Peer Revenue Equity in science

Papers

Fresh from arXiv, typeset properly. Highlighted words trade on the market.

Physics Condensed Matter Materials Science

cond-mat.mtrl-sci Watch Materials Science

Saturday 15 November

Materials Science · Cross-listed from physics.optics

Direct Photochemical Patterning of Lithium Niobate Thin Films for Scalable Nonlinear Optical Metasurfaces

Rana Faryad Ali and Guillermo Aguilar

Lithium niobate is one of the most sought-after materials for nanophotonic devices, including frequency converters, modulators, and quantum light sources. Integration of lithium niobate into optical devices, however, is hampered by significant top-down fabrication challenges due to its exceptional chemical resistance. Scalable fabrication methods that preserve material quality while reducing fabrication complexity and cost are, therefore, crucial to advancing lithium niobate devices. We present a photochemical metal-organic decomposition technique for the scalable patterning of lithium niobate at ambient conditions, eliminating the need for harsh etching conditions and cleanroom protocols. The method utilizes a solution of a custom-prepared photosensitive organometallic precursor as a negative photoresist. The UV light exposure of the thin films of the precursor through a photomask, followed by rinsing with ethanol, yields amorphous patterns, which transform into crystalline lithium niobate after a calcination step. This method enables a scalable fabrication of a range of complex geometric shapes with a feature resolution down to $30\,\mu\mathrm{m}$. The patterned lithium niobate structures exhibit a tunable second harmonic generation activity with an isotropic optical response. This approach offers a scalable and low-cost pathway for manufacturing lithium niobate photonics and the potential to fabricate other materials (e.g., barium titanite and lithium tantalate).
Read the full abstract

Materials Science

Stoichiometry and Phase Control in K$_{1-x}$CrSe$_2$ via Self-Flux Synthesis

Felix Eder, Catherine Witteveen, Enrico Giannini et al. (+1 more)

Layered delafossite-type magnetic materials, such as KCrSe$_2$, are promising platforms for studying magnetic systems and potential frustration on triangular lattices. Synthesis, structure-type control, and off-stoichiometries remain major challenges in the investigation of these delafossite-type magnets. Starting from the same self-flux composition (K:Cr:Se = 8:1:8), we isolated three distinct K$_{1-x}$CrSe$_2$ phases with $x$ = 0, 0.13–0.17, and 0.32–0.35, each adopting a different structure type depending on the quenching temperature applied. The phase evolution indicates a sequence of transformations during synthesis between compounds with varying degrees of potassium deficiency. Building on these insights into phase stability and crystal growth, we successfully grew single crystals of full-stoichiometric KCrSe$_2$ – enabling direction-dependent magnetization measurements. These measurements reveal a pronounced field dependence of the Néel temperature at low external fields, as well as a weak metamagnetic transition. Our findings demonstrate that even a simple parameter – such as quenching temperature – can be used to control stoichiometry, direct phase formation, and ultimately tune the magnetic properties of delafossite-type materials.
Read the full abstract

All authors Felix Eder, Catherine Witteveen, Enrico Giannini, Fabian O. von Rohr

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

Deterministic Switching of Perpendicular Ferromagnets by Higher harmonics of Spin-orbit Torque in Noncentrosymmetric Weyl Semimetals

Naomi Fokkens and Fei Xue

Field-free deterministic switching of perpendicular ferromagnets is a central challenge for spintronics applications, typically requiring explicit symmetry breaking. Here we show that deterministic switching can instead be achieved through higher angular harmonics of spin-orbit torques, even in systems that preserve in-plane mirror symmetries. Using a vector spherical harmonics expansion, we demonstrate that these higher-harmonic torque components naturally give rise to additional out-of-equator fixed points, enabling reliable magnetization reversal when their magnitude is comparable to conventional lowest-order torques. We illustrate this mechanism with first-principles calculations on the noncentrosymmetric Weyl ferromagnet PrAlGe, where the combination of Weyl-node band topology and strong spin-orbit coupling produces sizable higher-harmonic torque components. Because the Fermi surface is small, the conventional lowest-order torques are relatively weak, allowing the higher-order harmonics to compete on equal footing and strongly reshape the magnetization dynamics. The resulting spin dynamics confirm deterministic switching without additional symmetry breaking. Our results establish higher-harmonic spin-orbit torque as a key ingredient for understanding and controlling magnetization dynamics in topological and spintronic materials.
Read the full abstract

Materials Science

Reinforcement Learning for Chemical Ordering in Alloy Nanoparticles

Jonas Elsborg, Emma L. Hovmand and Arghya Bhowmik

We approach the search for optimal element ordering in bimetallic alloy nanoparticles (NPs) as a reinforcement learning (RL) problem and have built an RL agent that learns to perform such global optimization using the geometric graph representation of the NPs. To demonstrate the effectiveness, we train an RL agent to perform composition-conserving atomic swap actions on the icosahedral nanoparticle structure. Trained once on randomized $Ag_{X}Au_{309-X}$ compositions and orderings, the agent discovers previously established ground state structure. We show that this optimization is robust to differently ordered initialisations of the same NP compositions. We also demonstrate that a trained policy can extrapolate effectively to NPs of unseen size. However, the efficacy is limited when multiple alloying elements are involved. Our results demonstrate that RL with pre-trained equivariant graph encodings can navigate combinatorial ordering spaces at the nanoparticle scale, and offer a transferable optimization strategy with the potential to generalize across composition and reduce repeated individual search cost.
Read the full abstract

