Materials Science
Human and LLM Collaboration for Accelerated Materials Synthesis and Discovery
Gregory Bassen, Wyatt Bunstine, Sarah Okandey et al. (+7 more)
Although Large
Language Models (LLM) and Artificial Intelligence (AI) tools have enabled a rapid increase in the generation rate of predicted materials, the rate of new materials discovery has lagged behind. This is due to the challenges associated with designing a sequence of chemical reactions to predictably produce new materials, especially in new structure types. Here, we report a study of human and LLM generated recipes for the synthesis of known and new materials. The success of the recipes is determined through in-lab experimentation, and the results are passed back to the humans and LLMs in a closed-loop process to study the effects of their collaboration. The Ruddlesden-Popper homologous series was selected for all material candidates to provide a materials phase space that is simultaneously well studied and likely to host undiscovered materials. We find that humans (H) and LLM (L) have similar success rates: 83(8)% (H) and 75(9)% (L) [known materials, round one], 17(9)% (H) and 22(10)% (L) [unknown materials, round one], 79(8)% (H) and 71(9)% (L) [known materials, round two], and 22(7)% (H) and 14(6)% (L) [unknown materials, round two]. Through this collaborative human-LLM effort, we discovered Ba3PtO5, a material with a new structural prototype that constitutes the missing 1D member of the herein reported dimensionally tunable Rock-Salt Perovskite (RSP) homologous series of the form (AX)m(ABX3)p, of which the Ruddlesden-Popper series is a subset.
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All authors Gregory Bassen, Wyatt Bunstine, Sarah Okandey, Sarah Cheung, Elaine Flowers, Ritwik Bose, Joshua Hummel, Christopher D. Stiles, Maxime A. Siegler, Tyrel M. McQueen
Materials Science
Monolithic GaN Systems Combining Non-Volatile Memory and Analog Computing via Area-Ratio-Engineered Ferroelectric AlScN Gate Stacks
Hyeong Jun Joo, Jong Min Park, Kieran Barrett-Snyder et al. (+2 more)
Gallium nitride (GaN) transistors have become the platform of choice for power electronics and
radio-frequency power amplifiers. To unlock capabilities beyond those of conventional GaN, integrating ferroelectric
heterostructure has been considered toward
memory, logic and reconfigurable systems. Here, we demonstrate ferroelectric GaN transistors employing an AlScN-based gate stack in which systematic engineering of the area-ratio (SMIS/SMFM) provides unified control over both
memory and analog functionality. Precise modulation of the intermediate electrode length yields a record
memory window of 27 V and a forward subthreshold swing of 27 mV/dec, driven by ferroelectric polarization reversal of a robust downward-polarization state pre-induced by two-dimensional electron gas. Low area-ratio devices (SMIS/SMFM = 1, 2) achieve 4-bit multi-level
cell operation and excellent spatial uniformity across a fabricated 4 x 4 array, benchmarking favorably against established silicon and
oxide ferroelectric architectures. High area-ratio devices (SMIS/SMFM = 4, 8) harness continuously tunable conductance states to demonstrate multi-state inverters and the first GaN-based ferroelectric frequency-to-voltage converter, delivering a linear frequency-voltage response across 0.5 - 500 Hz range with a conversion gain of 1.1 mV/Hz. This work establishes routes towards monolithically integrated GaN systems that combine non-volatile
memory and analog signal processing on a platform inherently suited to high-power and
radio-frequency applications.
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All authors Hyeong Jun Joo, Jong Min Park, Kieran Barrett-Snyder, Brendan Hanrahan, Geonwook Yoo
Materials Science · Cross-listed from cond-mat.str-el
Strain-tunable charge localization coupled to complex magnetic orders in EuAl$_4$
M. Baumgartner, Xunyang Hong, Tianren Wang et al. (+19 more)
Charge localization is particularly interesting when coupled to
antiferromagnetic spin structures. Coupled
spin-charge orders are well established in elemental chromium and correlated
oxide superconductors, yet the interplay between charge order and more complex
magnetic textures – such as skyrmion
lattices and
chiral spin structures – remains largely unexplored. Here we report a comprehensive study of how charge localization couples to the unusually rich sequence of
magnetic phases in EuAl$_4$. Using x-ray diffraction under applied
magnetic field and uniaxial pressure, we demonstrate a direct coupling between the charge and
spin order parameters. In the absence of external stimuli, charge localization is markedly enhanced upon entering the magnetically ordered phases. Strikingly, this effect is highly susceptible to strain: uniaxial pressure applied along the charge-order propagation direction further enhances localization, whereas pressure applied perpendicular to it weakens it. Application of
magnetic field reveals both competitive and possible collaborative interactions between
spin and charge ordering.This flexible coupling between
spin and charge ordering opens a new route to designing
symmetry-breaking states.
Chiral charge order may for example be patterned from
spin structures with that
symmetry.
