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Physics Condensed Matter Materials Science

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Friday 12 December

Materials Science

X-ray magnetic circular dichroism of altermagnet $\alpha$-Fe$_2$O$_3$ based on multiplet ligand-field theory using Wannier orbitals

Ruiwen Xie, Hamza Zerdoumi and Hongbin Zhang

Hematite $\alpha$-Fe$_2$O$_3$ is a $g$-wave altermagnetic material, which has an easy-axis phase and easy-plane weak ferromagnetic phase below and above Morin transition temperature, respectively. The presence of these phases renders it a good candidate to study the characteristic spin splitting in altermagnets under the impacts of relativistic effect and finite temperature. In this regard, we have calculated the band structure of $\alpha$-Fe$_2$O$_3$ based on density functional theory (DFT) which also considers the Hubbard-U correction and spin-orbit coupling (SOC) effects. Additionally, the charge self-consistent DFT + dynamical mean-field theory (DMFT) calculations have been performed at finite temperatures. It is found that the altermagnetic spin splitting in $\alpha$-Fe$_2$O$_3$ preserves with either SOC or temperature effect taken into account. Furthermore, we present a numerical simulation of the x-ray magnetic circular dichroism (XMCD) of the L$_{2,3}$ edge of Fe using a combination of DFT with multiplet ligand-field theory (MLFT). In terms of the different Néel vectors present in $\alpha$-Fe$_2$O$_3$, we calculate the x-ray absorption spectroscopy (XAS) of the L$_{2,3}$ edge of Fe in the form of conductivity tensor and analyze the XMCD response from a perspective of symmetry. A characteristic XMCD line shape is expected when the Néel vector is along [010] direction (magnetic point group $2^\prime/m^\prime$) and the light propagation vector is perpendicular to the Néel vector, which can be further distinguished from the XMCD response originated from weak ferromagnetism with the light propagation vector parallel to the Néel vector.
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Materials Science

Nano-engineered surface enhanced Raman spectroscopy substrates for probing tissue-material interactions

Connie M. Wang, Roberta M. Sabino, Aditya Garg et al. (+3 more)

Innovation in biomaterials has brought both breakthroughs and new challenges in medicine, as implant materials have become increasingly multifunctional and complex. One of the greatest issues is the difficulty in assessing the temporal and multidimensional dynamics of tissue-implant interactions. Implant biology remains hard to decipher without a noninvasive and multiplexed technique that can accurately monitor real-time biological processes. To address this, we developed a multifunctional, self-sensing implant material composed of gold nano-columns patterned on a titanium surface (AuNC-Ti). This material acts as a nanoengineered surface-enhanced Raman spectroscopy (SERS) substrate that amplifies biological Raman signals at the tissue-implant interface, providing the ability to sense tissue-material interactions in a multiplexed and nondestructive manner. AuNC-Ti SERS substrates were fabricated using oblique angle deposition (OAD) and characterized using scanning electron microscopy (SEM) to show uniform formation of AuNCs ($360 \pm 40$ nm in length and $50 \pm 16$ nm in width). X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and contact angle measurements demonstrated biocompatible surface chemistry with ideal wettability. Biocompatibility was further demonstrated via in vitro cytotoxicity assays on human aortic endothelial cells (HAECs) cultured on AuNC-Ti surfaces. The median SERS enhancement factor (EF) was calculated to be $1.8 \times 10^5$, and spatial identification of reporter molecules and porcine tissue components on AuNC-Ti surfaces was demonstrated using confocal Raman imaging and multivariate analysis. Our approach utilizes unlabeled SERS and machine learning, promising multiplexed characterization of tissue-material interactions and subsequently enabling tissue state determination and non-invasive monitoring of implant-tissue interaction.
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All authors Connie M. Wang, Roberta M. Sabino, Aditya Garg, Ahmed E. Salih, Loza F. Tadesse, Elazer R. Edelman

Materials Science

Influence of Exchange-Correlation Functionals and Neural Network Architectures on Li$^+$-Ion Conductivity in Solid-State Electrolyte from Molecular Dynamics Simulations with Machine-Learning Force Fields

Zicun Li, Huanjing Gong, Ruijuan Xiao et al. (+1 more)

With the rapid advancement of machine learning techniques for materials simulations, machine-learned force fields (MLFFs) have become a powerful tool that complements first-principles calculations by enabling high-accuracy molecular dynamics simulations over extended timescales. Typically, MLFFs are trained on data generated from density functional theory (DFT) using a specific exchange-correlation (XC) functional, with the goal of reproducing DFT-level properties. However, the uncertainties in MLFF-based simulations–arising from variations in both MLFF model architectures and the choice of XC functionals–remain insufficiently understood. In this work, we construct MLFF models of different architectures trained on DFT data from both semilocal and hybrid functionals to describe Li$^+$ diffusion in the solid-state electrolyte Li$_6$PS$_5$Cl. We systematically investigate how different XC functionals influence the Li$^+$ diffusion coefficient. To reduce statistical uncertainty, the mean squared displacements are averaged over 300 independent molecular dynamics (MD) trajectories of 70 ps each, yielding statistical variations below $1\%$. This enables a clear assessment of the respective influences of the functional and the MLFF model. Due to its tendency to underestimate band gaps and migration barriers, the semilocal functional predicts consistently higher Li$^+$ diffusion coefficients, compared to the hybrid functional. Furthermore, comparisons among various neural network methods reveal that the differences in predicted diffusion coefficients arising from different network architectures are of the same order of magnitude as those caused by different functionals, indicating that the choice of the network model itself substantially influences the MLFF predictions. This observation calls from an urgent need for standardized protocols to minimize model-dependent biases in MLFF-based MD.
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All authors Zicun Li, Huanjing Gong, Ruijuan Xiao, Xinguo Ren

