Materials Science · Cross-listed from cs.LG
Hybrid Machine Learning-Assisted Raman Spectroscopy with Generative Feature Augmentation for Pharmaceutical Identification
Quach Thi Thai Binh, Ton Nu Quynh Trang, Thang B. Phan et al. (+2 more)
Rapid and reliable identification of pharmaceutical residues is important for safeguarding public health, ensuring food safety, and enabling practical Raman-based screening. In this study, we propose HyMLRaman, a hybrid Raman spectroscopy framework that combines deep spectral feature extraction, generative models, and classical machine-learning classifiers to identify six pharmaceutical compounds, including amoxicillin, chloramphenicol, ciprofloxacin, tetracycline, ibuprofen, and paracetamol. Raman spectra are converted into spectral images and encoded with several deep neural-network backbones, among which EfficientNet-B3 yields the most effective representation. The resulting 1536-dimensional
embeddings are then used to train downstream classifiers, including SVM, KNN, logistic regression, random forest, XGBoost, and ANN, using stratified 10-fold cross-validation. The hybrid EfficientNet-B3–SVM configuration achieves the strongest baseline performance, reaching 96.31% accuracy and a macro-F1 score of 96.36%, outperforming the standalone CNN baseline. To address limited-data conditions, a generative model, a DDPM-based feature augmentation, is introduced in a PCA-reduced EfficientNet-B3 latent space. The low-data ablation results show that DDPM augmentation provides selective benefits, particularly for KNN with reduced training fractions, and that its effect remains classifier-dependent. Finally, an application-level Raman Pharmaceutical Analyzer demonstrates the feasibility of
embedding the trained model into an interactive Raman analysis workflow. These results suggest that HyMLRaman provides a practical and interpretable route for rapid Raman-based pharmaceutical screening.
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All authors Quach Thi Thai Binh, Ton Nu Quynh Trang, Thang B. Phan, Vu Thi Hanh Thu, Nguyen Tuan Hung
Materials Science
Thermally Robust and Strongly Pressure-Responsive NIR Luminescent Manometer Based on Cr3+-Ni2+ Emission
Weijia Xie, Maja Szymczak, Tongxi Luo et al. (+3 more)
The increasing demand for highly sensitive luminescent manometers capable of precise pressure determination, particularly those operating in the near-infrared (NIR) spectral range, motivates the continuous search for new pressure-responsive luminescent materials. In this work, we introduce NaLu2Ga3Ge2O12:Cr3+, Ni2+ as a highly sensitive NIR luminescent manometer in which pressure not only induces pronounced spectral shifts of the Cr3+ and Ni2+ emission bands but also strongly modulates their relative luminescence intensities. Remarkably, the 3T2(3F)->3A2(3F) emission band of Ni2+ exhibits a record-high absolute pressure sensitivity of SA = 34 nm GPa-1. Furthermore, by appropriately selecting narrow spectral ranges within the pressure-responsive emission bands, a ratiometric NIR luminescent manometer was developed, providing a maximum relative pressure sensitivity of SR = 158% GPa-1. Most importantly, the proposed ratiometric readout exhibits a thermal-invariance manometric factor (TIMF) of 19,900 K GPa-1, which, to the best of our knowledge, is the highest value reported to date for a luminescent manometer. The combination of exceptionally high-pressure sensitivity, NIR operation, and remarkable resistance to thermal interference establishes NaLu2Ga3Ge2O12:Cr3+, Ni2+ as a highly promising luminescent pressure sensor for reliable pressure determination under conditions involving simultaneous temperature variations.
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All authors Weijia Xie, Maja Szymczak, Tongxi Luo, Chan Wang, Lukasz Marciniak, Xinguo Zhang
Materials Science
Multimodal Visual Sensing of Temperature and Pressure: From Spectroscopic Readout to Multiple Linear Regression-Enhanced RGB Analysis
Maja Szymczak, Yufan Meng, Guanjun Xiao et al. (+4 more)
Transforming a single luminescent host into distinct temperature- and pressure-sensing systems through composition control provides a powerful route toward multifunctional optical sensors. Here, we introduce a concentration-tunable KGaGeO4:Bi3+,Eu3+ platform whose sensing function can be selectively directed toward thermometry or manometry by adjusting the dopant balance. Spectroscopically distinct Bi3+ centers and Eu3+ emission exhibit differentiated responses to temperature and pressure, enabling
multimodal readout through ratiometric luminescence, chromaticity coordinates, spectral shifts, and visible color changes. Importantly, these color changes were translated into quantitative temperature and pressure maps using RGB imaging combined with multiple linear regression (MLR). By simultaneously exploiting multiple color channels, MLR increased the maximum relative thermal sensitivity from approximately 1% K-1 for conventional RGB ratios to 8.8% K-1 and the pressure sensitivity from 169% GPa-1 to nearly 721% GPa-1. This work presents the first application of MLR-assisted RGB analysis for quantitative luminescence pressure sensing. The proposed strategy integrates composition-controlled functionality,
multimodal spectroscopic sensing, direct visual readout, and data-assisted imaging, demonstrating the synergy between material engineering and multivariate analysis for highly sensitive multifunctional optical sensing.
