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Physics Condensed Matter Materials Science

cond-mat.mtrl-sci Watch Materials Science

Saturday 15 August

Materials Science

DINO4DSTEM: A self-supervised framework for structural discovery in 4D-STEM

Daniel Khaykelson, Lothar Houben and Boris Rybtchinski

Nanodiffraction using 4D-STEM has become a key technique for quantitative nanoscale structural mapping in materials research, yet interpreting its high-dimensional datasets in structurally complex materials remains a major bottleneck. Existing analysis workflows typically rely on structural models, manual annotation, predefined classes, or sample-specific heuristics, limiting their ability to characterize heterogeneous complex materials. Here, we introduce DINO4DSTEM, a self-supervised machine learning framework that automatically discovers structurally meaningful states directly from raw diffraction data. Without structural models, manual labels, a predefined number of classes, or system-specific parameter tuning, the framework learns representations that organize diffraction patterns by their intrinsic structural similarities, transforming large collections of low-dose measurements into quantitative nanoscale structure maps. Across diverse datasets, DINO4DSTEM consistently identifies the dominant structural degrees of freedom, providing segmentation without human supervision. We applied the framework to the crystallization of indomethacin, a beam-sensitive, multidomain pharmaceutical system, revealing that crystallinity emerges from a partially ordered precursor and spans a continuous spectrum of structural order. The discovered nanoscale structural states are mapped to reveal the evolution of order across the specimen quantitatively. By replacing task-specific analysis with general self-supervised representation learning, DINO4DSTEM provides a broadly applicable framework for quantitative nanoscale structural mapping in complex materials, enabling the discovery of emergent structural organization in heterogeneous, beam-sensitive systems.
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Materials Science

Network Topology of Hafnia-Based Amorphous Optical Coatings by Grazing-Incidence X-ray Total Scattering and Atomic Modeling

K. Prasai, B. LaBell, K. H. Lee et al. (+4 more)

Amorphous hafnia-based films are promising optical-coating materials for cryogenic GW detectors, but their performance depends on how doping and annealing modify the atomic network. We combine grazing-incidence X-ray total scattering measurements with experimentally constrained atomic modeling to study the as-deposited HfO$_2$ and 27% SiO$_2$-doped HfO$_2$ films annealed at 150$^\circ$C and 400$^\circ$C. Pure amorphous HfO$_2$ is a dense, high-coordination network of Hf-centered polyhedra with substantial edge- and face-sharing connectivity. Incorporating SiO$_2$ introduces stable SiO$_4$ tetrahedra, lowers the Hf and O coordination, and replaces highly connected Hf-rich oxygen environments with mixed Si–O–Hf bridges. This produces a chemically mixed network rather than isolated SiO$_2$-rich regions, and shifts the cation topology toward corner-sharing connectivity. Annealing to 400$^\circ$C produces only modest additional structural relaxation. These results provide an atomic-scale description of how SiO$_2$ modifies the topology of amorphous HfO$_2$-based coatings and suggest structural descriptors relevant to understanding their mechanical-loss behavior.
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All authors K. Prasai, B. LaBell, K. H. Lee, A. Mehta, B. Shyam, M. M. Fejer, R. Bassiri

Materials Science

Discovering Physically Interpretable Mathematical Expression for Predicting CO2 Adsorption in Metal-Organic Frameworks via Machine Learning-Symbolic Regression

Yimin Shao, Shengluo Ma, Shenghong Ju et al. (+2 more)

This work presents a machine learning-symbolic regression (ML-SR) strategy to develop a physically interpretable formula for predicting low pressure CO2 adsorption capacity in hypothetical metal-organic frameworks (hMOFs). Four ML models were trained on a small dataset of 1,000 samples, and five key descriptors-largest cavity diameter, pore limiting diameter, void fraction, gravimetric surface area, and number of hydrogen atoms-were identified through SHAP and feature importance analyses. Symbolic regression was then employed to derive a concise adsorption formula, Q=aA, where a represents an adsorption baseline (mmol/g) and A is a dimensionless adsorption number incorporating four structural descriptors. We interpret A as the ratio between an adsorption binding force and a diffusion driving force, revealing how pore topology and surface chemistry jointly influence adsorption. Validation against a comprehensive dataset of 137,652 hMOFs demonstrates that this formula achieves over 70% prediction accuracy for 62,448 structures, confirming strong applicability within defined structural and operational ranges. Unlike conventional black box ML models, the proposed physics-guided expression enables efficient prediction and provides clearer insight into adsorption mechanisms.
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All authors Yimin Shao, Shengluo Ma, Shenghong Ju, Yijun Shi, Wei Li

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

Symmetry-Tunable Skyrmions and Merons in Magnetic Nanodisks via Spatially Engineered Anisotropy

X. D. Wang, J. F. Oliveira da Silva, Z. H. Tao et al. (+3 more)

We demonstrate that spatially engineered magnetic anisotropy can stabilize skyrmion and meron spin textures in magnetic nanodisks even in the absence of Dzyaloshinskii-Moriya interaction (DMI). Using a constrained analytical model and micromagnetic simulations, we show that competing perpendicular and in-plane anisotropies can generate non-collinear topological textures in non-chiral magnetic systems. We further show that DMI and dipolar interactions lift the helicity degeneracy and select preferred chiral configurations; micromagnetic simulations were used to identify physically stable states. These results establish anisotropy-patterned nanodisks as a platform for studying DMI-free topological spin textures and their controllable magnetic response. We also show that arrays of anisotropy-engineered skyrmions can control spin-wave transmission by manipulating their vorticity arrangement, pointing to reconfigurable magnonic elements based on non-chiral topological textures.
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All authors X. D. Wang, J. F. Oliveira da Silva, Z. H. Tao, H. M. Dong, K. Chang, M. V. Milošević

