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Physics Condensed Matter Materials Science

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Friday 4 September

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

Nonreciprocal plasmonic response of drift-biased two-dimensional metals

Gonzalo Álvarez-Pérez and Joel D. Cox

We develop a nonlocal electrodynamic framework for drift-biased two-dimensional electron gases (2DEGs) with Dirac (linear) and parabolic (quadratic) dispersions, deriving closed-form drift-dependent conductivity tensors from the Boltzmann transport equation. We obtain the plasmon dispersion and near-field emission of a point dipole, revealing nonreciprocal propagation in both systems. At equal drift parameter, the parabolic 2DEG exhibits stronger nonreciprocity than the Dirac system, although we find that a larger drift parameter does not by itself produce stronger nonreciprocity: the response is set by the interplay of drift and plasmon nonlocality. As such, the combination of strong nonlocality and experimentally accessible drift velocities of semiconductor 2DEGs identifies parabolic systems as a promising platform for tunable, nonreciprocal plasmonics.
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Materials Science

Multi-task deep-learning optimization of trade-off properties for superior-performance Fe-based soft magnetic alloys

Kang-Yuan Li, Mao-Zhi Li and Wei-Hua Wang

Fe-based amorphous alloys are promising soft magnetic materials for developing next-generation devices with high frequency and efficiency. However, optimization of Fe-based alloys with ultra-high saturation magnetic flux density (B_s), ultra-low coercivity (H_c), and good glass-forming ability is a notorious problem, owing to the vast composition space and complex trade-offs of these properties. Thus, conventional design methods encounter great challenges. Here we develop a generative multi-task deep learning (GMTDL) to achieve simultaneous optimization of compositions and trade-off properties. The GMTDL can sufficiently exploit and share the knowledge of datasets across different tasks, despite the limitation and imbalance of these datasets. Therefore, it exhibits superior performance in prediction of alloys with multiple targeted properties, outperforming previous machine learning-based design strategies. Moreover, the GMTDL can also tailor compositions, providing an efficient way to regulate properties and generate desired candidates for further experimental processing. The validity and reliability of GMTDL are rigorously tested by benchmarking with Fe-based alloys reported very recently. Moreover, some new alloys with ultra-high B_s and ultra-low H_c are predicted. The optimal content windows of key elements and their synergistic effects are also unraveled for practical guidance. Thus, our study establishes an effective and reliable paradigm for simultaneous prediction and optimization of high-performance materials with multiple properties.
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Materials Science

Challenges in orbital current-driven domain wall motion in light metal/ferrimagnet heterostructures

Min-Gu Kang, Jaerin Kim, Benjamin J. Jacot et al. (+2 more)

Recent advances in spintronics suggest that orbital Hall currents generated by charge injection in light metals can provide nonequilibrium angular momentum without relying on strong spin-orbit coupling (SOC). Here, we examine whether such orbital currents can drive domain wall (DW) motion in an amorphous ferrimagnetic alloy, Gd$_{25}$(Fe$_{9}$Co$_{1}$)$_{75}$ (GFC), where the rare-earth sublattice offers strong SOC for orbital-to-spin conversion. We compare three representative heterostructures: Pt/GFC as a spin Hall reference, light-metal (Mn or Ti)/GFC for direct orbital-current injection, and light-metal/Pt/GFC incorporating an ultrathin Pt layer for orbital-to-spin conversion. Whereas Pt/GFC exhibits robust and reproducible spin-orbit-torque-driven DW motion, no current-driven DW motion is detected in Mn/GFC or Ti/GFC. Second-harmonic Hall measurements nevertheless reveal finite damping-like torques in both Mn/GFC and Ti/GFC, demonstrating that angular-momentum transfer into GFC does occur but is far weaker than in Pt/GFC. Inserting a 1-nm-thick Pt conversion layer strongly enhances the damping-like torque and restores DW motion. Thickness-dependent analysis further shows that DW mobility and depinning thresholds correlate with the interfacial Dzyaloshinskii-Moriya interaction and domain-wall width, highlighting weak torque conversion and insufficient interfacial stabilization of chiral DWs as key challenges for orbital-driven DW motion in light-metal/ferrimagnet heterostructures.
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All authors Min-Gu Kang, Jaerin Kim, Benjamin J. Jacot, Laura Van Schie, Pietro Gambardella

Materials Science

Field-Driven Coupled Magnon–Phonon–Electron Relaxation in Magnetite Using Steepest-Entropy-Ascent Quantum Thermodynamic Formalism

Deepak Dhariwal, William T. Reynolds, Jr. et al. (+1 more)

A field-driven steepest-entropy-ascent quantum thermodynamic (SEAQT) formulation is developed for longitudinal nonequilibrium relaxation in magnetite (Fe$_3$O$_4$) with coupled electron, phonon, and magnon populations. Material-specific excitation spectra define the thermodynamic state space, while one relaxation parameter for each population sets its kinetic scale. A longitudinal magnetic field shifts the dressed magnon eigenenergies while the occupation basis remains fixed; irreversible redistribution conserves instantaneous energy and electron number while allowing the magnon population to vary. The formulation yields nonequilibrium subsystem temperatures, entropy production, magnetic-work identities, and a coupled small-signal susceptibility incorporating energy-conservation feedback among all three populations; the one-pole Debye response appears only as a limiting case. Numerical results under sinusoidal driving show a transition from nearly quasistatic behavior to frequency-dependent lag, finite-amplitude departure from the linear-response ellipse, and increasing higher-harmonic content. Relaxational work per cycle increases strongly with field amplitude and frequency, while the complex susceptibility is broader and shifted relative to a Debye reference. Entropy production remains positive, and the electron, phonon, and magnon temperatures show distinct excursions followed by secular heating when positive magnetic work is retained without heat rejection. The calculated work represents longitudinal magnon quasiparticle relaxation in a homogeneous single-domain model, not the total core loss of a finite ferrite specimen.
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All authors Deepak Dhariwal, William T. Reynolds, Jr., Michael R. von Spakovsky