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All authors Maja Szymczak, Yufan Meng, Guanjun Xiao, Miguel A. Hernández-Rodríguez, Iga Sawaryn, Bo Zou, Lukasz Marciniak
Materials Science
Highly Lattice-Mismatched Selective Area Epitaxy and Coalescence of PbSe Nanostructures on GaAs
Ashlee M. García, Hosni A. Kaissi, Jarod E. Meyer et al. (+9 more)
Selective area growth of PbSe has the potential to realize deterministic placement of high-density, defect-tolerant nanostructure networks toward a scalable
quantum platform. PbSe is a narrow bandgap
semiconductor with advantageous (opto)electronic properties that has been shown to have a desirable defect-tolerance, enabling bright emission even when grown on highly-dissimilar platforms, and could be leveraged in combination with selective growth for site-selective
quantum emitters and low-disorder hybrid nanowire networks. In this work, we achieve site-selective growth of well-faceted and ordered PbSe nanostructures, despite a large 8%
lattice mismatch. Structural and morphological characterization reveal that $>$99% of selectively grown islands within 100 nm opening are single-orientation and cube-on-cube oriented with sub-nm root-mean-square surface roughness. Defect analysis showed that 74% of the islands and 86% of the coalesced regions between different mask openings were free of threading dislocations. These PbSe islands achieved equivalent emission in the mid-infrared despite having a higher surface-to-volume ratio than the planar control. Further, we present a gate-tunable two-terminal Josephson junction fabricated from the PbSe nanowires grown with conditions identified in this study. The combination of the accessible selective growth regime, morphological control of island growth and demonstrations of optical and electrical transport properties indicates promise for PbSe SAG as a defect-tolerant scalable
quantum platform.
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All authors Ashlee M. García, Hosni A. Kaissi, Jarod E. Meyer, Kira J. Martin, Maksim Gomanko, Laura A. Stern, Pooja D. Reddy, SeongJin Park, Wilson J. Yánez-Parreño, Sergey M. Frolov, Vlad S. Pribiag, Kunal Mukherjee
Materials Science
LiNiO2/NiO Phase Prediction Using Artificial Neural Networks
Jonas Scheunert, Shamail Ahmed, Thomas Demuth et al. (+2 more)
In the realm of material analysis, identifying different material phases is of key importance. Artificial intelligence in the form of neural networks provides a very fast and, once trained, computationally inexpensive method for analysing large amounts of image data, like the sets of diffraction patterns generated during four-dimensional scanning transmission electron microscopy (4DSTEM)
dataset acquisition. In this work, we train multiple network architectures on images of this type to distinguish between the phases of LiNiO2 and NiO, an important and challenging distinction in the lithium-ion battery community, since the formation of NiO limits battery capacity. We test both classical convolutional neural networks (CNNs) and different forms of
vision transformers (ViTs). Our networks are trained on synthetic images and tested on experimentally recorded diffraction patterns. Additionally, we also investigate the decision-making of our networks using the GradCAM method. We test our networks on both synthetic as well as experimental diffraction patterns. Our networks exhibit very robust results, especially when dealing with highly varying data, an area where traditional template-matching methods typically struggle.
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All authors Jonas Scheunert, Shamail Ahmed, Thomas Demuth, Andreas Beyer, Kerstin Volz
Materials Science · Cross-listed from cond-mat.mes-hall
Vanadium doping induced valley asymmetries in WS$_2$ monolayers
Frederico B. Sousa, Boyang Zheng, Elizabeth Grace Houser et al. (+10 more)
Transition metal dichalcogenide (TMD) monolayers offer an innovative platform for encoding and manipulating information through the valley degree of freedom. While unique valley-related physical phenomena have been reported so far, practical applications still require advanced control over the valley polarization efficiency and the valley Zeeman effect. Recently, the introduction of
spin-polarized metal atoms as substitutional defects was reported to break the time-reversal
symmetry in TMD monolayers, consequently inducing a room-temperature ferromagnetic ordering and enhancing the valley-dependent optical responses. Here, we report valley asymmetries for vanadium-doped WS$_2$ monolayers. With a given
magnetic polarization, one valley exhibits larger Zeeman slope and degree of circular polarization than the other valley. Additionally, the overall degree of circular polarization in the doped samples is approximately twice that of the pristine WS$_2$ monolayer. Density functional theory calculations in the doped structure show that different energy shifts in conduction band edges due to
spin-dependent hybridization lead to different
exciton energies between valleys, which is consistent with the experimental observations. Our results pave the way for valleytronic technologies based on defect-engineered two-dimensional materials.
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All authors Frederico B. Sousa, Boyang Zheng, Elizabeth Grace Houser, Paulo E. Faria Junior, Zhuohang Yu, Alessandra Ames, Gabriel A. D. Souza, Mingzu Liu, Gilmar Eugenio Marques, Leandro M. Malard, Mauricio Terrones, Vincent H. Crespi, Marcio D. Teodoro
Materials Science
Compressive Splitting in Brittle Solids: The Inverse of Wrinkling in Sheets
Maryam Khodadad, Francois Barthelat, John D. Clayton et al. (+2 more)
Axial splitting is the dominant failure mode of brittle solids under compression, yet its mechanical origin remains unclear. We show that clamped loading platens suppress lateral Poisson expansion, generating boundary-induced tensile stresses at the specimen interior – the compressive analog of wrinkling in stretched sheets. This mechanism provides a predictive strength law, relating axial splitting to tensile strength, geometry, and confinement pressure. This is validated against diverse materials ranging from rocks to ceramics, establishing axial splitting as a geometry-controlled elastic process rather than a
stochastic flaw problem.