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All authors M. Baumgartner, Xunyang Hong, Tianren Wang, Fazhi Yang, Yuetong Wu, Junzhang Ma, Tian Shang, J. Oppliger, J. Küspert, M. Hücker, O. Ivashko, F. Igoa Saldaña, M. v. Zimmermann, S. Pyon, K. Kudo, M. Nohara, P. Sačer, A. Akrap, N. Barišić, M. Novak, Qisi Wang, J. Chang
Materials Science
Stability-threshold control of helicity-selective antiferromagnetic resonance
Masato Todani, Satoshi Iihama, Yuto Moritake et al. (+1 more)
We study helicity-selective
antiferromagnetic resonance in an
antiferromagnetic-
insulator/nonmagnetic-metal junction with sublattice-dependent damping and
spin-orbit torque. By formulating the linearized Landau–Lifshitz–Gilbert equation as a 2x2 non-Hermitian
eigenvalue problem, we analyze the complex resonance frequencies and the stability threshold, using MnF$_2$ parameters as a representative example of a uniaxial antiferromagnet. We show that the absorption is strongly enhanced near the stability threshold, where one helicity mode becomes weakly damped, leading to linewidth narrowing and pronounced helicity selectivity in the sub-THz regime. The selected helicity can be switched by reversing the current direction, which reverses the
spin-orbit torque acting on the interfacial sublattice. These results identify stability-threshold control as a design principle for electrically tunable helicity-selective
antiferromagnetic resonance in uniaxial antiferromagnets.
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All authors Masato Todani, Satoshi Iihama, Yuto Moritake, Takeo Kato
Materials Science
Stress calculation in linear scaling DFT: convergence and dynamics
Shereif Y. Mujahed, Tsuyoshi Miyazaki and David R. Bowler
We present the approach needed to calculate stress within density functional theory (DFT) using a localised orbital basis, both for exact diagonalisation and linear scaling approaches, and demonstrate our implementation within the large scale DFT code Conquest. For the linear scaling approach, we test the rate of convergence of stress with density
matrix range, and compare it to the convergence of energy and forces for different materials with a range of band gaps. We show that excellent convergence is found for modest cutoffs (below 0.1GPa error for range of 20a0), and show that large-scale isothermal-isobaric molecular dynamics is stable and accurate, showing negligible drift over picoseconds of dynamics.
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Materials Science
A Multi-Scale Machine Learning Framework for Coupled Chemical, Spin, and Structural Disorder in Alloys
Zhenyao Fang and Qimin Yan
Understanding the thermodynamic properties of disordered
magnetic alloys requires a unified treatment of configurational (chemical,
spin, etc.) and structural degrees of freedom, which has remained beyond the scope of existing computational frameworks. Here we present a general framework that integrates machine learning models (such as graph neural networks and machine learning interatomic potentials) and statistical sampling methods (such as Monte Carlo and molecular dynamics simulations) to study the coupled chemical,
spin, and structural disorder in
alloys. We demonstrate the framework on body-centered-cubic Fe-Co
alloys with interstitial carbon dopants, where the Fe-Co host exhibits intrinsic chemical and
spin disorder, and the interstitial carbon introduces additional structural disorder through local
lattice distortions, making the system a prototypical multi-disorder
magnetic alloy. The framework predicts the order-to-disorder phase transition temperature and the melting temperature of Fe-Co
alloy to be 1,000 K and 1,690 K, in excellent agreement with the experimentally measured values of 1,006 K and approximately 1,700 K, respectively. It also predicts the tetragonal-to-nearly-cubic structural transitions in Fe-Co-C
alloy as temperature increases. These results establish the framework as a reliable tool for studying multi-disorder
alloys, with applications to complex disordered systems such as high-
entropy alloys, multiferroics, and spintronic devices.
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Materials Science
Growth of (111)-textured SrTiO3 thin films on Pt(111)/Al2O3(1-102) substrates by rf magnetron sputter deposition
Ekaterina Taylor, Ethan R. Cronk, Kalani Perera et al. (+2 more)
SrTiO3 thin films, 20-30nm, with high quality
crystal structure and low roughness can be used as growth templates for complex
oxides or as the dielectric materials for capacitor structures. In this work, stoichiometric STO thin films were grown by
radio frequency magnetron sputtering on Pt (111) templates grown on rAl2O3 substrates, and the effects of growth parameters as well as the underlying Pt templates structural properties on the quality of STO films were studied. A comparison between room temp grown Pt and Pt grown at elevated temps showed that the latter lead to highly ordered Pt and STO films with quasi 2D surface roughness. Xray diffraction showed that the STO thin films had (111) and (222)
crystal orientation. A rocking curve full width at half maximum value of 0.2{\deg} was achieved, indicating that the STO films are high-quality. The STO films have a roughness less than 1 nm, as measured using atomic force microscopy, comparable to the underlying Pt templates roughness.