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

Voltage-embedded equivariant machine learning potential for open system simulations

Yiming Guan, Rongzhi Gao, ChiYung Yam et al. (+2 more)

Modeling electrochemical interfaces under operational non-equilibrium conditions is vital for energy technologies but remains bottlenecked by the expensive cost of ab initio methods. Current machine learning potentials, largely designed for closed systems under homogeneous electric fields, are limited in open quantum transport applications. To overcome this, we present an E(3)-equivariant graph neural network that embeds voltage bias for open-system simulations. Our approach decouples the system energy and forces into zero-bias and bias-dependent contributions, assigning distinct vector encodings to electrode and scattering-region atoms to capture non-equilibrium conditions. Trained on limited discrete bias data, the model achieves high predictive accuracy and robust extrapolation transferability. When applied to a lithium/water interface, our model successfully captures the field-induced dynamic reorientation of water molecules and reproduces asymmetric electrochemical behavior at different electrodes.
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All authors Yiming Guan, Rongzhi Gao, ChiYung Yam, GuanHua Chen, Ziyang Hu

Materials Science

4 MV/cm (010) $\beta$-Ga$_2$O$_3$ Heterojunction Diodes Realized by Low-Damage e-Beam NiO$_x$ Interlayers

Carl Peterson, Yizheng Liu, Chinmoy Nath Saha et al. (+3 more)

We report on the utilization of a low-damage e-beam NiO$_x$ deposition process to realize field-plated heterojunction diodes (FP-HJDs) on (010) $\beta$-Ga$_2$O$_3$ films with high critical breakdown field strengths beyond 4 MV/cm and power figure of merits (PFOM) of >1 GW/cm$^2$. Diodes were fabricated on a 2.67 $\times$ 10$^{16}$ cm$^{-3}$ intentionally doped 6.2 $\mu$m thick epitaxial layer grown by metalorganic chemical vapor deposition (MOCVD) on a conductive Sn-doped $\beta$-Ga$_2$O$_3$ (010) substrate using TMGa, O$_2$, Ar carrier gas, and SiH$_4$ as the silicon dopant source. The mesa etched FP-HJD devices utilized a thin 7 nm e-beam NiO$_x$ interlayer before the sputtered NiO$_x$ layers to eliminate the effects of sputter-induced ion damage on the (010) epilayers. Current-Voltage measurements resulted in a forward current density of 700 A/cm$^2$ at 4 V, HJD ideality factor of 1.29, a V$_{bi}$ of 2 V, rectification ratio of 10$^{11}$, and a differential specific on resistance (R$_{on,sp}$) value of 2.36 m$\Omega$ $\times$ cm$^2$. Breakdown of the (010) FP-HJDs was 1.64 kV, leading to a parallel plane electric field at breakdown (E$_{||,max}$) of 4.02 MV/cm and a PFOM of 1.14 GW/cm$^2$, which is a state-of-the-art result for diodes on MOCVD-grown (010) drift layers.
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All authors Carl Peterson, Yizheng Liu, Chinmoy Nath Saha, Rachel Kahler, Akhila Mattapalli, Sriram Krishnamoorthy

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

Evidence of Crystal-Field-Mediated Anisotropic Orbital Rashba Effect in Epitaxial Ru/FM Heterostructure

Yu Zhang, Wenhao Niu, Yumin Yang et al. (+5 more)

Electrical generation of orbital angular momentum provides a promising route to current-induced torques, yet effective control of orbital Rashba textures still remains challenging, particularly because the role of the interfacial crystal field remains largely unexplored. Here, we report experimental evidence for a crystal-field-mediated interfacial anisotropic orbital Rashba effect (AORE) in epitaxial Ru/ferromagnet heterostructures. Total orbital torque was disentangled into an isotropic bulk contribution and an in-plane anisotropic interfacial contribution. The latter was strongly suppressed by degrading the crystallinity of either constituent and by inserting a Cu spacer, highlighting the essential roles of coherent interfacial orbital hybridization and direct Ru/ferromagnet contact. These results identify interfacial crystal-field coherency as a key ingredient in manipulating orbital Rashba textures and establish a route toward engineering the symmetry and directionality of orbital torques.
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All authors Yu Zhang, Wenhao Niu, Yumin Yang, Wenqi Xu, Gengchen Meng, Hailong Wang, Na Lei, Dahai Wei

Materials Science

Hydrogen Storage on Transition-Metal-Decorated Nitrogen-Modified Carbon Nanoribbons

Gom Dorji, Amrutha M, Brahmananda Chakraborty et al. (+3 more)

Recently synthesized carbon nanoribbons (CNRs) were investigated for hydrogen (H2) storage using first-principles density functional theory calculations. Pristine CNRs exhibited weak H2 adsorption; therefore, the host structure was modified by substituting carbon atoms at the C-H edges with 12 nitrogen atoms, followed by Mn and Y doping to enhance H2 binding. A maximum of five metal atoms could be accommodated on the 12N-CNRs. Electronic structure analysis revealed strong orbital hybridization between the metal atoms and the CNRs, while binding energy calculations confirmed the structural stability of the doped systems. Bader charge analysis further quantified the charge transfer between the metal atoms and the host structure. The average H2 adsorption energies were calculated to be -0.40 eV/H2 for the Mn-doped system and -0.25 eV/H2 for the Y-doped system, which are within the desirable range for reversible hydrogen storage. The maximum theoretical gravimetric storage capacities at 0 K reached 7.48 wt% for the Mn-doped system and 6.55 wt% for the Y-doped system. Under practical conditions of 30 atm and 298.15 K, the storage capacity of the Y-doped system decreased to 6.04 wt%, whereas the Mn-doped system maintained its full capacity of 7.48 wt%. Thermodynamic analysis indicated that H2 adsorption is favored at low temperatures and high pressures, while desorption becomes feasible at elevated temperatures and lower pressures. These results demonstrate that Mn- and Y-doped CNRs satisfy key U.S. Department of Energy requirements for reversible H2 storage and show promise as potential hydrogen storage materials under near-ambient conditions.
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All authors Gom Dorji, Amrutha M, Brahmananda Chakraborty, Sonam Peden, Syed Faraz Hasan, Shabbir Ahmad Tanveer Hussain