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All authors Maryam Khodadad, Francois Barthelat, John D. Clayton, George Gazonas, Kaushik Dayal
Materials Science · Cross-listed from cond-mat.soft
Two-Stage Ordering Kinetics in Binary Mixtures of Ellipsoidal Particles
Parameshwaran A, Sanjay Puri and Bhaskar Sen Gupta
We investigate the nonequilibrium phase-ordering kinetics of a binary mixture of uniaxial ellipsoidal particles interacting via the anisotropic Gay-Berne potential using large-scale molecular dynamics simulations. Following a temperature quench from the isotropic and homogeneous phase into the coexistence region, the system exhibits two distinct ordering processes occurring on different time scales. At first, rapid orientational ordering leads to the formation and coarsening of nematic domains, characterized by dynamical scaling, generalized Porod-law behavior, and a growth law $\ell(t) \sim t^{1/2}$ consistent with nonconserved order-parameter dynamics. Later, the system undergoes binary phase separation driven by compositional fluctuations. This compositional ordering process shows a transition from diffusive growth $\ell(t) \sim t^{1/3}$ to hydrodynamic regimes, with finite-size scaling analysis indicating asymptotic viscous growth $\ell(t) \sim t$. Despite the presence of global orientational order, the phase-separation kinetics remains effectively isotropic. These results demonstrate a clear separation between orientational and compositional ordering dynamics, governed by distinct conservation laws, and provide a unified framework for understanding phase ordering in anisotropic particle systems.
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Materials Science
Experiments and Modeling of Defect Dynamics and BTI Behavior in Doped InO TFTs during $400^\circ$C Post-Processing Forming Gas Annealing
Yu-Hsin Kuo, Chengyang Zhang, Priyankka Ravikumar et al. (+13 more)
We investigate the impact of a monolithic three-dimensional (M3D) integration process-critical $400^\circ$C post-processing forming gas anneal (FGA) on the electrical performance, reliability, and defect
evolution of oxide-channel thin-film transistors (TFTs), combining systematic experiments with density-functional-theory (DFT)-based
liquid-quench molecular-dynamics (MD) simulations. Indium tungsten oxide (IWO) TFTs are employed as a model system and encapsulated with a thin 3 nm Al$_2$O$_3$ / 3 nm HfO$_2$ hybrid layer that effectively suppresses external hydrogen ingress. We reveal a non-monotonic
evolution of device behavior during FGA, governed by initial densification followed by partial crystallization. Short-duration FGA (10 min) induces channel densification and the formation of shallow, delocalized defect states, leading to pronounced positive bias temperature instability (PBTI) degradation and the emergence of a characteristic transfer-curve "kink." With prolonged annealing (>40 min), partial crystallization of the oxide channel occurs, stabilizing hydrogen in deep, localized defect states, suppressing hydrogen mobility, and restoring device reliability. As a result, the PBTI shift is reduced to 10.4 mV after 2000 seconds of stress, accompanied by complete elimination of the transfer-curve kink. These findings provide a mechanistic understanding of hydrogen-defect interactions during high-temperature post-processing FGA and demonstrate that appropriate hydrogen-blocking encapsulation enables oxide-channel TFT integration without compromising electrical performance or reliability.
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All authors Yu-Hsin Kuo, Chengyang Zhang, Priyankka Ravikumar, Sanghyun Kang, Taeyoung Song, Marco Villena, Luca Larcher, Hwan Kim, Minji Hong, Pilsang Yun, Gaurav Thareja, Shimeng Yu, Daewon Ha, Suman Datta, Julia Medvedeva, Asif Khan
Materials Science
Revealing epitaxial relationships at Ga$_2$O$_3$ interfaces with p-type oxides
Anna Sacchi, Krishna Acharya, Michelle A. Smeaton et al. (+5 more)
p-type oxide contact layers such as Cr$_2$O$_3$ and NiO are attracting increasing interest in pn-heterojunctions with n-type monoclinic $\beta$-Ga$_2$O$_3$ for high-power electronic devices and other extreme environment applications. However, scientific understanding of their epitaxial relationships remains incomplete. In this work we investigate the epitaxial relation of Cr$_2$O$_3$ and NiO layers to (001) and ($\bar{2}$01) out-of-plane oriented Ga$_2$O$_3$ substrates. Surprisingly, we find that, for the most commercially relevant (001)-orientation of the Ga$_2$O$_3$ substrate, the epitaxial relationships are Cr$_2$O$_3$ (0001) and NiO (111) $\parallel$ Ga$_2$O$_3$ (101), both at the non-intuitive $\chi$ = 22.5 $^\circ$ angle with respect to the substrate normal. We explain this unusual discovery by the interfacial atomistic bonding dominated by oxygen sublattice equivalence of these Cr$_2$O$_3$ and NiO polar surface orientations to the tilted Ga$_2$O$_3$ (101), rather than Ga$_2$O$_3$ (001) substrate surface planes. Furthermore, we assign the in-plane orientation for Cr$_2$O$_3$ on ($\bar{2}$01)-oriented Ga$_2$O$_3$ as: Cr$_2$O$_3$ $[12\bar{3}0]$ $\parallel$ Ga$_2$O$_3$ $[010]$ with two in-plane rotational domains. Interface modeling confirms the in-plane orientation for Cr$_2$O$_3$/$(\bar{2}01)$ Ga$_2$O$_3$ and shows that strained O-terminated Ga$_2$O$_3$ $(\bar{2}01)$ surfaces have the lowest interfacial energy with Cr$_2$O$_3$ (0001). Beyond establishing the specific epitaxial relationships for Cr$_2$O$_3$ and NiO on Ga$_2$O$_3$, this work provides a systematic methodology for the unambiguous structural characterization of heterointerfaces involving materials with markedly different
crystal symmetries.
