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Physics Condensed Matter Materials Science

cond-mat.mtrl-sci Watch Materials Science

Tuesday 16 June

Materials Science

Influence of Ultramicroporosity and Surface Chemistry on Dynamic CO2 Capture in Activated Carbons

S. Gooijer, P. Goosen, C. G. Díaz-Maroto et al. (+4 more)

Activated carbons are promising adsorbents for post-combustion CO2 capture due to their high surface area, tunable microporosity, and resistance to moisture and flue-gas impurities. Despite extensive equilibrium adsorption studies, the dynamic behavior of activated carbons under fixed-bed operating conditions relevant to post-combustion CO2/N2 remains insufficiently understood, particularly for renewable materials. In this work, the adsorption and separation behavior of CO2/N2 mixtures on a commercial coal-derived activated carbon (WS-480) and a biomass-based activated carbon (MSP700-A900CO2) is comparatively evaluated by combining experimental measurements and simulations. We examine the physicochemical properties of both materials, revealing that although WS-480 exhibits a higher of porosity, MSP700-A900CO2 contains a larger fraction of ultramicropores (<0.7 nm) and a broader distribution of oxygen-containing functional groups. These characteristics result in higher CO2 adsorption capacities for MSP700-A900CO2 in fixed-bed breakthrough experiments conducted under varying flow rates, temperatures and CO2 concentrations. We employ atomistic activated carbon models, augmented with surface functional groups as representations of WS-480 and MSP700-A900CO2, achieving close agreement with experimental adsorption data. The validated models are subsequently used to predict CO2/N2 separation under equilibrium and dynamic conditions, reproducing the experimental breakthrough behavior while providing molecular-level insight into the influence of pore structure and surface chemistry on adsorption performance.
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All authors S. Gooijer, P. Goosen, C. G. Díaz-Maroto, I. Moreno, S. Calero, J. Fermoso, J. M. Vicent-Luna

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

Robust Signatures of Fragile Topology in Nonmagnetic Materials

Viktor Könye, Ihor Nimyi, Oleg Janson et al. (+3 more)

Some topological phases of matter are called fragile. They can be trivialized by adding additional valence bands and do not generically host protected gapless boundary states. Here we establish a fragile topological index with a bulk signature: it guarantees the presence of gap closing points in the bulk band structure of systems with both time-reversal and twofold rotation symmetry. This result extends the established use of the Euler class in diagnosing the presence of Dirac cones for general two-dimensional systems with a combination of time-reversal and twofold rotation symmetry, to the case of nonmagnetic materials obeying both symmetries individually. The abundance of natural nonmagnetic materials with these symmetries renders the topological invariant practically useful, despite its fragility. We demonstrate this by applying first-principles calculations to five materials and finding that all of them host Dirac points identified by the invariant, suggesting its widespread applicability. Our results thus provide a robust spectroscopic signature of fragile topology in nonmagnetic systems which can be directly accessed in experiments on practically relevant materials. Furthermore, they enable an alternate method for finding Dirac cones in ab-initio simulations, and may be used as a route towards identifying materials with nonlinear transport properties.
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All authors Viktor Könye, Ihor Nimyi, Oleg Janson, Jeroen van den Brink, Jasper van Wezel, Cosma Fulga

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

The bixbyite framework as a platform for frustrated noncollinear magnetism: resolving the magnetic ground state of $\beta$-Fe$_2$O$_3$

Chenjun Tang, Ondřej Malina, Jiři Tuček et al. (+3 more)

Magnetic behavior across Fe$_2$O$_3$ polymorphs varies widely despite identical chemistry, highlighting crystal architecture as a key determinant of exchange topology, magnetic anisotropy, and ultimately magnetic order. Here, using neutron and synchrotron X-ray diffraction, we establish the magnetic ground state of the poorly understood bixbyite $\beta$-Fe$_2$O$_3$ polymorph and uncover the structural origin of its strong frustration. Below the Néel temperature, a noncollinear antiferromagnetic state emerges through activation of the $mH_1^{+}$ irrep at the H-point [$\mathbf{k}=(1,1,1)$] and the antitranslation $(1'|\tfrac{1}{2},\tfrac{1}{2},\tfrac{1}{2})$, breaking the body centering and yielding two interpenetrating primitive cubic magnetic subcells with inverted moments and nonpolar type-IV symmetry. Under exclusively antiferromagnetic Fe$^{3+}$-O-Fe$^{3+}$ interactions, $\beta$-Fe$_2$O$_3$ exhibits a large frustration index ($f \approx 7.56$). This behavior originates from the intrinsic geometry of the bixbyite lattice: two magnetic sublattices with distinct point symmetries and anisotropy constraints are embedded in a three-dimensional exchange network containing interconnected triangular and hexagonal motifs. In $\{111\}$ planes, Fe2 ions form hexagonal rings interconnected by frustrated triangular units, while locally Ising-like Fe1 ions occupy the ring centers. Our results thus identify the bixbyite architecture as a promising general platform for frustrated noncollinear magnetism. Extending this structural framework to other magnetic transition-metal or 4$f$ ions opens a materials space for engineering competing exchange interactions and anisotropies, potentially stabilizing new noncollinear and field-tunable magnetic states.
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All authors Chenjun Tang, Ondřej Malina, Jiři Tuček, Francois Fauth, Marti Gich, Jose Luis Garcia-Muñoz