Materials Science

Light alkali metal functionalized two-dimensional C5N monolayers for enhanced hydrogen storage

Gom Dorji, Sonam Peden, Syed Faraz Hasan et al. (+2 more)

This work presents a density functional theory (DFT) investigation of a two-dimensional (2D) C5N monolayer functionalized with Li, Na, and K for hydrogen storage. Pristine C5N exhibits weak H2 adsorption, while alkali-metal functionalization significantly enhances its storage capability. The C5N monolayer can stably accommodate up to six metal dopants, with binding energies stronger than the corresponding cohesive energies, indicating resistance to metal aggregation. Ab initio molecular dynamics simulations further confirm the thermal stability of the functionalized systems at 300 K. Charge transfer from the metal dopants to C5N enhances polarization and strengthens H2 adsorption. Each dopant can adsorb up to eight H2 molecules, yielding a maximum of 48 H2 molecules per unit cell and gravimetric storage capacities of 9.42, 8.61, and 7.93 wt% for Li-, Na-, and K-functionalized C5N, respectively. The average H2 adsorption energies of -0.16 to -0.17 eV/H2 indicate moderate interactions suitable for reversible storage. Thermodynamic analysis further demonstrates favourable H2 adsorption/desorption under practical operating conditions, while desorption-temperature, recovery-time, and volumetric analyses support the potential reversibility and storage performance of these systems. Overall, alkali-metal-functionalized C5N emerges as a promising 2D material for efficient and reversible H2 storage.
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All authors Gom Dorji, Sonam Peden, Syed Faraz Hasan, Kondo-Francois Aguey-Zinsou, Tanveer Hussain

Materials Science

Demonstration of room-temperature, magnetic-field-free, and ultralow-power spin-orbit torque logic device based on composition-uniform van der Waals magnet Fe3GaTe2

Zhengxiao Li, Qianbiao Liu, Wenliang Zhu et al. (+1 more)

Van der Waals magnets have received blooming interest in material science and spintronics for the advantages of low magnetization, flexible stacking, strong tunability, and dangling-bond-free interfaces. However, there has been no report of room-temperature magnetic-field-free spin logic device based on a van der Waals magnet. Here, we demonstrate a room-temperature, field-free, low-power, scalable spin-orbit torque in-memory computing logic device utilizing a van der Waals magnet Fe3GaTe2 bit with strong perpendicular magnetic anisotropy and a Pt channel with strong spin Hall effect, high electrical conductivity, and electric asymmetries. Current pulse width-dependent switching measurement reveals a low intrinsic critical magnetic-field-free switching current of 1.8e7 A cm-2, a high thermal stability factor of 50, and the potential of an ultralow write power of 1.5 fJ per bit at 1 ns pulse width for a typical industrial-level device dimensions (40 times lower than the industrially optimized W/FeCoB device). These results suggest a great potential of van der Waals magnets in dense, ultralow-power, scalable in-memory computing technologies.
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All authors Zhengxiao Li, Qianbiao Liu, Wenliang Zhu, Lijun Zhu

Materials Science

Initialization-free ultralow-power programmable spin-orbit torque logic devices enabled by chirally asymmetric switching

Qianbiao Liu and Lijun Zhu

Spin logic is of great interest for the development of high-performance, non-Von Neumann artificial intelligence chips. Of particular advantage is the programmable spin-orbit torque logic that can achieve the complete set of the 16 Boolean logic operations within a single device in an initialization-free, low-power, and scalable manner, which is, however, a challenge despite remarkable efforts over more than two decades. Here, utilizing chirally asymmetric switching, we demonstrate an initialization-free, low-power, programmable spin-orbit torque logic device that is capable of the complete set of 16 Boolean logic operations within a single device with only three inputs and ultralow power of < 1 fJ/bit. We also propose the first initialization-free, all-electrical spin-based cascading computing devices, including a half adder, a three-level full adder, a two-level full adder, and a Transfer/NOT selector. These compact and scalable computing devices are enabled by the chirally asymmetric spin-orbit torque switching of a Ta/FeCoB bilayer with a significant perpendicular Dzyaloshinskii-Moriya interaction field. These results pave an intriguing way for the development of next-generation high-performance large-scale in-memory computing chips based on chirally asymmetric spin-orbit torque switching.
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Materials Science

Metallic Organometallic and Semiconducting Covalent Phases of Free-Standing $\gamma$-Graphdiyne Molecular Wires

Antony G. L. Rodrigues, Guilherme S. L. Fabris, Bruno Ipaves et al. (+3 more)