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All authors Anna Sacchi, Krishna Acharya, Michelle A. Smeaton, Renae N. Gannon, Vladan Stevanovic, Steven R. Spurgeon, M. Brooks Tellekamp, Andriy Zakutayev
Materials Science
Mobility-lifetime relation links photodegradation in spin-coated and gravure-printed organic solar cells
Maria Saladina, Paul Weitz, David Holzner et al. (+24 more)
The degradation mechanisms of organic solar
cells (OSCs) have been studied primarily in
spin-coated, laboratory-scale devices, whereas scalable processing modifies the device architecture, active-layer morphology, and underlying charge-transport and recombination properties. Whether these changes also alter how solar
cells degrade remains unclear. Here, we compare
spin-coated and fully roll-to-roll-compatible gravure-printed PM6:Y12 solar
cells during $\sim$1000 h of continuous illumination. Despite distinct initial properties and degradation signatures, the loss of power-conversion efficiency systematically follows the mobility-lifetime product $\mu\tau$. Remarkably, ageing of the printed devices increases the recombination lifetime while strongly reducing charge-carrier mobility, showing that a longer lifetime alone does not imply improved device performance. The mobility reduction is accompanied by decreased PM6 lamellar order, whereas the additional open-
circuit voltage loss originates predominantly from increased non-radiative recombination. Dark recovery further reveals a metastable contribution specific to the printed architecture. These results identify the mobility-lifetime product as a unifying physical descriptor for photodegradation, linking ageing-induced microscopic changes to macroscopic performance loss across
spin-coated and scalable printed OSCs.
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All authors Maria Saladina, Paul Weitz, David Holzner, Chen Wang, Robert Eland, Svitlana Taranenko, Christopher Wöpke, Toni Seiler, Fabian Eller, Doyoung Sun, Alexander Ehm, Bekcy Joseph, Peli̇n Çi̇loğlu, Carmen Tretmans, Andreas Willert, Harald Kuhn, Roderick C. I. Mackenzie, Jan-Frederik Pietschmann, Martin Stoll, Yana Vaynzof, Dietrich R. T. Zahn, Safa Shoaee, Eva M. Herzig, Arved Carl Hübler, Thomas Heumüller, Christoph J. Brabec, Carsten Deibel
Materials Science
Laser-Ablated Au Electrodes with Preferred Orientation and Flat Interface on Oxides
Ambrose Seo, Richard Lai, Sujan Shrestha et al. (+5 more)
Gold (Au) thin-film electrodes deposited on oxides by pulsed
laser deposition (PLD) exhibit distinctive structural properties compared with thermally evaporated Au films. While thermally evaporated Au forms polycrystalline films with randomly oriented grains, PLD-grown Au films show a strong preferred [111] orientation perpendicular to the substrate surface, likely due to the energetic nature of the
laser-ablated Au plume. High-resolution transmission electron microscopy reveals atomically flat interfaces between the PLD-grown Au electrodes and epitaxial oxide thin films, separated by nanometer-scale gaps comparable to interlayer spacings in van der Waals materials. The highly ordered microstructure and flat interfacial morphology result in enhanced adhesion of the Au films to oxide surfaces. These results demonstrate that PLD can produce both high-quality Au electrodes and oxide thin films within a single deposition platform, offering improved interfacial control and potential benefits for a wide range of oxide electronic and functional devices.
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All authors Ambrose Seo, Richard Lai, Sujan Shrestha, Tina Tong, Joseph W. Brill, Menglin Zhu, Chris Chae, Jinwoo Hwang
Materials Science
A low-symmetry ground state of dense two-dimensional hydrogen
Cesare Cozza, Chris J. Pickard and Guglielmo Mazzola
Hydrogen under pressure is an extremely complex system featuring molecular dissociation, metallization, and anomalous melting. While bulk hydrogen has been studied for nearly a century, its two-dimensional counterpart remains unexplored. Using first-principles structural searches and relaxations in supercells containing up to 512 atoms, we identify ground-state structures of dense two-dimensional hydrogen showing no evidence of long-range crystalline order over the simulated length scales. Within density functional theory, these structures have lower enthalpy than all crystalline candidates considered over an intermediate pressure interval between molecular and atomic
crystals. This preference already emerges with classical
nuclei and persists as the supercell size increases, while the dominant structure-factor peaks grow substantially more slowly than in the crystalline reference phases. Although
crystals with very large primitive
cells cannot be rigorously excluded, these findings support the possibility of a disordered ground state and identify dense two-dimensional hydrogen as a promising setting for investigating competition between crystallization and structural disorder.