Materials Science

Probing three-dimensional structures of complex colloidal quantum dots at the single-atomic level

Qikai Wu, Meng Pei, Jiancheng Zhang et al. (+6 more)

Colloidal quantum dots (QDs) are promising optoelectronic materials due to their size-tunable properties, yet their three-dimensional (3D) quantum confinement makes electronic states highly sensitive to structural and chemical heterogeneity, which critically impacts their optoelectronic performance. Accurately resolving the 3D atomic structure with sub-angstrom precision is thus essential for rational design. Here, we applied atomic electron tomography (AET) to determine, for the first time, the 3D atomic structure of complex core/shell QDs, resolving over 14,000 atoms per particle. Our reconstructions reveal surface morphology, eccentric cores, and nearly atomically abrupt heterovalent interfaces and identify anisotropic shell growth directed by twin boundaries. Utilizing an AET-derived atomic structure, we performed large-scale quantum mechanical calculations to uncover an orientation-dependent strain accommodation mechanism where the heterogeneous strain is compensated at interfaces and twin boundaries. Furthermore, our results reveal strain-induced localized states near the band edge, which contribute to the key features of the experimental ensemble absorption spectrum. This work sets a new benchmark for atomic-level characterization, establishing a powerful framework for the rational design of next-generation nanomaterials.
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All authors Qikai Wu, Meng Pei, Jiancheng Zhang, Wei Xu, Tianding Xu, Colin Ophus, Zaiping Zeng, Botao Ji, Yao Yang

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

Anharmonicity and Nonadiabaticity in Hydride Superconductors

Shashi B. Mishra, Francesco Belli, Eva Zurek et al. (+1 more)

We study superconductivity in representative hydrides using anharmonic phonons, electron-phonon vertex corrections, and full-bandwidth Eliashberg theory. The high-pressure binary hydrides H3S, YH6, and YH9 must be treated with both anharmonic and nonadiabatic corrections, whereas the ambient-pressure PdH/PdD/PdT series is strongly anharmonic but remains adiabatic, reproducing the inverse isotope effect without sizable vertex contributions. LaBeH8 exhibits weak anharmonicity, while vertex corrections reduce the critical temperature (Tc) by approximately 4 K, leaving the predicted Tc above experiment. To identify when treatments beyond harmonic, adiabatic Migdal-Eliashberg theory are required, we introduce the anharmonic renormalization $A_{\lambda}$ and the vertex ratio $R_{V}$ as material-specific diagnostics.
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All authors Shashi B. Mishra, Francesco Belli, Eva Zurek, Elena R. Margine

Friday 14 August

Materials Science

Paraexciton Excitation in Cu$_2$O under Laguerre–Gaussian Illumination

Nguyen Que Huong and David W. Facemyer

In Cu$_2$O the lowest yellow exciton, the $\Gamma_2^+$ paraexciton, is optically inaccessible in conventional spectroscopy because transitions to this state are forbidden in both electric-dipole and electric-quadrupole approximations. We investigate whether optical fields carrying orbital angular momentum (OAM) can overcome this restriction. A microscopic symmetry analysis identifies the gradient-assisted $l=5$ and direct $l=6$ OAM channels as the leading contributions that couple to the paraexciton, independent of the detailed radial profile of the optical field. Calculations for finite-waist Laguerre–Gaussian beams, however, show that the corresponding matrix elements are strongly suppressed because the optical field varies only weakly over the exciton Bohr radius. Thus, satisfying the OAM selection rule alone is insufficient: efficient excitation requires not only the correct angular symmetry but also optical-field variations on the spatial scale of the exciton. This second condition is achieved by localized OAM fields. Expressing the coupling in terms of the physical intensity-ring radius provides a direct comparison between the optical and excitonic length scales and reveals that the optimal localization is determined primarily by the polynomial degree of the target cubic harmonic. For the degree-six $\Gamma_2^+$ paraexciton the strongest coupling occurs for an intensity-ring radius of approximately $6a_B$–$7a_B$. These results establish that paraexciton excitation is governed jointly by symmetry and spatial localization: cubic symmetry selects the allowed OAM channels, whereas the polynomial degree sets the characteristic radial scale for efficient coupling. This work provides both the symmetry framework and a practical design rule for engineering structured-light excitation of paraexcitons in Cu$_2$O.
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Materials Science

Data-Efficient Construction of Material-Specific Machine-Learning Interatomic Potentials from Ab Initio Molecular Dynamics Trajectories