Materials Science

LLM tools in the prediction of the stability of perovskite solar cells

S. Frenkel, V. Zakharov and E. A. Katz

Predicting degradation rates is an important task in the development of new perovskite solar cells (PSCs). In this paper, we explore the feasibility of solving this problem using Machine Learning models supported by LLM tools. We consider both the "lifetime" prediction of the device and the prediction of degree of its degradation at specific time intervals. We demonstrate the ability of common LLM tools (ChatGPT, DeepSeek) to suggest and justify prediction methods in a dialogue with the user under conditions of incomplete information about the physical models of PSC degradation and the influence of the environment, providing rather accurate prediction. The results cover the formation of time series of efficiency with a given architecture, calculated using various available mathematical models together with environmental characteristics archived in various meteorological databases (illumination, temperature, humidity, UV level). We conclude that ChatGPT currently has sufficient access to training samples, can suggest to PSC designer various PSC models in the literature, and has adequate solutions for predicting degradation trends.
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Materials Science · Cross-listed from physics.chem-ph

Exceptional Alkaline Methanol Electrooxidation on Bi-modified Pt3M Intermetallics: Kinetic Origins and an OH Binding Energy Descriptor

Lecheng Liang, Hengyu Li, Shao Ye et al. (+7 more)

The exploration of advanced CO-free catalysts and clarifying the ambiguous kinetic origins and governing factors would undoubtedly open up opportunities to overcome the sluggish kinetics of methanol electrooxidation and promote the development of direct methanol fuel cells. Herein, we constructed a family of Bi-modified Pt3M intermetallic catalysts (Bi-Pt3M/C, M=Cr, Mn, Co, Zn, In, Ga, and Sn) that follow CO-free dominated pathway and exhibit exceptional catalytic activity. More significantly, leveraging this platform, we have identified the pivotal factor governing the reaction kinetics in CO-free pathway, namely OH binding energy (OHBE). This arises because the rate-determining step (RDS) encompasses both C-H bond activation and water dissociation, whose respective barriers can be reflected by the OHBE. Accordingly, OHBE can act as an activity descriptor. Specifically, Bi-Pt3In/C stands out from other Bi-Pt3M/C and delivers the unprecedented mass activity of 36.7 A mgPt-1 at peak potential, far exceeding state-of-the-art Pt-based catalysts reported to date. Taking Bi-Pt3In/C as a proof of concept, we clearly elucidate the origin of enhanced MOR activity by combining theoretical calculations, kinetic isotope effects, and formaldehyde electrooxidation. Moreover, there exhibits a volcano-type trend between OHBE and the activity of Bi-Pt3M/C. Beyond the discovery of ultrahigh-performance catalysts, these findings provide a detailed mechanistic picture of RDS and offer an innovative design principle for advanced catalysts.
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All authors Lecheng Liang, Hengyu Li, Shao Ye, Peng Li, Kaiyang Xu, Jinhui Liang, Binwen Zeng, Bo Shen, Taisuke Ozaki, Zhiming Cui

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

Recovering long-range cumulative response to geometric frustration in quasi-1d systems, mediated by constitutive softness

Snir Meiri and Efi Efrati

Cumulative geometric frustration can drive self-limited assembly and morphology selection through size-dependent energetic costs. However, the slenderness of quasi-one-dimensional systems generally suppresses the formation of long-range longitudinal gradients. We show that the suppression of longitudinal gradients can be overcome by tuning the ratio between the longitudinal and transverse (shear) moduli. We demonstrate the recovery of cumulative frustration across distinct quasi-one-dimensional systems, each frustrated through a different mechanism, by the introduction of a soft response mode. The resulting saturation length scale is universal and is dictated by the local constitutive information of the system.
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Materials Science

Unidirectional magnetoresistance driven by nonequilibrium antiferromagnetic magnons

Xue He, Hans Gløckner Giil, Caiqiong Xu et al. (+6 more)

Magnetoresistive effects are typically symmetric under magnetization reversal. However, nonlinear spin transport can give rise to unidirectional magnetoresistance in systems with strong spin-orbit interaction and broken inversion symmetry. Here, we demonstrate that the nonequilibrium magnon accumulation characterized by a finite magnon chemical potential can lead to a large and robust magnonic unidirectional spin Hall magnetoresistance (USMR) in the weakly coupled van der Waals antiferromagnet CrPS4 in contact with Pt. Unlike conventional magnonic USMR driven by magnetization fluctuations, this effect persists under strong magnetic fields and low temperatures, with a pronounced peak near the spin-flip transition. The magnitude of magnonic USMR in CrPS4/Pt exceeds that of YIG/Pt by more than two orders of magnitude and surpasses the electrical USMR in metallic Ta/Co bilayers by a factor of two. The observed field and temperature dependence indicates that spin transport is dominated by magnon chemical potential gradients rather than thermal- or fluctuation-driven magnon generation. These findings establish a new mechanism for nonlinear magnetoresistance in antiferromagnetic van der Waals heterostructures and open a route to magnon-based antiferromagnetic spintronic functionalities in two-terminal device geometries.
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All authors Xue He, Hans Gløckner Giil, Caiqiong Xu, Jicheng Wang, Arne Brataas, Jinbo Yang, Yanglong Hou, Rui Wu, Shilei Ding

Materials Science

Progress on Data-Driven, Multi-Objective Quantum Optimization

Thomas Plehn, Daniel Barragan-Yani, Eric Breitbarth et al. (+2 more)