One-dimensional carbon allotropes combining sp and sp2 hybridizations provide a versatile platform for atomically precise quantum wires with tunable electronic, vibrational, and mechanical responses. Recent on-surface synthesis has realized the $\gamma$-graphdiyne molecular wire on Au(100) in two interconvertible phases sharing an identical aromatic backbone but distinct linkage chemistry: an organometallic intermediate with C-Au-C bridges and a fully covalent product with diacetylenic linkages. While experimental techniques characterize the on-surface periodicity and C$\equiv$C Raman signatures, the intrinsic properties of the free-standing wires remain inaccessible. Here, we address this gap using hybrid-functional first-principles calculations. The covalent phase is a semiconductor with a direct band gap of 2.02 eV, a polyynic bond-length alternation of 0.117 Å, and a chain periodicity reproducing experiment within -0.5%. Conversely, the organometallic phase exhibits partial cumulenization and 1D metallic behavior, with spin channels crossing the Fermi level. Both isolated polymers demonstrate dynamic stability with Young's moduli of 995 nN and 861 nN, respectively, where the C-Au-C bridge acts as a soft link absorbing 9.2% of axial deformation at +6% macroscopic strain. Species-resolved vibrational analysis identifies an effective-conjugation-coordinate band at 1408 cm$^{-1}$ for the covalent phase and Au-projected modes below 400 cm$^{-1}$ for the intermediate, offering diagnostic fingerprints for phase discrimination during thermal or chemical conversion.
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All authors Antony G. L. Rodrigues, Guilherme S. L. Fabris, Bruno Ipaves, Fábio L. L. de Mendonça, Douglas S. Galvão, Marcelo L. Pereira Junior

Thursday 3 September

Materials Science · Cross-listed from cs.LG

SCALE: Simulation-Calibrated Amortized Learning for Energy Materials (A hybrid architecture connecting deterministic modeling, real-world data, and transformer-scale inference for accelerated energy-materials discovery)

Kuan Huang and Bo Bai

Energy systems face converging pressures for security, affordability, resilience, and sustainability, creating a need for faster discovery of deployable energy materials. Here we introduce SCALE (Simulation-Calibrated Amortized Learning for Energy Materials), a physics-grounded, real-world-data-calibrated learning architecture that connects deterministic scientific operators, experimental calibration, expanded calibrated label generation, and transformer-scale inference. SCALE converts selected high-cost mechanistic computation and measured evidence into reusable models for rapid screening, ranking, inverse design, and active learning. We formulate the framework, identify ten method-based application regimes, and demonstrate SCALE for solid-state metal-hydride hydrogen-storage capacity prediction. In this implementation, a hydride phase-equilibrium capacity operator is calibrated against 381 measured ML-HydPARK capacity anchors and used to generate 5,000 candidate-condition-prototype teacher labels. A crystallographically anchored periodic-graph representation preserves atomic sites, periodic neighbor relationships, and local metal environments absent from formula-only encodings. An edge-biased graph transformer with 2.90 million parameters reproduces calibrated teacher labels with five-fold surrogate fidelity of MAE 0.0582 wt% H2, RMSE 0.0833 wt% H2, R2 = 0.9927, and Pearson r = 0.9963. Post hoc attention analysis suggests that SCALE learns chemically organized element groupings and metal-metal relationships consistent with established hydride chemistry, without chemistry-group labels as supervision. Once trained, SCALE shifts million-candidate evaluation from repeated deterministic workflow execution to batched learned inference, reducing per-candidate screening cost by approximately 10^7-10^8 while retaining links to simulation and experimental evidence.
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Materials Science

Structural tuning of reduced exciton mass in layered HOIP compounds: Causation vs. correlation

Isaac R. Burkholder, Cindy Y. Wong, André Schleife et al. (+3 more)

Reduced exciton mass ($\mu$) was recently reported to correlate strongly with a framework distortion in a series of nine single-layer (2D) metal-halide perovskite (HOIP) compounds. Specifically, $\mu$ was observed to increase in tandem with an alternating PbI4 octahedral tilt about an in-plane axis. In this work, we use group representation theory to decompose the observed framework distortions into displacive symmetry modes of a common high-symmetry parent framework. We find that all nine distorted frameworks involve linear combinations of the same six symmetry modes, which have been reported to contribute to the framework distortions of a wide range of HOIP compounds. We show that these modes have highly correlated impacts on the band structure. To differentiate causation from correlation, we vary the amplitude of each mode independently and use density-functional theory to determine the resulting electronic band structures, from which $\mu$ is extracted. We find that bond-transverse displacements of the equatorial halide atoms increase $\mu$, while bond-transverse displacements of the apical halide atoms decrease it. Bond-axis displacements appear to have little or no effect on $\mu$. Our results demonstrate three new structure-property relationships, revealing a promising new avenue for exciton engineering in layered perovskite materials.
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All authors Isaac R. Burkholder, Cindy Y. Wong, André Schleife, Kameron R. Hansen, John S. Colton, Branton J. Campbell

Materials Science · Cross-listed from cs.AI

Data-Driven Discovery of Composition-Dependent Constitutive Models for Hyperelasticity and Viscoelasticity of Digital Materials

Josué García-Ávila, Beijun Shen, Manuel K. Rausch et al. (+2 more)

Digital materials fabricated by multi-material 3D printing are designed as controlled mixtures of stiff and compliant constituents, yielding effective responses that span more than an order of magnitude in apparent stiffness and exhibit strongly nonlinear, composition-dependent, and rate-dependent dissipative behavior. Classical finite-strain viscoelastic models represent such behavior with closed-form strain energy functions for equilibrium and non-equilibrium stresses as well as evolution of internal variables, which may limit flexibility when a single constitutive model is expected to generalize across materials and loading rates. Here, we present a data-driven multi-material constitutive modeling framework that generalizes a formulation by Bergström and Boyce. The proposed framework retains the structure of the classical model, namely multiplicative kinematics, invariant-based strain-energy functions, and a scalar dissipative evolution law directed along the normalized nonequilibrium deviatoric stress. For the equilibrium branch, the data-driven discovery framework either directly predicts closed-form model parameters as functions of composition or automatically constructs a polyconvex strain-energy function using neural ordinary differential equations (NODEs). The nonequilibrium branch kinetics are learned similarly, either by directly identifying closed-form parameters across compositions or by using appropriately constrained artificial neural networks. Using multi-rate uniaxial compression data across multiple material compositions, we show that the proposed formulation captures rate-dependent stiffness and hysteresis across compositions while preserving thermodynamic consistency.
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All authors Josué García-Ávila, Beijun Shen, Manuel K. Rausch, Mary C. Boyce, Adrián Buganza-Tepole