Materials Science · Cross-listed from quant-ph

Skyrmionic qubits stabilized by Dzyaloshinskii-Moriya interaction as platforms for qubits and quantum gates

Doru Sticlet, Romulus Tetean and Coriolan Tiusan

Quantum computation departs from the classical paradigm of deterministic, bit-based processing by exploiting inherently quantum phenomena such as superposition and entanglement. We propose a framework for qubit realization based on skyrmionic states stabilized by the Dzyaloshinskii-Moriya interaction (DMI) in two-dimensional spin lattices. The model incorporates competing exchange interactions, perpendicular magnetic anisotropy, and Zeeman coupling, solved via exact diagonalization under periodic (PBC) and open boundary conditions (OBC). A quantum skyrmionic phase emerges for PBC within a parameter space defined by DMI, exchange, field, and anisotropy, while OBC favor classical-like, topologically protected skyrmions. Quantum logic gates (Pauli X, Y, Z, Hadamard) are implemented on both skyrmion types. Energy density and entanglement entropy analyses reveal that quantum skyrmions suffer from DMI-driven decoherence and reduced gate fidelity, whereas classical-like skyrmions maintain stability. Exact simulations of qubit dynamics, including drive effects and Lindblad decoherence, demonstrate tunable anharmonic energy levels and coherent Bloch-sphere manipulation, making these skyrmionic states promising candidates for qubit implementation. Overall, the Dzyaloshinskii-Moriya interaction plays a dual role-stabilizing skyrmionic qubits while simultaneously inducing decoherence during gate operations.
Read the full abstract

Materials Science

Equivariant Atomic and Lattice Modeling Using Geometric Deep Learning for Crystal Structure Optimization

Ziduo Yang, Yi-Ming Zhao, Xian Wang et al. (+3 more)

Structure optimization, which yields the relaxed structure (minimum-energy state), is essential for reliable materials property calculations, yet traditional ab initio approaches such as density-functional theory (DFT) are computationally intensive. Machine learning (ML) has emerged to alleviate this bottleneck but suffers from two major limitations: (i) existing models operate mainly on atoms, leaving lattice vectors implicit despite their critical role in structural optimization; and (ii) they often rely on multi-stage, non-end-to-end workflows that are prone to error accumulation. Here, we present E3Relax, an end-to-end equivariant graph neural network that maps an unrelaxed crystal directly to its relaxed structure. E3Relax promotes both atoms and lattice vectors to graph nodes endowed with dual scalar-vector features, enabling unified and symmetry-preserving modeling of atomic displacements and lattice deformations. A layer-wise supervision strategy forces every network depth to make a physically meaningful refinement, mimicking the incremental convergence of DFT while preserving a fully end-to-end pipeline. We evaluate E3Relax on four benchmark datasets and demonstrate that it achieves remarkable accuracy and efficiency. Through DFT validations, we show that the structures predicted by E3Relax are energetically favorable, making them suitable as high-quality initial configurations to accelerate DFT calculations.
Read the full abstract

All authors Ziduo Yang, Yi-Ming Zhao, Xian Wang, Wei Zhuo, Xiaoqing Liu, Lei Shen

Materials Science

Rapid Machine Learning-Driven Detection of Pesticides and Dyes Using Raman Spectroscopy

Quach Thi Thai Binh, Thuan Phuoc, Xuan Hai et al. (+3 more)

The extensive use of pesticides and synthetic dyes poses critical threats to food safety, human health, and environmental sustainability, necessitating rapid and reliable detection methods. Raman spectroscopy offers molecularly specific fingerprints but suffers from spectral noise, fluorescence background, and band overlap, limiting its real-world applicability. Here, we propose a deep learning framework based on ResNet-18 feature extraction, combined with advanced classifiers, including XGBoost, SVM, and their hybrid integration, to detect pesticides and dyes from Raman spectroscopy, called MLRaman. The MLRaman with the CNN-XGBoost model achieved a predictive accuracy of 97.4% and a perfect AUC of 1.0, while it with the CNN-SVM model provided competitive results with robust class-wise discrimination. Dimensionality reduction analyses (PCA, t-SNE, UMAP) confirmed the separability of Raman embeddings across 10 analytes, including 7 pesticides and 3 dyes. Finally, we developed a user-friendly Streamlit application for real-time prediction, which successfully identified unseen Raman spectra from our independent experiments and also literature sources, underscoring strong generalization capacity. This study establishes a scalable, practical MLRaman model for multi-residue contaminant monitoring, with significant potential for deployment in food safety and environmental surveillance.
Read the full abstract

All authors Quach Thi Thai Binh, Thuan Phuoc, Xuan Hai, Thang Bach Phan, Vu Thi Hanh Thu, Nguyen Tuan Hung

Materials Science

Ba-substitution induced evolution of structural and magnetic properties of La2-xBaxCoIrO6 double perovskites

