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Physics Condensed Matter Materials Science

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Wednesday 26 November

Materials Science

Unified interface dipole theory for Fermi level pinning effect at metal-semiconductor contacts

Ziying Xiang, Jun-Wei Luo and Shu-Shen Li

We present a unified bond dipole theory for metal-semiconductor interfaces to explain the microscopic origin of interface dipoles and Fermi level pinning (FLP) in terms of Harrison's bond-orbital model. By combining first-principles calculations with tight-binding analysis, we show that localized bonding between semiconductor surface dangling bonds and metal orbitals is sufficient to generate a large interface dipole and induce strong FLP, even when only a single metal monolayer is present. Within this framework, metal-induced gap states (MIGS), dangling-bond-induced surface states (DBSS), and bonding states embedded in the valence band are all understood as different outcomes of the same underlying interface bonding mechanism, rather than as independent causes of FLP. We further establish that the key parameter governing FLP strength is the density of surface dangling bonds that can form new chemical bonds with the metal, which directly controls the magnitude of the bond-induced interface dipole. This picture naturally explains the weaker pinning observed in more ionic semiconductors than in covalent ones and provides practical guidance for engineering metal-semiconductor interfaces and tuning Schottky barrier heights.
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Materials Science

Fast machine learned interatomic potential for hydrogen-induced embrittlement in {\alpha}-Fe

Eetu Makkonen, Alvaro Lopez-Cazalilla and Flyura Djurabekova

In this work, we present a machine-learned interatomic potential for the ${\alpha}$-Fe-H system based on the tabulated Gaussian Approximation Potential (tabGAP) formalism. Trained on a Density Functional Theory (DFT) dataset of atomic configurations, energies, forces, and virials, the potential is designed for simulations on the mechanisms of hydrogen embrittlement (HE), the issue of H-induced acceleration of mechanical failure of metals. The proposed potential is shown to outperform the widely used classical and machine-learned interatomic potentials in fundamental properties of the ${\alpha}$-Fe-H system. We show that the tabGAP model reproduces H-point defect properties, H-dislocation interaction, H-H interaction, and elastic constants with nearly DFT-level accuracy at a computational cost that is competitive with the efficient classical Embedded Atom Method (EAM) potentials. As an application of the tabGAP model we simulate the effect of H on the mobility of the $\tfrac{1}{2}\langle 111\rangle$ screw dislocation, which show that the model predicts an enhancement of the mobility of the screw dislocation via trapped H atoms lowering the energy barrier of kink-pair nucleation, resulting in a decreased critical shear stress of dislocation motion at $300\,\mathrm{K}$.
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Materials Science

Lattice-Distortion-Mediated Proton Pairing and Trapping in Solid State Oxides

Hang Ma, Jiajun Linghu, Nannan Han et al. (+4 more)

Experiments have evidenced proton pairing in Y-doped BaZrO3. However, the nature of proton pairing and its impact on conduction remain insufficiently understood theoretically. Here, through quantitative computational analysis of proton-proton interactions in Y-doped BaZrO3, we identify lattice-distortion-mediated elastic interaction as the key factor determining whether two protons form a stable pair or exhibit net repulsion. When a proton resides at an inward-bending distortion site induced by another proton, the resulting net repulsive interaction leads to an unstable configuration. In contrast, the proton tends to be trapped at a nearby outward-bending site that favors the formation of a stable proton pair. Moreover, the site where the two protons form the lowest-energy configuration also corresponds to a proton trapping site. By calculating the long-range diffusion pathways accessible to protons under different local environments in both single- and two-proton cases, we find that the range of rate-limiting barriers is 0.24-0.45 eV for two-proton conduction and 0.19-0.39 eV for single-proton conduction. The higher and more experimentally consistent barriers in the two-proton pathways indicate that the proton trapping effect induced by pairing hinders proton conduction. Our study elucidates the multi-proton diffusion mechanism, providing a theoretical foundation for the experimental design of electrolytes with enhanced proton conductivity.
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All authors Hang Ma, Jiajun Linghu, Nannan Han, Ying Liang, Yiyang Sun, Tianxing Ma, Zhi-Peng Li

Materials Science

Controlled nucleation in methylamine-treated perovskite films by artificial seeding and phase-field simulations

Emilia R. Schütz, Martin Majewski, Olivier J.J. Ronsin et al. (+2 more)

Large perovskite crystals with reduced defect density enable superior charge transport and stability. Therefore, controlling their nucleation and growth is key to advancing high-performance optoelectronic devices based on perovskite semiconductors. Millimeter-scale perovskite crystals can be synthesized as a continuous film through methylamine treatment, with nucleation sites directed by pre-patterned seeds. Nonetheless, certain configurations may lead to unwanted parasitic nucleation. To predict and mitigate this effect, we employ phase-field simulations alongside an analytical model. Their predictive capability is demonstrated across three distinct material-substrate systems, enabling precise control over nucleation and subsequent crystal growth. Notably, the only material-specific input required is the nucleation density (i.e., the number of crystals nucleated per unit area on an unpatterned substrate). This generality makes the models broadly applicable to diverse material systems for achieving controlled two-dimensional crystallization for improved optoelectronic device performance.
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All authors Emilia R. Schütz, Martin Majewski, Olivier J.J. Ronsin, Jens Harting, Lukas Schmidt-Mende