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Materials Science · Cross-listed from eess.IV
AutoRASOR: Autonomous Rapid Scanning Electron Microscope Operator
Kevin Zhang, Mohammad Taha, Rafael Espinosa Castañeda et al. (+7 more)
Scanning Electron Microscopy (SEM) is a foundational technique for characterizing material microstructure, which dictates many fundamental physical and chemical properties. With the rise of Self-Driving Labs (SDLs), samples are now synthesized in large batches, demanding equally high-throughput, autonomous characterization. Existing automated electron microscopy pipelines are task-specific: they detect pre-defined features, optimize known properties, or require prior knowledge of the sample, restricting each pipeline to the material system it was built for. We introduce AutoRASOR, a task-agnostic autonomous SEM pipeline that captures the multi-scale morphology of an unknown sample without domain-specific pre-training, fine-tuning, or human prompting. AutoRASOR embeds micrographs in real time with a
vision foundation model (VFM), DINOv3, and selects regions of interest (ROIs) through two complementary policies: Latent Farthest Point Sampling (LFPS) and active learning on morphological ambiguity, which is the conditional variance of unresolved fine-scale features given lower magnification appearance. Active learning on ambiguity consistently captures more diverse and rare morphologies than random ROI selection, while LFPS reliably recovers the specimen's morphological distribution within a limited capture budget, tested both on real SEM micrographs and synthetic phase-field images. By shifting autonomous characterization from pre-defined, task-specific targeting of features to morphological survey, AutoRASOR generates information-rich multi-scale
datasets for diverse downstream tasks. Without the need for domain-specific pre-training or prior material assumptions, this framework can be deployed out-of-the-box to characterize novel materials produced by SDLs.
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All authors Kevin Zhang, Mohammad Taha, Rafael Espinosa Castañeda, Yutong Liu, Yin Zhu, Lotan Portal, Robert A. Mcleod, Vahid Attari, Jane Y. Howe, Jason Hattrick-Simpers
Materials Science · Cross-listed from cs.SD
Causal limits and optimal allocation for passive frequency-selective hearing protection
Geonhwi Hwang, Jaewoo Lee, Hyunjun Kim et al. (+1 more)
Passive Helmholtz-resonator earplugs aim to attenuate hazardous noise while keeping
speech audible; the air volume of an ear-sized shell is finite, and we treat it as the resource a design spends. For a vented bore transparent at zero frequency and loaded by reactive side branches, causality fixes a conserved integral of transmission loss. We derive it in device variables, add viscous and flanking constraints, and allocate the budget by hazard-weighted water-filling with a continuous
speech-cost price. The audio-band budget B_ad = (20/ln10) pi^2 V / 2cS is set by the ratio of total cavity volume V to bore area S; occluding plugs are exempt. The f^2 price signal favours frequencies well above the source peak. Replacing strict transparency by a
speech-cost price gives an exchange rate of about 1.3 dB of protection per decibel of
speech cost under the present model, with the budget setting where it saturates. Across three form factors, low-frequency-selective designs stay near a decibel while hazard-matched mid/high-frequency designs reach twelve. The binding variables are bore area and
speech allowance, not resonator count.
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All authors Geonhwi Hwang, Jaewoo Lee, Hyunjun Kim, Hyeonwoo Na
Materials Science
Symmetry Classification of Multipolar Orders in Crystals: Theory, Property Tensors and Automated Analysis with MagSymMultipoles
Maxime Braun and Quintin N. Meier
Many structural and
magnetic phases and properties of crystalline materials can be related to the ordering of electric and
magnetic multipoles. Examples include ferroelectricity, linear magnetoelectricity, and altermagnetism. Determining the
symmetry-allowed multipoles in a
crystal is therefore useful for characterizing its ordered phases and physical properties. Here, we present a unified Cartesian framework for decomposing moment tensors of arbitrary rank into ordinary, toroidal, and poloidal multipoles, and for determining, from crystallographic and
magnetic symmetry, their ferroic, antiferroic, and noncollinear arrangements within the
crystal. We further establish the direct
symmetry relationship between multipolar order and the allowed components of associated physical-property tensors in both relativistic and non-relativistic settings. We implement this methodology in MagSymMultipoles (https://mag-sym-multipoles.com), an interactive web application for calculating and visualizing
symmetry-adapted electric and
magnetic multipoles. The application uses
magnetic symmetries both with and without
spin-orbit coupling to derive the allowed multipoles as well as the underlying Cartesian moment tensors, making it easy to explore the connection between a given multipolar order and the corresponding physical response tensors. We demonstrate the approach for ferroelectric BaTiO3, antiferroelectric PbZrO3, magnetoelectric Cr2O3, and the altermagnets MnF2, MnTe, and Mn3IrSi. These examples demonstrate how our method allows us to obtain an intuitive picture linking the multipolar order of a material directly to its physical properties, thereby facilitating the interpretation of theoretical and experimental results.