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All authors Ekaterina Taylor, Ethan R. Cronk, Kalani Perera, Nuri W. Emanetoglu, Nicholas S. Bingham
Materials Science
Optimizing high-temperature electron mobility in single-crystal Bi$_2$O$_2$Se based on its unconventional dependence on concentration
Antonín Sojka, Petr Knotek, Jan Zich et al. (+10 more)
Quasi-2D Bi$_2$O$_2$Se is part of an intensive materials research effort aimed at finding new
semiconductors that outperform silicon-based electronics in terms of speed and power consumption. This material exhibits exceptionally high carrier mobility at low temperatures but mediocre mobility at 300 K. Its high mobility is generally associated with its high permittivity ($\varepsilon_r$~500), which is also associated with
metallicity persisting down to very low carrier concentrations. This material exhibits a counterintuitive increase in carrier mobility as the concentration increases. The connection between low both carrier concentration and mobility in Se-rich conditions, and both high carrier concentration and mobility in Se-poor conditions suggests that the increase is related to native defects. We demonstrate that these defects can alter the effective mass of charge carriers. Specifically, substitutional Se(Bi) defects, which appear under Se-rich conditions, destroy the Bi$_2$O$_2$ channel and compromise charge transport properties. These defects increase the effective mass of charge carriers transforming the original
semiconductor into a semimetal and introducing holes into charge transport. Additionally, we show that single
crystals are generally inhomogeneous, particularly those grown under Se-rich conditions. Unlike Se-poor conditions, Se-rich conditions induce a higher concentration of dislocations and extraneous phases. These findings suggest that the perfection of the Bi$_2$O$_2$ channel is crucial for mobility, particularly at room temperature.
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All authors Antonín Sojka, Petr Knotek, Jan Zich, Martin Míšek, Roman Tesař, Kyo-Hoon Ahn, Petr Levinský, Jiří Navrátil, Pavlína Ruleová, Jiří Hejtmánek, Karel Knížek, Václav Holý, Čestmír Drašar
Materials Science · Cross-listed from cond-mat.mes-hall
Force-Isosurface Simulations Probe the Limits of High-Resolution AFM on Three-Dimensional Molecules
Edward J Dunn, Robert J Young and Samuel P Jarvis
High-resolution atomic force microscopy has transformed molecular imaging by revealing intramolecular structure directly in real space. A major remaining challenge is to extend this capability from largely planar molecules to non-planar molecular systems, where the most important structural information may be distributed across different heights above the surface. Here we use probe-particle-model simulations to predict the constant-force contours expected above molecules with increasing structural complexity. By extracting force isosurfaces from simulated three-dimensional force fields, we compare the molecular information retained in constant-height and constant-force images. For tilted benzene and pyrrole, constant-force images preserve the molecular framework across a range of adsorption angles and allow the molecular orientation to be recovered quantitatively. For larger non-planar and three-dimensional systems, simulations identify characteristic force-isosurface contrast associated with adsorption geometry, lower-lying molecular structure and curved molecular surfaces. These results provide target contrasts for force isosurfaces that could be extracted from three-dimensional force-mapping experiments, evaluating the molecular information retained by ideal force-isosurface imaging across progressively non-planar systems.
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Materials Science
Machine Learning Materials Properties by Encoding Orbital-Projected Density of States
Paulo Pires, Pierre-Paul De Breuck, Mauro Fava et al. (+2 more)
Graph neural networks have become the dominant machine-learning architecture for predicting materials properties from
crystal structures. Yet the initialization of atomic node features has received comparatively little
attention, and conventional approaches rely on static elemental descriptors that carry no information about the
quantum-mechanical electronic environment of each atom in its crystalline host. Here we show that augmenting atomic node representations with site-projected orbital density of states (pDOS) fingerprints, computed directly from density functional theory calculations, yields systematic and substantial improvements in predictive performance.These representations are fused with Pettifor elemental
embeddings at each atomic site before message passing. For the superconducting critical temperature $T_c$ and the optical dielectric constant $\epsilon_{\infty}$,the pDOS augmentation reduces prediction errors by 22.9% and 27.9%, respectively, relative to the elemental-descriptor baseline. These improvements are comparable to those achieved by doubling the training-set size. The gains are, however, contingent on training-set size. For the
magnetic exchange energies of Heusler compounds, a substantially smaller
dataset, the improvement is reduced,indicating that pDOS augmentation is most effective when the training data exceeds the length of the pDOS feature vector. We introduce an interpretable spectral
attention-gating mechanism that reveals that the model autonomously learns to prioritize the orbital channels and energy windows most physically relevant to each target property. These results establish pDOS-augmented graph nodes as a broadly applicable strategy for infusing first-principles electronic-structure knowledge into graph networks, opening a practical route to high-accuracy property prediction in data-scarce regimes.
