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Physics Condensed Matter Materials Science

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Monday 1 December

Materials Science

Microscopic origin of the spin-splitting in altermagnets

Suyoung Lee, Minjae Kim and Changyoung Kim

Altermagnets, characterized by spin-split bands without net magnetization, have recently emerged as a promising platform for spintronics. However, their microscopic mechanisms remain elusive, often relying on abstract group theory. In this work, we present an intuitive and pedagogical framework to understand the origin of spin splitting in altermagnets. We identify two essential ingredients: (1) alternating spin-polarized wavefunction localization on sublattices, and (2) broken translational symmetry caused by distortions in non-magnetic ion cages. We discuss a minimal model Hamiltonian based on an atomic exchange-driven spin splitting and anisotropic hopping that captures these effects and reproduces the hallmark features of altermagnetic band structures, including nodal spin degeneracies and large spin splittings. Our model is further validated by ab initio calculations on MnF2. By demystifying the microscopic origins of altermagnetism, our work bridges symmetry analysis and material realizations, shedding light on practical designs of altermagnetic spintronic devices.
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Sunday 30 November

Materials Science

Aging-driven in situ polymerization of FEC additive boosts the calendar-life of silicon anodes via surface passivation enhancement

Sattajit Barua, Rownak J. Mou and Koffi P. C. Yao

The role of additives such as FEC in extending the calendar life of silicon anodes beyond the cycling benefits is still not fully understood. Herein, the calendar life of high-loading Si (80 wt%) using baseline 1.2 M LiPF6 in EC-EMC electrolyte versus adding 10 wt% FEC is investigated over months. Over 8 days of aging, FEC leads to a 13-fold reduction in irreversible capacity loss in Si-LiFePO4 full cells. Cells without FEC are projected to fall below 80% of their initial capacity within approx. 22 days versus approx. 279 days with FEC. Symmetric Si-Si cells from harvested electrodes show greater increase in interphase resistance without FEC, whereby an increase of 10.81 Ohms is measured for 0 wt% FEC vs. only 3.37 Ohms for 10 wt% FEC over 2 months. Power law modeling of this long-term interphase resistance finds mixed transport-reaction growth behavior in FEC-free cells, suggesting significant dissolution, whereas cells with 10 wt% FEC added display a diffusion-controlled impedance growth behavior, suggesting a robust surface passivation film. Post-mortem FTIR and XPS confirm polycarbonate enrichment of the SEI, which was discovered to predominantly emerge from FEC self-polymerization during the idle aging. When the Si electrodes aged with and without FEC are harvested and reassembled into full cells with the same electrolytes used at aging, the first-cycle coulombic efficiency is 71% for 0 wt% FEC versus 97% for 10 wt% FEC. Subsequent cycling maintains over 99.7% CE with 10 wt% FEC, surpassing the pre-aging CE of 98.8%. This elevated CE indicates better passivation provided by the polymer fragments formed during aging compared to electrochemically formed SEI where no strong polymer FTIR signal is found. The self-polymerization during idle aging with additives such as FEC is therefore an opportune in situ mechanism to further engineer in extending the life of Si-based batteries.
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2512.01084 · 30 Nov · 7 Main Manuscript and 9 Supporting Information figures. Work funded by U.S Department of Energy. Li-Ion battery material research. Silicon anodes. Calendar Aging of Silicon Anodes in presence of electrolyte additives. Novel insights into the calendar aging of silicon due to internal passivation via polymerization of Fluoroethylene Carbonate during open-circuit aging

Abstract PDF $CELL ×6$POLY ×2$DIFF ×1

Materials Science

Building Trustworthy AI for Materials Discovery: From Autonomous Laboratories to Z-scores

Benhour Amirian, Ashley S. Dale, Sergei Kalinin et al. (+1 more)

Accelerated material discovery increasingly relies on artificial intelligence and machine learning, collectively termed "AI/ML". A key challenge in using AI is ensuring that human scientists trust the models are valid and reliable. Accordingly, we define a trustworthy AI framework GIFTERS for materials science and discovery to evaluate whether reported machine learning methods are generalizable, interpretable, fair, transparent, explainable, robust, and stable. Through a critical literature review, we highlight that these are the trustworthiness principles most valued by the materials discovery community. However, we also find that comprehensive approaches to trustworthiness are rarely reported; this is quantified by a median GIFTERS score of 5/7. We observe that Bayesian studies frequently omit fair data practices, while non-Bayesian studies most frequently omit interpretability. Finally, we identify approaches for improving trustworthiness methods in artificial intelligence and machine learning for materials science by considering work accomplished in other scientific disciplines such as healthcare, climate science, and natural language processing with an emphasis on methods that may transfer to materials discovery experiments. By combining these observations, we highlight the necessity of human-in-the-loop, and integrated approaches to bridge the gap between trustworthiness and uncertainty quantification for future directions of materials science research. This ensures that AI/ML methods not only accelerate discovery, but also meet ethical and scientific norms established by the materials discovery community. This work provides a road map for developing trustworthy artificial intelligence systems that will accurately and confidently enable material discovery.
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All authors Benhour Amirian, Ashley S. Dale, Sergei Kalinin, Jason Hattrick-Simpers

Materials Science

First-Principles Investigation of X2NiH6 (X = Ca, Sr, Ba) Hydrides for Hydrogen Storage Applications