Materials Science

Calculation of DFT Spin-Orbit Spillage with Quantum ESPRESSO

Duy Quan Nguyen and Paul C. H. Li

This work describes the calculation of spin-orbit spillage from a crystal structure. Spin-orbit spillage provides a measure of the likelihood that a material has topological character. The spillage also provides the reference quantity for the machine-learning classifier of Choudhary et al., which predicts whether the spillage exceeds a specified threshold rather than the calculation of its numerical value directly. The complete computation workflow was applied to the insulating compound BaMg2Bi2, yielding a spillage of 2.094 compared with the published VASP spillage of 2.075, corresponding to a difference of 0.9%. The calculation is described in terms of two Quantum ESPRESSO (QE) calculations of spillage performed with and without spin-orbit coupling, the role of relativistic pseudopotentials, and the subsequent wavefunction-overlap analysis. The limitations of the same calculation procedure for semimetals are also examined.
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Materials Science

Triboelectrification of a dense metal-organic framework for resilient mechanical energy harvesters

Chuzhan Jin, Debayan Mondal, Jiahao Ye et al. (+1 more)

Triboelectric nanogenerators (TENGs) incorporating metal-organic frameworks (MOFs) have largely been designed around porous architectures, based on the assumption that high internal surface area is the primary driver for triboelectric enhancement. Herein, we demonstrate that a dense, nominally nonporous MOF called ZIF-zni can instead function as an effective high-loading filler within a tribopositive polyurethane (PU) matrix, offering a design strategy for harnessing interfacial electromechanical effects. A 20 wt% ZIF-zni@PU composite delivers an output voltage of 470+/-15 V and a peak power density of 1.31+/-0.03 W m-2 against polydimethylsiloxane (PDMS). The device exhibits stable performance over ~94,000 cycles under a contact force of ~100 N, and it remains operational under higher impact beyond 500 N. This concept enables the demonstration of a proof-of-concept triboelectric floor tile. Combined experimental and theoretical studies indicate that the performance enhancement arises from favourable interfacial polarization, reduced dielectric screening, and surface accessible ZIF-zni rich domains, rather than porosity alone. These features are accompanied by reduced work of adhesion and modified surface roughness, hence improving contact electrification. These findings establish dense MOFs as an effective triboelectric filler and identify interfacial electronic structure and polarization as key design parameters for engineering mechanical energy harvesters and self-powered sensors.
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All authors Chuzhan Jin, Debayan Mondal, Jiahao Ye, Jin-Chong Tan

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

Low electrical conductivity of dry CaSiO3 perovskite under lower mantle conditions

Yoshiyuki Okuda, Bin Chen, Juliana Peckenpaugh et al. (+1 more)

Electrical conductivity (EC) provides important constraints on the composition and volatile distribution of Earth's deep mantle, yet the EC of davemaoite (CaSiO3 perovskite), a major lower-mantle phase, remains poorly constrained. We measured the EC of nominally dry CaSiO3 perovskite at pressures up to 89 GPa and temperatures up to 2200 K using impedance spectroscopy in a laser-heated diamond anvil cell. Conductivity increases with temperature but decreases systematically with pressure and it is substantially lower than previously reported, yet broadly consistent with recent theoretical predictions for oxygen-vacancy-mediated ionic transport. A distinct change in the temperature dependence coincides with the tetragonal-to-cubic phase boundary, revealing a modest enhancement of ionic transport across the structural transition. Along a normal lower-mantle geotherm, dry davemaoite is comparable in conductivity to bridgmanite near the top of the lower mantle but becomes progressively less conductive with depth. Under cold-slab conditions, dry davemaoite is substantially less conductive than dry subducted MORB and cannot account for the observed high-conductivity anomalies. Dry davemaoite therefore contributes little to bulk lower-mantle conductivity.
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All authors Yoshiyuki Okuda, Bin Chen, Juliana Peckenpaugh, Hirokazu Kadobayashi

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

Composition-dependent nonlinear viscoelastic-viscoplastic behavior and constitutive framework for digitally mixed polymers spanning the glass transition

Beijun Shen and Mary C. Boyce

Multi-material PolyJet printing produces voxel-scale digital mixtures of an elastomeric photopolymer (Agilus) and a glassy photopolymer (Vero), giving a material family whose room-temperature response ranges from elastomeric to glassy; a unified description spanning the family has remained challenging. Large-deformation uniaxial compression over nearly three orders of magnitude in strain rate reveals a nonlinear, rate-dependent load-unload response that evolves continuously with composition, from recoverable elastomeric hysteresis to glassy yield with post-yield softening, hardening, and substantial residual strain. Dynamic mechanical analysis (DMA) shows that each mixture has a single glass transition temperature ($T_g$) that shifts to higher temperature with both Vero fraction and frequency, so composition acts much as temperature or loading rate does. This time-composition equivalence motivates one constitutive structure for the whole family rather than a separate property set per mixture: an equilibrium hyperelastic network with three non-equilibrium, rate-dependent branches carrying reptational, intermolecular, and glassy resistance. Its properties are anchored at the two endpoints and interpolated by smooth composition scaling laws. The model captures the compression response of all seven calibrated compositions and predicts a withheld mixture from the scaling laws alone. Resolving the predicted stress into its branches shows the load passing from the elastomeric to the glassy mechanism, and the work from elastic storage to dissipation, as Vero content and rate rise. The glass transition that DMA maps at small strain therefore governs the large-strain deformation mechanisms. The framework gives a compact, physically based description of digitally mixed polymers and a predictive basis for designing functionally graded, architected multi-material structures.
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Materials Science