Here, we present two complementary approaches that advance quadratic unconstrained binary optimization (QUBO) toward practical use in data-driven materials design and other real-valued black-box optimization tasks. First, we introduce a simple yet powerful preprocessing scheme that, when applied to a machine-learned QUBO model, entirely removes system-level equality constraints by construction. This makes cumbersome soft-penalty terms obsolete, simplifies QUBO formulation, and substantially accelerates solution search. Second, we develop a multi-objective optimization strategy inspired by Tchebycheff scalarization that is compatible with non-convex objective landscapes and outperforms existing QUBO-based Pareto front methods. We demonstrate the effectiveness of both approaches using a simplified model of a multi-phase aluminum alloy design problem, highlighting significant gains in efficiency and solution quality. Together, these methods broaden the applicability of QUBO-based optimization and provide practical tools for data-driven materials discovery and beyond.
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All authors Thomas Plehn, Daniel Barragan-Yani, Eric Breitbarth, Guillermo Requena, David Melching

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

Pressure-induced Lifshitz and quantum phase transitions in electron-doped cuprate superconductor

Jinyu Zhao, Shu Cai, Zhaoyu Liu et al. (+14 more)

We report the first observations of a pressure-induced Lifshitz transition coupled with a quantum phase transition in electron-doped cuprate superconductor Pr0.87LaCe0.13CuO4 (PLCCO), by combining high-pressure electrical resistance, Hall coefficient and synchrotron X-ray diffraction (XRD) measurements at low temperatures. Our low-temperature Hall coefficient measurements reveal that the Hall coefficient decreases continuously and reaches zero at about 10 GPa (critical pressure of Pc1). Upon further compression beyond Pc1, Hall coefficient unexpectedly changes its sign from negative to positive, signaling a reconstruction of the Fermi surface from electron-dominated to hole-dominated topology. Concurrently, the superconducting transition temperature (Tc) exhibits a monotonic suppression, vanishing completely at 17.6 GPa (critical pressure of Pc2), where the system enters a non-superconducting metallic state. Our low temperature XRD measurements unequivocally demonstrate the absence of any structural phase transition across Pc1 and Pc2. Therefore, the sign change in RH at Pc1 is associated with a Lifshitz transition, which is never found in the compressed bulk electron- or hole-doped cuprate superconductors. Moreover, the quantum phase transition observed at Pc2 contrasts sharply with known high-pressure behavior of hole-doped cuprates, uncovering a fundamental difference on how pressure tunes the ground states of electron- versus hole-doped systems. These findings provide crucial insights into the different pressure responses on the interplay among Fermi surface topology, electronic correlations, and superconductivity between these two kinds of cuprate superconductors.
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All authors Jinyu Zhao, Shu Cai, Zhaoyu Liu, Jianfeng Zhang, Shuaihang Sun, Pengyu Wang, Jing Guo, Yazhou Zhou, Shiliang Li, Fuyang Liu, Luhong Wang, Haozhe Liu, Yang Ding, Qi Wu, Tao Xiang, Richard L Greene, Liling Sun

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

Hydrodynamic permeability of fluctuating porous membranes

Albert Dombret, Adrien Sutter, Baptiste Coquinot et al. (+3 more)

In this paper we examine how porosity fluctuations affect the hydrodynamic permeability of a porous matrix or membrane. We introduce a fluctuating Darcy model, which couples the Navier-Stokes equation to the space- and time-dependent porosity fluctuations via a Darcy friction term. Using a perturbative approach, a Dyson equation for hydrodynamic fluctuations is derived and solved to express the permeability in terms of the matrix fluctuation spectrum. Surprisingly, the model reveals strong modifications of the fluid permeability in fluctuating matrices compared to static ones. Applications to various matrix excitation models - breathing matrix, phonons, active forcing - highlight the significant influence of matrix fluctuations on fluid transport, offering insights for optimizing membrane design for separation applications.
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All authors Albert Dombret, Adrien Sutter, Baptiste Coquinot, Nikita Kavokine, Benoit Coasne, Lydéric Bocquet

Materials Science

Defect-Engineered Multifunctionality in Cu-Doped Bi2Te2: Interplay of Thermoelectric, Piezoelectric, and Optoelectronic Properties from First-Principles Insights

Muhammad Usman Javed, Sikander Azam, Qaiser Rafiq et al. (+1 more)

Defect engineering can improve the linked charge, spin, and lattice behavior of thermoelectric topological insulators. Using density functional theory with spin orbit coupling, we study structural, electronic, optical, thermoelectric, piezoelectric, and charge density features of pristine and Cu doped Bi2Te3. Cu substitution slightly expands the lattice and lowers the total energy minimum, which stabilizes the structure. The density of states shows that Cu d and Te p hybridization creates sharp states near the Fermi level, raising the carrier concentration and supporting higher Seebeck coefficient and power factor. Transport calculations show an increase in the Seebeck coefficient from about 180 microvolts per kelvin in pristine Bi2Te3 to about 220 microvolts per kelvin at 300 K while keeping the electrical conductivity nearly unchanged. Optical spectra reveal strong low energy absorption and very large static dielectric constants (greater than 600), indicating tunable light matter coupling. The piezoelectric coefficient e33 rises from 0.19 C/m2 in pristine Bi2Te3 to 0.38 C/m2 at 5 percent Cu and 0.51 C/m2 at 10 percent Cu, reflecting symmetry breaking and strain driven polarization. Charge density difference maps show anisotropic redistribution, with Cu donating about 0.8 electrons mainly to Te sites, which enhances p type behavior and phonon scattering. Overall, Cu doping reshapes Bi2Te3 into a multifunctional material with coupled thermoelectric, piezoelectric, and optical responses suitable for hybrid energy harvesting, infrared detection, and spin based devices.
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All authors Muhammad Usman Javed, Sikander Azam, Qaiser Rafiq, Hamdy Khamees Thabet

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

Magnetic field-induced momentum-dependent symmetry breaking in a kagome superconductor

Jianwei Huang, Zheng Ren, Hengxin Tan et al. (+17 more)