K. Aafi, Z. El Fatouaki, A. Jabar et al. (+2 more)

First-principles DFT calculations on the hydrides Ca2NiH6, Sr2NiH6, and Ba2NiH6 reveal key thermodynamic properties. These compounds exhibit increasing entropy and heat capacity with temperature, and are thermodynamically stable at elevated temperatures due to negative free energies. The kinetics of hydrogen storage is influenced by entropy changes during hydrogen adsorption and desorption. Optically, Ba2NiH6 shows a high refractive index at low energies. Mechanical assessments indicate Sr2NiH6 is incompressible with moderate malleability, Ca2NiH6 has the highest resistance to deformation, while Ba2NiH6 is most compressible. Formation energies and hydrogen storage capacities (4.005 wt% for Ca2NiH6, 2.548 wt% for Sr2NiH6, and 1.750 wt% for Ba2NiH6) highlight Ca2NiH6 as the most promising candidate for hydrogen storage technology.
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All authors K. Aafi, Z. El Fatouaki, A. Jabar, A. Tahiri, M. Idiri

2512.01072 · 30 Nov · We kindly request the withdrawal of our manuscript from arXiv. After submission, we determined that the paper requires significant revisions and further validation of the results. In order to ensure scientific accuracy and maintain the quality of our work, we prefer to withdraw the current version and plan to submit a revised manuscript in the future

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Materials Science

On The Finetuning of MLIPs Through the Lens of Iterated Maps With BPTT

Evan Dramko, Yizhi Zhu, Aleksandar Krivokapic et al. (+4 more)

Accurate structural relaxation is critical for advanced materials design. Traditional approaches built on physics-derived first-principles calculations are computationally expensive, motivating the creation of machine-learning interatomic potentials (MLIPs), which strive to faithfully reproduce first-principles computed forces. We propose a fine-tuning method to be used on a pretrained MLIP in which we create a fully-differentiable end-to-end simulation loop that optimizes the predicted final structures directly. Trajectories are unrolled and gradients are tracked through the entire relaxation. We show that this method consistently improves performance across all evaluated pretrained models; resulting in an average of roughly 32% reduction in prediction error. Interestingly, we show the process is robust to substantial variation in the relaxation setup, achieving negligibly different results across varied hyperparameter and procedural modifications.
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All authors Evan Dramko, Yizhi Zhu, Aleksandar Krivokapic, Geoffroy Hautier, Thomas Reps, Christopher Jermaine, Anastasios Kyrillidis

Materials Science

Second-Order Jahn-Teller Distortions and Dynamic Lattice Polarizability as the Origin of Broadband Emission in Bi3+-Doped Cs2SnCl6

Shruti Prasad, Pabitra Kumar Nayak and Dibyajyoti Ghosh

Lead-free vacancy-ordered perovskites (VOHPs) such as Cs2SnCl6 have emerged as promising materials for optoelectronic applications but typically suffer from wide band gaps and low photoluminescence quantum yields (PLQY). In this work, the electronic origins of broadband blue emission in Bi3+-doped Cs2SnCl6 are elucidated by combining density functional theory (DFT) calculations and ab initio molecular dynamics simulations. The study systematically explores the spatial configurations of Bi3+ dopants and Cl-vacancies, assessing their impact on structural and electronic properties. Results demonstrate that the formation of square pyramidal BiCl5(2-) units serves as efficient exciton traps, fundamentally enabling strong luminescence in an otherwise non-emitting host. The Bi3+ 6s2 lone pair in an asymmetric coordination environment drives second-order Jahn-Teller distortions, creating a highly polarizable local lattice. This softness, in contrast to the rigid SnCl6(2-) framework, produces heterogeneous distributions of bond lengths, bond angles, and band edges around dopant sites. Defect-induced states strongly localize charge carriers, while coupling to vibrational modes at 300 K dynamically broadens the band edges, accounting for the large Stokes shift and broadband photoluminescence. These results establish lone-pair-driven Jahn-Teller distortions and lattice heterogeneity as key design principles for efficient luminescence in lead-free perovskites.
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Materials Science

Crystalyse: a multi-tool agent for materials design

Ryan Nduma, Hyunsoo Park and Aron Walsh

We present Crystalyse, an open, provenance-enforced scientific agent for computational materials design of inorganic crystals that orchestrates tools for compositional screening, crystal structure generation, and machine-learning force-field evaluation. Crystalyse offers three operating modes to trade exploration speed against validation depth: creative (rapid query), adaptive (context-aware routing) and rigorous (comprehensive checks). We release the underlying source code and evaluation scripts to enable plug-and-play use and development. In demonstrations on quaternary oxide exploration, sodium-ion cathode design, and lead-free indoor photovoltaic candidate generation, the agent integrates chemical compound generation with fast stability and property filters. Under adversarial testing, provenance enforcement eliminated material-property hallucinations (a broad adversarial suite pass rate reached 86% from a 57% baseline). Crystalyse provides an agentic artificial intelligence system that can complement existing materials design pipelines, assisting in hypothesis generation while preserving transparency and reproducibility.
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Materials Science

Observation of hidden altermagnetism in Cs$_{1-\delta}$V$_2$Te$_2$O

Guowei Yang, Ruihan Chen, Changchao Liu et al. (+25 more)