Accelerating Atom Simulations with Variable-Block Sparse Matrix Library

Zhanghao Zhouyin and Hong Guo

Modern atomistic simulations increasingly employ localized orbitals to represent quantum operators, yielding sparse block matrices whose block shapes vary with chemical species and basis choice. Conventional scalar sparse formats store the entries of each block individually, obscuring this local structure and limiting the use of efficient block algorithms. We present VBCSR, a distributed sparse matrix library that preserves variable-size atomic blocks and accelerates the core linear algebra of large-scale atomistic simulations. A unified interface automatically maps scalar, uniform-basis, and multispecies operators to compressed sparse row (CSR), block sparse row (BSR), or variable-block compressed sparse row (VBCSR). Our advanced acceleration method groups blocks of equal shape and dispatches them to optimized dense kernels. In the reported benchmarks, VBCSR outperforms the tested Python-accessible reference implementations for several block-sparse benchmarks. We further demonstrate VBCSR in an InP nanoparticle application containing more than \(10^6\) atoms.
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Materials Science

Reproducible capillary fluctuation analysis of solid-liquid interfaces for stiffness and anisotropy calculations

Kai Liu, Douglas E. Spearot and Damien Tourret

The capillary fluctuation method (CFM) is widely used to compute solid–liquid interfacial properties from atomistic simulations, but its accuracy depends on choices in interface construction, wave-vector selection, sampling, and simulation geometry. Here, we develop a diagnostics-driven workflow for reproducible CFM calculations using pure Al as a representative system. Employing both ribbon models and thick two-dimensional references, we show that apparent linearity of the fluctuation spectrum alone does not ensure reliable stiffness or anisotropy estimates. Instead, a reliable CFM analysis requires a fitting window consistent with both temporal sampling and continuum capillary-wave assumptions, systematic sensitivity tests of the interface identification procedure, explicit propagation of replica variability, and independent verification of model-thickness convergence. We further propose a practical thickness-selection rule based on coexistence-temperature consistency, which enables finite-size effects to be controlled while retaining the substantial computational efficiency of ribbon geometries. By making the main sources of uncertainty explicit and diagnosable, the proposed workflow improves the reliability of the CFM as a quantitative tool and provides a foundation for its broader application to complex solid–liquid interfaces.
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Materials Science · Cross-listed from cond-mat.soft

Reciprocity can halve what a mechanical network can learn

Thai-Son Vu, Hoang-Giang Nguyen, Quoc-Bao Nguyen et al. (+2 more)

A passive, reciprocal, linear network driven by forces or currents and read at points it drives cannot be trained below an error floor computed from the target beforehand. The usual parameter count for such networks does not charge for Maxwell-Betti reciprocity. We prove that when such an elastic, resistor or flow network has a symmetric response operator and p driven degrees of freedom are also read, its reachable response blocks lie in a subspace of codimension p(p-1)/2, whatever its size and topology, and the floor is the distance to it. On targets with a reachable symmetric part, a second-order optimiser ends within 0.1% of the floor in 142 of 144 simulated runs, and a contrastive rule with a bond-local update direction, within its step budget, in 22 of 24. Reciprocity charges a list of single drive-read tasks only for the pairs it instruments in both directions, and a rank test on the passive network says in advance whether, and on which bonds, odd couplings locally restore the lost directions, at a cost in non-reciprocity that the target bounds from below. Under an imposed-displacement drive, the one most physical-learning hardware uses, reciprocity survives as a weaker law, an exact balance between forward and reverse transmissions once each is weighted by the driving-point compliance at its input, and an inequality on their product, under which no symmetric positive-definite chain meets both targets of a published robotic metamaterial. All nineteen published layouts we tabulated pay nothing; a force-driven layout that asks one pair to respond differently in its two directions will.
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All authors Thai-Son Vu, Hoang-Giang Nguyen, Quoc-Bao Nguyen, Sengaloun Keoalounxay, Bao-Viet Tran

2609.04169 · 3 Sep · 75 pages, 8 figures, 3 tables; 24 reproducible experiments, all result tables as ancillary files. Code and data: doi:10.5281/zenodo.22952768. v4 supersedes v3: new Sec. 4.2 prices the odd coupling (a lower bound from the target, the least coupling, a torque-free realisation); new Fig. 8 runs the task-list floor on one network; 15 new references. Novelty narrowed: the halved count is classical

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Materials Science

Strengthened Silicate Glasses by Residual Stress: Depth of Compression and Surface Flaws Stability Conditions

Guglielmo Macrelli

The application of silicate glasses in severe service environments requires a precise evaluation of structural strength under mechanical loads and surface tribological conditions. Because glass strength is governed by surface flaws and microcracks rather than being an intrinsic material property, residual surface compression fields, balanced by interior tensile zones, are widely implemented to inhibit flaw opening. Rather than relying on conventional allowable stress criteria to establish product acceptance, this study adopts a fracture mechanics framework based on the stress intensity factor KI and fundamental material limits: the critical stress intensity factor KIC for rapid fracture and the threshold stress intensity factor KIth for time-delayed static fatigue failure. Using the Weight Function Method (WFM), KI is evaluated across generic surface flaw depths for two-dimensional continuous (2D-Continuous) surface cracks subjected to non-uniform internal residual stress fields and external loads. Flaw stability criteria are established for both zero-risk and moderate-risk design methodologies. Finally, the interaction and superposition of externally applied mechanical and thermal stresses with internal residual stress fields are evaluated.
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Materials Science

Synthesis and Characterization of Compositionally Complex (Gd/Ho/Er/Dy)2Zr2O7 Thin Film Combinatorial Library