When multiple degrees of freedom share similar energy scales in quantum materials, intertwined electronic orders, which exhibit broken symmetries, are often strongly coupled. Recent studies on kagome superconductors such as CsV$_3$Sb$_5$ report rotational and time-reversal symmetry breaking linked to a charge density wave. Here, we observe a momentum-selective response of the electronic structure of CsV$_3$Sb$_5$ to an external magnetic field. By performing angle-resolved photoemission spectroscopy in a tuneable magnetic field, we demonstrate that the response of the electronic structure is compatible with piezomagnetism along with strong orbital selectivity. Our results show that the origin of the time-reversal symmetry breaking is associated with the vanadium Van Hove singularities at the onset of the charge density wave order. We also demonstrate the presence of fluctuations beyond the charge ordering temperature. Our results reveal that magnetic fields can be used as tuning knobs for disentangling intertwined orders in the momentum space for quantum materials.
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All authors Jianwei Huang, Zheng Ren, Hengxin Tan, Jounghoon Hyun, Yichen Zhang, Thomas Hulse, Zhaoyu Liu, Jonathan M. DeStefano, Yaofeng Xie, Ziqin Yue, Junichiro Kono, Pengcheng Dai, Yu He, Aki Pulkkinen, Ján Minár, Jiun-Haw Chu, Ziqiang Wang, Binghai Yan, Rafael M. Fernandes, Ming Yi

Materials Science

Optical properties of InGaN quantum wells: accurately modeling the effects of disorder

Aurelien David

A model including random alloy disorder is used to account for the outstanding optical properties of InGaN quantum wells. The model provides excellent agreement to experimental observations on various structures. This study clarifies the prevalent role played by disorder in optical features such as the luminescence lineshape, the Stokes shift, and the radiative rate. Finally, the relationship between disorder and the peculiar properties of long-wavelength InGaN emitters is investigated.
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Materials Science

Deep Learning-Based Quantum Transport Simulations in Two-Dimensional Materials

Jijie Zou, Zhanghao Zhouyin, Qiangqiang Gu et al. (+1 more)

Two-dimensional (2D) materials exhibit a wide range of electronic properties that make them promising candidates for next-generation nanoelectronic devices. Accurate prediction of their quantum transport behavior is therefore of both fundamental and technological importance. While density functional theory (DFT) combined with the non-equilibrium Green$'$s function (NEGF) formalism provides reliable insights, its high computational cost limits applications to large-scale or high-throughput studies. Here we present DeePTB-NEGF, a framework that combines a deep learning-based tight-binding Hamiltonians derived learned directly from first-principles calculations (DeePTB) with efficient quantum transport simulations implemented in the DPNEGF package. To validate the method, we apply it to three prototypical 2D materials: graphene, hexagonal boron nitride (h-BN), and MoS$_2$. The resulting band structures and transmission spectra show excellent agreement with conventional DFT-NEGF results, while achieving orders-of-magnitude improvement in efficiency. These results highlight the capability of DeePTB-NEGF to enable accurate and efficient quantum transport simulations, thereby opening avenues for large-scale exploration and device design in 2D materials.
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All authors Jijie Zou, Zhanghao Zhouyin, Qiangqiang Gu, Shishir Kumar Pandey

Materials Science

Development of a Model for Irradiation-Assisted Grain Growth for Nanocrystalline UO2

Md Ali Muntaha, Larry Aagesen and Michael Tonks

In this work, we have developed a model for irradiation-assisted grain growth in nanocrystalline UO$_2$ using the MARMOT code. We include the impact of irradiation on UO$_2$ grain growth by coupling a phase field grain growth model with a heat conduction simulation that features a random heat source representing thermal spikes. Our model parameters have been calibrated against experimental measurements at 300 K. The calibrated model predicts grain growth in an irradiated UO$_2$ thin film that compares well with experimental data at 50 K. These results suggest that thermal spikes are the major cause of the irradiation-assisted grain growth observed in the UO$_2$ experiments. They also indicate that irradiation-assisted grain growth is only significant with average grain sizes less than 35 nm, and thus can be neglected when considering fuel performance of typical UO$_2$ fuel pellets.
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Materials Science · Cross-listed from physics.app-ph

Electrical Stability of Cr2O3/e̱ta}-Ga2O3 and NiOx/e̱ta}-Ga2O3 Heterojunction Diodes

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

This work reports the electrical characteristics comparison study between Cr2O3 and NiOx based heterojunction diodes (HJD) on halide vapor phase epitaxy (HVPE) grown e̱ta}-Ga2O3 epitaxial layers. Both as-fabricated Cr2O3 and NiOx HJDs exhibited forward current density in a range of 130-150 A/cm^2 at 5 V with rectifying ratios >10^10 and a reverse leakage current density at 10^-8 A/cm^2 at -5 V. The differential specific on-resistance of Cr2O3 and NiOx HJDs was 12.01 m{\Omega}*cm^2 and 12.05 m{\Omega}*cm^2, respectively. Breakdown voltages of Cr2O3 HJDs ranged from 1.4-1.9 kV and 1.5-2.3 kV for NiOx HJDs. Theoretical band alignment between Cr2O3 and e̱ta}-Ga2O3 was calculated from first principles. The ambient exposed NiOx/HVPE e̱ta}-Ga2O3 HJDs forward current density degraded after 10 days while that of Cr2O3/HVPE e̱ta}-Ga2O3 HJDs remained nearly unchanged after the same amount of time. It was later confirmed that the ambient exposed sputtered NiOx sheet resistance (Rsh) degradation gave rise to the reduction of the forward current density of the NiOx based HJDs, and water (H2O) was qualitatively determined to be the agent attributed to the forward conduction degradation by measuring the Rsh of NiOx-on-sapphire reference wafer after exposing it to different environments. The Cr2O3/HVPE e̱ta}-Ga2O3 HJD also exhibited enhanced thermal stability compared to the NiOx/e̱ta}-Ga2O3 heterostructures at elevated temperatures. Interfacial nickel gallate (Ga2NiO4) phase formation expected from phase diagrams can explain the reduced thermal stability of NiOx/e̱ta}-Ga2O3 HJDs. This study indicates that Cr2O3 is a stable p-type oxide for the realization of robust multi-kV e̱ta}-Ga2O3 HJDs.
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All authors Yizheng Liu, Haochen Wang, Carl Peterson, Chinmoy Nath Saha, Chris G. Van de Walle, Sriram Krishnamoorthy