Altermagnets are characterized by anisotropic band/spin splittings in momentum space, dictated by their spin-space group symmetries. However, the real-space modulations of altermagnetism are often neglected and have not been explored experimentally. Here we combine neutron diffraction, angle-resolved photoemission spectroscopy (ARPES), spin-resolved ARPES and density functional theory to demonstrate that Cs$_{1-\delta}$V$_2$Te$_2$O realizes a spatially modulated form of altermagnetism, i.e., hidden altermagnetism. Such a state in Cs$_{1-\delta}$V$_2$Te$_2$O results from its G-type antiferromagnetism and two-dimensional electronic states, allowing for the development of spatially alternating altermagnetic layers, whose local spin polarizations are directly verified by spin-resolved ARPES measurements. Our experimental discovery of hidden altermagnetism broadens the scope of unconventional magnetism and opens routes to exploring emergent phenomena from real-space modulations of altermagnetic order.
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All authors Guowei Yang, Ruihan Chen, Changchao Liu, Jing Li, Ze Pan, Teng Hua, Pengyue Xiong, Liwei Deng, Naifu Zheng, Yu Tang, Hao Zheng, Weifan Zhu, Yifu Xu, Xinying Zheng, Xin Ma, Xiaoping Wang, Shengtao Cui, Zhe Sun, Zhengtai Liu, Mao Ye, Chao Cao, Ming Shi, Lunhui Hu, Qihang Liu, Shan Qiao, Guanghan Cao, Yu Song, Yang Liu

Materials Science

Charge state equilibration of nitrogen-vacancy center ensembles in diamond: The role of electron tunneling

Audrius Alkauskas, Chris G. Van de Walle, Lukas Razinkovas et al. (+1 more)

The charge state stability of nitrogen-vacancy (NV) centers critically affects their application as quantum sensors and qubits. Understanding charge state conversion and equilibration is critical not only for NV centers in diamond but also for defects and impurities in wide-bandgap materials in general. The mechanisms by which these centers change charge state upon optical or electronic excitation without the presence of mobile carriers remain unclear, potentially affecting the performance of applications ranging from phosphors to power electronics. Here, we elucidate this issue for the case of photoionization of NV center ensembles. Using pump-probe spectroscopy, we ionize negatively charged NV centers and monitor the recovery of $\NVm$ on timescales of up to several seconds. We find that the recovery rate depends strongly on the concentration of surrounding nitrogen donors. Remarkably, the equilibration dynamics exhibit no discernible dependence on temperature, ruling out thermally activated processes. The multiphonon-assisted electron tunneling model, supported by density-functional calculations, explains the measurements and identifies tunneling as the equilibration mechanism.
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All authors Audrius Alkauskas, Chris G. Van de Walle, Lukas Razinkovas, Ronald Ulbricht

Materials Science

Exchange-Correlation Functionals in 2D Materials: Applications, Challenges, and Limitations

Ahsan Javed, Mahvish Shaheen, Muhammad Shahbaz et al. (+3 more)

The rapid development of two-dimensional (2D) materials has reshaped modern nanoscience, offering properties that differ fundamentally from their bulk counterparts. As experimental discovery accelerates, the need for reliable computational techniques has become increasingly important. Within the framework of density functional theory, this review explores the critical role of exchange-correlation functionals in predicting key material properties such as structural, optoelectronic, magnetic, and thermal. We examine the challenges posed by quantum confinement, anisotropic screening, and van der Waals interactions, which conventional functionals often fail to describe. Advanced approaches, including meta-GGA, hybrid functionals, and many-body perturbation theory (e.g., GW and Bethe-Salpeter equation), are assessed for their improved accuracy in capturing electronic structure and excitonic effects. We further discuss the non-universality of functionals across different 2D material families and the emerging role of machine learning to enhance computational efficiency. Finally, the review outlines current limitations and emerging strategies, providing a roadmap for advancing exchange-correlation functionals and beyond, to enable the practical design and application of 2D materials.
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All authors Ahsan Javed, Mahvish Shaheen, Muhammad Shahbaz, M. Sufyan Ramzan, Rafi Ullah, Wei Jiang

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

Field-Tunable Quantum Metric in Few-Layer Phosphorene

Md Afsar Reja, Arka Bandyopadhyay and Awadhesh Narayan

The quantum metric – which quantifies the distance between quantum states – is a fundamental component of the quantum geometric tensor, playing a crucial role in a wide range of physical phenomena. Its direct detection and control remains a challenge, requiring suitable material candidates. In this work, we present the emergence of a tunable quantum metric in a versatile two-dimensional material platform, namely, few-layer phosphorene. Using ab-initio-derived models, we show how electric fields can be used to substantially enhance the quantum metric as well as the associated quantum weight. Furthermore, we present a layer-dependent evolution of the quantum metric and its interplay with the electric field in this material. Our results establish few-layer phosphorene as a promising platform for exploring control over the quantum metric and the resulting metric responses in real materials.
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Materials Science

Universal Fabrication of Graphene/Perovskite Oxide Hybrid Heterostructures

Yeongju Choi, Seungjin Lee, Dongwon Shin et al. (+12 more)

Hybrid heterostructures composed of graphene and perovskite oxides provide a promising platform for exploiting synergetic interfacial functionalities. Conventional fabrication methods of the hybrid heterostructures rely on transferring graphene grown on metallic substrates– a process that is time-consuming, labor-intensive, and prone to introducing numerous defects. In this study, we present a universal, catalyst-free method for the direct growth of graphene on insulating substrates by employing three different perovskite oxide substrates (SrTiO$_3$, LaAlO$_3$, and (La$_{0.18}$Sr$_{0.82}$)(Al$_{0.59}$Ta$_{0.41}$)O$_3$) using atmospheric chemical vapor deposition. Comprehensive characterization via Raman spectroscopy, X-ray spectroscopy, scanning probe microscopy, and electron microscopy confirmed the formation of a uniform, continuous monolayer graphene on all substrates. We identified that growth temperature critically governs graphene quality, as excessive active species may lead to secondary nucleation and the formation of multilayer graphene. Notably, all substrates shared the same optimal growth conditions. Low-temperature Raman spectroscopy and scanning tunneling microscopy of the graphene/SrTiO$_3$ hybrid heterostructure revealed cooperative phenomena, including substrate-induced lattice-phonon and electron-phonon coupling. Our work establishes a reproducible, transfer-free fabrication route for graphene/perovskite oxide hybrid heterostructures and provides empirical support for the universal growth of graphene on insulating substrates.
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All authors Yeongju Choi, Seungjin Lee, Dongwon Shin, Sukhoon Sim, Min-Hyoung Jung, Dirk Wulferding, Minjae Kim, Jaesik Eom, Myeesha Mostafa, Wonhee Ko, SeungNam Cha, Jungseek Hwang, Hu Young Jeong, Ki Kang Kim, Woo Seok Choi