C. A. S. Vieira, B. J. Santos, J. G. Duque et al. (+2 more)

The Iridium-based oxides are the subject of great recent interest due to the non-conventional physics that may emerge from the strong spin-orbit coupling present in 5d ions. Here, we explore the coupling between Ir and Co in the La2-xBaxCoIrO6 perovskites (x = 0, 0.5, 0.75 and 1.0), where the structural, electronic, and magnetic properties of the series are investigated by means of x-ray powder diffraction and magnetometry. The system's crystal structure evolves from the monoclinic P2_1/n to the triclinic I-1 space group as the Ba concentration increases. Measurements of magnetization revealed ferrimagnetic behavior in x = 0, 0.5 and 0.75 compounds, possibly resulting from antiferromagnetic coupling between Co2+/3+ and Ir4+. In contrast, for x = 1.0 a clear collinear antiferromagnetic character is observed for the Co2+ ions, resulting from the quenching of the Ir5+ magnetic moment. The evolution of the magnetic properties of the series is discussed in terms of the structural and electronic changes, as well as the spin-orbit coupling in Ir.
Read the full abstract

All authors C. A. S. Vieira, B. J. Santos, J. G. Duque, E. M. Bittar, L. Bufaiçal

Materials Science · Cross-listed from cs.CE

Preference Learning from Physics-Based Feedback: Tuning Language Models to Design BCC/B2 Superalloys

Satanu Ghosh, Collin Holgate, Neal R. Brodnik et al. (+4 more)

We apply preference learning to the task of language model-guided design of novel structural alloys. In contrast to prior work that focuses on generating stable inorganic crystals, our approach targets the synthesizeability of a specific structural class: BCC/B2 superalloys, an underexplored family of materials with potential applications in extreme environments. Using three open-weight models (LLaMA-3.1, Gemma-2, and OLMo-2), we demonstrate that language models can be optimized for multiple design objectives using a single, unified reward signal through Direct Preference Optimization (DPO). Unlike prior approaches that rely on heuristic or human-in-the-loop feedback (costly), our reward signal is derived from thermodynamic phase calculations, offering a scientifically grounded criterion for model tuning. To our knowledge, this is the first demonstration of preference-tuning a language model using physics-grounded feedback for structural alloy design. The resulting framework is general and extensible, providing a path forward for intelligent design-space exploration across a range of physical science domains.
Read the full abstract

All authors Satanu Ghosh, Collin Holgate, Neal R. Brodnik, Doug Downey, Samantha Daly, Tresa M. Pollock, Samuel Carton

Materials Science

Ionic Interdiffusion at Cathode-Solid-Electrolyte Interface: A Machine Learning-Assisted Multiscale Investigation and Mitigation Strategies

Musawenkosi K. Ncube, Pallab Barai, Selva Chandrasekaran Selvaraj et al. (+3 more)

Future lithium-based batteries are expected to use solid electrolytes to achieve higher energy density and fast charge capabilities. The majority of solid electrolytes are thermodynamically unstable against layered oxide cathodes. Here, the stability of LiCoO2 (LCO) cathode with Li10GeP2S12 (LGPS) solid electrolyte is investigated using ab initio molecular dynamics (AIMD) and machine learning molecular dynamics (MLMD). The propensity of ionic interdiffusion, formation of a passivation layer, and corresponding decay in cell performance is addressed using a continuum model. The large-scale MLMD simulations confirm that the LCO|LGPS interface permits interdiffusion of Co and other ionic species, leading to the formation and growth of a resistive interphase and dramatic capacity fade even in the first cycle. We then examine the literature evidence that incorporating a thin layer of LiNb0.5Ta0.5O3 (LNTO) between LCO and LGPS prevents the interdiffusion of ions. Atomistic simulations suggest that the substitution of Li in LNTO with Co is not thermodynamically favorable, which helps to minimize the ionic interdiffusion process. The stable Nb/Ta5+ states form a rigid metal-oxide framework, which consequently also prevents the substitution of Nb/Ta. However, continuum level analysis suggests that due to the higher mechanical stiffness of LNTO, interfacial delamination between the LCO and LNTO is possible, which can minimize the effectiveness of the protective layer. This paper suggests the need for the development of novel interlayers that balance low interdiffusion with low stiffness.
Read the full abstract

All authors Musawenkosi K. Ncube, Pallab Barai, Selva Chandrasekaran Selvaraj, Larry A. Curtiss, Anh T. Ngo, Venkat Srinivasan

Friday 14 November

Materials Science

Effects of Yttrium Doping on Oxygen Conductivity in Ba(Fe, Co, Zr, Y)O_{3-\delta} Cathode Materials for Proton Ceramic Fuel Cells

Chiyoung Kim, Ryan Jacobs, Jack H. Duffy et al. (+3 more)

