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Physics Condensed Matter Materials Science

cond-mat.mtrl-sci Watch Materials Science

Monday 14 September

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

Growth of superconducting boron doped diamond on 4inch silicon wafers

Soumen Mandal and Oliver A Williams

Superconducting boron-doped diamond (BDD) films were grown on 4-inch silicon wafers by microwave plasma chemical vapour deposition using gas-phase B/C ratios ranging from 6536 to 36421 ppm. Surface morphology, boron incorporation and superconducting properties were investigated as a function of gas-phase boron concentration. No systematic variation in apparent lateral grain size was observed across the series. Superconductivity was observed in all films except that grown at a B/C ratio of 6536 ppm within the measured temperature range down to 2 K. The superconducting transition temperature initially increased with increasing B/C ratio, reaching a maximum T$_c$ of 4.03 K at 24691 ppm, before decreasing at higher gas-phase B/C ratios. The corresponding resistive upper critical field at 2 K reached 3.091 T. Raman spectroscopy showed an increase in boron incorporation with increasing gas-phase B/C ratio up to 30303 ppm, followed by a slight decrease at 36421 ppm. Spatial measurements across the film grown at 24691 ppm showed T$_c$ values of 4.02, 4.19 and 3.33 K at the centre, intermediate and edge positions, respectively, with Raman spectroscopy showing a corresponding spatial variation in boron concentration. Comparison with previous growth on 2-inch wafers showed that substantially higher gas-phase B/C ratios were required to obtain comparable boron concentrations and superconducting properties on 4-inch wafers, indicating reduced boron incorporation efficiency during large-area growth. These results demonstrate the feasibility of producing superconducting BDD over a substantial area of a 4-inch silicon wafer while identifying boron incorporation and radial uniformity as key parameters for further wafer-scale optimisation.
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Materials Science

A cylindrical sintering method for more realistic grain boundaries in nanocrystalline thin films

Ankit Yadav, Lucia Bajtošová, Miroslav Cieslar et al. (+1 more)

Discrepancies between simulated and experimental mechanical properties in molecular dynamics simulations of nanocrystalline metals typically arise from the sample-construction method and the interatomic potential choice. We introduce a cylindrical sintering method to generate nanocrystalline aluminum thin-film samples with wider, more disordered grain boundaries than the usual Voronoi tessellation method, while maintaining deterministic control over grain size, shape, and orientation. Cylindrical sintered samples are benchmarked against hexagonal Voronoi references under identical conditions using both the classical Pascuet15 MEAM and tabGAP machine-learning potentials. Cylindrical sintered samples consistently show lower mechanical properties than hexagonal Voronoi samples due to their wider, more disordered grain boundaries - an effect independent of the choice of potential. Notably, changing the sample geometry and changing the interatomic potential produce comparable, additive, and independent shifts in predicted properties, highlighting that future molecular dynamics studies must hold both variables fixed for meaningful comparisons. Common neighbor and dislocation extraction analyses confirm that deformation is dominated by grain-boundary-mediated plasticity. Uniaxial tensile tests reveal an inverse Hall-Petch relationship for both sample types and both potentials, with mechanical properties decreasing monotonically as grain size reduces from 40.34 to 4.84 nm. The cylindrical sintering method offers a physically realistic, geometrically controlled alternative that bridges idealized Voronoi models and disordered experimental grain-boundary structures.
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All authors Ankit Yadav, Lucia Bajtošová, Miroslav Cieslar, Jan Fikar

Materials Science

Evaluating Predicted Densities, Hamiltonians, and Density Matrices as Periodic SCF Initializers

Pin Chen, Jiang Li and Yutong Lu

Learned electronic states are usually evaluated by prediction error, even though their intended use is to accelerate the self-consistent-field (SCF) loop of density functional theory (DFT). We ask whether lower offline error actually yields a better SCF initializer. We construct $\rho$HD-43K, a 43,851-crystal DFT corpus with aligned charge-density, Hamiltonian, and density-matrix labels, and extend the solver workflow to inject all three predicted states. The closed-loop benchmark compares direct converged-state prediction against residual prediction from solver-native references on a frozen test set of non-magnetic crystals, using paired convergence, iteration, and SCF-loop timing measurements. Injecting the exact converged density matrix or Hamiltonian as an oracle upper bound cuts the median SCF count from 16 to one, revealing substantial acceleration headroom. Among learned inputs, direct charge-density prediction (Charge3Net-E3) accelerates about 91% of paired crystals, saves a median of three SCF iterations, and yields a $1.18\times$ SCF-loop speedup. In contrast, the tested residual-density and matrix initializers do not consistently improve over the standard superposition-of-atomic-densities baseline. These results establish that target-space accuracy alone is insufficient: a learned initializer must also be compatible with the nonlinear solver trajectory, and its utility must be measured in the loop.
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Materials Science

Navigating Sparse Singlet Fission Chemical Space: An Intelligent Generative-Predictive Paradigm

Longfei Lv, Li Fu, Si Zhou et al. (+2 more)