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

New record in optical gain and room-temperature nanolasers in multiple wavelengths in 2D ErOCl single crystals

Shipeng Yao, Hao Sun, Zhang Liang et al. (+5 more)

Erbium-based materials have long been recognized for their important telecom-band applications, yet their widespread adoption in integrated optoelectronics has been hindered by two fundamental limitations: the difficulty in achieving high erbium density without concentration quenching which leads to small optical gain in doped materials, and the difficulty in fabricating a practical device with single crystal nanowires that demonstrated high optical gain previously1,2. Here, we overcome these limitations by synthesizing 2D single crystal ErOCl that has an Er density of 1.75*1022 cm-3. The high-quality single crystal material significantly reduces the density-related quenching effect that dominates in randomly doped materials with high Er concentration. This results in a record optical gain coefficient over 1500 dB/cm at 1536 nm band, at least larger by an order of magnitude than the previous gain record in Er materials. Leveraging this exceptional gain medium, we demonstrate room-temperature continuous-wave lasing operation by integrating with a photonic crystal microcavity, achieving a record-low threshold of 7 {\mu}W with the most compact size of any Er-based lasers. Furthermore, the unique Stark splitting characteristics of ErOCl provide optical gain in three wavelength bands and lead to lasing in these wavelengths by engineering the cavity. This is the first time that optical gain has been shown in three different wavelength bands in Er materials, together with the smallest size of laser cavity, could have many important applications in on-chip sensing and optical communication.
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All authors Shipeng Yao, Hao Sun, Zhang Liang, Zhen Wang, Lin Gan, Jinhua Wu, Zhangyu Hou, Cun-Zheng Ning

Materials Science

First-principles calculations of elasto-optical properties of $R$Te$_3$

Kuiqing Tang

Rare-earth tritellurides ($R$Te$_3$) exhibit complex charge-density-wave (CDW) phases intertwined with lattice symmetry, offering a platform to explore unconventional symmetry breaking in correlated materials. Elasto-optical probing, which detects strain-induced changes in birefringence, provides a non-invasive approach to visualize anisotropy and emergent order in these quasi-two-dimensional systems. However, the magnitude and symmetry of the expected optical response remain poorly quantified, hindering experimental interpretation. Here, we perform first-principles calculations of the elastic, dielectric, and piezo-optical tensors of NdTe$_3$ to establish a quantitative framework for strain-induced optical anisotropy. These results establish a quantitative link between lattice strain and optical response in $R$Te$_3$, providing a predictive framework for probing symmetry-breaking states via elasto-birefringence.
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Materials Science

A Dimensionally Consistent Size-Strain Plot Method for Crystallite Size and Microstrain Estimation

Anand Pal

X-ray diffraction (XRD) peak broadening analysis remains a cornerstone for quantifying crystallite size and lattice microstrain in materials. Among various approaches, the Size Strain Plot (SSP) method is widely employed for its conceptual simplicity and ease of use. However, this study reveals that the equation most commonly applied in SSP analysis is dimensionally inconsistent, a critical flaw that has gone largely unnoticed and replicated across decades of materials research. This pervasive error raises concerns about the validity of a significant body of published microstructural data. By tracing the historical origin of the misformulated equation, we demonstrate how a seemingly minor oversight evolved into a widely accepted standard practice within the field. We then present a dimensionally consistent formulation that restores physical meaning and analytical reliability to the SSP method. The corrected framework re-establishes the SSP approach as a robust and physically valid tool for XRD-based microstructural characterization. \en
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Saturday 29 November

Materials Science

Neural Networks as Physics-Consistent Surrogates: An Explainable AI Validation Framework for Learning Constitutive Relations

Chandana Pati and S. M. Mallikarjunaiah

This paper presents a Physics-Explainable AI (XAI) framework to validate and interpret neural networks for the constitutive modeling of solid materials. The study bridges the gap between data-driven models and continuum mechanics by applying a suite of explainability methods to neural networks trained on three distinct material behaviors: hyperelasticity (Mooney-Rivlin), elastoplasticity (Chaboche), and viscoelasticity (Fractional Zener). First, high-fidelity surrogate models, including dense feed-forward networks, LSTMs, and GRUs, are trained on synthetically generated data to accurately capture complex material responses. The core of the work then employs XAI techniques to "open the black box" and confirm that the networks learn physically meaningful principles. For hyperelasticity, gradient-based attributions (Grad Input (GI)) successfully match the analytical tangent modulus, proving the network learned material stiffness. For elastoplasticity, SHapley Additive exPlanations (SHAP) and Principal Component Analysis (PCA) demonstrate the Recurrent Neural Network (RNN) internalizes path-dependent memory, with SHAP identifying plastic strain as the dominant feature governing the stress prediction. For viscoelasticity, latent-space and wavelet analyses of the Gated Recurrent Unit. GRU layers reveal a clear temporal hierarchy, with different layers encoding instantaneous elastic response, intermediate relaxation, and long-term fractional memory. Ultimately, the study demonstrates that the XAI framework can verify that the neural networks are not merely curve-fitting but are, in fact, learning the underlying physical mechanisms of stiffness, history-dependence, and temporal damping.
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Materials Science