Jonas Hänseroth and Christian Dreßler

Pretrained machine-learning interatomic potentials, so-called universal or foundation models offer an appealing starting point for atomistic simulations, but their accuracy for material-specific observables often remains limited without additional reference data (fine-tuning). Here, we systematically quantify how much first-principles data are required to convert universal models into ab initio-accurate material-specific potentials, and ask whether fine-tuning is necessarily preferable to training from scratch. We compare five universal MLIP frameworks, MACE-MP-0, SevenNet-0, GRACE-1L-OAM, MatterSim-v1-5M and ORB-v2, across seven chemically diverse systems incorporating rare and reactive events. Fine-tuning on only 10 AIMD-derived configurations is insufficient for the investigated systems; 200 configurations succeed in favorable cases, but the outcome remains strongly system-dependent. By contrast, 2000 AIMD configurations constitute a robust default, yielding low force and energy errors and reproducing the target material-specific observables. Moderately dense sub-sampling of the AIMD trajectory reduces the required trajectory length tenfold with little loss in model quality. Training from scratch on the same datasets is competitive with, and often slightly more accurate than, naive fine-tuning for MACE and SevenNet, whereas GRACE requires more data. The energy profile for a sulfur-vacancy jump in MoS$_2$ reveals that low trajectory-level errors do not guarantee a correct reaction profile, highlighting the need for observable-level validation. Finally, we show that averaging independently trained models improves predictions in scarce-data regimes at no additional first-principles cost. Together, these results provide practical guidelines for converting limited AIMD reference data into reliable material-specific MLIPs for nanosecond-timescale simulations at near-DFT accuracy.
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Materials Science

Higher-order nonadiabaticity governs the temperature dependence of the phonon spectrum

Nina Girotto Erhardt and Samuel Poncé

Nonadiabatic effects determine the frequency and linewidth of coupled phonon modes, shape of Kohn anomalies and have important implications on many material properties. State-of-the-art ab-initio nonadiabatic phonon self-energy relies on an infinite electron lifetime approximation, which cannot capture the temperature dependence of the phonon spectrum, neglects long-wavelength intraband phonon decay, and exhibits exaggerated phonon splitting. In MgB$_2$, we show how the higher-order nonadiabatic phonon corrections mitigate these deficiencies, yielding linewidths in a closer experimental agreement and a dome-like coupling strength temperature dependence.
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Materials Science

Coherent Phonon Blocking in Superlattices

Anil Erol, Xiang Hua, Kirby Myers et al. (+9 more)

At cryogenic temperatures, phonons become one of the dominant energy carriers and thus can strongly influence the performance of electronic and sensing devices. In this work, we present a wave-mechanics based framework that predicts phonon transmission and thermal resistance of arbitrarily thick superlattices while retaining all acoustic branches, mode-conversion pathways, and angles of incidence. By enforcing phase coherence, our model predicts frequency-dependent transmission through arbitrary multi-layered structures.We use a genetic algorithm (NSGA-II) to efficiently select both materials and layer thicknesses. Our success criterion is that constituent layers satisfy the quarter-wavelength condition of the dominant phonon frequencies at a target temperature. This strategy identifies novel bilayer combinations that achieve thermal resistance of up to 3000 times greater than previously reported superlattices. The identified superlattices are poised to advance any technology that relies on coherent acoustic scattering, from ultra-low-temperature thermal insulation in superconducting flip-chip assemblies to phonon-blocking components in micro- and nano-electromechanical systems.
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All authors Anil Erol, Xiang Hua, Kirby Myers, Lawrence Friedman, Alexander Marakov, Melissa G. Loving, Joshua Shipman, Arsha Mamoozadeh, Sarah Millen, Ronald J. Warzoha, Jeremy Clark, Robert M. Young

Materials Science

When do machine-learned exchange-correlation improvements inherit into density-functional tight binding?

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

Machine-learned exchange-correlation functionals correct band gaps at near-semilocal cost, while density-functional tight binding reaches the $10^3$-$10^6$-atom regime; combining them assumes that a better parent yields a better parameterization, but we show it does not. Current-generation functionals are orbital-dependent generalized Kohn-Sham operators, whereas the parameterization channel is built on a multiplicative potential, preventing exact representation. Using the transfer ratio, the surviving fraction of a parent-level change, we find anti-transfer: coherently negative ratios across four covalent semiconductors move the gap in the wrong direction, consistent with a molecular proxy and an r$^2$SCAN control. The minimal-basis overgap is dominated by the on-site convention rather than basis incompleteness; correcting the on-site block removes most of it, while one $d$-polarization shell closes a further $16$-$40%$, depending on the placement of the empty $d$ level, which no free-atom eigenvalue uniquely fixes. Occupied-manifold enhancements, ionic and closed-shell repulsive potentials, and rocksalt-oxide gaps inherit, whereas elemental and III-V covalent networks inherit neither gaps nor repulsive potentials and oxide networks inherit only the latter. We screen 23 elements and release the parameter sets, showing that the transfer ratio provides a cheap pre-test before any parameterization campaign.
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All authors Can Polat, Mustafa Kurban, Erchin Serpedin, Hasan Kurban

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

Physics-Informed Symbolic Regression for Predicting the Glass Transition Temperature of Alkali Borate Glasses

Leonardo dos Santos Vitoria, Marcio Luis Ferreira Nascimento, Susana de Souza Lalic et al. (+1 more)