Singlet fission (SF) offers a promising route to surpass the Shockley-Queisser limit by converting a photoexcited singlet exciton into two triplet excitons, thereby enhancing photovoltaic energy conversion efficiency. However, realizing efficient SF process requires stringent energetic requirements among low-lying excited states that render SF molecules intrinsically rare within the vast chemical space. This extreme sparsity presents a grand challenge for molecular discovery. Due to low hit rates and trial-and-error computational waste on nonviable structures, conventional high-throughput virtual screening faces significant constraints, even when accelerated by machine learning models. Here, we establish a synergistic generative-predictive framework for the targeted inverse design of SF molecules by integrating a structure generator, a properties predictor and a multi-criteria validation workflow. By continuously coupling generative exploration with SF predictive models, the framework progressively enriches SF species and achieves a success rate of approximately 90% in generating molecules that satisfy the target SF energetic criteria. High-throughput evaluation of about 100 million generated structures with time-dependent density functional theory (TDDFT) validation of just a random 1% subset confirmed a 90.8% success rate for SF candidates. All together, we constructed an SF database of 283,559 candidates with favorable energetics of excited states and synthetic accessibility. From it, we identified a key fragment strongly associated with the requirements for SF, namely, CN([O])N(C)[O]. These findings establish an efficient route for overcoming the sparsity difficulty in SF molecular discovery and provide interpretable design principles for the development of novel excited-state functional materials.
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All authors Longfei Lv, Li Fu, Si Zhou, Lingzhi Zhao, Jijun Zhao

Materials Science

Demonstrate of High-Performance Top-Gate ALD Crystalline In2O3 Transistor Enabled by Lattice-Matched HfO2 and In2O3 Heterostructure

Kai Jiang, Chen Wang, Ziheng Wang et al. (+2 more)

In this work, we demonstrate high-mobility top-gate (TG) atomic-layer-deposited (ALD) crystalline In2O3 transistors through simultaneous interface and crystallinity engineering. First, a HfO2/In2O3/HfO2 stack is employed, enabling epitaxial-like crystallization of the ultrathin In2O3 channel, because of the lattice matching between monoclinic phase HfO2 and cubic phase In2O3. Second, an oxygen-rich gate insulator process is applied using high-dose O3 precursor and elevated deposition temperature, effectively suppressing oxygen scavenging during gate dielectric deposition, significantly reducing interfacial defect formation. Third, the homogeneous In-O bonding network in crystalline In2O3 exhibits substantially enhanced resistance to oxygen scavenging by source/drain contacts, which significantly improves the immunity to threshold voltage (VTH) roll-off at short channel length compared to amorphous In2O3. As a result, high-performance TG long-channel In2O3 transistors are achieved with a high mobility of 163 cm2/V s and a steep subthreshold slope of 64 mV/dec. High-performance TG short-channel In2O3 transistors with high ION of 1650 {\mu}A/{\mu}m at VD of 1 V, large on/off ratio over 1010 and VTH of -0.27 V are demonstrated. These results establish lattice-engineered crystalline In2O3 as an effective strategy for high-mobility, aggressively scaled TG oxide transistors suitable for BEOL-compatible applications.
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All authors Kai Jiang, Chen Wang, Ziheng Wang, Zhiyu Lin, Mengwei Si

Materials Science

Ionic-Radius Mismatch as a Structural Lever for Tuning Phase Transitions and Luminescent Thermometry

A. Javaid, M. Szymczak, A. Sieradzki et al. (+1 more)

The widespread implementation of luminescence thermometers requires a comprehensive understanding of the structural factors governing their thermometric performance. Establishing such structure-property relationships is essential for the rational design of sensing materials with application-tailored characteristics. This is particularly relevant for phase-transition-based luminescence thermometers, which offer exceptionally high relative sensitivities. The systematic analysis of K3Lu(PO4)2:Eu3+ demonstrates that introducing co-dopant ions with a controlled ionic-radius mismatch provides an effective strategy for tailoring phase-transition characteristics. This approach enables both the phase-transition temperature and thermal operating range to be controlled. Specifically, the transition temperature shifts from 210 K for K3Lu(PO4)2:Eu3+ to 310 K for K3Lu(PO4)2:Eu3+,10%La3+, while the operating range broadens from 30 to 60 K. Importantly, linear correlations between the ionic-radius mismatch parameter, {\Omega}, and the phase-transition temperature, enthalpy, and entropy provide a quantitative framework for controlling the thermodynamics of the transition through compositional engineering. Beyond luminescence thermometry, these relationships establish a general strategy for designing materials exhibiting first-order phase transitions with tailored thermodynamic characteristics, opening opportunities for their optimization across a broad range of functional applications.
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All authors A. Javaid, M. Szymczak, A. Sieradzki, L. Marciniak

Materials Science

Re4+ Luminescence as a Highly Sensitive Alternative to Ruby for Optical Pressure Sensing

Yeshan Wu, Maja Szymczak, Lukasz Marciniak et al. (+5 more)

Luminescence-based remote pressure sensing provides a powerful approach for pressure determination under conditions where conventional contact methods are difficult to implement. Although ruby remains the undisputed gold standard among luminescent pressure indicators, its relatively low pressure sensitivity and susceptibility to temperature variations represent important limitations. Therefore, in this work, Cs2HfCl6:Re4+ is proposed as an alternative luminescent pressure indicator exhibiting a 15-fold higher pressure sensitivity (6.93 nm GPa-1) than ruby while maintaining a comparable thermal sensitivity, making it a particularly attractive material for optical manometry. Furthermore, Cs2HfCl6:Re4+ enables ratiometric pressure readout, providing a high relative pressure sensitivity reaching 175.1% GPa-1. To the best of our knowledge, this work represents the first demonstration of Re4+ luminescence for pressure sensing, introducing a new class of luminescent pressure indicators and opening new opportunities for the development of highly sensitive optical manometers based on Re4+-activated materials.
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All authors Yeshan Wu, Maja Szymczak, Lukasz Marciniak, Yifei Yu, Shuailing Ma, Tian Cui, Laihui Luo, Peng Du