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Materials Science · Cross-listed from cond-mat.mes-hall
Non-Hermitian impurity scattering in graphene: Boltzmann transport and thermoelectric response
Juan A. Cañas, Daniel A. Bonilla and A. Martín-Ruiz
We investigate charge and thermoelectric transport in monolayer
graphene containing a dilute distribution of finite-range non-Hermitian scattering centers. The impurities are modeled as circular complex potentials, whose imaginary component describes local carrier loss or gain. By solving the Dirac scattering problem exactly within a partial-wave approach, we obtain the nonunitary scattering
matrix and derive the transport and absorption cross sections, which separately characterize momentum relaxation and net carrier exchange with the environment. To connect the microscopic scattering problem with stationary transport, we formulate a semiclassical Boltzmann description in which an external reservoir compensates the
equilibrium particle loss or gain. This leads to an effective relaxation time governed by both elastic momentum scattering and non-Hermitian flux exchange. Using the full energy-dependent relaxation time, we evaluate the Onsager coefficients and the resulting electrical conductivity, electronic thermal conductivity, Seebeck coefficient, Lorenz ratio, and electronic thermoelectric figure of merit. We find that weak gain increases the effective carrier lifetime and enhances both charge and heat conductivities, while absorption produces the opposite behavior. More importantly, gain enhances the magnitude of the thermopower and the electronic figure of merit, whereas loss suppresses them. The Lorenz ratio remains close to the Sommerfeld value, with non-Hermiticity mainly modifying its finite-temperature corrections. Our results show that non-Hermitian scattering provides an additional mechanism for controlling the energy dependence of carrier relaxation and, consequently, the thermoelectric response of
graphene.
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Materials Science
Insights into the long-standing controversy over sound velocities in lizardite
Chenxing Luo, Timothy Liao, Hongjin Wang et al. (+1 more)
Serpentine minerals are abundant H-bearing phases in the upper mantle and play a central role in water transport in subduction zones. Lizardite is the low-temperature polymorph expected in cold slabs and shallow serpentinized mantle. Using an ab initio thermoelastic framework combining density-functional theory with the r2SCAN meta-GGA and the quasiharmonic approximation, we calculate its compression curve, elastic tensor, and acoustic velocities at 300 K. r2SCAN reproduces the measured compression curve and
equilibrium volume to within 0.2%. Weak interlayer hydrogen bonding gives rise to pronounced axial softening, with $C_{33} \simeq 0.21C_{11}$ and $C_{44} \simeq 0.13C_{66}$ at 0 GPa. Solving the Christoffel equation over all propagation directions, we construct the velocity density of states (VelDOS), which reveals a high density of slow acoustic modes and other directional features obscured by Voigt-Reuss-Hill (VRH) aggregate averages. Reported experimental velocities preferentially sample the slower portion of this distribution rather than clustering near the VRH values, a correspondence consistent with subtle crystallographic texture or preferential orientation not resolved experimentally. Thus, the appropriate seismic-velocity endmember for lizardite depends on its orientational state, and reliance on VRH velocities alone may lead to overestimation of the degree of serpentinization when seismic observations preferentially sample slow crystallographic directions. Direction-resolved single-
crystal measurements and aggregate measurements with independently quantified texture would provide direct tests of this interpretation.
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All authors Chenxing Luo, Timothy Liao, Hongjin Wang, Renata M. Wentzcovitch
Materials Science
PAOFLOW: an automated suite for ab initio electronic, transport, and topological properties of materials
Anooja Jayaraj, Sergio Alvarruiz, Mia Falatko et al. (+10 more)
High-throughput first-principles property calculations are often constrained by costly post-processing and dense Brillouin-zone sampling, impeding the creation of large, internally consistent materials-property
datasets and limiting AI-driven discovery workflows. Pseudo-atomic-orbital (PAO)
Hamiltonians provide an exact tight-binding representation of first-principles electronic structure that enables the calculation of a wide range of electronic, optical, topological, and transport properties at negligible cost, thereby supporting scalable generation of training-quality data and AI-ready data infrastructures. In this work, we present PAOFLOW 3.0 – an open-source Python suite that automates the construction and analysis of PAO
Hamiltonians from plane-wave density functional theory calculations performed with either
Quantum ESPRESSO or VASP. The resulting
Hamiltonians enable efficient electronic structure interpolation, Fermi surface analysis, optical and dielectric response, transport coefficients, Berry phase and topological quantities,
quantum transport, and other materials properties. Compared with previous releases, PAOFLOW 3.0 substantially extends the scope of the package through the introduction of internal projections enabling support for VASP calculations, self-consistent Hubbard U and V corrections obtained using ACBN0 and eACBN0 methods, generation of environment-dependent Slater-Koster tight-binding models, Landauer–BÃŒttiker
quantum transport, and calculation of
quantum oscillations using the integrated PySKEAF module. The theoretical foundations and the software architecture are presented together with representative calculations illustrating the current capabilities of the package.