Materials Science

Revealing Fast Ionic Conduction in Solid Electrolytes through Machine Learning Accelerated Raman Calculations

Manuel Grumet, Takeru Miyagawa, Olivier Pittet et al. (+4 more)

Fast ionic conduction is a defining property of solid electrolytes for all-solid-state batteries. Previous studies have suggested that liquid-like cation motion associated with fast ionic transport can disrupt crystalline symmetry, thereby lifting Raman selection rules. Here, we exploit the resulting low-frequency, diffusive Raman scattering as a spectral signature of fast ionic conduction and develop a machine learning-accelerated computational pipeline to identify promising solid electrolytes based on this feature. By overcoming the steep computational barriers to calculating Raman spectra of strongly disordered materials at finite temperatures, we achieve near-ab initio accuracy and demonstrate the predictive power of our approach for sodium-ion conductors, revealing clear Raman signatures of liquid-like ion conduction. This work highlights how machine learning can bridge atomistic simulations and experimental observables, enabling data-efficient discovery of fast-ion conductors.
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All authors Manuel Grumet, Takeru Miyagawa, Olivier Pittet, Paolo Pegolo, Karin S. Thalmann, Waldemar Kaiser, David A. Egger

Materials Science

Large longitudinal and anomalous transverse Magneto-thermoelectric effect in kagome antiferromagnet FeGe

Jiajun Ma, Rong Chen, Yazhou Li et al. (+14 more)

Topological Kagome magnets, characterized by nontrivial electronic band structures featuring flat band, Dirac cone and van Hove singularities, provide a new avenue for the realization of thermoelectric devices. Unlike the conventional longitudinal Seebeck effect, transverse thermoelectric (TE) effects like the Nernst effect have attracted growing interest due to their unique transverse geometry and potential advantages. Here, we report the observation of a significant transverse thermoelectric conductivity alpha A_zx of 15 A K-1m-1 at low temperatures, together with a pronounced anomalous Nernst effect in the Kagome antiferromagnet FeGe, which exhibits a charge density wave inside the antiferromagnetic (AFM) state. This value is the highest record among known AFM materials. Furthermore, the thermopower at 14 T increases by 102-104% around the canted-AFM (CAFM) transition temperature, Tcant, comparable to that of the well-known AFM thermoelectric materials. These effects are attributed to large Berry curvature arising from the non-collinear spin texture in FeGe, highlighting its potential for enhancing thermoelectric performance and its candidacy for magneto-TE applications in Kagome antiferromagnetic materials.
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All authors Jiajun Ma, Rong Chen, Yazhou Li, Chenfei Shi, Yantao Cao, YuWei Zhang, Jiaxing Liao, Yunfei Han, Guangxi Wen, Jialu Wang, Hanjie Guo, Jianhui Dai, Chenguang Fu, Jin-Ke Bao, Yan Sun, Zhu-An Xu, Yuke Li

Materials Science

Discovery and recovery of crystalline materials with property-conditioned transformers

Cyprien Bone, Matthew Walker, Bradley A. A. Martin et al. (+6 more)

Generative models have recently shown great promise for accelerating the design and discovery of new functional materials. Conditional generation enhances this capacity by allowing inverse design, where specific desired properties can be requested during the generation process. However, conditioning of transformer-based approaches, in particular, is constrained by discrete tokenisation schemes and the risk of catastrophic forgetting during fine-tuning. This work introduces CrystaLLM-{\pi} (property injection), a conditional autoregressive framework that integrates continuous property representations directly into the transformer's attention mechanism. Two architectures, Property-Key-Value (PKV) Prefix attention and PKV Residual attention, are presented. These methods bypass inefficient sequence-level tokenisation and preserve foundational knowledge from unsupervised pre-training on Crystallographic Information Files (CIFs) as textual input. We establish the efficacy of these mechanisms through systematic robustness studies and evaluate the framework's versatility across two distinct tasks. First, for structure recovery, the model processes high-dimensional, heterogeneous X-ray diffraction patterns, achieving structural accuracy competitive with specialised models and demonstrating applications to experimental structure recovery and polymorph differentiation. Second, for materials discovery, the model is fine-tuned on a specialised photovoltaic dataset to generate novel, stable candidates validated by Density Functional Theory (DFT). It implicitly learns to target optimal band gap regions for high photovoltaic efficiency, demonstrating a capability to map complex structure-property relationships. CrystaLLM-{\pi} provides a unified, flexible, and computationally efficient framework for inverse materials design.
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All authors Cyprien Bone, Matthew Walker, Bradley A. A. Martin, Kuangdai Leng, Luis M. Antunes, Ricardo Grau-Crespo, Amil Aligayev, Javier Dominguez, Keith T. Butler

Materials Science

Active Learning Driven Materials Discovery for Low Thermal Conductivity Rare-Earth Pyrochlore for Thermal Barrier Coatings

Amiya Chowdhury, Acacio Rincon Romero, Grazziela Figueredo et al. (+1 more)