The glass transition temperature ($T_{g}$) of alkali borate glasses is strongly composition-dependent and difficult to predict from first principles due to the structural complexity of the boron network. Here, we apply physics-informed symbolic regression (combining evolutive search with physically meaningful descriptors) to derive an interpretable closed-form expression for $T_{g}$ in the $x\mathrm{M}_2\mathrm{O}\cdot(100-x)\mathrm{B}_2\mathrm{O}_3$ glass family, with M = Li, Na, and K and $x$ expressed in mol%, and subsequently extrapolate it to M = Rb and Cs. The resulting model achieves a root-mean-square error of 14-16 K while maintaining clear physical interpretability, explicitly capturing the interplay among $T_{g}$, structural dissociation energy, and network packing. Critically, models built on the Rigid Unit Packing Fraction (RUPF) yield substantially more realistic $T_{g}$ predictions than those using the conventional Atomic Packing Fraction (APF), as APF overestimates structural rigidity at intermediate compositions. The fitted dissociation energies are further validated against the revised Makishima-Mackenzie model, confirming that the inferred parameters are physically consistent, not merely statistically effective, within the alkali borate family. Finally, Monte Carlo uncertainty quantification reveals that prediction uncertainty is highest in the compositional regions associated with the boron anomaly, directly linking model limitations to a known structural transition in these glasses. This result highlights the potential of physics-informed symbolic regression as a transparent and interpretable alternative to black-box models for property prediction in glass systems.
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All authors Leonardo dos Santos Vitoria, Marcio Luis Ferreira Nascimento, Susana de Souza Lalic, Daniel Roberto Cassar

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

GPU implementation of mixed quantum-classical Liouville molecular dynamics without momentum jump

Koji Ando

We implemented on GPU a mixed quantum-classical Liouville molecular dynamics simulation based on a momentum-jump-free theory. The trajectory spawning that was previously implemented on CPU for sampling enhancement was eliminated to avoid the overhead of thread divergence and dynamic memory allocation on the GPU. This achieved a speedup of an order of magnitude compared to the CPU computation with spawning, as well as a linear scaling with respect to the number of sampling trajectories.
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Materials Science

Universal Thermodynamic Interatomic Potentials for Crystalline Materials

Juno Nam, Bowen Deng, Xiaochen Du et al. (+3 more)

Free energies govern solid-state phase stability, yet computational materials discovery still relies largely on ground-state energies because free energy calculations require ensemble averages. We introduce the thermodynamic interatomic potential (TIP), which extends an interatomic potential from its static energy to a thermodynamically consistent Gibbs free energy model, with thermodynamic responses following from temperature and pressure by automatic differentiation. We implement TIP[UMA] using the universal potential UMA, train it on free energies from quasi-harmonic to molecular dynamics fidelity, and calibrate it to higher-resolution calculations or experiment. From a single evaluation, it returns the equation of state of a crystal and locates phase transitions among competing branches, including dynamically stabilized phases. Fine-tuning extends the model to alloy solubility limits and miscibility gaps. TIP makes the free energy as accessible as the potential energy, opening finite-temperature phase stability to high-throughput discovery.
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All authors Juno Nam, Bowen Deng, Xiaochen Du, Luis Barroso-Luque, Benjamin Kurt Miller, Rafael Gómez-Bombarelli

Materials Science

Unraveling the Roles of Shallow, Deep and Auger Trapping in Charge Carrier Recombination in Triple-Cation Perovskites

Jitendra Kumar, Thomas Kirchartz, Alexandr Marunchenko et al. (+7 more)

Understanding charge-carrier recombination in metal halide perovskites is essential for accurately identifying the factors limiting solar cell efficiency, yet it remains challenging due to the interplay of multiple competing processes. Here, we combine time-resolved photoluminescence and excitation dependent photoluminescence quantum yield measurements over a wide range of fluences and repetition rates to investigate recombination dynamics in triple-cation perovskite thin films. By jointly analyzing these multidimensional datasets, we develop a unified model that quantitatively reproduces both photoluminescence decays and absolute quantum yields across all excitation conditions. Our results reveal the coexistence of deep and shallow traps, as well as a second-order nonradiative recombination pathway attributed to Auger-assisted trapping. Importantly, this mechanism dominates under one-sun illumination, making it a critical limiting factor for photovoltaic performance. These findings provide a comprehensive framework for understanding recombination in perovskites and highlight the importance of higher-order defect-mediated processes in determining their efficiency.
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All authors Jitendra Kumar, Thomas Kirchartz, Alexandr Marunchenko, Alexander Kiligaridis, Shraddha M. Rao, Shivam Singh, Ankur Yadav, Monojit Bag, Yana Vaynzof, Ivan G. Scheblykin

Materials Science

Orbital Hall Effect in Weyl Semimetals from quantum geometric band interference

Chiara Pacella, Maximilian Ünzelmann, Ahmed Osman et al. (+4 more)

Orbital angular momentum (OAM) transport in solids, prominently manifested in the orbital Hall effect, has emerged as a fundamental phenomenon that can decisively exceed its spin-based counterparts. However, the microscopic mechanisms governing OAM dynamics remain only partially understood. In particular, the role of band geometry in orbital transport is still largely unresolved. Here we address this question in the TaAs family of Weyl semimetals, TaAs, TaP, NbAs, and NbP, whose well-established topology and associated OAM textures make them an ideal platform in this context. Using ab initio density functional theory, complemented by a minimal Weyl model based on adiabatic perturbation theory, we establish — both numerically and analytically — a direct link between OAM transport, band geometry, and topological electronic structure.
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All authors Chiara Pacella, Maximilian Ünzelmann, Ahmed Osman, Tim Figgemeier, Friedrich Reinert, Angel Rubio, Domenico Di Sante

Materials Science

Pressure-driven structural phase transition unlocks multifunctionality in KMgX (X = P, As, Sb, and Bi) compounds: A first-principles study