Materials Science

Machine learned potential for defected single layer hexagonal boron nitride

John Janisch, Duy Le and Talat S. Rahman

Development of machine learned interatomic potentials (MLIP) is critical for performing reliable simulations of materials at length and time scales that are comparable to those in the laboratory. We present here a MLIP suitable for simulations of the temperature dependent structure and dynamics of single layer hexagonal boron nitride (h-BN) with defects and grain boundaries, developed using a strictly local equivariant deep neural network as formulated in the Allegro code. The training dataset consisted of about 30,000 images of h-BN with and without point defects generated with ab-initio molecular dynamics simulations, based on density functional theory (DFT), at 500, 1000, and 1500K. The developed MLIP predicts potential energies and forces with a mean absolute error (MAE) of 4 meV/atom and 60 meV/Angstrom , respectively. It also reproduces phonon dispersion curves and density of vibrational states of pristine bulk h-BN that are comparable with that obtained from density functional theory-based calculations. Molecular dynamics simulations of the motion of the 4|8 grain boundary unit in h-BN shows the first step to have an activation barrier ~2.2 eV, indicating immobility of the grain boundary. Moving the grain boundary units past the first shows much lower activation barriers of ~0.42eV, suggesting a facile motion of the grain boundary once the first movement is stimulated. These simulations yield a scaled mobility of 1.739*10^(-11) m^3/Js for a temperature of 1500K which, given the inherent differences in the set-ups, is not too far from the experimental value of 1.36*10^(-9) m^3/Js. The ability to predict grain boundary mobility within reasonable agreement with experiment demonstrates the robustness of the MLIP and its suitability for reliable simulations of defect structures and dynamics in single layer h-BN.
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Thursday 11 December

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

Gate-controlled analog memcapacitance in LaAlO3/SrTiO3 interface-based devices

Soumen Pradhan, Victor Lopez-Richard, Igor Ricardo Filgueira e Silva et al. (+8 more)

Current memcapacitor implementations typically demand complex fabrication processes or depend on organic materials exhibiting poor environmental stability and reproducibility. Here, we demonstrate memcapacitor structures utilizing a quasi 2-dimensional electron gas, formed at the crystalline LaAlO3/SrTiO3 heterointerface, as electrodes and SiO2/SrTiO3 as dielectric layer. The observed memcapacitance originates from the charge localization in a lateral floating gate, while an applied gate voltage enables reversible tuning of the device capacitance. Furthermore, preprogrammed or erased gate biases enable controllable shifts of the capacitance hysteresis window toward positive or negative bias, leading to an enlarged capacitance gap at zero bias. A memcapacitor model developed for this system reproduces the main features of the experimental capacitance hysteresis, capturing the effects of charge fluctuations and dielectric frequency modulation within the oxide layer. The demonstrated low-voltage operation and gate tunability of oxide interface-based memcapacitors highlight their potential for power-efficient, capacitor-based neuromorphic and synaptic electronic architectures.
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All authors Soumen Pradhan, Victor Lopez-Richard, Igor Ricardo Filgueira e Silva, Fabian Hartmann, Ana Luiza Costa Silva, Leonardo K. Castelano, Merit Spring, Silke Kuhn, Michael Sing, Ralph Claessen, Sven Höfling

Materials Science · Cross-listed from physics.optics

Bismuth nanogratings with narrow plasmon resonances for dynamic polarized color generation and colorimetric sensing

Fernando Chacón-Sánchez, Fátima Cabello, Marina García Pardo et al. (+3 more)

Bismuth nanostructures are appealing for sustainable color generation and sunlight harvesting, thanks to their non-toxicity and their tunable visible-to-near infrared interband plasmon resonances. However, owing to their broad and polarization-insensitive spectral features, the nanostructures reported so far displayed a limited color tunability and were lacking other functionalities such as sensing. Herein, we report bismuth nanogratings with polarization-sensitive and narrow plasmon resonances (Q > 10). They were fabricated on the $cm^2$ scale following a lithography-free approach: conformal pulsed laser deposition of bismuth onto both the reflective and transparent nanostructured layers of DVDs. We characterized their specular reflectance for different orientations of the plane of incidence, angles of incidence, and polarizations of light. When light is polarized in the plane perpendicular to the lines, plasmon resonances occur and shift across the visible-to-near infrared upon changing the angle of incidence. In contrast, no such resonances occur when light is polarized in the plane parallel to the lines. This results in well-contrasted, polarization-sensitive colors, which are iridescent for the former orientation of polarization, and not for the latter. Resonances strongly shift upon changing the refractive index of the surrounding medium (> 500 nm/RIU), resulting in a marked change in the plasmonic color, e.g., from green in air to red in water. This showcases the potential of these nanogratings for dynamic polarized color generation and colorimetric sensing.
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All authors Fernando Chacón-Sánchez, Fátima Cabello, Marina García Pardo, Emmanuel Haro-Poniatowski, Rosalía Serna, Johann Toudert

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

Quasi-one-dimensional taco-shaped bands in large-angle twisted bilayer transition metal dichalcogenides