Resonant states and nuclear dynamics in solid-state systems: the case of silicon-hydrogen bond dissociation

Woncheol Lee, Mark E. Turiansky, Dominic Waldhör et al. (+3 more)

Bond breaking in the presence of highly energetic carriers is central to many important phenomena in physics and chemistry, including radiation damage, hot-carrier degradation, activation of dopant-hydrogen complexes in semiconductors, and photocatalysis. Describing these processes from first principles has remained an elusive goal. Here we introduce a comprehensive theoretical framework for the dissociation process, emphasizing the need for a non-adiabatic approach. We benchmark the results for the case of silicon-hydrogen bond dissocation, a primary process for hot-carrier degradation. Passivation of Si dangling bonds by hydrogen is vital in all Si devices because it eliminates electrically active mid-gap states; understanding the mechanism for dissociation of these bonds is therefore crucial for device technology. While the need for a non-adiabatic approach has been previously recognized, explicitly obtaining diabatic states for solid-state systems has been an outstanding challenge. We demonstrate how to obtain these states by applying a partitioning scheme to the Hamiltonian obtained from first-principles density functional theory. Our results demonstrate that bond dissociation can occur when electrons temporarily occupy the antibonding states, generating a highly repulsive excited-state potential that causes the hydrogen nuclear wavepacket to shift and propagate rapidly. Based on the Menzel-Gomer-Redhead (MGR) model, we show that after moving on this excited-state potential on femtosecond timescales, a portion of the nuclear wavepacket can continue to propagate even after the system relaxes back to the ground state, allowing us to determine the dissociation probability. Our results provide essential insights into the fundamental processes that drive carrier-induced bond breaking in general, and specifically elucidate hydrogen-related degradation in Si devices.
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All authors Woncheol Lee, Mark E. Turiansky, Dominic Waldhör, Byounghak Lee, Tibor Grasser, Chris G. Van de Walle

Materials Science

Ferroic Polarization from Nonpolar Phonons

Seongjoo Jung and Turan Birol

Born effective charge, a fundamental quantity in lattice dynamics and ferroelectrics, provides a quantitative measure of linear polarization response to ionic displacements. However, it does not account for higher-order effects, which can play a significant role in certain materials, such as fluorite HfO$_2$. In this paper, we use the second-order mode effective charges defined with the second-order atomic dynamical charges as a measure of the dipole moments generated by nonpolar lattice distortions. Using first-principles calculations, we demonstrate that specific combinations of nonpolar phonons in many oxides can induce strongly aligned second-order polarizations, reaching magnitudes comparable to those of intrinsically polar modes even in the zero frequency limit, broadening the understanding of second-order effects, which have historically been emphasized for their dynamical effects at specific frequency ranges. Through a symmetry-based analysis of the charge density, we elucidate the microscopic origin of these effects, tracing them to variations in bond covalency and local electronic rearrangements. We also demonstrate large second-order mode effective charge in well-studied perovskites, highlighting the generality of these phenomena. Our results offer insights into the design principles of next-generation ferroelectric, piezoelectric and multifunctional materials from the higher-order contribution to polarization in crystalline solids.
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Materials Science

Carrier localization and dynamics in In$_{0.10}$Ga$_{0.90}$N: the impact of alloying and Si doping

Ongeziwe Mpatani, Dominik Muth, Anton Krüger et al. (+4 more)

Alloying and doping are crucial for enhancing the electronic and optical properties of semiconductors while simultaneously introducing disorder. This report explores the effects of alloying and Si (0.5 at.%) doping on In$_{0.10}$Ga$_{0.90}$N thin films that were grown by metal-organic vapor phase epitaxy. Post-growth X-ray diffraction measurements indicate that Si doping does not affect the lattice parameters and screw dislocations but significantly increases the edge dislocation density. Temperature-dependent time-resolved photoluminescence spectroscopy shows that Si-doped In$_{0.10}$Ga$_{0.90}$N exhibits higher photoluminescence intensity, blue-shifted peaks, narrower emission linewidths, and quenching of lower energy sidebands when compared to pristine In$_{0.10}$Ga$_{0.90}$N. The peak energies of the most dominant feature, the donor-bound exciton, for both samples show an $S$-shape behavior indicating the presence of disorder. Although doping improves luminescence, it also introduces deeper localized states. This suggests that impurity-induced disorder outweighs compositional fluctuations, as confirmed by higher disorder parameters and Stokes shifts. Thus, the Si doping leads to increased localization, reducing nonradiative recombination channels while enhancing radiative processes. The deeper states in the doped sample confirm improved carrier confinement, and their saturation leads to early thermalization, thereby lowering the red-blue shift transition from 165 K to about 50 K. Even though the high doping level makes Si-doped In$_{0.10}$Ga$_{0.90}$N a degenerate system, it exhibits enhanced luminescence properties. These findings shed light on the impact of silicon doping on charge transport in InGaN alloys for optoelectronic applications.
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All authors Ongeziwe Mpatani, Dominik Muth, Anton Krüger, Rajdeep Adhikari, Alberta Bonanni, Marina Gerhard, Hilary Masenda

Materials Science

Spin-wave emission with current-controlled frequency by a PMA-based spin-Hall oscillator

Moritz Bechberger, David Breitbach, Abbas Koujok et al. (+4 more)