Chetna Saini, Neha Sadanandan, Tashi Nautiyal et al. (+3 more)

The search for materials with multifunctional properties has attracted significant attention due to their potential applications in various energy-related devices. Pressure-induced phase transitions provide an effective strategy for accessing different structural phases of a material without altering its chemical composition, thereby enabling the tuning of its physical properties and expanding its functional applications. In this work, we investigate the previously unexplored orthorhombic (Pnma) phase of the KMgX (X = P, As, Sb, and Bi) family using first-principles calculations and identify a pressure-induced structural transition from a tetragonal to orthorhombic phase. Stability of the pressure-accessible orthorhombic structure is rigorously confirmed by equation of state analysis together with phonon, elastic, and formation-enthalpy calculations, establishing its viability for further investigation. Optical properties calculated within the $G_0W_0$-Bethe-Salpeter equation (BSE) framework, incorporating quasiparticle corrections and excitonic effects, exhibit direct dipole-allowed transitions at the $\Gamma$ point and strong visible-light absorption with coefficients approaching $10^5~\text{cm}^{-1}$. Consequently, KMgAs and KMgSb achieve spectroscopic limited maximum efficiencies (SLME) of $27.12\%$ and $26.40\%$, respectively, at a thin-film thickness of $0.6~\mu\text{m}$. Furthermore, thermoelectric transport calculations predict (zT) values of 0.65 and 0.58 at $900~\text{K}$ for p-type and n-type KMgSb, respectively, demonstrating its potential for both legs of thermoelectric devices. These values are likely conservative, as the Slack model tends to overestimate thermal conductivity. Overall, the pressure-accessible orthorhombic phase of the KMgX family emerges as a stable multifunctional semiconductor with coupled photovoltaic and thermoelectric energy-conversion capabilities.
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All authors Chetna Saini, Neha Sadanandan, Tashi Nautiyal, Hongbin Zhang, Vikrant Chaudhary, Hem C. Kandpal

Materials Science

Efficient simulation of second-order phase transitions in quantum anharmonic materials

Andrea Baldanza and Lorenzo Monacelli

When a crystal undergoes a second-order structural phase transition, such as in ferroelectrics, Peierls, and charge-density waves, the diverging fluctuations of the order parameter lead to the break- down of the standard phonon quasiparticle picture. Simulating these highly anharmonic regimes is notoriously challenging, as methods such as molecular dynamics suffer from a critical slowdown near the transition point, while the harmonic approximation fails dramatically at saddle points of the energy landscape stabilized by quantum or thermal ionic fluctuations. This work introduces a new approach, based on the variational free-energy principle, to predict critical long-range behavior and dynamical spectra in strongly anharmonic systems, even when quantum ionic fluctuations dominate. The proposed framework builds upon the stochastic self- consistent harmonic approximation but reduces its computational scaling with the number of atoms, N, from O(N^6) to O(N^2) and the memory requirement from O(N^4) to O(N). We benchmark the method on the prototypical lead-free metal-halide perovskite CsSnI3, a promising candidate for photovoltaic engineering, simulating its phase stability and Raman spectrum near the phase transition, where the breakdown of the quasiparticle picture becomes evident. We demonstrate the effectiveness of the method by computing the full free-energy Hessian and the critical temperature in a supercell with 1080 atoms. Such simulations would have required tens of thousands of years with the legacy approach; it is now feasible in a few hours on consumer hardware.
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Materials Science

Dispersive-phonon-driven room-temperature Ni1+-Ni2+ polaron hopping in spin-charge coupled rutile niobate

Gourab Roy, Mohit Kumar, Sayan Ghosh et al. (+4 more)

Understanding how lattice dynamics mediate polaron hopping is essential for designing multifunctional correlated oxides. Here, we demonstrate room-temperature dispersive phonon excitations and elucidate the Ni1+-Ni2+ polaron-hopping mechanism and the presence of rare spin-charge-phonon coupling even in a magnetically short-range-ordered state in rutile niobate, a rare room-temperature magnetodielectric system. We reveal room-temperature dispersive phonon excitations using inelastic neutron scattering (INS), complemented by machine-learning-based phonon calculations, to establish the microscopic origin of the polaron-hopping mechanism. Experimental evidence of dispersive phonon-driven polaron hopping is scarce. INS measurements show significant dispersive phonon excitations at 21, 33, and 47 meV, implying collective lattice dynamics that enable delocalized polaron propagation via coupled charge-spin-phonon interactions. Dispersive phonons couple to charge carriers and promote correlated NiO6 lattice distortions, facilitating delocalized polaron hopping. Low-energy magnetic excitations at 4 and 8 meV indicate the presence of local short-range magnetic correlations or spin-orbit-coupling-induced anisotropy in deformed NiO6 octahedra, which are thoroughly discussed. Machine-learning phonon calculations replicate the experimentally observed phonon excitations and demonstrate lattice instability, which is compatible with dynamic local distortions caused by polaron production. These findings provide microscopic evidence for a coupled charge-spin-phonon mechanism that mediates polaron hopping in rutile oxide systems.
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All authors Gourab Roy, Mohit Kumar, Sayan Ghosh, Ekta Kushwaha, Manh Duc Le, Devashibhai T. Adroja, Tathamay Basu