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All authors Paulo Pires, Pierre-Paul De Breuck, Mauro Fava, Hai-Chen Wang, Miguel A. L. Marques
Materials Science
Electrical manipulation and detection of perpendicular altermagnetic order via proximitized Dirac semimetal
Zhaohui Li, Wenqing He, Hua Bai et al. (+14 more)
Altermagnets, which combine
antiferromagnetic-like
magnetic compensation with
ferromagnetic-like broken time-reversal
symmetry, hold great promise for high-density and ultrafast spintronic applications. However, the detection and switching of perpendicular altermagnetic order are fundamentally constrained by
magnetic symmetry, restricting both fundamental studies and practical implementation. We realize robust electrical reading and deterministic switching of perpendicular altermagnetic order by designing a Dirac semimetal/altermagnet
heterostructure of PtTe2/CrSb. This engineered interface enables anomalous
Hall readout via altermagnetic proximity effect and delivers efficient
spin-orbit torque for manipulating the epitaxial perpendicular Neel vector in CrSb. These findings significantly broaden the functional scope of altermagnetic
heterostructures and pave the way for highly scalable altermagnetic
memory.
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All authors Zhaohui Li, Wenqing He, Hua Bai, Yang Wang, Alexander J. Grutter, Guoyi Shi, Xiwen Zhang, Christy Kinane, Andrew Caruana, Hui Ru Tan, Yuchen Pu, Chenhui Zhang, Yongxi Wang, Hanbum Park, Anjan Soumyanarayanan, Lei Shen, Hyunsoo Yang
Materials Science
A Topotactic Phase Transition in the Uranium Oxide System
Jacek Wasik, Renaud Podor, Jarrod Lewis et al. (+4 more)
A topotactic phase transition involves the transformation of one crystalline solid to another, which may include the loss or gain of material, where the orientation of the parent
crystal determines the orientation of the daughter. We set out an experimental approach, based on polyepitaxial thin film deposition, where the precise transformation mechanism in important physico-chemical processes can be revealed in brilliant detail. Here, we find a reversible topotactic transition from (001) cubic UO2 to a (130) orthorhombic U3O8 structure; a >35% expansion/contraction. This remarkable result solves a puzzle that has eluded researchers for decades, and presents a method for determining the mechanism of crystallographic transformation in many other compounds.
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All authors Jacek Wasik, Renaud Podor, Jarrod Lewis, Niamh Cuffe, Connor Beer, Christopher Bell, Ross Springell
Materials Science
Bayesian Optimization of Genetic Algorithm Hyperparameters in a Multi-Fidelity Framework for Efficient Lattice Material Design
Sergei Zorkaltsev, Maciej Haranczyk and Christina Schenk
This study presents a multi-fidelity framework for the systematic optimization of genetic
algorithm (GA) hyperparameters. The framework integrates three fidelity levels: high-fidelity Fast
Fourier Transform (FFT) homogenization for validation, a medium-fidelity 3D convolutional neural network surrogate for rapid property evaluation, and a low-fidelity Gaussian process (GP) surrogate within a
Bayesian optimization (BO) framework to guide the hyperparameter search. Various acquisition functions are evaluated, with logNEI achieving the best performance by effectively accounting for the noise inherent in GA evaluations. The proposed framework identifies hyperparameter configurations that enable a 25-generation GA run to achieve elastic modulus values comparable to those obtained in a full 75-generation optimization. Furthermore, introducing a penalized BO objective significantly reduces the number of required
lattices with only minor decreases in absolute achieved elastic modulus, revealing a practical trade-off between performance and the number of structures that must be evaluated. High-fidelity FFT validation verifies the effectiveness of the surrogate-driven optimization strategy. The optimized hyperparameters allow for rapid convergence, eliminate the need for
lattice mutation, and reduce the overall computational cost by 24% (from 225 to 171 hours) while preserving mechanical performance. These results demonstrate the potential of multi-fidelity optimization as an efficient and practical approach for GA hyperparameter tuning and future experimental
lattice design studies.
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Materials Science
Improving feature resolution and pore back effect in focused ion beam tomography of porous GaN thin films
Ben Thornley, Thom R. Harris-Lee, Menno J. Kappers et al. (+2 more)
Porous gallium nitride (GaN) is a mesoporous crystalline material, typically in the form of a thin film on an unlike substrate, prepared by electrochemically etching conductive GaN. The use of porous GaN in electronics and optoelectronics is rapidly expanding, but is held back significantly by a lack of structural control and understanding of the principles of pore formation from underlying electrochemical mechanisms, where high-quality characterisation of pore morphology is essential to understanding these principles. Focused ion beam (FIB)
tomography is an invaluable tool for such characterisation, but is hindered greatly by the pore back effect, where unwanted contrast appears in an image due to electrons scattering out from the back wall of a pore. No major attempts to formally quantify or assess the extent of the effect for different
tomography experiments has been demonstrated. In this work, we demonstrate an advanced methodology for performing FIB
tomography on porous GaN thin films, where the experiment is rotated to image pores perpendicular to the surface of the sample, and introduce new voxel intensity-based formalisms for assessing the impact of the pore back effect based on voxel intensities for individual features and the whole
dataset. The new approach, which requires more complex preliminary setup, is found to significantly mitigate the pore back effect in porous GaN thin films with a range of pore morphologies without increasing the total experimental duration. The pore back effect can thus be quantified and mitigated in FIB
tomography of porous GaN and similar mesoporous thin films.