Spin-torque and spin-Hall oscillators (SHOs) have emerged as promising candidates for building blocks in neuromorphic computing due to their ability to synchronize mutually, a process that can be mediated by propagating spin waves. We demonstrate a SHO that takes advantage of a low-damping magnetic garnet with dominant perpendicular magnetic anisotropy (PMA), namely gallium-substituted yttrium-iron-garnet (Ga:YIG). In-plane magnetized Ga:YIG allows for the operation at a high efficiency level while also enabling resonant spin-wave emission. A nonlinear self-localization of the excitation is avoided by exploiting the positive nonlinear frequency shift, which facilitates a current-controlled frequency of the emitted spin waves. Via micro-focused Brillouin light scattering spectroscopy, we investigate the properties of the local auto-oscillation and its spin-wave emission. Multiple modes are excited and compete internally, with two propagating modes detected up to distances larger than 10 $\mu$m. Their frequencies combine to an extended frequency bandwidth of approximately 1.6 GHz. The experimentally observed two-mode system and its transition to a single mode at higher currents are reproduced via micromagnetic simulations, which account for spatial variation of the PMA arising due to the microstructures on Ga:YIG. Our results propose a promising platform for hosting SHOs, interconnected via propagating spin waves with particular relevance to neuromorphic computing.
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All authors Moritz Bechberger, David Breitbach, Abbas Koujok, Björn Heinz, Carsten Dubs, Abbass Hamadeh, Philipp Pirro

Materials Science

Thermomechanical investigation of silicon wafer dynamics within the melting regime driven by picosecond laser pulses for surface structuring

Helen Papadaki, Inam Mirza, Nadezhda M. Bulgakova et al. (+2 more)

Laser-induced periodic surface structures (LIPSS) on silicon, generated by ultrashort pulsed lasers, provide an efficient means to tailor surface functionality. This work presents a multiphysics finite element study on the thermomechanical dynamics of silicon wafers irradiated by picosecond laser pulses, focusing on the melting regime where thermomechanical and hydrodynamic effects dominate. To illustrate the sequential nature of laser scanning, single-pulse irradiation models are developed as thermomechanical analogues of double-pulse interactions. By positioning the laser focus near reflective boundaries and corners of the target, these models reproduce the stress-wave interference that would occur between successive pulses in scanning. The results show that periodic surface structures originate from mechanical standing wave interference within the molten layer, forming ripples with near-wavelength periodicity. The penetration depth (PD) is identified as a key factor controlling the duration and stability of these ripples: shallow PDs (75-150 nm) yield distinct, persistent patterns, while deeper PDs (app. 2.5 micrometers) lead to extended melting and hydrodynamic smoothing. Simulations of sequential double-pulse irradiation confirm that residual stresses and strains from the first pulse amplify deformation during the second, enhancing ripple amplitude and uniformity. Controlled excitation of mechanical standing waves governed by PD, boundary geometry, and pulse sequencing - thus represents a fundamental mechanism for deterministic LIPSS formation on silicon.
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All authors Helen Papadaki, Inam Mirza, Nadezhda M. Bulgakova, Evaggelos Kaselouris, Vasilis Dimitriou

Materials Science

Dual Role of Nb in Defect-Mediated Strength and Ductility of {\gamma}-TiAl Alloys

Zhiqiang Zhao, Siyao Shuang, Kepeng Ouyang et al. (+8 more)

The origin of the superior high-temperature strength of {\gamma}-TiAl with high Nb addition remains highly controversial, largely due to the unclear role of Nb atoms. Using large-scale hybrid Monte Carlo and molecular dynamics simulations with a self-developed neural network potential,we show that Nb atoms predominantly occupy Ti sites and form short-range order with neighboring Al atoms, but a non-negligible fraction also occupies Al sites (NbAl) and promotes the formation of antisite defects (TiAl). Both the NbAl and TiAl antisites exceptionally reduce stacking fault energies and facilitate deformation twinning, thereby enhancing plasticity. Meanwhile, these substitutional and antisite defects also increase the Peierls stress of both screw and edge dislocations, which hinders dislocation motion to cause pronounced solid-solution strengthening. This work provides mechanistic insights into the dual role of Nb in enhancing both strength and ductility in {\gamma}-TiAl and further offers guidance for defect and composition engineering in advanced alloy systems.
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All authors Zhiqiang Zhao, Siyao Shuang, Kepeng Ouyang, Maolin Yu, Junping Du, Liangli Chu, Xiaokai Chen, Shigenobu Ogata, Wanlin Guo, Zhuhua Zhang, Yong-Wei Zhang

Materials Science

A Rapid Thermal Chemical Vapor Deposition System for Fast Synthesis of Epitaxial Graphene Under Ambient Pressure

Shikhar Kumar Gupta, Meet Ghelani, Pragna Datta et al. (+10 more)

Graphene has emerged as a promising material for next-generation electronic and thermal devices owing to its exceptional charge transport and thermal conductivity. However, high-quality samples are predominantly obtained via mechanical exfoliation from graphite crystals, a process that inherently lacks scalability. Despite extensive efforts toward large-area synthesis, cost-effective approaches for producing high-quality, large-area, single-crystalline graphene with fast turnaround time remain limited. Here, we report the design, fabrication, and performance benchmarking of a rapid thermal chemical vapor deposition (RTCVD) system capable of synthesizing epitaxial monolayer graphene under atmospheric pressure. The entire growth process, from sample loading to unloading, is achieved within $25$ minutes with a temperature ramp rate exceeding $23^\circ\mathrm{C}/s$. Growth at atmospheric pressure eliminates the need for vacuum components, thereby reducing both system complexity and operational costs. The structural and electronic quality of epitaxial graphene is comprehensively characterized using Raman spectroscopy, selected area electron diffraction (SAED), and magnetotransport measurements, which reveal signatures of quantum Hall effect in synthesized graphene samples. Furthermore, we demonstrate van der Waals epitaxial growth of palladium (Pd) thin films on graphene transferred to Si/SiO$_{2}$ substrates, establishing its single-crystalline nature over a large area and its potential as a versatile platform for subsequent heteroepitaxial growth.
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All authors Shikhar Kumar Gupta, Meet Ghelani, Pragna Datta, Subhalakshmi Guha, Shivesh Yadav, Nilesh Kulkarni, Maheshwar Gokhale, Bhagyashree Chalke, Devendra Buddhikot, Naveen Paneri, Lavudya Devendar, Arnab Bhattacharya, Shouvik Chatterjee