Giovanny Espitia, Seung Hun Lee, Calvin Kaiyu Chiu et al. (+2 more)

Two-dimensional moiré materials offer a powerful, twist-tunable platform for engineering electronic bands and correlations, though most studies to date have focused on small twist angles where flat bands arise from symmetry-pinned monolayer momenta. Here, we observe the surprising emergence of flat electronic bands with a distinctive quasi-one-dimensional dispersion at large twist angles in bilayer transition metal dichalcogenides that originate from the $\Lambda$ valley states at generic momenta between $\Gamma$ and $K$ points. These taco-shaped anisotropic bands result from optimal interlayer hybridization between like-spin $\Lambda$ valleys at the conduction band minimum in the Brillouin zone, resulting in directional band flattening at a magic twist-angle of 21.8$^{\circ}$. The bands form six anisotropic channels with a sixfold alternating spin texture reminiscent of altermagnetic textures. At low energies, the density of states shows a power-law dependence due to the quasi-one-dimensional character, enhancing the potential for correlated phases. Our results provide a new platform for correlated phenomena and broaden the scope of moiré engineering to large twist angles in 2D materials.
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All authors Giovanny Espitia, Seung Hun Lee, Calvin Kaiyu Chiu, Junyeong Ahn, Mit H. Naik

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

Site Preference and Possible Coexistence of Antiferromagnetic Order and Magnetic Frustration in (Co1-xMgx)10Ge3O16 (0 <= x <= 30%)

Gina Angelo, Qiang Zhang, Dylan Correll et al. (+1 more)

Geometrically frustrated magnetism has attracted tremendous attention while chemical doping has been utilized as an important tool to probe frustrated magnetism in various systems. Here we perform a systematic study by doping non-magnetic Mg2+ into a magnetically complicated system, Co10Ge3O16, which contains three frustrated sublattices of Co2+, e.g., triangular Co1, Kagome Co2 and Co3 sublattices. By growing crystals for (Co1-xMgx)10Ge3O16 (0 < x <= 30%), we observed obvious site preference of Mg2+ on Co1 and Co3 sites over the Co2 site. Powder X-ray diffraction (XRD) patterns confirm the high purity of the samples and indicate systematic peak shift, consistent with the loading compositions. Although previously investigated, the magnetic structure and expected magnetic frustration in this system are not fully uncovered. Our temperature-dependent magnetic susceptibility measurements suggest that the high-temperature magnetostructural phase transition with antiferromagnetic ordering and a low-temperature broad peak are suppressed with Mg2+ doping, while two new magnetic features emerge at high Mg2+ level. Moreover, the structural phase transition from high-temperature R-3m to low-temperature C2/m space group is absent at the antiferromagnetic ordering temperature, as confirmed by single-crystal XRD. By analyzing the heat capacity and neutron powder diffraction results of the highest doped sample, (Co0.7Mg0.3)10Ge3O16, we speculate that the Co1 site is responsible for the long-range antiferromagnetic ordering, while the other two sites are short-range correlated in addition to a Mg2+-induced spin-glass state. This study provides more insights into the complex magnetism in Co10Ge3O16 by using the non-magnetic Mg2+ as a probe. However, detailed magnetic structure requires further efforts on growing large single crystals.
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All authors Gina Angelo, Qiang Zhang, Dylan Correll, Xin Gui

Materials Science

Creep Behavior of High-Entropy Alloys: A Critical Review

Mingwei Zhang, Uwe Glatzel, Martin Heilmaier et al. (+1 more)

High-entropy alloys (HEAs) comprise a compositionally complex class of materials that in certain cases exhibit outstanding mechanical properties. While substantial progress has been made in understanding their phase stability, microstructure, and deformation mechanisms at room and cryogenic temperatures, the long-term creep behavior (>100 h) of HEAs at high temperatures (>0.6 Tm, where Tm is the melting temperature) remains relatively underexplored. This knowledge gap is critical, as many engineering applications, including those in aerospace, power generation, aero engines and nuclear energy, require materials with good creep resistance to maintain structural integrity over extended service lifetimes. This review provides a focused and critical assessment of the current understanding of high-temperature deformation and creep behavior of HEAs, with particular attention paid to face-centered cubic HEAs and body-centered cubic refractory HEAs. The underlying deformation mechanisms governing their creep response and the influence of phase stability at elevated temperatures are examined in detail. Recent studies reveal mechanistic differences between HEAs and conventional dilute alloys that do not always lead to improved creep resistance belying their initial promise. Based on these findings, we discuss the challenges in designing HEAs for high-temperature structural applications and outline future research directions that may lead to creep-resistant HEAs.
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All authors Mingwei Zhang, Uwe Glatzel, Martin Heilmaier, Easo P. George

Materials Science

A probabilistic framework for crystal structure denoising, phase classification, and order parameters

Hyuna Kwon, Babak Sadigh, Sebastien Hamel et al. (+3 more)

Atomistic simulations generate large volumes of noisy structural data, yet extracting phase labels and continuous order parameters (OPs) in a robust and general manner remains challenging. Existing tools are often specialized to a limited set of prototypes and split thermal-noise removal, phase classification, and OP construction into separate steps. Here we present a unified probabilistic framework for analyzing noisy atomic configurations with respect to known crystal prototypes. The model predicts per-atom, per-prototype logits and aggregates them into a scalar log-probability (logP) landscape over atomic coordinates. Its gradient defines a conservative denoising field, while the logits provide local phase labels, prototype-resolved OPs, and ambiguity measures through logit margins. We train on AFLOW-mapped crystalline structures from the Materials Project with synthetic positional and elastic perturbations, then test extrapolation to stronger noise, finite-temperature disorder, point defects, water–ice coexistence, binary polymorphs, and shock-compressed Ti. A single differentiable scalar model recovers prototype identity after denoising, tracks smooth transformations such as Bain and Burgers paths, and exposes low-confidence regions near defects and phase boundaries. This provides an integrated and extensible tool for analyzing complex atomistic simulations.
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All authors Hyuna Kwon, Babak Sadigh, Sebastien Hamel, Vincenzo Lordi, John Klepeis, Fei Zhou