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All authors Ben Thornley, Thom R. Harris-Lee, Menno J. Kappers, Simon M. Fairclough, Rachel A. Oliver
Materials Science
Understanding surface potential dynamics of passivated perovskites via Kelvin Probe Force Microscopy
Rehmat Sood-Goodwin, Xue-Li Cao, Benjamin C. Kinvig et al. (+4 more)
Molecular passivation has become central to reducing photovoltage losses in metal-halide perovskite
solar cells, but its electronic action is still often inferred from device-level metrics rather than directly resolved at the nanoscale. Here, we use amplitude-modulated Kelvin probe force microscopy to examine how [3-(2-aminoethylamino)propyl]trimethoxysilane (AEAPTMS) modifies the surface potential and photovoltage dynamics of mixed-cation, mixed-halide perovskite thin films. AEAPTMS homogenises the dark contact potential difference (CPD), narrowing its distribution from ~45.7 to ~14.6 mV without obvious morphological changes. Under illumination, passivated films show a larger steady-state surface photovoltage (SPV) and faster stabilisation, with the SPV increasing from ~345 to ~417 mV and the stabilisation time constant decreasing from ~840 to ~470 s. Wavelength-dependent SPV further indicates reduced sub-bandgap electronic disorder. By separating grain-boundary and grain-interior contributions, we show that AEAPTMS suppresses grain-boundary potential barriers, linking amino-silane passivation to a more homogeneous and stable carrier landscape.
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All authors Rehmat Sood-Goodwin, Xue-Li Cao, Benjamin C. Kinvig, Robert D. J. Oliver, Yen-Hung Lin, Nic Mullin, Alexandra J. Ramadan
Materials Science
Terahertz Phase Inversion via Field-Free Spin-Orbit Torque Switching in an Antenna-Integrated Spintronic Heterostructure
Amir Khan, Tiago de Oliveira Schneider, Suraj Joshi et al. (+4 more)
We demonstrate microsecond-timescale electrical control of the terahertz (THz) emission phase in broadband field-free spintronic THz emitters, enabling megahertz-rate phase inversion while overcoming the kilohertz limitations of conventional mechanical and field-driven approaches. Our device integrates an H-dipole
antenna with a spintronic
heterostructure exhibiting uniaxial
magnetic anisotropy, enabling deterministic
spin-orbit torque induced in-plane magnetization switching without external
magnetic fields. The corresponding THz phase inversion is directly observed in the time domain signal, by applying $1\,\mu \mathrm{s}$ electrical pulses on the bias striplines of the H-dipole. This field-free operation reduces system complexity while significantly extending modulation bandwidth. Our results establish electrically programmable spintronic THz emitters that could be used to develop a compact and scalable platform for integrated on-chip THz devices and ultrafast applications, including phase-sensitive spectroscopy and near-field imaging, where high-speed and precise control of THz waveforms is essential.
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All authors Amir Khan, Tiago de Oliveira Schneider, Suraj Joshi, Mohammad Faraz Abdullah, Reshma Rajeev Lekha, Sascha Preu, Markus Meinert
Materials Science
Interplay of Umklapp scattering and Sb-Au hybridization in surface-reconstructed Sb/Au(111)
Zhe Zheng, Celine Wassenberg, Stefanie Hilgers et al. (+2 more)
Surface reconstructions induced by atomic adsorption can strongly reshape metallic surface states, providing a direct pathway to tune their electronic structure. Using angle-resolved photoemission spectroscopy, we investigate the electronic structure of Sb/Au(111) during the coverage-driven
evolution from the clean Au(111) surface to the $(14\times14)$ and Rec$(3\times\sqrt{3})$ phases. In the Rec$(3\times\sqrt{3})$ phase, triangular
Fermi pockets emerge at the Brillouin-zone boundary. Their momentum positions are consistent with a reciprocal-space folding construction, but their reduced size near the
Fermi level indicates a modification of the Au-derived $sp$ dispersion. The substantial modifications of deeper Au $d$-derived bands observed in ARPES further indicate significant mixing between Sb $p$ orbitals and Au $d$ states. These results show that the electronic structure of Sb/Au(111) is governed by the interplay between reconstruction-induced Umklapp scattering and interfacial orbital hybridization, highlighting adsorbate-substrate hybridization as a key mechanism for tuning and engineering surface electronic structures.