Proton ceramic fuel cells (PCFCs) achieve high efficiency at reduced operating temperatures, but their performance is often limited by slow oxygen reduction reaction (ORR) kinetics at the cathode. The BaCoFeZrY (BCFZY) perovskite family is a promising triple-conducting air-electrode material, yet the role of Y dopants in governing oxygen transport remains unclear. In this study, we examine the effect of Y content on oxygen conductivity in three compositions: BCFZ, BCFZY0.1, and BCFY. Oxygen conductivity was evaluated from the product of oxygen tracer diffusivity and oxygen defect concentration. Ab initio molecular dynamics simulations were used to determine tracer diffusivity and migration energies, while defect concentrations were estimated from reference data. Y doping slightly decreases oxygen conductivity from BCFZ to BCFZY0.1, from 337 to 203 mS/cm at 500 C, with activation energies of 0.155 and 0.172 eV. BCFY shows much lower conductivity (99 mS/cm) and a higher activation energy of 0.261 eV. Computed conductivities are higher and more Arrhenius-like than experimental values, suggesting that microstructural features such as grain boundaries strongly limit oxygen transport in real materials. A series-circuit model combining bulk conductivity and fitted grain-boundary parameters provides semi-quantitative agreement with experiment. These results clarify the role of Y doping in oxygen transport and provide insight for optimizing cathode performance in PCFCs.
Read the full abstract

All authors Chiyoung Kim, Ryan Jacobs, Jack H. Duffy, Kyle S. Brinkman, Harry W. Abernathy, Dane Morgan

Materials Science

Layer breathing Raman mode in two-dimensional van der Waals material $\mathrm{Cr_2Ge_2Te_6}$

Nilesh Choudhury, Sandeep, Neesha Yadav et al. (+2 more)

Two-dimensional (2D) van der Waals (vdW) magnetic materials have emerged as key materials for next-generation magneto-electric and spintronic devices, where understanding the relationship between layer number, lattice dynamics, and magnetic interactions is very important. In this work, we report the observation of the layer breathing mode (LBM) in few-layer $\mathrm{Cr_2Ge_2Te_6}$, a ferromagnetic semiconductor with thickness dependent electronic, magnetic and optical properties, using Raman spectroscopy, which serves as a direct fingerprint of interlayer coupling and lattice symmetry. Group-theoretical symmetry analysis confirms that the CGT falls under the non-polar category of layered material. The evolution of the LBM-frequency with increasing layer number (N) reveals a distinct softening trend, characteristic of weakening restoring forces in thicker flakes. By fitting the experimental Raman data using the Linear Chain Model (LCM), we quantitatively extract the interlayer force constant ($\mathrm{K_c}$), providing a measure of the vdW coupling strength between layers.
Read the full abstract

All authors Nilesh Choudhury, Sandeep, Neesha Yadav, Mayank Shukla, Pintu Das

Materials Science · Cross-listed from quant-ph

2025 Quantum Diamond Workshop Findings Report

Danielle A. Braje, Matthew L. Markham, Jennifer M. Schloss et al. (+2 more)

This report synthesizes the outcomes of a two-day workshop held in Washington, D.C. in May, 2025 that convened researchers, industry representatives, and government stakeholders to examine the current state and future directions of quantum diamond technologies. The workshop's goals were to assess the most promising use cases, to identify the key technical and structural challenges limiting adoption, and to chart potential pathways for aligning application needs with diamond material and device development. Through a series of technical presentations and open discussions, participants explored both near-term demonstrations and long-term infrastructure needs, highlighting the critical role of coordination between material suppliers, device engineers, and end users. The goal of this report is to distill those insights into a coherent set of cross-cutting themes, challenges, and strategic actions that can guide government, industry, and academic efforts to accelerate the maturation and commercialization of quantum diamond technologies.
Read the full abstract

All authors Danielle A. Braje, Matthew L. Markham, Jennifer M. Schloss, Michael A. Slocum, Ronald L. Walsworth

Materials Science

Edwards Localization

Riccardo Fantoni

We study the localization problem in quantum stochastic mechanics. We start from the Edwards model for a particle in a bath of scattering centers and prove static localization of the ground state wavefunction of the particle in a one dimensional square well coupled to Dirac delta like scattering centers in arbitrary but fixed positions. We see how the localization increases for increasing coupling $g$ and increasing number of scattering centers at constant density. Then we choose the scattering centers positions as pseudo random numbers with a uniform probability distribution and observe an increase in the localization of the average of the ground state over the many positions realizations. We discuss how this averaging procedure is consistent with a picture of a particle in a Bose-Einstein condensate of of non interacting boson scattering centers interacting with the particle with Dirac delta functions pair potential. We then study the dynamics of the ground state wave function. We conclude with a discussion of the affine quantization version of the Lax model which reduces to a system of contiguous square wells with walls in arbitrary positions independently of the coupling constant $g$.
Read the full abstract

Materials Science

Human-AI collaborative autonomous synthesis with pulsed laser deposition for remote epitaxy

Asraful Haque, Daniel T. Yimam, Jawad Chowdhury et al. (+10 more)

Autonomous laboratories typically rely on data-driven decision-making, occasionally with human-in-the-loop oversight to inject domain expertise. Fully leveraging AI agents, however, requires tightly coupled, collaborative workflows spanning hypothesis generation, experimental planning, execution, and interpretation. To address this, we develop and deploy a human-AI collaborative (HAIC) workflow that integrates large language models for hypothesis generation and analysis, with collaborative policy updates driving autonomous pulsed laser deposition (PLD) experiments for remote epitaxy of BaTiO$_3$/graphene. HAIC accelerated the hypothesis formation and experimental design and efficiently mapped the growth space to graphene-damage. In situ Raman spectroscopy reveals that chemistry drives degradation while the highest energy plume components seed defects, identifying a low-O$_2$ pressure low-temperature synthesis window that preserves graphene but is incompatible with optimal BaTiO$_3$ growth. Thus, we show a two-step Ar/O$_2$ deposition is required to exfoliate ferroelectric BaTiO$_3$ while maintaining a monolayer graphene interlayer. HAIC stages human insight with AI reasoning between autonomous batches to drive rapid scientific progress, providing an evolution to many existing human-in-the-loop autonomous workflows.
Read the full abstract