Dalton A. Pearl, Jade Holliman Jr, Reece Emory et al. (+13 more)

High-throughput synthesis and characterization of novel ceramic materials with improved thermomechanical properties and phase stability are needed to accelerate the discovery of next-generation thermal barrier materials. A combinatorial thin film material library of (GdDyHoEr)2Zr2O7 were created via combinatorial magnetron reactive sputtering with rare-earth/zirconium alloy targets. Structural, chemical, and thermal property characterization mapping across the four component composition space was performed and correlated with thermal transport measurements. Steady state thermoreflectance mapping identifies a pronounced minimum in thermal conductivity within the Dy/Gd-rich quadrant. This minimum does not coincide with either the equiatomic composition or the region predicted to exhibit maximum cation size disorder. Instead, it corresponds to the largest experimentally observed lattice parameter, despite deviating from Vegard-like chemical averaging, and is independent of grain size and whole-pattern microstrain. These observations suggest that the way the fluorite lattice accommodates compositional complexity, rather than cation size disorder alone, provides a more informative descriptor of thermal transport. Overall, this work establishes a high-throughput workflow for combinatorial thin-film synthesis and multimodal characterization, enabling the rapid identification of previously inaccessible structure-property relationships in compositionally complex ceramics.
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All authors Dalton A. Pearl, Jade Holliman Jr, Reece Emory, Joshua Safin, Aditya Raghavan, Kamyar Barakati, Andrew H. Jones, Ethan A. Scott, Jack C. Lasseter, Adam Corrao, Daniel Olds, Bruce Ravel, Sergei K. Kalinin, Patrick E. Hopkins, Katharine Page, Philip D. Rack

Materials Science

Hierarchical automation of scanning probe microscopy through agentic orchestration and algorithmic control

Boris N. Slautin, Sheryl L. Sanchez, Aidan Swanger et al. (+5 more)

Rapid advances in agentic artificial intelligence enable scientific systems to interpret open-ended objectives, combine heterogeneous information, invoke specialized tools, and revise experimental strategies as evidence accumulates. However, physical experimentation also contains many tasks for which agentic reasoning provides little advantage and can reduce reliability. Quantitative analysis, optimization, spatial targeting, validation, and instrument execution are often better posed as deterministic or algorithmic operations with explicit objectives and verifiable outputs. Here, we introduce a hierarchical architecture for autonomous experimentation that separates these roles. Agentic components interpret scientific intent, construct task-dependent experimental representations, evaluate accumulated evidence, and select high-level actions, whereas deterministic algorithms perform numerical analysis, coordinate selection, validation, and physical execution. We implement this architecture in piezoresponse force microscopy. Starting from a broad scientific question concerning the relation between local domain structure and polarization switching, the system constructs spatial descriptors from multichannel imaging, selects and analyzes local hysteresis measurements, adapts the spectroscopy waveform, and terminates the experiment when additional measurements cease to provide new evidence. The autonomous trajectory also identifies a confounding relationship between polarization state and domain-wall proximity and recognizes that the requested contrast is not independently represented within the available field of view. These results demonstrate a route toward scientific autonomy in which agents determine what evidence is required while algorithms determine how that evidence is acquired reproducibly and within validated physical constraints.
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All authors Boris N. Slautin, Sheryl L. Sanchez, Aidan Swanger, Yu Liu, Gerd Duscher, Vladimir V. Shvartsman, Mahshid Ahmadi, Sergei V. Kalinin

Materials Science

Experimentally constrained modeling of the Pockels response of KNbO3 and KTaNbO3

Virginie de Mestral, Lorenzo Bastonero, Petr Bednyakov et al. (+6 more)

The soft-mode of electro-optic (EO) metal-oxide perovskites plays a critical role in determining their Pockels responses. This is the case of potassium tantalate niobate (KTN), which exhibits an intrinsic Pockels response 2.5 times larger than that of state-of-the-art barium titanate (BTO), highlighting its potential for high-performance EO applications. By combining ab initio calculations at the density-functional theory level and far-IR measurements, we reveal that the harmonic approximation combined with semi-local exchange-correlation functionals fails to accurately capture the soft transverse optical (TO) Slater mode of both potassium niobate and KTN, which dominates the technologically relevant r51 Pockels coefficient. Replacing the calculated mode frequency with its measured value provides an experimentally constrained approach that substantially improves the predicted Pockels response. For that purpose, the previously unreported TO Slater-mode frequency of KTN is extracted from far-IR reflectivity measurements. The results emphasize the potential of KTN-based EO modulators as an alternative to standard lithium niobate and BTO technologies, with a potentially lower energy consumption and device footprint.
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All authors Virginie de Mestral, Lorenzo Bastonero, Petr Bednyakov, Fedir Borodavka, Simon Mellaerts, Tetyana Ostapchuk, Alex Pescaru, Jiri Hlinka, Mathieu Luisier

Materials Science

Performance of Nanoring-based Transparent Conductors: a Computational Investigation

Gijs Vanoppen, Jef Hooyberghs, Wim Deferme et al. (+1 more)

Metallic nanoring networks can serve as promising flexible transparent electrodes. These materials are crucial components in a wide range of applications, including solar cells, touchscreens and displays. In this work, a computational investigation considers in detail (i) the electrical conductance and optical performance of nanoring networks and (ii) the breakdown of these networks due to electrical damage. The electrical resistance of both the nanorings and the contacts between the rings (junctions) is taken into account. In part (i), the effects of 5 parameters on the electrical sheet resistance and optical transparency are presented. It is shown that several parameter combinations achieve better performance in comparison to indium tin oxide, currently the most widely used transparent electrode. In part (ii), due to electrical damage, the nanoring systems display the formation of a crack, running parallel to the vertical terminals, where a voltage difference is applied. The network degradation is measured by its sheet resistance, and a universal effect is observed: networks with varying filling factors exhibit the same degradation profile.
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All authors Gijs Vanoppen, Jef Hooyberghs, Wim Deferme, Bart Cleuren