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All authors Zhe Zheng, Celine Wassenberg, Stefanie Hilgers, Carsten Westphal, Mirko Cinchetti
Materials Science
Unveiling Nanoscale Surface Damage Dynamics in Swift Heavy Ion Irradiated Gallium Nitride
Jiayu Liang, Shaowei He, Wenlong Liao et al. (+9 more)
This work systematically unveils the nanoscale surface damage dynamics in gallium nitride by investigating the atomistic mechanisms of hillock formation. The results identify two distinct hillock morphologies dependent on electronic energy loss (Se) values. Bell-shaped hillocks form under 18.2 keV/nm Kr irradiation, whereas crater-rim hillocks with central holes emerge under 40.2 keV/nm Ta irradiation. Microstructural analysis reveals that Ga-rich hillocks are accompanied by the generation of metastable zincblende nanodomains. These nanodomains preferentially aggregate around the periphery or sidewalls of the hillocks and exhibit a high spatial correlation with screw dislocations. Further temperature-dependent studies indicate that elevated temperatures significantly enlarge the overall dimensions of the hillock structures without altering their fundamental morphologies. Notably, under Ta irradiation above 1200 K, the high temperatures drastically reduce the viscosity and surface tension of
liquid gallium. This enhanced fluidity of the transient molten phase promotes the formation of penetrating nanochannels.
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All authors Jiayu Liang, Shaowei He, Wenlong Liao, Tan Shi, Hang Zang, Yonghong Li, Wenbo Liu, Xiaojun Fu, Chuanjian Yao, Huan He, Jianan Wei, Chaohui He
Materials Science
Ethaline deep eutectic solvent under nanoconfinement: Unveiling structural and dynamical changes
Kamar Mohammad Nadim, Mozhdehei Armin, Lefort Ronan et al. (+5 more)
Hybrid nanomaterials incorporating deep eutectic solvents (DES) in porous hosts or at solid interfaces are gaining increasing
attention for their potential interest across a wide range of applications. Under these conditions, the performances of DESs may be influenced by interfacial effects and spatial restrictions. In this study, we examined the effects of nanoconfinement on both the structure and molecular dynamics of the prototypical DES ethaline (a mixture of choline chloride and ethylene glycol) when confined within the cylindrical mesopores of SBA-15 (Dp $\approx$ 8.1 nm) and MCM-41 (Dp $\approx$ 3.5 nm) silicas, using
neutron diffraction and quasielastic
neutron scattering. It demonstrates that ethaline remains structurally homogeneous under confinement, showing no evidence of core-shell segregation within the pore cross-section. The molecular dynamics of the confined ethaline preserve the key characteristics observed in its bulk state. Translational
diffusion follows a jump-
diffusion mechanism, with
diffusion coefficients that remain remarkably close to the bulk values, showing only a modest reduction in MCM-41. A more pronounced increase in the residence time t0 between translational molecular jumps is observed. It corresponds to roughly a factor of 3-8 under confinement in SBA-15, and reaches up to a tenfold enhancement in MCM-41 relative to bulk. Similarly, the characteristic relaxation time, tL, associated with the localized in-cage motion of ethaline, increases by approximately 20% in SBA-15 and up to 50% in MCM-41. However, the molecular trajectories, modeled from the elastic incoherent structure factor, remain largely preserved under confinement, showing only a marginal reduction in intra-basin motional amplitudes.
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All authors Kamar Mohammad Nadim, Mozhdehei Armin, Lefort Ronan, Moréac Alain, Ollivier Jacques, Appel Markus, Viviana Cristiglio, Denis Morineau
Materials Science
Phonon scattering mechanisms in WTe$_2$ observed by ultrafast coherent phonon spectroscopy
Mizuki Akei, Yu Mizukoshi and Muneaki Hase
Revealing the mechanisms of
phonon scattering is crucial for understanding material properties such as transport characteristics and optical responses. It can be discussed by measuring the temperature dependence of the
phonon energy and lifetime. To gain insight into these mechanisms in Weyl semimetal T$_d$-WTe$_2$, we investigated coherent
phonons using time-resolved pump-probe spectroscopy in a wide temperature range from 4.6 to 300 K. The temperature dependence of the frequency and decay rate of the two high-frequency optical modes was described by the conventional anharmonic
phonon-
phonon scattering model. In contrast, the low-frequency mode at 2.4 THz exhibited anomalous behavior, which can be interpreted as the contribution of
phonon-electron scattering.