All authors Asraful Haque, Daniel T. Yimam, Jawad Chowdhury, Ralph Bulanadi, Ivan Vlassiouk, John Lasseter, Sujoy Ghosh, Christopher M. Rouleau, Kai Xiao, Yongtao Liu, Eva Zarkadoula, Rama K. Vasudevan, Sumner B. Harris

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

STEM EBIC as a Quantitative Probe of Semiconductor Devices

Sebastian Schneider, Sebastian Beckert, René Hammer et al. (+3 more)

Electron beam-induced current (EBIC) imaging in the scanning transmission electron microscope (STEM), STEM-EBIC, provides direct access to carrier transport at the nanoscale. While well established in bulk SEM geometries, its application to thin TEM lamellae remains largely unexplored. Here, we present a systematic STEM-EBIC study of silicon photodiode lamellae prepared by gallium and xenon focused ion beam (FIB) milling. We directly visualize the p-n junctions in thin cross sections and extract effective diffusion lengths for electrons and holes as a function of local thickness. The values are orders of magnitude smaller than those obtained by SEM-EBIC on bulk silicon, reflecting pronounced surface recombination and FIB-induced surface modifications. Current-voltage measurements further reveal severe deviations from the expected diode-like behavior, which we attribute to ohmic metal-semiconductor contacts in the emasurement setup. Our analysis establishes STEM-EBIC as a quantitative probe of carrier transport in nanoscale devices.
Read the full abstract

All authors Sebastian Schneider, Sebastian Beckert, René Hammer, Markus König, Grigore Moldovan, Darius Pohl

Materials Science

The Interoperability Challenge in DFT Workflows Across Implementations

S. K. Steensen, T. S. Thakur, M. Dillenz et al. (+11 more)

Interoperability and cross-validation remains a significant challenge in the computational materials discovery community. In this context, we introduce a common input/output standard designed for internal translation by various workflow managers (AiiDA, PerQueue, Pipeline Pilot, and SimStack) to produce results in a unified schema. This standard aims to enable engine-agnostic workflow execution across multiple density functional theory (DFT) codes, including CASTEP, GPAW, Quantum ESPRESSO, and VASP. As a demonstration, we have implemented a workflow to calculate the open-circuit voltage across several battery cathode materials using the proposed universal input/output schema. We analyze and resolve the challenges of reconciling energetics computed by different DFT engines and document the code-specific idiosyncrasies that make straightforward comparisons difficult. Motivated by these challenges, we outline general design principles for robust automated DFT workflows. This work represents a practical step towards more reproducible and interoperable workflows for high-throughput materials screening, while highlighting challenges of aligning electronic properties, especially for non-pristine structures.
Read the full abstract

All authors S. K. Steensen, T. S. Thakur, M. Dillenz, J. M. Carlsson, C. R. C. Rego, E. Flores, H. Hajiyani, F. Hanke, J. M. G. Lastra, W. Wenzel, N. Marzari, T. Vegge, G. Pizzi, I. E. Castelli

Materials Science

Visible and Terahertz Nonlinear Responses in the Topological Noble Metal Dichalcogenide PdTe2

George J. de Coster, Lucas Lafeta, Stefan Heiserer et al. (+5 more)

Nonlinear processes can offer pathways to next-generation sensors and frequency mixing devices to overcome modern imaging, detection, and communication challenges. In this article, we report on strong second and third-order nonlinear optical responses in visible and terahertz (THz) light in single crystals of the noble metal dichalcogenide PdTe$_2$. We find that buried conduction and valence topological surface states of PdTe$_2$ lead to resonant optical second-harmonic generation. On the other hand, although the nonlinear responses obtained with THz excitation are not close to this resonance, they can be clearly observed in reflection geometry, even in the presence of broadband excitation, where optical filters are not necessary to observe the enhanced odd-order higher harmonic output. By carefully considering the radiative photocurrent framework of stimulated THz emission, we are able to extract fingerprints of both second- and third-order processes in the THz regime, and show that PdTe$_2$ is a promising material candidate for radio frequency rectification, frequency mixing, and beam focusing.
Read the full abstract

All authors George J. de Coster, Lucas Lafeta, Stefan Heiserer, Cormac Ó Coileáin, Zdenek Sofer, Achim Hartschuh, Georg S. Duesberg, Paul Seifert

Materials Science · Cross-listed from cs.LG

Data-efficient U-Net for Segmentation of Carbide Microstructures in SEM Images of Steel Alloys

Alinda Ezgi Gerçek, Till Korten, Paul Chekhonin et al. (+2 more)