Materials Science

Multiple Linear Regression-Enhanced RGB-based Luminescence Thermometry for High-sensitivity Thermal Readout

Y. Abe, M. Szymczak, Miguel A. Hernandez-Rodriguez et al. (+2 more)

The practical implementation of phosphors for luminescence-based thermal sensing and imaging requires simple, user-friendly approaches that enable convenient and sensitive temperature readout. To the best of our knowledge, this is the first demonstration of combining RGB-based thermal imaging using a conventional digital camera with multiple linear regression (MLR) to achieve straightforward and highly sensitive temperature determination and spatially resolved thermal imaging. Importantly, the implementation of the MLR approach enhances the relative sensitivity by more than 3-fold, compared with conventional analysis based solely on the G/R or B/R intensity ratios. The application of Ca3Al2O6:Mn2+-Ce3+ as a luminescent temperature probe, in which the intensity ratio between the Ce3+ and Mn2+ emission bands exhibits a pronounced temperature dependence, enables temperature readout through several complementary approaches. These include conventional luminescence intensity ratio thermometry (SR = 1.46% K-1), analysis of the CIE 1931 chromaticity coordinates (SRx = 0.45% K-1 and SRy = 0.14% K-1), as well as RGB-based thermal sensing and imaging using a digital camera. This multimodal optical response, together with the accessibility of camera-based readout and the substantial sensitivity enhancement enabled by MLR, establishes a practical strategy for spatially resolved luminescence thermometry.
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All authors Y. Abe, M. Szymczak, Miguel A. Hernandez-Rodriguez, M. Runowski, L. Marciniak

Materials Science

Scalable construction of force-constant basis sets for large-scale anharmonic lattice-dynamical calculations

Atsuto Seko and Atsushi Togo

A projector-based formulation of force constants in crystalline materials provides a systematic framework for constructing force-constant bases and determining force constants from force–displacement datasets while rigorously satisfying crystal symmetry, permutation symmetry, and translational invariance. In this work, we develop an efficient eigenvalue solver for projection matrices and integrate it into the projector-based framework. The proposed method substantially reduces the computational cost and enables practical calculations for large-scale systems, low-symmetry crystals, and higher-order force constants that are difficult to treat using conventional approaches. Applications to self-consistent phonon calculations for assessing the grain-boundary excess free energy, lattice thermal conductivity calculations in complex compounds, and fourth-order force-constant estimations demonstrate the efficiency and robustness of the proposed framework for large and complex materials systems.
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Materials Science

Thermally stimulated depolarization in hafnium oxide: experiment and numerical simulation

Yu. N. Novikov, D. E. Temnov, E. A. Volgina et al. (+2 more)

This paper presents an experimental and theoretical study of thermally stimulated depolarization (TSD) in hafnium oxide. Three different models for the probability of trap ionization are considered: the Frenkel effect and two variants of the multiphonon trap ionization mechanism, the multiphonon ionization mechanism of isolated traps at low trap concentrations and phonon-assisted tunneling between neighboring traps at high trap concentrations. The best agreement between the TSD experiment and theory is observed for the multiphonon ionization mechanism of isolated traps. Similar thermal energies of electron and hole traps in HfO2 are obtained ~ 1.3 eV.
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All authors Yu. N. Novikov, D. E. Temnov, E. A. Volgina, M. S. Lebedev, V. A. Gritsenko

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

1D Interface-Induced Real-Space Berry Curvature Gradient Encoded in SpinValley-Coupled Nonlinear Photocurrent in Lateral Heterostructure

Suman Kumar Chakraborty, Jinu James, Biswajeet Nayak et al. (+6 more)

Symmetry breaking enables helicity-dependent optoelectronic responses in quantum materials. In two-dimensional transition-metal dichalcogenides (TMDs), circular photocurrent (CPC) is typically observed under oblique illumination via the circular photon drag effect, while realization of the intrinsic circular photogalvanic effect (CPGE) under normal incidence remains challenging. Here, we report a clear signature of CPGE in chemical vapor deposition-grown monolayer 2D lateral heterostructure (LHS). By probing the nonlocal photocurrent across the 1D hetero-interface, we observe a helicity-dependent photocurrent consistent with a spin-valley-coupled CPGE-dominated mechanism driven by interface-induced Berry-curvature asymmetry, i.e., Berry curvature dipole. Spatially and spectrally resolved measurements under selective excitation of the MoSe2, WSe2, and the interface regions exhibit distinct magnitudes and polarities of the CPG responses. These contrasting behaviors highlight the opposite spin-valley dichroism for MoSe2 and WSe2, as well as enhanced valley mixing at the 1D interface. Our findings establish LHS as a robust platform for realizing a hetero-interface-induced CPGE-like response and highlight its potential for valleytronics and optospintronics.
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All authors Suman Kumar Chakraborty, Jinu James, Biswajeet Nayak, David Tebbe, Purbasha Ray, Christoph Stampfer, Bernd Beschoten, Lutz Waldecker, Prasana Kumar Sahoo

Materials Science

Quantitative control and recording of materials-synthesis processes using an automated experimentation platform

Yusuke Hashimoto, Takaya Muramoto, Hikari Terada et al. (+3 more)