Materials Science

Microscopic investigation of spin dynamics in the single-chain magnet Sr4Mn2CoO9

G. Roy, S. Ghosh, M. Kumar et al. (+8 more)

One-dimensional single-chain magnets offer a unique platform for studying the interplay of crystal-field effects, exchange interactions, and lattice dynamics. Here, we investigate spin excitations in Sr4Mn2CoO9 using inelastic neutron scattering (INS) and theoretical modelling. INS reveals two low-energy magnetic excitations at 4 and 7 meV from Mn-Co-Mn spin chains, alongside higher-energy crystal-electric-field (CEF) excitations from two crystallographically inequivalent Co2+ sites. Interestingly, these spin excitations persist at room temperature, demonstrating dynamic magnetic correlations in the absence of long-range order. Furthermore, the crystal-field modelling, based on Stevens operator formalism, reproduces well the CEF spectra, establishing Ising-like Kramers ground-state doublets with strong uniaxial magnetic anisotropy for both Co2+ ions. In addition, the spin wave simulation using SpinW reproduces the spin excitation spectrum and reveals microscopic exchange interactions in two non-interacting Mn-Co-Mn spin chains. Finally, machine-learning lattice-dynamics calculations confirm the phonon spectrum and spin-phonon coupling. By projecting the exchange Hamiltonian onto CEF ground-state doublets, we estimate exchange-induced splittings matching the observed excitations. Thus, our results elucidate low-energy spin dynamics arising from combined crystal-field anisotropy and exchange interactions, with the persistent low-energy excitation providing a microscopic pathway for thermally activated spin relaxation. Furthermore, this work delivers a unified microscopic understanding of the interplay between crystal-field effects, magnetic exchange, and lattice dynamics in Sr4Mn2CoO9, advancing insights into spin dynamics in low-dimensional transition-metal oxides.
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All authors G. Roy, S. Ghosh, M. Kumar, E. Kushwaha, J. Sannigrahi, V. Caignaert, W. Prellier, D. T. Adroja, D. Voneshen, V. Hardy, T. Basu

Materials Science

Probing intrinsic magnetic phases in low-dimensional nearly twin-free NiPS$_3$ single crystals

Yeochan An, Heejun Yang, Sung Jin Park et al. (+6 more)

We report the intrinsic thermal and magnetic properties of the low-dimensional van der Waals (vdW) antiferromagnet NiPS$_3$ and explore its emergent magnetic phases by controlling crystallographic twinning. Using nearly twin-free crystals, we resolve intrinsic properties that are typically obscured by multidomain effects in bulk samples. Magnetization results reveal a highly anisotropic, sharp spin-flop transition, confirming the high domain purity of our crystals. Furthermore, high-precision thermodynamic and transport data reveal a broad fluctuation regime around the Néel temperature ($T_{\mathrm{N}}$ = 157.5 K), with a heat capacity anomaly and a concurrent suppression of thermal conductivity. Field-dependent thermal transport shows a small but distinct contribution from spin-lattice coupling, as evidenced by the dip at the spin-flop transition. We develop a theoretical model to explain these properties reported in this paper, with good agreement between experiment and theory. Our work establishes a definitive baseline for bulk properties of NiPS$_3$ and demonstrates the feasibility of resolving intrinsic anisotropies by addressing crystallographic twinning in vdW magnets.
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All authors Yeochan An, Heejun Yang, Sung Jin Park, Giung Park, Woonghee Cho, Pyeongjae Park, Seokhwan Yun, Yoshimitsu Kohama, Je-Geun Park

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

Poly(1,4-anthraquinone) as an Organic Cathode Material: Simulation of Observable Bonding Properties to Li, Na, Mg, and Ca

Laura Femmer, Lukas Köbbing, Juliane Heitkämper et al. (+9 more)

Poly(1,4-anthraquinone) (P14AQ) has emerged as a promising cathode material, offering high capacity and good cycling stability, yet the atomic-scale mechanisms governing metal-ion binding and electrochemical behavior remain poorly understood. To address this, we investigate the binding mechanisms of Li, Na, Mg, and Ca to P14AQ using quantum mechanical methods, particularly DFT and DFTB. A key challenge lies in the material's structural complexity: multiple conformers of P14AQ are energetically similar but kinetically isolated due to significant energy barriers. To account for this, we develop an automated method to generate all unique P14AQ conformers for a periodic polymer chain without rotational duplicates through an orientation labeling scheme. For each conformer, we systematically place a metal atom adjacent to every oxygen site, enabling a complete exploration of binding configurations. We observe two structural motifs: a single metal-oxygen bond and coordination to two opposite oxygen atoms. While Li and Na exhibit continuous energy distributions, Mg and Ca show an energy gap between the two motifs, with a strong preference for the two-oxygen binding configuration. Galvanostatic measurements support these findings by showing lower gravimetric capacities for Ca and Mg than for Li and Na. For Na, the different numbers of metal-oxygen bonds are reflected in the two voltage plateaus observed experimentally. Overall, the combined computational and experimental results explain the higher capacity of monovalent ions in P14AQ: divalent ions cannot bind efficiently to a single oxygen site due to unfavorable energetics, and the conformational distribution of the polymer chain prevents optimal coordination.
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All authors Laura Femmer, Lukas Köbbing, Juliane Heitkämper, Sibylle Riedel, Devran Cay, Florin Adler, Birgit Esser, Alexander J. C. Kuehne, Zhirong Zhao-Karger, Piotr de Silva, Juan Maria García-Lastra, Birger Horstmann