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Materials Science
A modified Moss rule highlights underexplored classes of high refractive index materials
Eugène Bertin, Finja Tadge and Andrea Crovetto
High refractive index dielectrics are central to photonic applications, yet the empirical Moss rule imposes a fundamental trade-off between refractive index and optical transparency. We introduce a modified Moss rule anchored to the optical absorption edge rather than the fundamental bandgap, capturing materials where various physical mechanisms suppress absorption well above the electronic gap. Screening the Materials Project database with this metric reveals recurring chemical compositions and structural prototypes in the materials with the most promising refractive index/transparency trade-offs. These materials include chalcopyrites, Zintl pnictides, and early transition metal multi-anion chalconitrides and oxychalcogenides compounds. Hybrid density functional theory calculations reveal that the chalconitride (Hf,Zr)2(S,Se)N2 family can achieve a combination of ultra-high refractive indices, low effective masses and transparency windows extending deep into the UV, surpassing state-of-the-art TiO2 and SiC. Our results establish (Hf,Zr)2(S,Se)N2 compounds as a unique and largely unexplored material family for next-generation photonic applications.
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Materials Science
Minimizing propagated density errors of atomic core-electron for simultaneously accurate bandgaps and lattice constants in closed-shell Copper semiconductors
Kuiyu Ye, Haitao Liu, Yuanchang Li et al. (+1 more)
Density functional theory struggles to accurately determine electron density of atoms, whose error is inevitably encoded into the pseudopotential and propagated into solid-state calculations. However, little is known about how this affects accuracy nor how to remedy it. In this work, through a systematic study of the effect of Cu atomic density on bandgap and
lattice constants of over 50 Cu-containing simple closed-shell
semiconductors, we find that core-electron density can drastically affect
nuclear attraction to valence electrons and subsequent charge distribution and energy position of Cu 3$d$ electrons. The error can be eliminated at its source by employing modified Hartree-Fock pseudopotentials for Cu core while retaining (semi-)local functionals for valence electrons. This real-space partitioning approach leads to simultaneous high-accuracy in bandgap and
lattice constants across the entire material class.
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All authors Kuiyu Ye, Haitao Liu, Yuanchang Li, Shengbai Zhang
Materials Science
Size focusing in core-shell precipitates: A phase-field study
Soumya Mishra and T. A. Abinandanan
Due to their enhanced resistance to coarsening and/or creep, aluminium
alloys with precipitates of two distinct phases in a core-shell morphology are of great contemporary interest. In this paper, we focus on the curious observation in two recent studies on Al-Sc-Li and Al-Yb-Li
alloys that growth of the shell phase leads to a narrowing of the size distribution. We have studied this phenomenon, known as size focusing, using a theoretical framework (which extends Zener's theory of diffusional growth to a core-shell precipitate) and multi-precipitate simulations based on a phase field model. Our results yield key theoretical insights as well as conclusions with practical significance. (a) On the theoretical front, we show clearly that size focusing is a growth phenomenon: it ends when shell growth ends, and coarsening begins. (b) On the practical front, our results offer guidelines for designing
alloys with narrower size distributions: size focusing is promoted in
alloys with greater shell volume fractions and greater inter-precipitate spacing.
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Materials Science
Surface Reconstruction-Driven Insulating Behavior in Metallic Charge-Density-Wave 1T-TaSe$_{2}$
Sung-Hoon Lee and Doohee Cho
Bulk 1T-TaSe$_2$ is metallic, yet its surface consistently exhibits an insulating gap – a dichotomy long attributed to a surface Mott
insulator driven by enhanced electron correlations. Using density functional theory calculations, we show that this insulating surface instead originates from a charge-density-wave (CDW) stacking reconstruction. Whereas the bulk stabilizes a single-layer CDW stacking that supports metallic transport, the surface energetically favors a
bilayer stacking, in which interlayer hybridization of Ta $5d_{z^2}$ orbitals opens a $\sim$0.4 eV gap – a band
insulator requiring no on-site Coulomb repulsion. This reconstruction is the thermodynamic ground state for slab thicknesses from two to eight layers, and the calculated surface density of states quantitatively reproduces scanning tunneling spectra of both insulating and metallic domains. CDW surface reconstruction, rather than Mott physics, thus governs the surface electronic structure of 1T-TaSe$_2$, providing a unified explanation for the observed coexistence of metallic and insulating domains.