Data-driven materials development requires the collection of large amounts of high-quality materials data. Full autonomy of materials experiments is anticipated, but its technical hurdles are high and its adoption remains limited. In this study, we constructed a simple, easy-to-deploy automated experimentation platform that focuses not on full autonomy but on the reliable automation and quantitative recording of experimental processes. Specifically, commercially available instruments such as robot arms, electric pipettes, web cameras, and an electronic balance are combined, components such as fixtures are fabricated with a 3D printer, and the instruments are operated by control code generated by an AI agent based on a large language model. As a demonstration, we applied the platform to a two-solution mixing experimental system and synthesized ZIF-8, a metal-organic framework. A white suspension phase was observed in the product, and X-ray diffraction measurements confirmed that it was ZIF-8. We also found that its particle size distribution depends strongly on the solution dispensing speed of the electric pipette, which is a parameter that is difficult to control or record in manual operation. This dependence was reproduced in repeated runs, confirming the repeatability of the automated synthesis. This result is a good example showing that the control and recording of process parameters that are rarely quantified in manual work can govern the quality of materials data. All control code, CAD models, and documentation are made publicly available to encourage the spread of laboratory-scale automation of experiments.
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All authors Yusuke Hashimoto, Takaya Muramoto, Hikari Terada, Harim Song, Yuan Wang, Takaaki Tomai

Materials Science

Machine Learning Guided CALPHAD Design of Ru-Stabilized BCC B2 Refractory Alloys

Nathan Peterson, Avik Mahata, Nick Beaver et al. (+1 more)

Refractory alloys with a ductile body-centered-cubic (BCC) matrix strengthened by ordered B2 precipitates offer a high-temperature analogue to the gamma/gamma-prime architecture of Ni-based superalloys. Ruthenium is particularly attractive as a B2 stabilizer because RuHf, RuZr, and RuTi can retain ordered phases well above 1300 C. In this work, equilibrium CALPHAD calculations were coupled with random-forest-guided active learning to explore a ten-element Nb-based, Ru-bearing composition space containing Nb, Ta, Mo, V, Ru, Ti, Zr, Hf, Al, and Y at 1 at.% resolution. Across 500 CALPHAD-evaluated alloys, the calculations reproduced the principal trends reported for the Ru-B2 design space. RuHf and RuZr remained stable to the solidus, RuTi commonly exhibited a solutionizing window, and Al-containing alloys preferentially formed competing sigma and A15 phases. The upper bound of the BCC+B2 field increased from a median of approximately 1570 C at 5 at.% Ru to approximately 1980 C near 9-10 at.% Ru. Among the group-IV additions, Hf, Zr, and Ti produced progressively lower two-phase stability. Re-screening using physically motivated criteria identified 100 alloys satisfying requirements for high-temperature BCC+B2 stability, absence of liquid, phase purity, and appropriate secondary-phase fraction, including 19 Ru-lean compositions and two independently reported HfRu-B2 alloys. The results establish practical compositional design rules for Ru-stabilized dual-phase refractory alloys and identify phase-specific BCC/B2 lattice misfit as a key target for future design cycles.
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All authors Nathan Peterson, Avik Mahata, Nick Beaver, Mohsen Kivy

Materials Science

Neural-Network Solutions to Real-Space Charge Density and Generalization

Yuxuan Zeng, Tong Xie, Taoyuze Lv et al. (+1 more)

The Hohenberg-Kohn theorem establishes that, in principle, the ground state (GS) charge density contains all GS information of a many-electron system, such that all GS observables can be expressed as functionals of the GS charge density. Conventional Kohn-Sham density functional theory requires iterative solution of the self-consistent-field equations at substantial computational cost, motivating the development of deep learning surrogates for electronic structure calculations and, in turn, accelerating computer-aided materials design. Here, we propose AIDEN, an Atomic-Interaction Density Equivariant Network for solving real-space charge density. AIDEN separates the element-dependent one-center density from environment-induced density redistribution and represents the latter through complementary atom- and edge-centered tensor correlations. A continuous low-rank Gaussian decoder then reconstructs the density at arbitrary spatial coordinates while reusing atomic encodings independently of the evaluation grid. AIDEN achieves state-of-the-art accuracy on periodic crystal benchmarks while remaining competitive for molecular systems, and further demonstrates zero-shot transferability across several structurally distinct out-of-distribution case studies. Furthermore, AIDEN provides substantially faster inference than both baseline models and full SCF calculations, enabling efficient charge density reconstruction for large-scale electronic structure calculations.
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All authors Yuxuan Zeng, Tong Xie, Taoyuze Lv, Zhicheng Zhong

Sunday 13 September

Materials Science

Predicting energy and structural response to force correction in molecular dynamics

Peng Kang, Da Wan, Shulin Bai et al. (+7 more)

We predict how force correction changes energy exchange and structural statistics by measuring leading response coefficients on shared reference trajectories. Residual power and the displacement virial distinguish the transfer of energy from the change in restoring forces, including intermittent reference updates. Independent simulations then test the predicted kinetic and configurational shifts. A matched-timetable experiment shows that reference timing affects heating through its coupling to the evolving state. In an anharmonic chain, the displacement virial predicts a structural shift missed by a power-only description. Local force constants in silicon predict a complementary directional tradeoff: scalar calibration repairs optical motion while degrading an already accurate low-frequency direction. Full nonlinear trajectories confirm this tradeoff and distinguish the benefits of static curvature correction and repeated reference impulses. Independent finite-temperature integrals in orthorhombic tin selenide (SnSe) support the configurational-response direction predicted from separate reference calculations. These results provide a physical basis for choosing how reference information enters molecular dynamics. The framework assesses force correction through its effect on atomic motion and statistical observables, beyond the accuracy of individual force evaluations.
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All authors Peng Kang, Da Wan, Shulin Bai, Pengfei Zhang, Peng Wang, Chenglong Wen, Zhen Li, Yu Liu, Lei Zheng, Li-Dong Zhao