High-Entropy/multicomponent rare-earth oxides (HECs and MCCs) show promise as alternative materials for thermal barrier coatings (TBC) with the ability to tailor properties based on the combination of rare-earth elements present. By enabling the substitution of scarce or supply-risk rare-earths with more readily available alternatives while maintaining comparable material performance, HECs and MCCs offer a valuable path towards alternative TBC material design. However, navigating this search space of compositionally complex materials is both time and resource intensive. In this study, an active learning (AL) framework was employed to identify HEC/MCC materials with a pyrochlore structure, with acceptable thermal conductivity (TC) for TBC applications. The AL framework was applied through a Bayesian optimisation (BO) strategy, coupled with a random forest surrogate model. TC was selected as the optimisation criterion as that is the most basic requirement of TBC materials. Over two iterations of the AL cycle, four compositions were generated and synthesized in the lab for experimental evaluation. The first iteration yielded two single-phase pyrochlores, $(La_{0.29}Nd_{0.36}Gd_{0.36})_2Zr_2O_7$ and $(La_{0.333}Nd_{0.26}Gd_{0.15}Ho_{0.15}Yb_{0.111})_2Zr_2O_7$, with measured thermal conductivities of 2.03 and 1.90 $W/mK$, respectively. The surrogate model predicted a TC of 2.009 $W/mK$ for both compositions, demonstrating it's accuracy for completely new compositions. The second iteration compositions showed dual-phase when synthesized, highlighting the need to take into account phase formation in the AL framework.
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All authors Amiya Chowdhury, Acacio Rincon Romero, Grazziela Figueredo, Tanvir Hussain

Materials Science

Coupled Structural and Electronic Requirements in Alpha-FASnI3 Imposed by the Sn(II) Lone Pair

Mridhula Venkatanarayanan, Vladislav Slama, Madhubanti Mukherjee et al. (+3 more)

Alpha-Formamidinium-tin-iodide (alpha-FASnI3) is a leading candidate for lead-free photovoltaic applications, adopting a nearly cubic structure at room temperature, but its stability remains limited by oxidation-driven degradation. Reliable first-principles modelling of the photovoltaic alpha-phase is further complicated by inconsistent structural models and levels of theory in the literature. Here, we identify the structural and electronic requirements needed for a physically sound description of alpha-FASnI3, whose behaviour is governed by a pseudo-Jahn-Teller (PJT) instability arising from the stereochemically active Sn(II) lone pair. Using 0 K relaxations, cross-code hybrid-functional benchmarks, and finite-temperature ab initio molecular dynamics, we show that a 4x4x4 supercell with randomly oriented FA+ cations is the smallest model that removes macroscopic dipoles, preserves cubic symmetry, recovers local octahedral tilts, and captures the characteristic PJT-driven Sn off-centering. Accurate band edges and a reliable band gap require a PBE0-level hybrid functional with spin-orbit coupling to treat Sn relativistic effects, together with nonlocal dispersion (rVV10) to capture the enhanced Sn-I covalency. Finite-temperature simulations reveal that Sn off-centering remains local, <111>-oriented, and robust against thermal fluctuations, and that reproducing the experimental 300 K band gap requires a 6x6x6 supercell. These results define the essential ingredients for reliable modelling of alpha-FASnI3 and provide a rigorous foundation for studying lone-pair-driven physics in tin halide perovskites.
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All authors Mridhula Venkatanarayanan, Vladislav Slama, Madhubanti Mukherjee, Andrea Vezzosi, Ursula Rothlisberger, Virginia Carnevali

Materials Science

Mechanisms of Resistive Switching in 2D Monolayer and Multilayer Materials

M. Kaniselvan, Y. R. Jeon, M. Mladenović et al. (+2 more)

The power and energy consumption of resistive switching devices can be lowered by reducing their active layer dimensions. Efforts to push this low-energy switching property to its limits have led to the investigation of active regions made with two-dimensional layered materials (2DLM). Despite their small dimensions, 2DLM exhibit a rich variety of switching mechanisms, each involving different types of atomic structure reconfigurations. In this review, we highlight and classify the mechanisms of resistive switching in mono and bulk 2DLM, with a subsequent focus on those occurring in a monolayer and/or localized to point defects in the crystalline sheet. We discuss the complex energetics involved in these fundamentally defect-assisted processes, including the co-existence of multiple mechanisms and influence of the contacts used. Examining the highly localized 'atomristor'-type switching, we provide insights into the atomic motions and electronic transport across the metal-2D interfaces underlying their operation. Finally, we present the progress and our perspective on the challenges associated with the development of 2D resistive switching devices. Promising application areas and material systems are identified and suggested for further research.
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All authors M. Kaniselvan, Y. R. Jeon, M. Mladenović, M. Luisier, D. Akinwande

Materials Science · Cross-listed from quant-ph

The effects of decoherence on Fermi's golden rule

Caihong Zheng and Fan Zheng

Fermi's golden rule which describes the transition rates between two electronic levels under external stimulations is used ubiquitously in different fields of physics. The original Fermi's golden rule was derived from perturbative time-dependent Schrödinger's equation without the direct contribution by decoherence effect. However, as a result of recent developments of quantum computing and ultra fast carrier dynamics, the decoherence becomes a prominent topic in fundamental research.Here, by using the non-adiabatic molecular dynamics which goes beyond the time-dependent Schrödinger's equation by introducing decoherence, we study the effect of decoherence on Fermi's golden rule for the fixed basis and the adiabatic basis, respectively. We find that when the decoherence time becomes short, there is a significant deviation from the Fermi's golden rule for both bases. By using monolayer $\mathrm{WS_2}$ as an example, we investigate the decoherence effect in the carrier transitions induced by the electron-phonon coupling with first-principle method.
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Materials Science