Materials Science

Structural, physical, and Judd-Ofelt analysis of germanium magnesium-telluroborate glass containing different amounts of Tm2O3

A. A. El-Maaref, Kh. S. Shaaban and E. A. Abdel Wahab

Germanium magnesium-telluroborate glasses with the composition 78B2O3-10GeO2-5TeO2-7-x MgO-xTm2O3, x = 0, 0.25, 0.5, 1, and 1.5 mol% were fabricated by using the melt quenching process. With the increase of Tm2O3 concentration, the density values increase from 3.574 to 4.153 g/cm^3, while the molar volume values decrease from 21.145 to 19.445 cm3/mol. Fourier transform infrared analysis supports the existence and conversion of BO3 and BO4. The conversion of BO3 to BO4 would lead to greater bridging oxygens BOs, influencing and reinforcing the glass network. The optical features were studied. The optical band gap decreased by increasing Tm2O3 content in the glass formula, while the index of refraction increased. The parameters take the values between 3.16 eV and 2.31 eV. Other optical and physical constants were determined like optical conductivity, electronegativity, metallization, reflection loss, steepness parameters, and transmission coefficient. Judd-Ofelt theory is used to estimate the optical intensities and line strengths of the present glasses. Radiative lifetimes and branching ratios are evaluated of different manifolds belonging to Tm3+ doped present glasses. The results showed the possibility of potential applications for these materials in the fields of laser development, Light-emitting diodes (LEDs), optical amplification and optoelectronic devices.
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Materials Science

Disorder mediated fully compensated ferrimagnetic spin-gapless semiconducting behaviour in Cr3Al Heusler alloy

Reshna Elsa Philip, Pooja Vyas, Nikhil Joseph Joy et al. (+9 more)

Spin-gapless semiconductors (SGSs) that simultaneously host fully compensated ferrimagnetism are highly sought for energy-efficient and stray-field-free spintronic technologies, yet their realization in chemically disordered systems has remained elusive. Here, we demonstrate that the binary Heusler alloy Cr3Al despite adopting a fully A2-disordered structure exhibits a rare coexistence of SGS transport and a fully compensated ferrimagnetic (FCF) ground state. Single-crystalline and polycrystalline Cr3Al samples were synthesized, and comprehensive structural analyses using single crystal XRD, synchrotron powder XRD, and neutron powder diffraction reveal complete Cr/Al site mixing. Remarkably, this chemical disorder does not disrupt magnetic order; instead, magnetization, X-ray magnetic circular dichroism (XMCD), and temperature-dependent neutron diffraction establish a robust compensated ferrimagnetic state with a vanishingly small ordered moment of 0.1(1) muB/f.u and a high Curie temperature of 773(2) K. Electrical and thermal transport measurements uncover clear SGS characteristics, including weak temperature-dependent conductivity, very low Seebeck coefficients, and electron-hole compensated transport. Hall measurements show unusual temperature-dependent carrier concentrations consistent with disorder-modified electronic states. First-principles calculations on an A2-disordered SQS structure reproduce the experimentally observed negligibly small magnetization (0.0072 muB/f.u) and reveal a vanishing spin-up band gap unambiguously supporting SGS behavior driven by chemical disorder. Our results identify Cr3Al as the first experimentally verified A2-disordered Heusler alloy exhibiting both fully compensated ferrimagnetism and spin-gapless semiconducting transport, positioning it as a robust and disorder-tolerant platform for next-generation, high-temperature spintronic devices.
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All authors Reshna Elsa Philip, Pooja Vyas, Nikhil Joseph Joy, Sandip Kumar Kuila, Sonia Beniwal, Akshata Magar, Dinesh Kumar Shukla, Partha Pratim Jana, Amit Kumar, Aftab Alam, Jayakumar Balakrishnan, Soham Manni

Materials Science

Large Language Models for Superconductor Discovery

Suman Itani, Yibo Zhang, Ranjit Itani et al. (+1 more)

Large language models (LLMs) offer new opportunities for automated data extraction and property prediction across materials science, yet their use in superconductivity research remains limited. Here we construct a large experimental database of 78,203 records, covering 19,058 unique compositions, extracted from scientific literature using an LLM-driven workflow. Each entry includes chemical composition, critical temperature, measurement pressure, structural descriptors, and critical fields. We fine-tune several open-source LLMs for three tasks: (i) classifying superconductors vs. non-superconductors, (ii) predicting the superconducting transition temperature directly from composition or structure-informed inputs, and (iii) inverse design of candidate compositions conditioned on target Tc. The fine-tuned LLMs achieve performance comparable to traditional feature-based models and in some cases exceed them, while substantially outperforming their base versions and capturing meaningful chemical and structural trends. The inverse-design model generates chemically plausible compositions, including 28% novel candidates not seen in training. Finally, applying the trained predictors to the GNoME database identifies unreported materials with predicted Tc > 10 K. Although unverified, these candidates illustrate how integrating an LLM-driven workflow can enable scalable hypothesis generation for superconductivity discovery.
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All authors Suman Itani, Yibo Zhang, Ranjit Itani, Jiadong Zang

Materials Science

Computational Approach to Investigate Structure-Property Relationship of a series of Carbazole Containing Thermally Activated Delayed Fluorescent Molecules