Materials Science

Prescreening Point Defects in Semiconductors With Machine Learning

Paul Karlsson, Joel Davidsson and Rickard Armiento

High-throughput calculations using density-functional theory (DFT) are commonly used to explore point defects for applications in power electronics and quantum technologies. There is currently a major shift away from these traditional simulation techniques towards machine learning (ML) methods. We explore a class of physics-guided ML models for predicting defect formation energies and zero-phonon lines (ZPL) to identify point defects for quantum applications. The models are specifically targeted for use in a prescreening step for accelerated high-throughput workflows, and are therefore designed to avoid the costly relaxation step typically present with ML interatomic potentials (MLIPs). We compare performance for single and double point defect systems in 4H-SiC with ridge, kernel ridge, and multilayer perceptron (MLP) models using three different descriptors representing the defect systems. For vacancies and substitutions, the optimized models give mean absolute errors (MAEs) of 0.437 eV for the formation energy and 0.202 eV for ZPLs, which is just above the level at which such predictions can be useful even beyond the targeted prescreening, i.e., in some applications they may completely replace the need for costly DFT calculations. For interstitials the MAEs are larger, 1.101 eV for the formation energy and 0.230 eV for the ZPL, which, while still useful for prescreening, will not generally be useful for more detailed characterization. Hence, while the results may be further improved by model design and optimization, the models presented in this work are already useful for prescreening in high-throughput characterization of point defects.
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Materials Science · Cross-listed from cond-mat.str-el

The Propagating Nature of Single- and Multimagnons in LaCrO$_3$

Masoud Lazemi, Fabian J. Mohammad, Ellen M. Kiens et al. (+6 more)

The dispersion of an excitation is commonly used to infer its microscopic character: dispersive modes are associated with propagation, whereas nondispersive features are often interpreted as localized. This distinction becomes less straightforward for composite excitations, whose spectral maxima can remain nearly dispersionless even when they are built from propagating quasiparticles. Here we use momentum- and temperature-dependent resonant inelastic X-ray scattering (RIXS) to reveal the origin of multimagnon excitations in antiferromagnetic LaCrO$_3$. Whereas the single magnon disperses strongly, the two- and three-magnon features remain nearly flat. On approaching the Neel temperature, thermal population of the magnon band produces an anti-Stokes branch and opens an additional three-magnon channel involving the creation of two magnons and annihilation of one. Its energy and momentum dependence are reproduced by a thermally weighted multimagnon joint density of states calculations. These results establish thermal population as a means of exposing the propagating constituents hidden within nondispersive composite excitations, and position RIXS as a probe of multimagnon dynamics and, ultimately, magnon-magnon interactions.
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All authors Masoud Lazemi, Fabian J. Mohammad, Ellen M. Kiens, Yorick A. Birkhölzer, Paras Mehta, Emma van der Minne, Stefano Agrestini, Frank M.F. de Groot, Hebatalla Elnaggar

Materials Science · Cross-listed from cs.CE

A property-registry contract for retrieve-or-refuse thermal-mechanical lattice search

Shaoliang Yang, Henry Chu, Zu Yashengjiang et al. (+1 more)

Early thermal-mechanical lattice requirements are knowledge-intensive and often jointly unsatisfiable: an engineer asks for a cell that is light, stiff, laterally conducting and cheap, and no cell in the library satisfies it. A design system should say so, and say which requirement to loosen and by how much, rather than return the nearest row. A generative model can return a candidate even when the library holds none. This work applies established conflict diagnosis to a catalogue of homogenised properties. Search over 1,397 homogenised unit cells and 19 base materials (26,543 combinations) returns a catalogue row that a second solver can rebuild, or, for an empty feasible set of at most eight constraints, inclusion-minimal unsatisfiable subsets (MUS) and the slack of a repair, not a neighbour. One registry declaration generates the prompt and the evaluator, so undeclared parsed keys cannot reach search. On a frozen suite of 64 typed queries, retrieve-or-refuse matches min-repair on every feasible query (48/48) and refuses every empty one (16/16) with MUS and slack. Constraint-ignoring nearest-neighbour and penalty search violate stated cost or density limits. On 216 empty queries, repairs printed at three significant figures and rounded outward stay feasible in every case (216/216). When density and cost must be kept, a list of minimum-cardinality repairs keeps them on 209 of 211 queries; a protection-first repair keeps them on all 211, the same as full diagnosis. A 308-request parse benchmark is a template-text check, not unconstrained engineer prose.
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All authors Shaoliang Yang, Henry Chu, Zu Yashengjiang, Jun Wang

Materials Science

Colossal magnetostriction effect in rare-earth orthoferrites

Moumita Das, Arup Ghosh, Moumita Nandi et al. (+3 more)