Lattice-to-Total Thermal Conductivity Ratio: A Phonon-Glass Electron-Crystal Descriptor for Data-Driven Thermoelectric Design

Yifan Sun, Zhi Li, Tetsuya Imamura et al. (+3 more)

Thermoelectrics (TEs) are promising candidates for energy harvesting with performance quantified by figure of merit, $ZT$. To accelerate the discovery of high-$ZT$ materials, efforts have focused on identifying compounds with low thermal conductivity $\kappa$. Using a curated dataset of 71,913 entries, we show that high-$ZT$ materials reside not only in the low-$\kappa$ regime but also cluster near a lattice-to-total thermal conductivity ratio ($\kappa_\mathrm{L}/\kappa$) of approximately 0.5. This optimal ratio provides a quantitative descriptor for the well-known phonon-glass electron-crystal (PGEC) design concept. Building on this insight, we construct a framework consisting of two machine learning models for the lattice and electronic components of thermal conductivity that jointly provide both $\kappa$ and $\kappa_\mathrm{L}/\kappa$ for screening and guiding the optimization of TE materials. By applying this framework to 104,567 inorganic compounds, we identify 2,522 ultralow-$\kappa$ candidates while simultaneously evaluating their proximity to the optimal PGEC regime. A follow-up case study on chemical doping demonstrates how the framework can qualitatively provide optimization strategies that shift pristine materials toward the ideal $\kappa_\mathrm{L}/\kappa$ $\approx$ 0.5 target. Ultimately, by integrating rapid screening with PGEC-guided optimization, our data-driven framework takes a critical step towards closing the gap between materials discovery and performance enhancement.
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All authors Yifan Sun, Zhi Li, Tetsuya Imamura, Yuji Ohishi, Chris Wolverton, Ken Kurosaki

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

Giant critical current peak induced by pressure in kagome superconductor RbV$_{3}$Sb$_{5}$

Lingfei Wang, Wenyan Wang, Tsz Fung Poon et al. (+11 more)

Superconductivity can coexist or compete with other orders such as magnetism or density waves. Optimizing superconductivity requires identifying competing orders that may disrupt Cooper pair coherence. Here, we use the self-field critical current ($I_{\rm c,sf}$) to probe pressure-tuned superconductivity in the kagome superconductor RbV$_3$Sb$_5$. As pressure destabilizes the charge-density wave (CDW) state, $I_{\rm c,sf}$ drastically enhances, peaking near the critical pressure where the CDW state is completely suppressed at zero temperature. Surprisingly, a weaker $I_{\rm c,sf}$ peak emerges within the CDW phase. Near the pressure of the weaker peak, the superconducting phase transition temperature shifts from an increasing trend with pressure to a near plateau. Our analysis suggests the possibility of a sudden change in the CDW pattern or a Lifshitz transition, highlighting the need for microscopic examinations of the CDW state for understanding the pressure evolution of superconductivity in RbV$_3$Sb$_5$.
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All authors Lingfei Wang, Wenyan Wang, Tsz Fung Poon, Zheyu Wang, Chun Wai Tsang, Xinyou Liu, Shanmin Wang, Kwing To Lai, Wei Zhang, Jeffery L. Tallon, Youichi Yamakawa, Hiroshi Kontani, Rina Tazai, Swee K. Goh

Materials Science

Accelerated Discovery of Crystalline Materials with Record Ultralow Lattice Thermal Conductivity via a Universal Descriptor

Xingchen Shen, Jiongzhi Zheng, Michael Marek Koza et al. (+9 more)

Ultralow glass-like lattice thermal conductivity in crystalline materials is crucial for enhancing energy conversion efficiency in thermoelectrics and thermal insulators. We introduce a universal descriptor for thermal conductivity that relies only on the atomic number in the primitive cell and the sound velocity, enabling fast and scalable materials screening. Coupled with high-throughput workflows and universal machine learning potentials, we identify the candidate materials with ultralow thermal conductivity from over 25, 000 materials. We further validate this approach by experimentally confirming record-low thermal conductivity values of 0.15-0.16 W/m/K from 170 to 400 K in the halide metal CsAg2I3. Combining inelastic neutron scattering with first-principles calculations, we attribute the ultralow thermal conductivity to the intrinsically small sound velocity, strong anharmonicity, and structural complexity. Our work illustrates how a universal descriptor, combined with high-throughput screening, machine-learning potential and experiment, enables the efficient discovery of materials with ultralow thermal conductivity.
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All authors Xingchen Shen, Jiongzhi Zheng, Michael Marek Koza, Petr Levinsky, Jiri Hejtmanek, Philippe Boullay, Bernard Raveau, Jinghui Wang, Jun Li, Pierric Lemoine, Christophe Candolfi, Emmanuel Guilmeau

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

Quantum Hard Spheres with Affine Quantization

Riccardo Fantoni

We study a fluid of quantum hard-spheres treated with affine-quantization. Assuming that the fluid obeys to Bose-Einstein statistics we solve for its thermodynamic properties using the path integral Monte Carlo method.