Materials Science

Exciton multipolarity controls coherent and squeezed phonons in van der Waals heterostructures

Indrajit Maity, Arash A. Mostofi, Johannes Lischner et al. (+1 more)

Photoexcitation-driven changes in the electronic distribution displace atoms, generating coherent phonons on ultrafast timescales. Two-dimensional (2D) materials and their heterostructures offer a powerful platform for engineering these phonons. Yet, despite the widespread observation of photoexcited coherent phonons, a design principle for controlling their character remains elusive. Here, using detailed atomistic simulations of multilayers of alternating MoSe$_2$ and WSe$_2$, we reveal exciton multipolarity as a design principle for tuning photoinduced phonons from coherent to squeezed. These phonons are interlayer breathing modes, with dipolar excitons coupling linearly to generate coherent states and quadrupolar excitons coupling quadratically to produce squeezed states. Moreover, an out-of-plane electric field enables switch-like control, converting quadrupolar excitons into dipolar excitons and switching the phonon state from squeezed to coherent. For example, in trilayer WSe$_2$/MoSe$_2$/WSe$_2$, the photoexcited 1.04-THz breathing mode switches from a squeezed state at zero field to a coherent state under an applied vertical field. Experimentally, these phonon states can be directly probed by ultrafast X-ray or electron diffraction and indirectly through transient reflectivity. Our results open new avenues for ultrafast control of lattice and electronic dynamics on picosecond timescales, with implications for THz quantum phononics, nanophotonic technologies, and quantum-noise-limited sensing.
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All authors Indrajit Maity, Arash A. Mostofi, Johannes Lischner, Ángel Rubio

Materials Science

Heesch Nodal Lines in Inadmissible Achiral Antiferromagnets

Xing-Yao Guo, Chung-Yuen Chan, Zi-Ting Sun et al. (+1 more)

Recently, a new class of Weyl semimetals in antiferromagnets named Heesch Weyl semimetals was discovered, which have inadmissible chiral magnetic point group symmetries (inadmissible magnetic point groups are incompatible with ferromagnetic order) and distinctive surface Fermi arcs. In Heesch Weyl semimetals, the Weyl points are pinned at high symmetry momenta with two-dimensional irreducible corepresentations in the Brillouin zone. As the Weyl points are pinned, the Weyl points with opposite topological charges cannot emerge or be brought together for creation and annihilation as in conventional Weyl semimetals. In this work, we show that when mirror or rotoinversion symmetries are restored so that the point group becomes achiral, long doubly degenerate lines connecting Weyl points with opposite topological charges emerge. We call these lines the Heesch nodal lines (HNLs) and their host materials the Heesch nodal line antiferromagnets. HNLs result in a large number of two-dimensional massless Dirac cones for planes intercepting the HNLs in the Brillouin zone. Moreover, a large subset of the HNL antiferromagnets has the special property that the lowest nonvanishing order of the nonlinear anomalous Hall effect starts with the third order. First-principles calculations on representative collinear and noncollinear antiferromagnets, such as MnTe, CrSb, and Mn$_3$GaN, confirm our predictions on the presence of HNLs. When the inadmissible symmetry is broken by strain, the double degeneracy of the HNLs is lifted and the associated massless Dirac cones are gapped out, providing a route to realizing sizable anomalous Hall effects in antiferromagnetic crystals. We conclude that all inadmissible antiferromagnets without parity-time symmetry are topological. They are either Heesch Weyl antiferromagnets or Heesch nodal line antiferromagnets.
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All authors Xing-Yao Guo, Chung-Yuen Chan, Zi-Ting Sun, Kam Tuen Law

Materials Science

Ion-Engineered Insulator-to-Semiconductor Transition in Natural 2D Biotite

Dipanwita Mitra, Raphael B. de Oliveira, Guilherme S. L. Fabris et al. (+7 more)

Naturally occurring layered silicates offer an abundant yet unexplored class of 2D materials, but their insulating nature limits their functional utility. Here, we demonstrate a chemical strategy that transforms liquid-phase-exfoliated biotite nanosheets into a tunable 2D semiconductor through controlled NaOH treatment. The resulting insulator-to-semiconductor transition originates from Na incorporation, defect generation, and local structural reconstruction while largely preserving the layered framework. Structural and chemical analyses reveal lattice distortion, interlayer reorganization, hydroxylation, and partial Na+-K+ exchange, establishing the origin of the electronic restructuring. This transformation broadens the optical response, shifting the approximately 221 nm absorption toward approximately 280 and 975 nm, reducing the optical bandgap from approximately 5.2 to 3.2-3.5 eV, and introducing low-energy transitions at approximately 1.12-1.17 eV. Electrical measurements reveal nonlinear transport with currents reaching close to 10 microA, demonstrating activated carrier conduction. Ultrafast transient absorption reveals pronounced excited-state absorption, with carrier cooling (0.16-0.38 ps) followed by fast (35-60 ps) and long-lived (336-491 ps) relaxation associated with trap-mediated recombination. Fluence-dependent dynamics reveal a hot-phonon bottleneck at elevated carrier densities. Together with density functional theory calculations, these results establish chemical defect and ion engineering as a powerful route for converting naturally abundant layered minerals into electronically tunable 2D materials for emerging optoelectronic and ultrafast photonic technologies.
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All authors Dipanwita Mitra, Raphael B. de Oliveira, Guilherme S. L. Fabris, Debkanta Ghosh, AyonJyoti Karmakar, Raphael M. Tromer, Marcelo L. Pereira Junior, Douglas S. Galvão, Chandra Sekhar Tiwary, Prasanta Kumar Datta