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Materials Science
AI2Pot: A scalable and unified framework for machine-learning interatomic potential development and large-scale molecular dynamic simulations
Hanyu Liu, Linggang Zhu, Xuanguang Zhang et al. (+3 more)
Machine-learning interatomic potentials (MLIPs) bridge the accuracy of first-principles calculations and the efficiency required for large-scale molecular dynamics (MD) simulations. However, existing MLIP software remains fragmented across different model architectures, making it difficult to establish unified workflows that support flexible model development, efficient training, and scalable MD deployment. Here, we present AI2Pot, a scalable and unified MLIP framework that seamlessly integrates model training, evaluation, and large-scale MD simulations with PyTorch-compatible ecosystem. Instead of relying on generic automatic differentiation for expensive atomistic operators, AI2Pot re-engineers the core computations of Moment tensor potential (MTP) and Neuroevolution potential (NEP) for both training and inference using hand-crafted C++/CUDA code. These specialized operators constitute a unified computational backend shared by training and inference, improving training-inference consistency and reducing
memory usage by avoiding large intermediate caches. As a result, AI2Pot enables fast inference for large-scale atomic systems containing millions of atoms on a single GPU, while retaining the flexibility of PyTorch for model construction, training, and evaluation. Trained models can be deployed in ASE and LAMMPS for MD simulations. Furthermore, AI2Pot provides a companion command-line toolkit (AI2Pot-cli) and Python APIs to facilitate practical MLIP workflows. By unifying high-performance atomistic computing with modern machine-learning ecosystems, AI2Pot offers an user-friendly end-to-end framework for the developing, training, and deploying MLIPs for large scale MD.
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All authors Hanyu Liu, Linggang Zhu, Xuanguang Zhang, Ning Yang, Jian Zhou, Zhimei Sun
Materials Science · Cross-listed from physics.comp-ph
Radiation Damage Cascades in Fullerite Using Molecular Dynamics
Ethan P. Turner, Paolo Raiteri and Nigel A. Marks
Molecular dynamics is used to study radiation cascades in solid C60 under ambient conditions. Simulations are performed for Primary Knock-On Atom (PKA) energies from 0.1 to 1 keV, and cascades are sampled over many PKA directions to collect statistics. Energies and forces are described using the Environment Dependent Interaction Potential for carbon paired with the Ziegler-Biersack-Littmark potential for short-range interactions, and cascade behaviour is characterized by tracking kinetic energy, hybridization and bond connectivity as a function of time. Compared to most materials, fullerite exhibits an unusual radiation response due to weak thermal transfer between C60 molecules leading to a thermalization phase lasting hundreds of picoseconds. The cascades damage the C60 molecules and link them together, and a linear relation is found between the number of cross-linked molecules and the number of new sp3 atoms. The threshold displacement energy computed is 18 eV, in agreement with experiments
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Materials Science
Negative and Zero Linear Compressibility in MCN (M = Ag, Au, Cu): A First-Principles Study
Arlies Valdespino, Abduljelili Popoola, Sergey Lisenkov et al. (+1 more)
Negative linear compressibility (NLC) is the counterintuitive phenomenon in which a crystallographic axis expands under hydrostatic pressure. A related phenomenon, zero linear compressibility (ZLC), occurs when an axis shows no length change under pressure. Both responses are rare and arise in materials with highly anisotropic mechanical properties. Motivated by recent reports of anomalous behavior in metal cyanides - including negative thermal expansion and NLC - we use first-principles calculations to investigate the potential of the MCN family (M = Ag, Au, Cu) to exhibit ZLC or NLC. Our simulations reveal three main findings. First, we predict the existence of previously unreported phases: the P6mm phase for AgCN and CuCN, and the R3m phase for AuCN. Second, all six members of the MCN family studied exhibit extreme elastic anisotropy, which indeed leads to ZLC or NLC in each case. Third, we identify a mechanism for these responses distinct from previously reported ones. The mechanism arises from the unique "bamboo forest" geometry of the material: weakly interacting rigid rods whose sparse packing allows pressure to be accommodated through changes in packing density rather than rod compression. This mechanism enables the anomalous response to persist over a wide pressure range, contrasting favorably with other materials that exhibit similar behavior. Our findings expand the relatively small family of materials known to exhibit ZLC or NLC and provide deeper insight into the microscopic origin of these unusual mechanical responses.
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All authors Arlies Valdespino, Abduljelili Popoola, Sergey Lisenkov, Inna Ponomareva
Materials Science
Thermoelectric and Magnetic Properties in Doped Fe$_2$VAl within a Bipolar Random Anderson Model
Takami Tohyama and Hidetoshi Fukuyama
We investigate the thermoelectric and
magnetic properties of Si-substituted $n$-type and Ti-substituted $p$-type Heusler
alloy Fe$_2$VAl using the bipolar random Anderson model, which has been introduced recently to study antisite-defect effects associated with the sign change of the Seebeck coefficient in thermally quenched Fe$_2$VAl. Based on the electronic states of both $n$-type and $p$-type compounds, with the rigid-band shift of the
Fermi energy and a temperature-dependent scattering rate taken into account, we elucidate how antisite defects simultaneously influence thermoelectric transport and local
magnetic moments. We find that the
magnetic moments are enhanced in $n$-type Fe$_2$VAl, whereas they are suppressed in $p$-type Fe$_2$VAl compared with the undoped compound. These contrasting
magnetic responses highlight the impact of antisite
spin polarization on thermoelectric properties and demonstrate the crucial role of antisite defects in realizing magneto-thermoelectric functionalities in Heusler-type
alloys.
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