Within the entire gamut of magnetostrictive, piezomagnetic, and ferromagnetic shape memory alloy systems, the striction effect is found to vary from a few tens of parts per million to a few percent. Here, we report the observation of an unprecedentedly large magnetic-field-induced lattice strain along the $c$ axis (more than 60-100% at 90 kOe field) in single crystals of orthorhombic $R$FeO$_3$ ($R$ = Dy, Ho) below their spin-reorientation transition temperature $T_{SR}$. However, the striction effect is two orders of magnitude smaller along the $a$ and $b$ axes. Like magnetostriction, the magnetodielectric effect is highly anisotropic and very large along the $c$ axis. Such gigantic striction and dielectric effects along the $c$ axis arise as a result of a magnetic-field-induced first-order structural phase transition which possibly stems from large spin-orbit coupling (and, thereby, enormous magnetocrystalline anisotropy). The observed colossal striction in rare-earth orthoferrites could open new opportunities for applications requiring large, reversible magnetic-field-induced strain.
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All authors Moumita Das, Arup Ghosh, Moumita Nandi, Arumugam Thamizhavel, Dipten Bhattacharya, Prabhat Mandal

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

Rhombohedral Multilayer Graphene as a $p$-Wave Magnet

Rintaro Eto and Johannes Knolle

We propose rhombohedral multilayer graphene in an applied in-plane magnetic field as a highly tunable platform for nonrelativistic collinear $p$-wave magnetism. The orbital coupling to the magnetic field breaks time-reversal symmetry and, together with interaction-driven layer antiferromagnetism, generates an odd-in-momentum spin splitting without relying on spin-orbit coupling. Using a minimal low-energy effective theory, we show that the resulting $p$-wave spin splitting is strongly enhanced with increasing layer number. This enhancement originates from the surface-localized nature of the low-energy states and their layer-dependent orbital coupling to the in-plane field. The Zeeman coupling only weakly perturbs this predominantly orbital-field-induced mechanism. We further estimate stability of the $p$-wave magnetism under hole-doping and distinct transport signature using a more realistic Hubbard model. Our results establish orbital coupling to an external magnetic field as a controllable route to odd-parity spin splitting in collinear magnets.
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Materials Science

Misfit-dislocation hierarchy governs sliding of asymmetric non-CSL grain boundaries

Kunqing Ding, Yazhuo Liu, Yin Zhang et al. (+3 more)

Grain boundaries (GBs) strongly affect the mechanical response of polycrystalline materials, yet most atomistic studies have focused on coincidence site lattice (CSL) boundaries. Motivated by in situ atomic-resolution observations, we investigate step-free sliding along asymmetric non-CSL tilt GBs in face-centered cubic (FCC) metals using atomistic modeling. In these incommensurate GBs, a dense array of non-glissile primary misfit dislocations accommodates local interfacial mismatch, whereas a more widely spaced array of glissile secondary misfit dislocations accommodates residual mismatch. Uniform-sliding calculations reveal two distinct quantities: the minimum GB structural periodicity {\lambda}, defined by the repeating arrangement of primary GB misfit dislocations, and the slip vector b, corresponding to the minimum displacement-shift-complete translation that restores an equivalent GB structure. Nonuniform sliding proceeds through the glide of secondary GB misfit dislocations, which carry b and transform successive boundary segments between crystallographically equivalent translation states. The characteristic spacing between secondary misfit dislocations defines a longer periodicity {\Lambda}. For the representative {331}/{111} GB, each secondary misfit dislocation glides through a thermally activated two-step kink-pair mechanism below the athermal stress, advancing by one structural period {\lambda}. These results establish a unified crystallographic and dislocation-based framework for understanding stress-driven sliding in structurally complex asymmetric GBs.
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All authors Kunqing Ding, Yazhuo Liu, Yin Zhang, Lihua Wang, Xiaodong Han, Ting Zhu

Materials Science

Origins of Pressure-Enhanced Thermal Transport in Organic Semiconductors

Lukas Legenstein, Sandro Wieser, Michele Simoncelli et al. (+1 more)

While pressure is known to dramatically alter the electronic properties of organic semiconductors, its impact on their thermal conductivity remains poorly understood. We combine machine learned potentials with the Wigner transport equation to compute the pressure-dependent thermal conductivity of crystalline naphthalene as a model system. When high-pressure reference data are included in the training, our simulations quantitatively reproduce the experimentally observed dramatic increase in thermal conductivity for compressed naphthalene. Most importantly, our results reveal the microscopic origin of this massive enhancement: pressure stiffens especially the intermolecular bonds, increasing the group velocities of heat-carrying phonons and simultaneously suppressing the scattering that impedes intraband (propagation) thermal transport. In contrast, interband (tunneling) transport is relatively weakened by a reduced spectral overlap between different phonon bands. These findings provide fundamental insights into heat conduction in soft molecular materials and suggest that strengthening intermolecular interactions, here, via applying pressure can be used to tune thermal transport in molecular crystals.
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All authors Lukas Legenstein, Sandro Wieser, Michele Simoncelli, Egbert Zojer

Materials Science

Binder chemistry sets the interfacial balance constant in CsPbBr$_3$ nanocrystal supercapacitor electrodes