Understanding reactor-pressure-vessel steel microstructure is crucial for predicting mechanical properties, as carbide precipitates both strengthen the alloy and can initiate cracks. In scanning electron microscopy images, gray-value overlap between carbides and matrix makes simple thresholding ineffective. We present a data-efficient segmentation pipeline using a lightweight U-Net (30.7~M parameters) trained on just 10 annotated scanning electron microscopy images. Despite limited data, our model achieves a Dice-Sørensen coefficient of 0.98, significantly outperforming the state-of-the-art in the field of metallurgy (classical image analysis: 0.85), while reducing annotation effort by one order of magnitude compared to the state-of-the-art data efficient segmentation model. This approach enables rapid, automated carbide quantification for alloy design and generalizes to other steel types, demonstrating the potential of data-efficient deep learning in reactor-pressure-vessel steel analysis.
Read the full abstract

All authors Alinda Ezgi Gerçek, Till Korten, Paul Chekhonin, Maleeha Hassan, Peter Steinbach

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

Theoretical study of orbital torque: Dependence on ferromagnet species and nonmagnetic layer thickness

Daegeun Jo and Peter M. Oppeneer

The manipulation of magnetization in ferromagnetic metals (FMs) through orbital torque (OT) has emerged as a promising route for energy-efficient magnetic devices without relying on heavy metals. While Ti and Cu are among the most extensively studied light nonmagnetic metals (NMs) for OT devices, theoretical calculations of the resulting torque have remained limited. Here, we present a systematic and quantitative theoretical study of current-induced torques in Ti/FM and Cu/FM (FM = Co, Ni) bilayers using realistic tight-binding models derived from ab initio electronic structures. We find that the torque in Ti/FM is larger for Ni than for Co, but this trend does not necessarily hold in Cu/FM, revealing that the FM dependence of OT is not universal but varies with the orbital current source. Moreover, the dependence of OT on NM thickness clearly indicates its NM bulk origin in both Ti- and Cu-based systems. Notwithstanding, the quantitative characteristics of OT cannot be explained by a simplified picture based on the individual bulk properties of the NM or FM layers. These results provide microscopic insight and practical guidance for designing light-metal-based orbitronic devices.
Read the full abstract

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

ARPES signatures of trions in van der Waals materials

Giuseppe Meneghini, Maja Löwe, Raul Perea-Causin et al. (+5 more)

Angle-resolved photoemission spectroscopy (ARPES) has recently emerged as a direct probe of excitonic correlations in two-dimensional semiconductors, resolving their dispersion and dynamics in energy-momentum space, including dark exciton states inaccessible to optical techniques. However, the ARPES fingerprint of charged excitons (trions), which plays a key role in all doped and gated 2D material systems, has remained unknown so far. We present a first theoretical analysis of trion signatures in monolayer transition-metal dichalcogenides, highlighting how the additional charge carrier modifies the spectral position and shape relative to neutral excitons in ARPES spectra. Interestingly, we further predict that mass-imbalanced trions yield a characteristic double-peak structure, clearly separated in energy and line shape from neutral excitons. The predicted temperature dependence of these features offers guidance for experimental investigations aimed at identifying trionic states, thereby establishing a framework for ARPES studies of many-body Coulomb complexes in doped two-dimensional semiconductors.
Read the full abstract

All authors Giuseppe Meneghini, Maja Löwe, Raul Perea-Causin, Jan Philipp Bange, Wiebke Bennecke, Marcel Reutzel, Stefan Mathias, Ermin Malic

Materials Science

Metavalent Bonding-Induced Phonon Hardening and Giant Anharmonicity in BeO

Xuejie Li, Yuzhou Hao, Yujie Liu et al. (+6 more)

The search for materials with intrinsically low thermal conductivity ($\kappa_L$) is critical for energy applications, yet conventional descriptors often fail to capture the complex interplay between bonding and lattice dynamics. Here, first-principles calculations are used to contrast the thermal transport in covalent zincblende (zb) and metavalent rocksalt (rs) BeO. We find that the metavalent bonding in rs-BeO enhances lattice anharmonicity, activating multi-phonon scattering channels and suppressing phonon transport. This results in an ultralow $\kappa_L$ of 24 W m$^{-1}$ K$^{-1}$ at 300 K, starkly contrasting with the zb phase (357 W m$^{-1}$ K$^{-1}$). Accurately modeling such strongly anharmonic systems requires explicit inclusion of temperature-dependent phonon renormalization and four-phonon scattering. These contributions, negligible in zb-BeO, are essential for high-precision calculations of the severely suppressed $\kappa_L$ in rs-BeO. Finally, we identify three key indicators to guide the discovery of metavalently bonded, incipient-metallic materials: (i) an NaCl-type crystal structure, (ii) large Grüneisen parameters ($\textgreater$2), and (iii) a breakdown of the Lyddane-Sachs-Teller relation. These findings provide microscopic insight into thermal transport suppression by metavalent bonding and offer a predictive framework for identifying promising thermoelectrics and phase-change materials.
Read the full abstract

All authors Xuejie Li, Yuzhou Hao, Yujie Liu, Shengying Yue, Xiaolong Yang, Turab Lookman, Xiangdong Ding, Jun Sun, Zhibin Gao

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

Multi-wavelength transparent microfluidics for UV-visible spectroscopy and X-ray scattering studies of photoactive systems