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All authors Anooja Jayaraj, Sergio Alvarruiz, Mia Falatko, Zhiren He, Jonathan Red, Caua F. Schuch, Karma Tenzin, Chao Chen Ye, Davide Ceresoli, Marcio Costa, Stefano Curtarolo, Jagoda Slawinska, Marco Buongiorno Nardelli
Materials Science · Cross-listed from physics.chem-ph
Development of a Non-Empirical Exchange-Hole Dipole Moment Dispersion Model
Alastair J. A. Price and Alberto Otero-de-la-Roza
The inclusion of dispersion effects is important in density-functional theory (DFT) to model non-covalent interactions correctly, a task that is essential in many applications of the theory. Many dispersion functionals have been proposed in the past. The exchange-hole dipole moment (XDM) model combines the simplicity of a damped pairwise asymptotic expression for the dispersion energy with a theory-grounded approach to calculate the dispersion coefficients. XDM is, arguably, the most accurate dispersion correction for the description of molecular
crystals and it has been thoroughly tested for other applications across a wide range of chemistries. Here, we address the two main shortcomings of XDM. First, XDM relies on the use of experimentally determined free-atom polarizabilities. Second, because the XDM atom-in-molecule properties (volumes, polarizabilities, exchange-hole dipole moments) use the Hirshfeld partition method, XDM describes systems with large atomic partial charges, like alkali cations or halide anions, poorly. We propose neXDM, a non-empirical variant of XDM that removes the experimental parameters by using the Kirkwood polarizability formula, thereby making neXDM a pure meta-GGA dispersion functional. In addition, following previous work by Bučko et al. on the similar Tkatchenko–Scheffler (TS) method, we replace the Hirshfeld partitioning with its iterative counterpart. The performance of neXDM is shown to be on par with XDM in standard molecular and
crystal benchmark sets, and greatly improves the modeling of ionic systems. The new neXDM method sets a new record for the best dispersion-corrected generalized-gradient approximation (GGA) functional for molecular
crystal lattice energies in the X23 set (0.700~kcal/mol).
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Materials Science · Cross-listed from cond-mat.str-el
Machine learning magnetic interactions from neutron powder diffraction data
Adit S. Desai, Yongqiang Cheng and Joseph A. M. Paddison
Neutron diffraction is a versatile experimental technique capable of probing a material's
magnetic properties. While diffraction is typically used to determine the
magnetic structure of a material,
magnetic diffuse scattering data from a diffraction experiment are also sensitive to the
magnetic interactions in its
Hamiltonian. However, accurately determining
magnetic interaction parameters from
neutron-scattering data involves an inverse scattering problem that is challenging to solve in general. Here, we investigate the effectiveness of a machine learning approach to predict the interaction parameters given
magnetic diffuse-scattering data measured on powder samples, for a comprehensive survey of isotropic interactions on eight high-
symmetry lattices. Across all
lattices we considered, the machine-learning approach estimates the interaction parameters with high (~2%) accuracy, while avoiding the issue of false minima that is encountered with non-linear least squares refinement. Our results highlight that powder diffuse-scattering data can provide a compact "fingerprint" of the
magnetic interactions for many materials.
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Materials Science
Low resistance NiO/\beta-Ga_{2}O_{3} heterojunction diodes grown via molecular beam epitaxy
Dagny Sacksteder, Anna Sacchi, Renae Gannon et al. (+4 more)
NiO is one of the most important p-type oxide contact materials used in many
semiconductor technologies. However, current NiO growth methods can induce interfacial damage that diminishes device performance. Fine control of interfaces is especially important in implementing NiO heterojunction diodes and transistors based on ultra wide band gap (UWBG)
semiconductors such as AlGaN and Ga_{2}O_{3} used for power electronic applications. Here, we report on how molecular beam epitaxy can be used to achieve low-defect, lightly doped NiO contact layers for a \beta-Ga_{2}O_{3} diodes. Although high-temperature growth does not measurably decrease the on-state resistance of the diode, increased growth rates up to 600 nm/hr lower on-state resistance in p– NiO / \beta-Ga_{2}O_{3} heterojunction diodes without reducing film quality. At a NiO growth rate of 380 nm/hr, unoptimized diodes with 35 nm thick p– NiO layers demonstrate a device-average specific on-state resistance of 1.46 \Omega-cm^{2} and an ideality factor of 1.46. Individual devices grown at this condition show specific on-state resistance as low as 25 m{\Omega}-cm2 with a rectification ratio of 2.7x106. Scanning transmission electron microscopy imaging reveals the (100) NiO/ (100) \beta-Ga_{2}O_{3} interface is coherent and atomically abrupt. These results open a new avenue to optimizing the NiO interface to produce robust, competitive kV-class power electronic devices based on \beta-Ga_{2}O_{3} and other UWBG
semiconductors.