Materials Science

Ion Jump Motion as the Background for Muon Diffusion in Battery Materials Research Using $\mu$SR

Ryosuke Kadono

Numerical simulations of muon spin relaxation ($\mu$SR) in ion diffusion were performed using the extended Kubo-Toyabe (KT) relaxation function $G_z^{\rm EA}(t)$ that incorporates an Edwards-Anderson type autocorrelation function for the jump motion of ions. The analysis of the generated $\mu$SR spectra using the conventional KT function $G_z^{\rm KT}(t;\Delta_{\rm KT},\nu_{\rm KT})$ (mimicking the previous analysis procedure) suggest that the anomalous peak in the fluctuation rate $\nu_{\rm KT}$ around a specific temperature $T^*$ and associated decrease of the linewidth $\Delta_{\rm KT}$ above $T^*$, often observed in the previous $\mu$SR studies on ion diffusion, originate from the sharp increase in the ion jump rate $\nu_{\rm i}$ against that of the muon $\nu_\mu$ with increasing temperature. This indicates that a more detailed reanalysis of the vintage data using $G_z^{\rm EA}(t)$ is useful for the proper evaluation of $\nu_{\rm i}$ and $\nu_\mu$. Meanwhile, it also suggests that the $\mu$SR results showing no such anomaly convey little information on ion diffusion.
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Materials Science

Hierarchical high-throughput screening of alkaline-stable lithium-ion conductors combining machine learning and first-principles calculations

Zhuohan Li, KyuJung Jun, Bowen Deng et al. (+1 more)

Solid-state batteries require lithium-ion conductors that combine high ionic conductivity with stability under harsh electrochemical and chemical conditions. Here, we investigate the chemical factors governing the stability of NASICON-type and garnet-type Li-ion conductors in highly alkaline environments. This is particularly relevant to solid-state Li-air cells operated under humidified air where alkaline conditions arise due to the formation of LiOH discharge products. We implement a hierarchical high-throughput screening workflow that consists of a pre-screening step using a universal machine-learning interatomic potential and a more accurate DFT-based screening. This approach enables rapid evaluation of over 320,000 compositions, from which 209 alkaline-stable candidates are identified. We identify specific cation substitutions that improve alkaline stability in NASICON and garnet compounds and reveal the underlying mechanism. More importantly, we highlight design trade-offs that require careful composition optimization to simultaneously enhance synthesizability, operational stability, and Li-ion/electronic conductivities for practical humid Li-air battery applications.
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All authors Zhuohan Li, KyuJung Jun, Bowen Deng, Gerbrand Ceder

Materials Science

Optical contrast-based determination of number of layers for two-dimensional van der Waals magnet Fe$_3$GeTe$_2$

Neesha Yadav, Sandeep and Pintu Das

Recent advances in revealing intrinsic magnetism in two-dimensional (2D) materials have highlighted their potential for future spintronic applications, driven by their novel physical properties, promising for future spintronic devices. In order to explore layer dependent magnetic behavior, in general, mechanically exfoliated flakes from high-quality single crystals are used. It is crucial to determine the number of layers of these materials accurately. In the absence of an efficient and quick method, researchers often rely on atomic force microscopy (AFM) imaging to identify their number of layers. In this work, we report an optical contrast study as a quick and cost-effective technique to determine the number of layers of Fe$_3$GeTe$_2$ (FGT). Here, we observed a linear relationship between the optical contrast (derived from optical microscopic images) observed for mechanically exfoliated FGT nano-flakes and their thickness, as measured by the AFM imaging method. This technique requires no additional equipment; it relies solely on a conventional optical microscope. Additionally, our results reveal a thickness-dependent evolution of the intensity; in contrast, the Raman frequency demonstrates no significant dependence on layer thickness. Also, our studies reveal two additional Raman modes of FGT, at the frequency of 129\,cm$^-1$ & 190\,cm$^-1$. Both modes show the intensity dependence on the thickness of FGT, same as out-of-plane (A$_{1g}$) Raman modes.
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Tuesday 25 November

Materials Science

Photo-induced carrier dynamics in InSb probed with broadband THz spectroscopy based on BNA crystals

Elodie Iglesis, Alexandr Alekhin, Maximilien Cazayous et al. (+3 more)

We report an optical pump - terahertz (THz) probe study of the photoinduced transient carrier dynamics in the low bandgap semiconductor Indium Antimonide (InSb). Using an organic N-benzyl-2-methyl-nitroaniline (BNA) crystal as a broadband THz source, we access the full spectral response over more than 5 THz, for varying pump-probe delay following the optical excitation. Using the Drude-Lorentz model accounting for differences between the excited length in material and the penetration depth of THz beam in pumped InSb, we extract the absolute carrier density as a function of the pump-probe delay, and provide insights on the diffusion length at given carrier densities, for different pump fluences. The mismatch between the THz penetration depth and the actual excited sample depth after carrier diffusion is discussed, since their evolutions with time and pump fluence are not intuitive as both quantities depend on carrier density.
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All authors Elodie Iglesis, Alexandr Alekhin, Maximilien Cazayous, Alain Sacuto, Yann Gallais, Sarah Houver

Materials Science

Cr2O3/e̱ta}-Ga2O3 Heterojunction Diodes with Orientation-Dependent Breakdown Electric Field up to 12.9 MV/cm