Md. Asif and Nazia Chawdhury

Donor-acceptor type compounds are an important category of organic materials that show properties suitable for light emission applications. To achieve a full understanding of the mechanism of thermally activated delayed fluorescence (TADF) process, we studied the structure-property relationship for a series of carbazole based TADF emitters, 2CzPN, 4CzPN, 4CzIPN, 4CzBN and 5CzBN. We applied density functional theory to investigate kinetic and electronic properties. We find that the energetic position of triplet excited state of these emitters depends on their molecular structure. Our findings emphasize that to enable reverse intersystem crossing and eventually TADF, strong spin orbit coupling and minimal energy difference between singlet and triplet states $\Delta E_{ST}$ must be obtained simultaneously. We also find that the reverse intersystem crossing rates $k_{RISC}$ values are higher where $\Delta E_{ST}$ values are closer to reorganization energy. Furthermore, a small change in the absorption peak of optical absorption spectra with and without spin orbit coupling (SOC) is observed for each emitter. This result is extremely beneficial for the design of new TADF molecules, and we believe that our work contributes to the progress of future development of high-performance organic molecular light-emitting devices.
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Materials Science

Towards ultra-scaled nanoelectronics using the zipper material system $Bi_2O_2Se/Bi_2SeO_5$

Mohammad Rasool Davoudi, Mina Bahrami, Axel Verdianu et al. (+19 more)

Two-dimensional (2D) materials could overcome the scaling bottleneck of nanoelectronics by enabling atomically thin channels, superior electrostatic control, and reduced short-channel effects. However, progress is limited by the lack of semiconductor&ndash;insulator interfaces being simultaneously scalable, stable, and reliable. Conventional 2D interfaces are often low quality or require transferring dissimilar materials, limiting reproducibility and scalability. We show that the zipper heterostructure formed by the high-mobility 2D semiconductor Bi<sub>2</sub>O<sub>2</sub>Se and its native high-<i>&kappa;</i> oxide Bi<sub>2</sub>SeO<sub>5</sub> addresses these challenges, providing an atomically sharp, chemically matched interface with excellent electrostatics and promising scaling potential. We further present the first comprehensive multiscale assessment of Bi<sub>2</sub>O<sub>2</sub>Se/Bi<sub>2</sub>SeO<sub>5</sub> transistors targeting thermal stability, reliability, and scalability by linking atomic-scale structure and defects to device-level behavior across <i>four</i> transistor generations (top-gated, fin, and two gate-all-around architectures). Benchmarking against IRDS-2035 targets indicates that Bi<sub>2</sub>O<sub>2</sub>Se/Bi<sub>2</sub>SeO<sub>5</sub> devices could deliver high drive current with low gate leakage under aggressive scaling, potentially surpassing the targets in the upper-bound region of the sensitivity analysis. Finally, we identify oxygen-related oxide defects as the dominant origin of hysteresis consistent with a beneficial role of encapsulation and oxygen-rich annealing. Together, our findings support the potential of this zipper material system as a technologically-credible and manufacturing-relevant platform for future nanoelectronics.
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All authors Mohammad Rasool Davoudi, Mina Bahrami, Axel Verdianu, Pedram Khakbaz, Dominic Waldhoer, Mahdi Pourfath, Alexander Karl, Christoph Wilhelmer, Yury Illarionov, Seyed Mehdi Sattari-Esfahlan, Yichi Zhang, Junchuan Tang, Aftab Nazir, Ye Li, Xiaoying Gao, Congwei Tan, Yu Zheng, Changze Liu, Michael Waltl, Hailin Peng, Theresia Knobloch, Tibor Grasser

Materials Science

Composition/structure directed search for new chalcogenide compounds

Alon Hever, Ohad Levy, Stefano Curtarolo et al. (+1 more)

This work presents a simple scheme for finding new crystalline compounds by adapting structure types from neighbor atoms compounds. The approach is demonstrated for the selenide and sulfide families of binary compounds. It predicts ten new compounds that are not currently included in the inorganic crystal structure database (ICSD). The compounds primarily originated from a small search domain that includes near neighbors. Comparison with extended searches that include structures from binary systems of more remote atoms in the periodic table demonstrate the relative efficiency of near neighbor screening. This points at the possibility of using similar directed searches as a heuristic rule for efficiently finding new stable compounds in additional compound families.
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All authors Alon Hever, Ohad Levy, Stefano Curtarolo, Amir Natan

Materials Science · Cross-listed from quant-ph

Understanding Surface-Induced Decoherence of NV Centers in Diamond

Jonah Nagura, Mykyta Onizhuk and Giulia Galli

Nitrogen vacancy centers (NV) in proximity to diamond surfaces are promising nanoscale quantum sensors. However, their coherence properties are negatively affected by magnetic and electric surface noise, whose origin and detailed impact have remained elusive. Using atomistic models of diamond surfaces derived with density functional theory, together with decoherence time calculations with cluster correlation expansion methods, we quantify the effects of surface crystallographic orientation and functionalization, and of the density of unpaired electrons on the NV Hahn-echo time $T_2$. We determine a crossover depth at which $T_2$ ceases to be limited by surface nuclear spins and recovers the bulk-limited value. We find that for static surface-electron baths, the ratio between the NV depth and the separation between surface electron spins determines a transition from fast-fluctuating to quasi-static noise, leading to a dependence of $T_2$ on orientation for specific surfaces. We also find that the modulation of $T_2$ by spin-phonon relaxations leads to motional-narrowing at sub-microsecond relaxation times. Importantly, our calculations show that it is only when accounting for surface-spin in-sequence hopping that measured $T_2$ values as a function of depth can be reproduced, thus highlighting the importance of hopping-mediated models to describe the surface spin noise affecting NV sensors. Overall, our work provides clear guidelines for engineering diamond surfaces to achieve enhanced NV coherence for quantum sensing and information processing applications.
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