Materials Science

Anisotropic and isotropic elasticity and thermal transport in monolayer C$_{24}$ networks from machine-learning molecular dynamics

Qing Li, Haikuan Dong, Penghua Ying et al. (+1 more)

Two-dimensional fullerene networks have recently attracted increasing interest due to their diverse bonding topologies and mechanically robust architectures. In this work, we develop an accurate machine-learned potential NEP-C$_{24}$ for both the quasi-hexagonal phase (qHP) and the quasi-tetragonal phase (qTP) C$_{24}$ monolayers, based on the neuroevolution potential (NEP) framework. Using this NEP-C$_{24}$ model, we systematically investigate the elastic and thermal transport properties. Compared with C$_{60}$ monolayers, both C$_{24}$ phases exhibit markedly enhanced stiffness, arising from the combination of reduced molecular size and increased density of covalent bonds. The qTP C$_{24}$ monolayer shows nearly isotropic elastic properties and thermal conductivities along its two principal axes owing to its four-fold symmetry, whereas the chain-like, misaligned bonding topology of the qHP C$_{24}$ monolayer leads to pronounced in-plane anisotropy. Homogeneous nonequilibrium molecular dynamics and spectral decomposition analyses reveal that low-frequency ($<5$ THz) acoustic phonons dominate heat transport, with directional variations in phonon group velocity and mean free path governing the anisotropic response in qHP C$_{24}$. Real-space heat flow visualizations further show that, in these fullerene networks, phonon transport is dominated by strong inter-fullerene covalent bonds rather than weak van der Waals interactions. These findings establish a direct link between intermolecular bonding topology and phonon-mediated heat transport, providing guidance for the rational design of fullerene-based two-dimensional materials with tunable mechanical and thermal properties.
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All authors Qing Li, Haikuan Dong, Penghua Ying, Zheyong Fan

Materials Science

Emergent Anomalous and Topological Hall Responses in an Epitaxial Ferromagnetic Weyl Nodal-Line metal Fe5Si3

Shubhashish Pati, Sonali Srotaswini Pradhan, Abhay Pandey et al. (+9 more)

The interplay between real and reciprocal space topology yields intrinsically linked transport phenomena in magnetic Weyl systems, wherein the broken time-reversal symmetry, strong Dzyaloshinskii-Moriya interaction, and pronounced uniaxial anisotropy stabilize the momentum-space Berry-curvature monopoles (Weyl nodes) and real-space chiral spin textures. We present a combined first-principles and experimental study of epitaxial Fe5Si3 thin films, establishing them as a magnetic Weyl nodal-line material. First-principles Density Functional Theory (DFT) calculations unambiguously reveal that Fe5Si3 hosts a topologically nontrivial electronic structure containing six pairs of Weyl nodes at or near the Fermi level, accompanied by pronounced Berry curvature at high-symmetry points of the Brillouin Zone. High-quality epitaxial films exhibit robust ferromagnetism with a Curie temperature of ~370 K and strong magneto crystalline anisotropy. The magneto transport measurements on epitaxial films reveal the corresponding Berry curvature-driven responses, including a significantly large intrinsic anomalous Hall conductivity of 504 S/cm and a high anomalous Hall angle of 5.5%, which is in good agreement with DFT calculations. A negative and non-saturating longitudinal magnetoresistance is observed, consistent with a chiral-anomaly contribution from Weyl fermions near the Fermi level (EF). Furthermore, a substantial topological Hall resistivity of 1.6 {\mu}{\Omega} cm robust across a wide temperature range, indicating the possibility of robust chiral spin textures in the thin-film geometry. These combined theoretical and experimental results establish Fe5Si3 as a unique, low-cost, centrosymmetric magnetic Weyl nodal-line material, providing a versatile platform for exploring coupled real and reciprocal space topologies in topological spintronic applications.
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All authors Shubhashish Pati, Sonali Srotaswini Pradhan, Abhay Pandey, Nikita Sharma, Nanhe Kumar Gupta, Nakul Kumar, Nidhi Shukla, Saurav Singh, Vidhi Jain, Mitali, V. Kanchana, Sujeet Chaudhary

Materials Science

Interpretable Graph Neural Networks for Classifying Structure and Magnetism in Delafossite Compounds

Jovin Ryan Joseph, Do Hoon Kiem, Sinchul Yeom et al. (+1 more)

Delafossites (ABC2, where A and B are metals and C is a chalcogen) are a versatile family of quantum materials and layered oxides/chalcogenides whose properties are highly sensitive to atomic composition and stacking geometry. Their broad chemical tunability makes them an ideal platform for large-scale combinatorial exploration and high-throughput computational screening with desirable quantum properties. In this work, we employ a Concept Whitening Graph Neural Network, a gray-box AI model, to classify delafossite structures by stacking sequence and magnetic states. By aligning learned representations with human-interpretable physical concepts, this gray-box approach enables both accurate prediction and insight into the structural and chemical features driving magnetic behavior. The magnetic-ordering models achieved validation accuracies exceeding 80 percent, with a further slight uptick observed in the model incorporating the largest number of concepts. Concept alignment analysis revealed measurable learning across nine physically meaningful descriptors, with coefficients of determination ranging from approximately 0.6 for the d-shell valence-electron concepts to 0.4-0.5 for the magnetic coupling parameters. Furthermore, we mapped the concept importances onto the material graph representation, elucidating interpretable physical trends and the progression of stable concept-aligned regions across training. These results demonstrate the potential of interpretable graph-based learning to capture the underlying physics of complex materials systems and provide an interpretable framework for accelerating the discovery and understanding of delafossites and related crystalline materials.
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All authors Jovin Ryan Joseph, Do Hoon Kiem, Sinchul Yeom, Mina Yoon