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

Simplified Silicon Nitride Nanomembrane Circuits for van der Waals Integration

Tommaso Confalone, Vasilisa Gerega, Flavia Lo Sardo et al. (+8 more)

Two-dimensional (2D) materials and van der Waals (vdW) heterostructures provide an exceptional platform for engineering quantum devices, yet realizing their potential requires electrical integration without compromising the pristine properties of atomically thin crystals through conventional nanofabrication. Transferable circuitry addresses this challenge by decoupling circuit fabrication from device assembly, enabling electrical contacting without directly processing the active material. Here, we introduce SiN$_x$ nanomembrane (NMB) circuits realized through a simplified top-down strategy that reduces fabrication complexity, processing steps and specialized tools required by our previous bottom-up approach. As a stringent benchmark of material preservation, we electrically integrate a four-unit-cell-thick, optimally doped Bi$_2$Sr$_{2-x}$La$_x$CuO$_{6+\delta}$ (Bi2201) flake and observe a superconducting transition at T$_c^{inf}$~32K, close to the T$_c^{onset}$~34K measured by susceptibility in the parent crystals. The preservation of superconductivity demonstrates electrical integration of fragile layered materials without direct exposure to conventional cleanroom procedures, providing a versatile platform for integrating increasingly complicated vdW heterostructures, moiré materials, and hybrid quantum architectures.
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All authors Tommaso Confalone, Vasilisa Gerega, Flavia Lo Sardo, Shreya Kumbhakar, Davide Massarotti, Francesco Tafuri, Shigeyuki Ishida, Hiroshi Eisaki, Kornelius Nielsch, Golam Haider, Nicola Poccia

Materials Science

Electrostatic Phenomenology Benchmarks for Machine-Learned Interatomic Potentials in Electrochemistry: Beyond the Energy-Force Metric

Barbara Sumić, Ria Vasdev, Sudheesh Kumar Ethirajan et al. (+8 more)

Accurate treatment of long-range interactions in machine learning interatomic potentials (MLIPs) is essential for electrochemical simulations. However, aggregate energy and force errors alone are insufficient to establish an MLIP's physical accuracy since they do not detect qualitative inconsistencies in the model such as the prediction of image-charge attraction, dielectric screening, or charge transfer. We introduce a benchmark suite EPhEct (Electrostatic Phenomena for Electrochemistry) of focused test cases designed to evaluate MLIPs on electrochemically relevant physical phenomena. The tests probe for image-charge attraction at a metal electrode, the splitting between longitudinal and transverse optical phonons as a probe of ionic and electronic screening, the dipole moment of interfacial water, and Fermi-level pinning during ion discharge. These tests establish a qualitative diagnostic routine complementary to aggregate energy-force metrics.
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All authors Barbara Sumić, Ria Vasdev, Sudheesh Kumar Ethirajan, Jing Yang, Clotilde S. Cucinotta, Richard G. Hennig, Karsten Reuter, Stefan Ringe, Mira Todorova, Christoph Freysoldt, Jörg Neugebauer

Materials Science

Accurate and efficient calculation of atomic forces in solids with non-self-consistent hybrid functionals

Damian Contant and Maria Hellgren

Hybrid functionals are routinely employed self-consistently within the generalized Kohn-Sham framework. The evaluation of the nonlocal Fock exchange operator makes hybrid functional calculations computationally expensive, in particular with plane-wave basis sets. Here, we investigate the advantages of non-self-consistent hybrid functional calculations, focusing on the evaluation of atomic forces. The analytical force terms that arise due to non-self-consistency are computed using density functional perturbation theory (DFPT), as implemented within the Quantum ESPRESSO distribution. A non-self-consistent hybrid force calculation thus consists of self-consistent DFPT calculations with a local or semi-local functional and a single evaluation of the Fock exchange operator. The overall computational cost is, thereby, reduced in general, especially for solids that require a dense Brillouin-zone sampling. Moreover, results for structural parameters are barely affected by self-consistency, and vibrational frequencies are typically agreeing within 0.5%, thus making non-self-consistent calculations an interesting alternative.
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Materials Science · Cross-listed from cs.CL

The conditional superiority of fast silicon sampling

Nickolas Hock Yuen Lam, Ji Xuan Voo and Xiangyu Ma

Silicon sampling can produce surprisingly good population estimates at times. Does doing it fast attenuate such fidelity? In this study, we extend and assess ongoing work in silicon sampling by comparing the algorithmic fidelity of "fast" and "slow" modes of silicon sampling among a nationally representative sample of Singaporean survey respondents. We find that silicon sampling with contemporary frontier models remains a method in early development to be used only with great caution. While silicon samples are able to produce moderately faithful estimates of population means, they continue to understate opinion variance and distort the latent contextual space behind human opinions. Conditional on such limitations, we find "fast" modes of silicon sampling to be relatively superior to traditional "slow" modes of silicon sampling. Fast silicon sampling is significantly more efficient in compute resources and run-time while being monotonically superior to slower modes of sampling in algorithmic fidelity.
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Materials Science · Cross-listed from cond-mat.str-el

Observation of in-plane anomalous Nernst effect

Tadashi Yoneda, Shinichi Nishihaya, Markus Kriener et al. (+7 more)