Arun Kumar and Monojit Bag

Previous work on lead-free tin halide perovskites showed that the binder instead sets the electrolyte concentration at which capacitance is maximised, following the relationship $100 \times [\mathrm{Li}^+]_{\mathrm{opt}} + \mathrm{PVDF}_{\mathrm{wt}\%} = \xi_{\mathrm{Int}}$ with $\xi_{\mathrm{Int}} = 25 \pm 2.5$, established by varying the loading of a single polymer. Whether $\xi_{\mathrm{Int}}$ is universal or specific to that polymer has not been tested. Here, four binders spanning fluorinated (PVDF), carboxylic (PAA), cellulosic (CMC) and sulfonic (PEDOT:PSS) chemistry are compared on $\mathrm{CsPbBr_3}$ nanocrystal electrodes at four LiTFSI concentrations in acetonitrile, with binder loading fixed at 15 wt% and all other formulation variables held constant. The relationship applies to $\mathrm{CsPbBr_3}$: PVDF at 15 wt% gives an optimum at 0.10–0.15 M and 112 F g$^{-1}$, against 126 F g$^{-1}$ reported for $\mathrm{CsSnCl_3}$ under the same conditions, extending the result to a different B-site cation, halide and crystal system. PVDF and CMC optimise at 0.10 M, giving $\xi_{\mathrm{Int}} = 25$, while PAA and PEDOT:PSS optimise at 0.15 M, giving $\xi_{\mathrm{Int}} = 30$, with maximum values of 188 F g$^{-1}$ for PAA and 146 mF cm$^{-2}$ for PEDOT:PSS. The two binders showing the shift carry ionisable acid groups at high density, indicating that $\xi_{\mathrm{Int}}$ expressed in weight percent requires a binder-specific value. In all four electrodes, $\mathrm{CsPbBr_3}$ converts to $\mathrm{PbBr_2}$ and CsBr during electrochemical characterisation, and the surface lead content of the PEDOT:PSS electrode decreases.
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Materials Science · Cross-listed from cond-mat.stat-mech

A New Framework for Interfacial Statistics: Exact n-Point Correlations of Gaussian Level Sets

Aleksei M. Cherkasov, Kirill M. Gerke and Aleksey Khlyupin

We derive exact analytical expressions for higher-order correlations of Gaussian level-set interfaces, establishing a direct link between bulk field statistics and interface geometry. This framework enables efficient reconstruction of disordered media, detailed modeling of {Gaussian foams}—structured, double-thresholded interfaces with tunable morphology—and analysis of {memory-enhanced anisotropy} reflecting directional persistence in surface structure. These results open new possibilities for characterizing complex transport, guiding stochastic reconstructions, designing materials with desired properties, quantifying the information content of correlation functions and modelling directional processes on irregular boundaries.
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Materials Science · Cross-listed from cond-mat.soft

Anisotropic Nanoparticle Rejamming Triggers Thermodynamic Cavitation in Elastomer Nanocomposites

Harshad Bhapkar, Pierre Kawak and David S. Simmons

Nanoparticles can dramatically reinforce elastomers while paradoxically causing cavitation at lower strains. Despite decades of research, the microscopic origin of this behavior has remained unsettled. Here, molecular dynamics simulations reveal that cavitation and failure arise from the nanoparticulate reinforcement mechanism itself. Initial jamming of the nanoparticulate network leads to a buildup of negative pressure in the elastomer matrix, reinforcing it and simultaneously driving it towards a cavitation limit. This crisis is initially averted by yield of the particle network. However, an anisotropic rejamming event of the nanoparticles ultimately drives a runaway negative pressure buildup that leads to cavitation and failure. These results identify nanoparticle-network-induced thermodynamic cavitation as the origin of void formation in elastomeric nanocomposites, and they establish collective filler dynamics as a potential point of control of ultimate failure.
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Materials Science

Contribution of photogenerated charge carriers to photothermal effect in optically opaque semiconductor samples

Milica Dragas, Slobodanka Galovic and Katarina Djordjevic

As a consequence of laser radiation absorption, the photothermal response of semiconductors is governed by both the thermalization of the crystal lattice and the dynamics of photogenerated charge carriers. This carrier-related contribution leaves a characteristic signature in the temperature field through carrier diffusion and recombination, making the photothermal response sensitive to electronic transport and recombination properties. This sensitivity provides the basis for using photothermal methods to characterize the electronic properties of semiconductors. In this paper, we develop a theoretical model of the photothermal response of moderately doped opaque semiconductors under harmonically modulated laser excitation, accounting for the generation, diffusion, and recombination of minority charge carriers. We analyze how carrier lifetime, diffusion length, and surface recombination velocity affect the resulting temperature field and, consequently, the photothermal signal. In particular, we show that the thermal contribution associated with carrier recombination remains nonzero even when the surface recombination rate vanishes and for short carrier lifetimes, demonstrating that the signature of photogenerated carriers may persist under conditions where their contribution might otherwise be expected to become negligible. The results provide guidance for both the design and interpretation of photothermal and photoacoustic experiments, including the choice of modulation frequency and detection geometry, to enhance the sensitivity to carrier-related thermal signatures and improve the determination of electronic properties of semiconductor materials and devices.
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Materials Science · Cross-listed from cond-mat.soft

Dynamical Anisotropy of a Colloidal Glass Under Pressure

Shengyun Shi, Li Tian and Bo Li

Pressure is a critical thermodynamic parameter that profoundly influences the physical properties of glasses. Pressure-induced densification and structural transformation endow glasses manufactured under such conditions with exceptional mechanical and optical properties. Although pressure-treated glasses have been characterized by ensemble-averaged methods such as X-ray diffraction and Raman spectroscopy, their microscopic dynamics have rarely been addressed, limiting our understanding of the coupling among structure, dynamics, and mechanics. Here, using a binary hard-sphere colloidal glass confined in cylindrical capillary tubes, we impose a constant pressure on the particles through the tangential component of gravity. This approach enables the first investigation of pressure effects on colloidal glasses. We find that the dynamics are substantially frozen, whereas the structural change remains comparatively mild. At low pressure, spatial correlations among structural, dynamical, and local elastic heterogeneities are observed. Remarkably, dynamical anisotropy emerges in response to pressure, characterized by faster motion parallel to the pressure direction than perpendicular to it. This anisotropy is attributed to an instability induced by the strong pressure force. Concurrently, structural and dynamical heterogeneities are strongly suppressed under pressure. Our experiments characterize the microscopic dynamics of colloidal glasses under pressure and offer design principles for the manufacturing protocol of glass materials.
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Materials Science