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

Magnetosynthesis effect on the structure and ground state of Cu$^{2+}$-based antiferromagnets

Micaela E. Primer, Anna A. Berseneva, Ayesha Ulde et al. (+2 more)

Subtle synthetic variables can have an outsizes influence on the crystal structure and magnetic properties of a material, particularly those of quantum materials. In this work, we investigate the impact of synthesis under a magnetic field (magnetosynthesis) on the crystal structure and magnetic properties of several Cu$^{2+}$ ($S=1/2$) based materials with antiferromagnetic interactions and varying levels of magnetic frustration, from simple antiferromagnets to a quantum spin liquid. We employ small (0.09 - 0.37 T) magnetic fields applied during low-temperature hydrothermal or evaporative synthesis of the simple antiferromagnet CuCl$_2\cdot$2H$_2$O, the canted antiferromagnet (Cu,Zn)$_3$Cl$_4$(OH)$_2\cdot$2H$_2$O, the frustrated and canted antiferromagnet atacamite Cu$_2$(OH)$_3$Cl, and the highly frustrated quantum spin liquid herbertsmithite Cu$_3$Zn(OH)$_6$Cl$_2$. We found that (Cu,Zn)$_3$Cl$_4$(OH)$_2\cdot$2H$_2$O experiences structural changes well above its magnetic transition. Atacamite Cu$_2$(OH)$_3$Cl synthesized under a 0.19 T field experiences a 0.15 K (~3%) decrease in its Néel transition temperature and a significant strengthening of its antiferromagnetic interactions, suggesting that magnetosynthesis can influence the ground state of moderately frustrated materials.
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All authors Micaela E. Primer, Anna A. Berseneva, Ayesha Ulde, Wenhao Sun, Rebecca W. Smaha

Friday 28 November

Materials Science · Cross-listed from cs.LG

A self-driving lab for solution-processed electrochromic thin films

Selma Dahms, Luca Torresi, Shahbaz Tareq Bandesha et al. (+5 more)

Solution-processed electrochromic materials offer high potential for energy-efficient smart windows and displays. Their performance varies with material choice and processing conditions. Electrochromic thin film electrodes require a smooth, defect-free coating for optimal contrast between bleached and colored states. The complexity of optimizing the spin-coated electrochromic thin layer poses challenges for rapid development. This study demonstrates the use of self-driving laboratories to accelerate the development of electrochromic coatings by coupling automation with machine learning. Our system combines automated data acquisition, image processing, spectral analysis, and Bayesian optimization to explore processing parameters efficiently. This approach not only increases throughput but also enables a pointed search for optimal processing parameters. The approach can be applied to various solution-processed materials, highlighting the potential of self-driving labs in enhancing materials discovery and process optimization.
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All authors Selma Dahms, Luca Torresi, Shahbaz Tareq Bandesha, Jan Hansmann, Holger Röhm, Alexander Colsmann, Marco Schott, Pascal Friederich

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

Exploring the apparent violation of the Mott relation in a noncentrosymmetric kagome ferromagnet

Benjamin Kostroun, Tomoya Asaba, Sean M. Thomas et al. (+4 more)

In magnetic topological materials, time-reversal symmetry breaking gives rise to topological point and line nodes with distinctive signatures in the anomalous Hall and anomalous Nernst conductivity that satisfy the well-known Mott relation. However, this relationship can fail for doping-dependent transport measurements of materials with complex magnetism, topology, and electronic correlations. In this work, we present transport measurements of the correlated topological metal UCoAl doped with Ru, which appear to violate the Mott relation. We develop a model that captures the evolution of Stoner magnetism and topological Weyl points as a function of doping. Using this model, we show how the correlated flat band in this material pins the Weyl points to the Fermi energy, and demonstrate how this explains the unusual doping-dependent behavior of the anomalous Hall and anomalous Nernst conductivities in this material, while the Mott relation is in fact satisfied at each doping level.
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All authors Benjamin Kostroun, Tomoya Asaba, Sean M. Thomas, Eric D. Bauer, Sergey Y. Savrasov, Filip Ronning, Vsevolod Ivanov

Materials Science

Singularly isostatic and geometrically unstable rigidity of metal-organic frameworks

Christopher M. Owen and Michael J. Lawler

Metal-organic frameworks (MOFs) combine high porosity with structural fragility, raising important questions about their mechanical stability. We develop a rigidity-based framework in which spring networks parameterized by UFF4MOF are used to construct rigidity and dynamical matrices. Large-scale analysis of 5,682 MOFs from the CoRE 2019 database shows that most frameworks are formally over-constrained yet cluster sharply near the isostatic threshold, revealing accidental geometric modes and placing many MOFs near mechanical instability. In the representative case of UiO-66, we show that auxiliary long-range constraints introduced by tuning the neighbor cutoff lift these modes into soft, flat, finite-frequency bands. The results show that rigidity-matrix analysis can rapidly identify MOFs likely to remain mechanically stable. This near-criticality mirrors behavior known from topological mechanics and points to a deeper design principle in porous crystals.
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