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All authors Dagny Sacksteder, Anna Sacchi, Renae Gannon, Michelle Smeaton, Megan E. Holtz, Andriy Zakutayev, M. Brooks Tellekamp
Materials Science
PhonoMC: Occupation-based deviational Monte Carlo for phonon transport with temperature-dependent scattering
Shixian Liu, Fei Yin, Gang Wang et al. (+4 more)
Nanoscale self-heating involves
phonon transport across confined geometries, material interfaces, and temperature fields over which the scattering rates can vary substantially. We develop PhonoMC, an occupation-based deviational Monte Carlo method for solving the
phonon Boltzmann transport equation within the relaxation-time approximation. A fixed
equilibrium state is retained as the deviational reference, while the local temperature reconstructed from the represented energy is used to evaluate mode-dependent scattering rates. Collisions are updated with a separately determined relaxation temperature to conserve energy over each time step, and prescribed
lattice heating is introduced by changing carrier occupations rather than continuously adding computational particles. For cross-plane transport through a 100-nm Si film, the deviational formulation reproduces the full-population heat flux while reducing its standard deviation by a factor of approximately 3.3 at \(\Delta T=100\)~K with \(10^5\) carriers. In contrast, keeping the scattering rates fixed at 300~K overestimates the heat flux by 23.7% at \(\Delta T=250\)~K. Calculations of Si thin films distinguish finite-length effects from surface-scattering suppression, and Si/3C-SiC bilayers are used to examine interfacial thermal resistance. The method is further applied to localized heating in FinFET-like structures, where replacing the lower Si substrate with higher-conductivity 3C-SiC leads to a higher hotspot temperature because of the additional resistance associated with the confined Si region and the Si/SiC interface. These results show that a fixed deviational reference can be combined with local temperature-dependent scattering and sustained heat deposition in a mode-resolved Monte Carlo description of nanoscale thermal transport.
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All authors Shixian Liu, Fei Yin, Gang Wang, Bin Liu, Ge Zhang, Alexander A. Barinov, Ke Xu
Materials Science · Cross-listed from cond-mat.supr-con
Strong-coupling multigap superconductivity in the Heusler compound ScAu$_2$Al
Jozef Kačmarčík, Zuzana Pribulová, Yevhen Petrenko et al. (+9 more)
ScAu$_2$Al is the Heusler
superconductor with the highest reported transition temperature, Tc, close to 5 K. Here, we combine high-resolution ac calorimetry and electrical-transport measurements with first-principles-based Eliashberg calculations. The large specific-heat jump, ${\Delta}C/{\gamma_nT_c} =$ 2.2, well above the weak-coupling BCS value of 1.43, together with an electron-
phonon coupling constant ${\lambda} = $1.1, establishes ScAu2Al as a strong-coupling
superconductor. The electronic specific heat is described better by a two-gap {\alpha} model, with $2{\Delta}_S/k_BT_c = $ 4.1 and $2{\Delta}_L/k_BT_c = $ 4.8, than by a single-gap model. The thermodynamic upper critical field follows a conventional WHH-like temperature dependence with $B_{c2}(0) = 0.18$ T, whereas the resistively determined critical field reaches values about three times larger and exhibits a pronounced positive
curvature. We attribute the enhanced resistive field scale to superconductivity in disordered grain-boundary and interfacial regions. The experimental results are supported by calculations of the heat capacity and upper critical field within the Eliashberg formalism using Fermi-surface and electron-
phonon parameters obtained from first-principles calculations
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All authors Jozef Kačmarčík, Zuzana Pribulová, Yevhen Petrenko, Gabriel Kuderowicz, Paweł Wójcik, Michał J. Winiarski, Szymon M. Królak, Filip Košuth, Pavol Szabó, Tomasz Klimczuk, Bartlomiej Wiendlocha, Peter Samuely
Materials Science
Multivalley 3D Electronic Structure of PbSe from Soft-X-Ray ARPES and First-Principles Calculations
Zefeng Cai, Valentine V. Volobuev, Jędrzej Korczak et al. (+7 more)
PbSe is a narrow-gap IV-VI
semiconductor, whose multivalley valence bands, with maxima at the L, $\Sigma$, and $\Delta$ points, underpin its intermediate-temperature thermoelectric properties. We combine soft-X-ray angle-resolved photoemission spectroscopy (SX-ARPES) with first principles simulations to study the valence band structure of bulk PbSe. High resolution measurements are conducted at
photon energies of 400-900 eV to map the valence
manifold along X$\Gamma$X, WXW, and K$\Gamma$K, and iso-energy surfaces are collected in the $k_z=0$ plane. Comparison to ARPES enables a rigorous assessment of the performance of density functional theory (DFT), using semi-local and hybrid functionals, as well as many-body perturbation theory within the quasiparticle self-consistent $GW$ approximation. We find that the Heyd-Scuseria-Ernzerhof (HSE) hybrid functional and QP$GW$ reproduce the measured band dispersions to within 0.1-0.2 eV over the entire valence band. In contrast, the semi-local Perdew-Burke-Ernzerhof (PBE) functional compresses the band width and deviates from experiment by up to 0.6 eV. We further show that an accurate band structure and band gap are vital to obtaining a correct description of the dependence of the Seebeck coefficient of p-type PbSe on the hole concentration (Pisarenko relation). This has implications for computational efforts to discover thermoelectric materials.
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All authors Zefeng Cai, Valentine V. Volobuev, Jędrzej Korczak, Enrico Della Valle, Hantian Liu, Moritz Hoesch, Sergey M. Frolov, Tomasz Story, Vladimir N. Strocov, Noa Marom