Benedetta Marmiroli, Sumea Klokic, Barbara Sartori et al. (+3 more)

Microfluidic devices are increasingly used in synchrotron-based experiments to deliver and probe liquid samples, offering advantages such as minimal sample consumption and reduced radiation damage. Despite their growing use, few devices have been specifically designed for monitoring liquids under photoexcitation, a promising approach for fast structural transitions. Here, a microfluidic device that is transparent to X-rays in one direction, and simulaneously transmits UV and visible light in the perpendicular direction is presented. The device is fabricated using lamination and UV lithography on a dry-film resist, eliminating the need for cleanroom facilities and simplifying production. Its multi-wavelength transparency was validated through UV-visible spectroscopy, where photoexcitation at different wavelengths induced reversible trans-to-cis isomerization of azobenzene and fluoro-azobenzene. X-ray transparency was validated through Small Angle X-ray Scattering (SAXS) measurements on hemoglobin and CO-ligated hemoglobin sensitive to quaternary structural changes. These resusts confirm the suitability of the device for resolving protein structures and photoinduced conformational dynamics. The design further supports, as some proof of concept results show, temperature-jump and time resolved pump-probe experiments, providing a versatile platform for studying structural evolution in liquid samples using synchrotron SAXS.
Read the full abstract

All authors Benedetta Marmiroli, Sumea Klokic, Barbara Sartori, Marie Reissenbuechel, Alessio Turchet, Heinz Amenitsch

Materials Science · Cross-listed from cs.LG

Toward Multi-Fidelity Machine Learning Force Field for Cathode Materials

Guangyi Dong and Zhihui Wang

Machine learning force fields (MLFFs), which employ neural networks to map atomic structures to system energies, effectively combine the high accuracy of first-principles calculation with the computational efficiency of empirical force fields. They are widely used in computational materials simulations. However, the development and application of MLFFs for lithium-ion battery cathode materials remain relatively limited. This is primarily due to the complex electronic structure characteristics of cathode materials and the resulting scarcity of high-quality computational datasets available for force field training. In this work, we develop a multi-fidelity machine learning force field framework to enhance the data efficiency of computational results, which can simultaneously utilize both low-fidelity non-magnetic and high-fidelity magnetic computational datasets of cathode materials for training. Tests conducted on the lithium manganese iron phosphate (LMFP) cathode material system demonstrate the effectiveness of this multi-fidelity approach. This work helps to achieve high-accuracy MLFF training for cathode materials at a lower training dataset cost, and offers new perspectives for applying MLFFs to computational simulations of cathode materials.
Read the full abstract

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

Fokker-Planck approach to thermal fluctuations in antiferromagnetic systems

E. Martello, G. A. Falci, E. Paladino et al. (+1 more)

We develop a Fokker-Planck approach to describe the dynamics of staggered magnetization and thermal fluctuations in a two-dimensional antiferromagnetic system with uniaxial anisotropy. Beginning with a classical model for the antiferromagnetic system, we incorporate a Landau-Lifshitz-Gilbert equation augmented by Langevin fields to account for thermal fluctuations, and we derive the Fokker-Planck equation governing the probability distribution function of the spin configuration. Employing the mean-field approximation, we derive the equations of motion for the spin polarization and the two-time spin-spin correlation functions. The methodology is applied to the study of spin-wave dynamics and to the formulation of a phenomenological model for resistance fluctuations in two-dimensional antiferromagnetic semiconductors.
Read the full abstract

All authors E. Martello, G. A. Falci, E. Paladino, F. M. D. Pellegrino

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

Orbital Accumulation Induced by Chiral Phonons

Tetsuya Sato, Takeo Kato and Aurelien Manchon

We theoretically investigate orbital accumulation driven by chiral phonons via orbital-dependent electron-lattice coupling. We derive a formula for the orbital accumulation induced by classical lattice dynamics or nonequilibrium phonons, emphasizing the rectified second-order response of the orbital moment to lattice displacement. We show that chiral phonons primarily couple to orbital quadrupole moments and that static orbital dipole accumulation can be generated at second order in the lattice displacement. Our study provides a useful method for generating orbital accumulation without using spin-orbit interactions and suggests a strategy to boost its magnitude by harnessing band structure hot spots associated with orbital degeneracy.
Read the full abstract

Materials Science

Electronic and magnetic properties of light rare-earth cubic Laves compounds derived from XMCD experiments

Vilde G. S. Lunde, Benedicte S. Ofstad, Øystein S. Fjellvåg et al. (+4 more)