The Nernst effect, which enables the conversion of a heat current into a transverse voltage under magnetic field or spin magnetization, holds significant promise for energy harvesting and thermal management in future electronics. However, the conventional Nernst effect is fundamentally constrained by the orthogonality requirement that the applied field or spontaneous magnetization must be perpendicular to the plane defined by the temperature gradient and the induced voltage. Here we report that symmetry-tailored ultrathin films of a prototypical ferromagnetic oxide exhibit anomalous Nernst effect arising from intrinsic coupling to spontaneous in-plane spin magnetization. Systematic magnetothermoelectric measurements under spherical rotations of the magnetic field reveal that a pronounced Nernst signal, comparable in magnitude to the out-of-plane response, emerges robustly associated with out-of-plane orbital magnetization. Our findings demonstrate that the anomalous Nernst effect is no longer limited by the orthogonality condition, opening new opportunities for more flexible designs of magnetothermoelectric materials and devices.
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All authors Tadashi Yoneda, Shinichi Nishihaya, Markus Kriener, Haruto Kaminakamura, Ming-Chun Jiang, Naohiro Tezuka, Yoshiya Murakami, Ryotaro Arita, Hiroaki Ishizuka, Masaki Uchida

Materials Science · Cross-listed from quant-ph

Circuit Depth Compression via Spectral Gap Amplification in Quantum Phase Estimation

Sk Mujaffar Hossain and Satadeep Bhattacharjee

We show that quantum phase estimation (QPE) circuits can be significantly compressed in depth by preprocessing the input operator with a sigmoid spectral filter before estimation. For systems with small spectral gaps Delta_lambda, standard QPE requires m = ceil(log2(1/Delta_lambda)) precision qubits and depth Theta(2^m). Applying a soft-step transformation f(lambda; tau,w) amplifies the effective gap to Delta_f > Delta_lambda (for w < 1/4), reducing the required precision to m_f = ceil(log2(1/Delta_f)) and compressing circuit depth by 2^(alpha Delta_m), where alpha = 1 for the LMR density-matrix exponentiation framework and alpha is in [0.11,0.42] for controlled-phase-gate circuits. We prove that this compression is exact, bounded above by log2(1/(4w Delta_lambda)) + 1, and impossible for exactly degenerate spectra. We further show that the threshold parameter tau requires only O(w) accuracy, so classical preprocessing such as covariance diagonalisation or CASSCF avoids circularity. A net resource advantage occurs when 4w^2(2^Delta_m - 1) > Delta_lambda log(1/epsilon). Validation on LiH and BeH2 bond-stretch calculations, classical covariance datasets, and synthetic near-degenerate cases demonstrates depth reductions of up to 27x and CX-gate reductions of up to 21x. For LiH, QPE output fidelity improves from 0.66 to 0.98 at a 1% hardware error rate. The method preserves the principal subspace to machine precision, requires no modification of QPE, and can be combined with readout-stage and state-preparation filtering. Negative-control tests establish the benefit condition: m_raw >= 2 and Delta_lambda > 0.
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Materials Science · Cross-listed from cond-mat.str-el

Posterior Inference of Hamiltonian Parameters from RIXS Spectroscopy

Samuel Klein, Thomas M. Linker, Louis Conreux et al. (+14 more)

We present the first application of simulation-based inference to resonant inelastic X-ray scattering spectroscopy. Using truncated marginal neural ratio estimation to efficiently restrict the prior and conditional flow matching as the joint density estimator, we infer full posteriors with a modest simulation budget for two Ni$^{2+}$ compounds—NiPS$_3$ as a representative covalent case and K$_2$NiF$_4$ as a more atomic one. We demonstrate that a vision transformer encoder whose tokenization matches the physical layout of the RIXS map yields better-covered and sharper posteriors than generic image encoders. Applying the validated method to experimental NiPS$_3$ and K$_2$NiF$_4$ data, we recover a joint posterior that reveals parameter correlations invisible to point estimators, and a posterior predictive distribution that closely matches the observed spectrum. The amortized posterior unlocks a class of analyses not previously available to the field such as nuisance-marginalized uncertainty quantification, multi-measurement posterior fusion and active experimental design.
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All authors Samuel Klein, Thomas M. Linker, Louis Conreux, Daniel Ratner, Apurva Mehta, Makoto Tachibana, Jiemin Li, Jonathan Pelliciari, Valentina Bisogni, Wei He, Xiangpeng Luo, Mark P. M. Dean, Marton K. Lajer, Michael Kagan, Joshua J. Turner, Yongqiang Cheng, Sean Gasiorowski

Thursday 13 August

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

Centipede-Like Metastrip Enables On-Demand Programmable Droplet Motion

Sergio Britto and Stefano Gonella

We demonstrate programmable, frequency-tunable and size-selective drop motion on an elastic metastrip substrate with a centipede-like array of cantilever resonators. Under harmonic excitation, the strip experiences simultaneously an in-plane (IP) collective motion and out-of-plane (OOP) deformation, thus establishing a frequency-dependent IP-OOP phase landscape. This prescribes the direction of motion to the drops on the strip based on their position, causing the emergence of clustering and rarefaction regions. By tuning the tip masses of the resonators, we open reconfigurable OOP bandgaps that modify the IP-OOP phase makeup and locally suppress drop motion, contributing an additional layer of spatial selectivity. Using multi-frequency excitations, we selectively actuate drops based on their resonances, effectively filtering them by volume and position.
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