Yizheng Liu, Haochen Wang, Carl Peterson et al. (+3 more)

We report the fabrication of Cr2O3/e̱ta}-Ga2O3 heterojunction diodes using reactive magnetron sputtering of Cr2O3 on highly doped e̱ta}-Ga2O3 bulk substrates along (100), (010), (001), (110), and (011) orientation dependence of high electric field handling capability in e̱ta}-Ga2O3. Additional relative permittivity values in (110) and (011) orientations of e̱ta}-Ga2O3 were computed by using first-principles calculation methods for accurate apparent charge density (ND-NA) extraction and breakdown electric field analysis from capacitance-voltage measurements. The HJDs fabricated on n+ (110) exhibited breakdown electric fields >10 MV/cm up to 12.9 MV/cm, showing the highest experimentally observed parallel-plane junction electric field among e̱ta}-Ga2O3-based junctions. Breakdown electric fields among (100), (010), (001), and (011) orientations showed distinct distribution in the range of 5.13-5.26 MV/cm, 5.10-7.05 MV/cm, 2.70-3.33 MV/cm, and 3.88-4.38 MV/cm, respectively, validating the orientational dependence of parallel-plane junction electric field at breakdown in low-symmetry monoclinic e̱ta}-Ga2O3. The parallel-plane breakdown electric fields (EBr,||) reported in this work were extracted when the device experienced catastrophic breakdown at 100 mA/cm^2 current density compliance, and should not be confused with critical electric field (Ec) as a function of drift layer doping concentration, which accounts for electric-field dependent impact ionization coefficients in Si, SiC and GaN. This study can guide the choice of crystal orientation for high performance gallium oxide-based devices that require high electric field handling capability.
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All authors Yizheng Liu, Haochen Wang, Carl Peterson, James S. Speck, Chris Van De Walle, Sriram Krishnamoorthy

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

Analytical Interaction Potentials for Disks in Two Dimensions

Binghan Liu, Junwen Wang, Gary S. Grest et al. (+1 more)

Compact analytical forms are derived for the interactions involving thin disks in two dimensions using an integration approach. These include interactions between a disk and a material point, between two disks, and between a disk and a wall. Each object is treated as a continuous medium of materials points interacting by the Lennard-Jones 12-6 potential. By integrating this potential in a pairwise manner, expressions for the potentials and resultant forces between extended objects are obtained. All the results are validated with numerical integrations. The analytical potentials are implemented in LAMMPS and used to simulate two-dimensional suspension of disks with an explicit solvent modeled as a Lennard-Jones liquid. In monodisperse disk suspensions, a disorder-to-order transition of disk packing is observed as the area fraction of disks is increased or as the solvent evaporates. In bidisperse disk suspensions being rapidly dried, stratification is found with the smaller disks enriched at the evaporation front. Such "small-on-top" stratification echoes the similar phenomenon occurring in three-dimensional polydisperse colloidal suspensions that undergo fast drying. These potentials can be applied to a wide range of two-dimensional systems involving disk-like objects.
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All authors Binghan Liu, Junwen Wang, Gary S. Grest, Shengfeng Cheng

Materials Science · Cross-listed from quant-ph

Elucidating the Inter-system Crossing of the Nitrogen-Vacancy Center up to Megabar Pressures

Benchen Huang, Srinivas V. Mandyam, Weijie Wu et al. (+12 more)

The integration of Nitrogen-Vacancy color centers into diamond anvil cells has opened the door to quantum sensing at megabar pressures. Despite a multitude of experimental demonstrations and applications ranging from quantum materials to geophysics, a detailed microscopic understanding of how stress affects the NV center remains lacking. In this work, using a combination of first principles calculations as well as high-pressure NV experiments, we develop a complete description of the NV's optical properties under general stress conditions. In particular, our ab initio calculations reveal the complex behavior of the NV's inter-system crossing rates under stresses that both preserve and break the defect's symmetry. Crucially, our proposed framework immediately resolves a number of open questions in the field, including: (i) the microscopic origin of the observed contrast-enhancement in (111)-oriented anvils, and (ii) the surprising observation of NV contrast-inversion in certain high-pressure regimes. Our work lays the foundation for optimizing the performance of NV high-pressure sensors by controlling the local stress environment, and more generally, suggests that symmetry-breaking stresses can be utilized as a novel tuning knob for generic solid-state spin defects.
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All authors Benchen Huang, Srinivas V. Mandyam, Weijie Wu, Bryce Kobrin, Prabudhya Bhattacharyya, Yu Jin, Bijuan Chen, Max Block, Esther Wang, Zhipan Wang, Satcher Hsieh, Chong Zu, Christopher R. Laumann, Norman Y. Yao, Giulia Galli

Materials Science

CHIPS-TB: Evaluating Tight-Binding Models For Metals, Semiconductors, and Insulators