This work presents electronic and magnetic properties of selected members in the cubic Laves phase series Nd1-xPrxCoNi and Ce0.25Pr0.75CoNi, together with the corresponding binary compositions (NdCo2, NdNi2, PrCo2, PrNi2, CeCo2, CeNi2), using soft x-ray absorption spectroscopy, x-ray magnetic circular dichroism (XMCD), density-functional theory, and crystal field multiplet calculations. All transition-metal moments saturate below 1 T, while the rare-earth moments do not saturate even at 5 T, consistent with van Vleck paramagnetic contributions and crystal field suppression. While the sum rules are widely used to extract element-specific magnetic moments from XMCD, we show that for 3d transition metals, their application requires accurate estimates of the number of unoccupied 3d states. We observe a finite magnetic moment on Ni, challenging the common assumption of its nonmagnetic character in Laves phases. The orbital magnetic moments were determined using the spin rules, while the spin moments were estimated from single-ion values from multiplet calculations, due to the invalidity of the spin sum rule for light rare-earth elements. The magnetic moments of Nd and Pr are found to be suppressed relative to their free-ion values, with multiplet theory indicating that this is due to crystal field effects. Our results confirm that Nd and Pr maintain localized 4f3 and 4f2 configurations, respectively, and that their element-specific magnetic moments are robust to rare-earth substitution. Ce, on the other hand, exhibits a tunable mixed-valent ground state with both magnetic 4f1 and nonmagnetic 4f0 components. The relative fraction of these states varies with the electronegativity of the surrounding 3d transition metals, revealing a pathway to tune Ce magnetism via composition. This work establishes a framework for accurately interpreting XMCD in light rare-earth-based intermetallics.
Read the full abstract

All authors Vilde G. S. Lunde, Benedicte S. Ofstad, Øystein S. Fjellvåg, Philippe Ohresser, Anja O. Sjåstad, Bjørn C. Hauback, Christoph Frommen

Materials Science

Potential-Barrier Affinity Effect in Solid Systems

Qiang Xu, Zhao Liu and Yanming Ma

Electron accumulation in interatomic regions is a fundamental quantum phenomenon dictating chemical bonding and material properties, yet its origin remains elusive across disciplines. Here, we report a quantum accumulation effect – potential-barrier affinity (PBA) – revealed by solving the Schrödinger equation for a crystalline potential. PBA effect drives significant interatomic electron accumulation when electron energy exceeds the barrier maximum. This effect essentially enhances interatomic electron density, governing microstructures and properties of condensed matter. Our theory overturns the traditional wisdom that the interstitial electron localization in electride requires potential-well constraints or hybrid orbitals, and it serves as the fundamental mechanism underlying the formation of conventional solid bonding. This work delivers a paradigm shift in understanding electron distribution and establishes a theoretical foundation for the microscopic design of material properties.
Read the full abstract

Materials Science

Tunable electronic band structure in WSSe van der Waals Alloys

Meryem Bouaziz, Leonard Schue, Noeliarinala Felana Andriambelaza et al. (+12 more)

The electronic structure of semiconducting 2D materials such as transition metal dichalcogenides (TMDs) is known to be tunable by its environment, from simple external fields applied with electrical contacts up to complex van der Waals heterostructure assemblies. However, conventional alloying from reference binary TMD compounds to composition-controlled ternary alloys also offers unexplored opportunities. In this work, we use nano-angle resolved photoemission spectroscopy (nano-ARPES) and density functional theory (DFT) calculations to study the structural and electronic properties of different alloy compositions of bulk WS2(1-x)Se2x. Our results demonstrate the continuous variation of the band structure and the progressive evolution of the valence band splitting at the K points from 420 to 520 meV in bulk WS2(1-x)Se2x. We also carried out scanning tunneling microscopy (STM) measurements and DFT to understand the possible S or Se substitutions variants in WS2(1-x)Se2x alloys, with different local atomic configurations. Our work opens up perspectives for the fine control of the band dispersion in van der Waals materials and demonstrate how the band structure can be tuned in bulk TMDs. The collected information can serve as a reference for future applications.
Read the full abstract

All authors Meryem Bouaziz, Leonard Schue, Noeliarinala Felana Andriambelaza, Natalia Alyabyeva, Jean-Christophe Girard, Pavel Dudin, Fabian Cadiz, Jose Avila, Yannick Dappe, Cesar Gonzalez, Julien Chaste, Fabrice Oehler, Christine Giorgetti, Fausto Sirotti, Abdelkarim Ouerghi

Materials Science · Cross-listed from physics.optics

Perovskite Nanocrystals as Emerging Single-Photon Emitters: Progress, Challenges, and Opportunities

Jehyeok Ryu, Victor Krivenkov, Adam Olejniczak et al. (+2 more)

Metal-halide perovskite nanocrystals (PNCs) have emerged as leading candidates for next-generation quantum emitters, offering a unique combination of high photoluminescence quantum yield, tunable emission, short radiative lifetimes, and record-high single-photon purity under ambient conditions. These properties, together with low-cost and scalable solution-phase fabrication, position PNCs as attractive alternatives to traditional epitaxial and colloidal quantum dots. In this Review, we outline the physical parameters that define quantum emission in PNCs, compare their performance to other established and emerging quantum emitters, and assess the key figures of merit, including photostability, single-photon purity, and photon indistinguishability, required for practical quantum applications. We discuss underlying mechanisms affecting PNC emission behavior and highlight recent advances in improving their quantum emitting properties through synthetic and photonic engineering approaches. While challenges related to environmental stability and photon indistinguishability remain, emerging strategies, such as surface passivation, metal ion doping, and coupling with electromagnetic nano- and micro-cavities, are steadily closing the gap between PNCs and ideal quantum light sources.
Read the full abstract

All authors Jehyeok Ryu, Victor Krivenkov, Adam Olejniczak, Alexey Y. Nikitin, Yury Rakovich