4DMulti: automated multicomponent identification at complex material interfaces

Haoran Zhang, Zian Mao, Shufen Chu et al. (+6 more)

Mapping crystalline phases at heterogeneous interfaces is essential for understanding material performance and degradation. However, structural heterogeneity, phase overlap, and local disorder complicate diffraction interpretation, while growing data volumes make manual analysis increasingly impractical. We introduce 4DMulti, a physics-guided learning framework for automated multicomponent identification from large-scale four-dimensional scanning transmission electron microscopy (4D-STEM) data. The supporting diffraction data resource comprises over 6 million high-quality experimental patterns and labeled patterns generated by Sim2real. A retrieval-conditioned latent diffusion transformer (Sim2real) translates simulated patterns into experimental-style examples under constraints designed to preserve Bragg geometry, while a rotation-invariant coordinate convolutional network identifies phases across in-plane rotations. 4DMulti achieves 98.82% classification accuracy on a five-phase experimental nanoparticle benchmark, with ablation studies supporting the complementary benefits of domain adaptation and rotation-invariant classification. We define diffraction-inferred structural complexity (DISC), a normalized predictive entropy score that quantifies phase-assignment ambiguity within a specified candidate phase library. We apply 4DMulti to generate structural maps of superconducting heterostructures, corroded alloy surfaces, and degraded solid-state battery interfaces down to single-nanometer spatial resolution. 4DMulti connects simulation-derived crystallographic knowledge to automated experimental interpretation, establishing a foundation for scalable analysis of complex interfaces and data-driven discovery of interfacial design principles.
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All authors Haoran Zhang, Zian Mao, Shufen Chu, Xiaoya He, Yuyan Guan, Antong Yang, Mingze Li, Xiaoqin Zeng, Yujun Xie

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

Spectral density of angular momentum transfer from a swift electron to a large spherical nanoparticle

Jorge Luis Briseño-Gómez and Alejandro Reyes-Coronado

Swift electrons in scanning transmission electron microscopy transfer both linear and angular momentum to nanoparticles, underlying electron-beam-driven nanoscale manipulation ("electron tweezers"). Prior theory relied either on the small-particle (dipolar) approximation, valid only well below experimentally relevant sizes, or on frequency-integrated multipolar calculations that leave the spectral structure of the interaction unresolved. Here we present a fully retarded, causal, multipole-converged electrodynamical methodology for the angular momentum transfer from a swift electron to an isolated spherical nanoparticle, based on a closed-surface Maxwell stress tensor formulation whose angular integrals reduce analytically to a small, material- and trajectory-independent set of irreducible integrals over associated Legendre functions. This lowers the cost of the double multipolar sum, enabling convergence up to l_max=51 for nanoparticles as large as a=50 nm, nearly four times the order of the largest previous calculation at this size and previously unreached for an optically complex, interband-dominated material. Applied to aluminum and gold nanoparticles up to a=50 nm, the method resolves the transfer spectral density across the full frequency domain, showing it is set by interference between the electron field and the field scattered by the nanoparticle, which dominates the scattered-scattered contribution at essentially every frequency; the electric contribution dominates at moderate speeds, but the magnetic contribution, of the same sign, grows steadily in relative weight with electron speed, from a few percent of the total at v = 0.5c to between a quarter and a half of it at v = 0.95c for trajectories passing close to the nanoparticle surface.
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Materials Science

Interfacial Engineering Enabled High-Resolution Stretchable Metal-Level Conductive Lines and Transparent Conductor

Ke Chen, Eric Tianjiao Zhao, Weichen Wang et al. (+16 more)

As stretchable electronics advance toward higher integration density and finer feature sizes, stretchable conductors, which serve as the architectural backbone of these electronics, must be scaled down accordingly. However, achieving both high stretchability and high electrical conductivity at high resolution remains a challenge using existing conductive materials. Here, through material design and interfacial engineering, we develop a thiol-functionalized conducting polymer/gold hybrid stack that can be patterned down to 4 micrometer linewidths using standard photolithography, while maintaining high stretchability, metal-like conductivity (>40,000 S/cm), and environmental stability. Leveraging this capability, we demonstrate grid-based stretchable transparent electrodes that surpass the figure-of-merit of indium tin oxide, as well as a 1000-pixel-per-inch image interconnected with stretchable lines. This work helps to broaden the scope of next-generation functional soft electronics, including e-skins and bioelectronics.
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All authors Ke Chen, Eric Tianjiao Zhao, Weichen Wang, Yepin Zhao, Kostas Parkatzidis, Lukas Michalek, Yuran Shi, Elizabeth Zhang, Tianyang Chen, Ruiheng Wu, Hao Lyu, Yating Yao, Yujia Yuan, Tianhao Chen, Ruby Rong Zhou, Shiyuan Wei, Junyi Zhao, Jeffrey B.-H. Tok, Zhenan Bao