In Jun Park and Kamal Choudhary

As semiconductor technologies continue to scale down to the nanoscale, the efficient prediction of material properties becomes increasingly critical. The tight-binding (TB) method is a widely used semi-empirical approach that offers a computationally tractable alternative to Density Functional Theory (DFT) for large-scale electronic structure calculations. However, conventional TB models often suffer from limited transferability and lack standardized benchmarking protocols. In this study, we introduce a computational framework (CHIPS-TB) for evaluating and comparing tight-binding parameterizations across diverse material systems relevant to semiconductor design, focusing on properties such as electronic bandgaps, band structures, and bulk modulus. We assess model parameterizations including Density Functional Tight-Binding (DFTB)-based MatSci, PBC, PTBP, SlaKoNet and TB3PY against OptB88vdW, TBmBJ-DFT and experimental reference data from the JARVIS-DFT database for 50+ materials pertinent to semiconductor applications. The CHIPS-TB code will be made publicly available on GitHub and benchmarks will be available on JARVIS-Leaderboard.
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Materials Science

Towards superior van der Waals density functionals for molecular crystals

Dmitry V. Fedorov, Nikita E. Rybin, Mikhail A. Averyanov et al. (+3 more)

Ubiquitous van der Waals (vdW) interactions play a subtle yet crucial role in determining the precise atomic arrangements in solids, particularly in molecular crystals where these weak forces are the primary link between constituent building blocks. Within density functional (DF) theory, the most natural approach for addressing vdW forces is the use of vdW-inclusive density functionals. Through a detailed analysis of the underlying formalism, we have developed a computational scheme that combines vdW functionals of type DF1 and DF2 and serves as a well optimizable tool to improve the theoretical description and prediction of molecular crystals and other sparse materials. The proof of principle is demonstrated by our consideration of the molecular crystals from the X23 dataset.
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All authors Dmitry V. Fedorov, Nikita E. Rybin, Mikhail A. Averyanov, Alexander V. Shapeev, Artem R. Oganov, Carlo Nervi

Materials Science

Carrier transport and electrical bandgaps in epitaxial CrN layers

Duc V. Dinh, Jens Herfort, Andreas Fiedler et al. (+1 more)

The transport properties and electrical bandgap of nominally undoped ~75-nm-thick CrN layers simultaneously grown on AlN(0001) and AlN(11\bar{2}2) templates using plasma-assisted molecular beam epitaxy are investigated. The layers grown on AlN(0001) and AlN(11\bar{2}2) exhibit (111) and (113) surface orientations, respectively. All layers exhibit antiferromagnetism with a Néel temperature of ~280 K, observed by temperature-dependent magnetic and electrical measurements. Hall-effect measurements demonstrate n-type semiconducting behavior across a wide temperature range from 4 to 920 K. At low temperatures (4 - 260 K), the data show parallel conduction channels from a metallic impurity band and the conduction band. The carrier mobility exhibits a temperature dependence consistent with a nondegenerate semiconductor, governed by ionized-impurity scattering below 400 K and phonon scattering above 400 K. An analysis of the temperature-dependent carrier density between 300 and 920 K yields two activation energies associated with intrinsic conduction: 0.15 eV (with an uncertainty of -0.02/+0.10 eV), which we attribute to the fundamental bandgap, and 0.50 eV (with an uncertainty of -0.05/+0.15 eV) representing a higher energy transition.
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All authors Duc V. Dinh, Jens Herfort, Andreas Fiedler, Oliver Brandt

Materials Science

Emergent Superfluidity of Hard-Core Excitons in Single-Layer Breathing-Kagome Nb$_3$Te$_x$Cl$_{8-x}$

Mahtab A. Khan and Michael N. Leuenberger

We develop a microscopic theory of superfluidity for hard-core dark excitons on the triangular lattice by mapping the large-$U$ Bose–Hubbard model to an effective XXZ spin-$\frac{1}{2}$ Hamiltonian including virtual hopping processes. Within this framework, we identify the superfluid phase that emerges between the two Mott-insulating endpoints at fillings 0 and 1, and derive its mean-field structure via a canted-spin solution. We then construct the corresponding continuum Landau-Ginzburg (LG) functional and analyze phase fluctuations and vortex dynamics. In two dimensions, the superfluid–normal transition is shown to be governed by a Berezinskii–Kosterlitz–Thouless (BKT) mechanism with a stiffness determined by microscopic parameters. Our results provide a unified description connecting lattice-scale exciton dynamics to continuum critical behavior in triangular geometries.
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Materials Science

Physically Interpretable Interatomic Potentials via Symbolic Regression and Reinforcement Learning

Bilvin Varughese, Troy D. Loeffler, Suvo Banik et al. (+9 more)

The development of next-generation molecular simulation models requires moving beyond pre-defined functional forms toward machine learning (ML) techniques that directly capture multiscale physics. Here, we demonstrate such an approach using symbolic regression (SR) with equation learner networks and a reinforcement learning search engine to derive interpretable equations for interatomic interactions. Training data were generated through nested ensemble sampling with density functional theory (DFT) energetics, spanning crystalline to highly disordered states. The optimization of the learner network employed continuous-action Monte Carlo Tree Search (MCTS) combined with gradient descent, enabling efficient exploration of function space. For copper as a representative transition metal, an unconstrained search produced models that outperformed fixed-form Sutton-Chen EAM potentials. The SR-derived models (SR1 and SR2) reproduced key material properties - lattice constants, cohesive energies, equations of state, elastic constants, phonon dispersion, defect formation energies, surface/bulk energetics, and phase transformation with significantly improved accuracy. Furthermore, stringent melting simulations using two-phase solid-amorphous interfaces confirmed that SR models accurately capture the interplay of vibrational entropy, cohesive energy, and structural dynamics, surpassing SC-EAM in both qualitative and quantitative predictions. This highlights the potential of SR to deliver fast, accurate, flexible, and physically meaningful potentials, advancing predictive modeling across scales.
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All authors Bilvin Varughese, Troy D. Loeffler, Suvo Banik, Aditya Koneru, Sukriti Manna, Karthik Balasubramanian, Rohit Batra, Mathew J. Cherukara, Orcun Yildiz, Tom Peterka, Bobby G. Sumpter, Subramanian K.R.S. Sankaranarayanan

