaching {$10^5~\mathrm{m/s}$}. Unexpectedly, the trion flow induces a pronounced back-action on coexisting neutral excitons, driving them in the opposite direction and giving rise to counterpropagating exciton-trion transport. Our results reveal an interaction-driven nonequilibrium transport regime of mixed excitonic fluids and establish a direct route for imaging the dynamics of more complex charged quasiparticles, including doubly charged excitons.
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All authors Daniel Vaz, Yuanjun Guan, Qiaochu Wan, Bobby Bobby, Anshul Ramavath, Brandon Vargo, Juntong Ye, Jonathan Beaumariage, Om Patel, Kenji Watanabe, Takashi Taniguchi, Xiong Feng, James Hone, Nathan Youngblood, Zheng Sun, David W. Snoke

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

Universal scaling of electrochemical information transfer at solid-liquid interfaces

Eikichi Kimura, Ashutosh Rathi, Saki Tsuchiya et al. (+6 more)

Electrochemical potentials at solid-liquid interfaces govern diverse chemical and energy conversion processes; however, the extent to which their electrochemical influence extends into the solid remains unclear. Here, we show that the maximum accessible electrochemical information is governed by a single dimensionless screening parameter $u$, defined as the ratio of the effective electrostatic separation between the interface and probe to the electrostatic propagation length in the solid. The maximum Fisher information follows a universal inverse-square scaling with this parameter. This relation identifies electrostatic screening as a fundamental constraint on information transfer across solid-liquid interfaces and provides quantitative design principles for interfacial electrochemical sensing.
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All authors Eikichi Kimura, Ashutosh Rathi, Saki Tsuchiya, El Mustapha Mansouri, Sara Mandić, Kristi Kanya Saikia, Keisuke Oshimi, Masazumi Fujiwara, Keigo Arai

Materials Science

From Amorphous to Amorphous-Crystalline Mixed-Phase Boron Nitride: Evolution of the Thermal and Elastic Properties

Jiaqi Yang, Thomas Souvignet, Onurcan Kaya et al. (+11 more)

Amorphous boron nitride (aBN) is a promising dielectric and protective coating, yet its nanoscale heat dissipation and elastic response remain poorly quantified. Here we synthesize a variety of BN thin films by borazine-based chemical vapor deposition (800-1000 C) and study the temperature-driven structural transition from fully amorphous networks to mixed amorphous-crystalline films with embedded BN nanocrystallites.Frequency-domain thermoreflectance data show an ultralow, thickness-dependent cross-plane thermal conductivity for aBN (kout < 0.5 W m-1 K-1 for 10-40 nm), which increases systematically with crystalline order up to 1.5 W m-1 K-1. Micro-Brillouin light scattering and finite-element modelling reveal a concomitant stiffening, with Young's modulus rising from 7.5 +/- 0.7 GPa (800 C) to 53 +/- 5 GPa (1000 C). Green-Kubo molecular dynamics simulations rationalize these trends via bonding topology and vibrational transport, and highlight how oxygen, hydrogen and carbon impurities and composition provide practical knobs to further tune the thermal and mechanical responses in BN films for improving nano-electronics, interconnects and coating applications.
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All authors Jiaqi Yang, Thomas Souvignet, Onurcan Kaya, Peng Xiao, Emigdio Chavez-Angel, Daniel Capolat Palomar, Zuzanna Ewa Kaczmarska, Bartlomiej Graczykowski, Javier Rodriguez Viejo, Clivia M. Sotomayor Torres, Catherine Marichy, Catherine Journet, Stephan Roche, Marianna Sledzinska