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

Magnetic Bulk Photovoltaic Effect in Bernal Bilayer Graphene

Yuncheng Mao and Claudio Attaccalite

We investigate the shift-current response of inversion-broken AB-stacked bilayer graphene under in-plane and perpendicular magnetic fields, from the perturbative regime to strong orbital quantization, in both two-dimensional bulk systems and finite nanoribbons. An in-plane field enters through opposite momentum shifts in the two layers and leaves the bulk band dispersion essentially unchanged, producing only a modest, frequency-dependent redistribution of the shift-current spectrum. A weak perpendicular field is treated using a gauge-covariant Peierls expansion. The resulting band corrections are concentrated near Berry-curvature hot spots, although the dominant shift-current transitions occur elsewhere, and the valley-summed response is even in the field with a leading quadratic correction. At strong perpendicular field, a rational-flux magnetic supercell reveals nearly flat Landau-level-like bulk bands and a greatly enhanced density of states, yet the bulk shift current is almost completely quenched because the relevant optical matrix elements and shift-vector contributions are suppressed or cancel. Finite ribbons retain optically active boundary channels: in zigzag ribbons, magnetic reconstruction turns edge-derived states from dark states into bright photovoltaic channels, with the associated peak scaling inversely with ribbon width. These results show that magnetic control of the nonlinear photovoltaic response is governed by wave-function reconstruction and quantum-geometric matrix elements rather than by the density of states alone.
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Materials Science

Tuning Yttrium {\Sigma}7(0001) Twist Grain Boundary Properties through Segregation and Co-segregation of Low Neutron Absorption Elements: First-Principles Insights

Guanlin Lyu, Yuguo Sun, Panpan Gao et al. (+1 more)

Elements with low thermal neutron absorption cross-sections are ideal for enhancing structural materials in nuclear systems. In this study, We systematically investigate the segregation and co-segregation behaviors of eleven elements at the {\Sigma}7(0001) twist grain boundary in yttrium and their effects on stability and strength. The {\Sigma}7(0001) grain boundary exhibits weakening, with fracture occurring preferentially along path I. Segregation energy calculations show that Si, Cu, Cr, Mo and Fe prefer interstitial sites, while others occupy substitutional ones. Si, Al, Zn, Cu, Mg and Fe stabilize the boundary, while Mo, Fe, Si, Cr, Cu, Nb and Ti strengthen it, with Si offering the most balanced improvement. Co-segregation studies reveal that Si induces the enrichment of other solutes at the boundary, promoting synergistic stabilization and turning embrittling elements (Al, Mg, Zn, Zr) into strengthening agents. Electronic structure analysis shows that Si-Y covalent bonds enhance electron localization, and Si+Mg co-segregation optimizes electronic distribution through metallic-covalent cooperation, significantly improving fracture resistance. The density of states analysis indicates new low-energy deep states in the Si, and Si+Al, Si+Mg systems, which lower grain boundary energy and improve stability. This study provides guidance for designing high-performance, low-neutron-absorption Y-based alloys.
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All authors Guanlin Lyu, Yuguo Sun, Panpan Gao, Ping Qian

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

Real-Space Imaging of Moiré-Confined Excitons in Twisted Bilayer MoS$_2$

Laurens J.M. Westenberg, Lumen Eek, Jort D. Verbakel et al. (+8 more)

Twisted two-dimensional semiconductors generate a moiré landscape that confines excitons (bound electron-hole pairs) into programmable lattices, offering routes to efficient light sources, sensing, and room-temperature information processing. However, direct real-space imaging of confined excitonic species within a moiré unit cell remains challenging; existing claims are inferred from spatially averaged far-field signals that are intrinsically insufficient to resolve nanometre-scale variations. Here, we imaged excitons across the moiré of a 2$^{\circ}$ twisted bilayer MoS$_2$ with nanometre resolution using room-temperature photocurrent atomic force microscopy. We directly resolved site-selective confinement: direct and indirect excitons localize at different stacking registries of the moiré, with contrast governed by alignment between site-selective generation and confinement minima. A Wannier-based moiré-exciton model reproduces the measured energies and the moiré-induced localization of the exciton wavefunction. These species-specific, unit-cell-resolved measurements constrain microscopic models of moiré excitons, provide benchmarks for excitonic order, and establish a device-compatible route to engineering excitonic lattices in van der Waals heterostructures.
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All authors Laurens J.M. Westenberg, Lumen Eek, Jort D. Verbakel, Kevin Vonk, Stijn J.H. Borggreve, Kenji Watanabe, Takashi Taniguchi, Paul de Boeij, Rodrigo Arouca, Cristiane Morais Smith, Pantelis Bampoulis