Materials Science

Bridging the continuum and the kinetic-Boltzmann theories of heat flow through generalized Knudsen numbers

Nikhil Malviya and Navaneetha K. Ravichandran

Heat conduction in semiconductor crystals is fundamentally governed by the linearized Peierls-Boltzmann equation (LPBE) for phonon transport, that arises out of a kinetic theory for phonon quasiparticles. Yet, continuum theories such as the Fourier's heat diffusion, weakly quasiballistic and hydrodynamic heat equations are often used to explain the experimental observations of heat flow in these materials. Here, we show that a systematic reduction of the LPBE into such equivalent continuum descriptions are possible only for the limiting values of a set of generalized Knudsen numbers. We further show that all of these continuum heat flow regimes, along with the ballistic heat flow, can be described by a single continuum equation for the temperature field that originates from the eigenmode analysis of the LPBE, thus offering a unified picture of all possible heat flow regimes in semiconducting crystals. Using quantitative examples on twenty three technologically important semiconductors, we show that several previously-unidentified features of the non-Fourier heat flow regimes emerge from this generalized Knudsen number framework such as (1) the mutual exclusivity of the weakly quasiballistic and the hydrodynamic heat flow regimes, (2) length-dependent velocity of the hydrodynamic second sound temperature wave and a characteristic heating length for the strongest hydrodynamic second sound, (3) characteristic frequency-domain temperature response distinguishing the hydrodynamic second sound from the ballistic heat flow regime and, (4) a new non-oscillatory signature of transient hydrodynamic heat flow. Our work formally bridges the continuum and the particulate descriptions of heat flow, and provides insights into the important signatures of temperature dynamics in each of these heat flow regimes, that will aid in their unambiguous experimental observations in the future.
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Materials Science · Cross-listed from math-ph

When Volumetric Growth Selects Surface Growth

Rohn Abeyaratne, Roberto Paroni and Marco Picchi Scardaoni

We investigate the relationship between volumetric and surface growth within a recently proposed optimization-driven framework for linearly elastic solids. In this approach, growth is not prescribed through an evolution law; instead, the growth distribution is determined as the solution of a constrained optimization problem. Focusing on processes driven by the minimization of the work performed by external loads in one-dimensional and axisymmetric settings, we derive explicit analytical solutions for the resulting growth distributions. Although growth is initially formulated as a volumetric process through a distributed growth strain tensor, we show that the optimal growth distributions are singular and concentrate on boundaries or internal interfaces. These results provide a variational mechanism through which, under certain conditions, surface growth is selected as the optimal realization of volumetric growth.
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Materials Science · Cross-listed from cond-mat.supr-con

AC-flux-driven SQUID diode spectroscopy as a probe of current-phase relations

Yuriy Yerin, Iman Askerzade, Alexey Fedorchenko et al. (+2 more)

The current-phase relation (CPR) of a Josephson junction encodes microscopic information on superconducting states through higher-order and fractional harmonics. However, their unambiguous extraction is challenging, as different CPR components produce nearly identical static interference patterns that are further obscured by device asymmetries, damping, and dynamical effects. Here, we propose probing individual CPR harmonics via the ac magnetic-flux-driven diode effect in asymmetric dc SQUIDs with unequal junction critical currents. Using two complementary reductions of the fast-driven dynamics – a Kapitza-type perturbation theory for the conventional junction and a Jacobi–Anger averaging for a general CPR – we show that ac flux modulation dresses each harmonic with a distinct Bessel function, yielding characteristic signatures in the diode efficiency $\eta(\phi_{\rm ac},\omega)$ as a function of ac flux amplitude $\phi_{\rm ac}$ and frequency $\omega$. We verify and extend these predictions by numerical solutions of the coupled dynamical equations for CPRs containing $\sin\varphi$, $\sin(\varphi/2)$, and $\sin 2\varphi$ terms ($\varphi$: superconducting phase difference), and construct phase diagrams of $\eta(\phi_{\rm ac},\omega)$. Distinct CPR components are revealed to produce characteristic weak, sparse, dense, or intermodulated arc patterns that remain robust in both overdamped and underdamped regimes. This suggests ac-flux-driven SQUID diode spectroscopy as a probe of current-phase relations in topological materials, multiband systems, and other unconventional superconductors.
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All authors Yuriy Yerin, Iman Askerzade, Alexey Fedorchenko, Ali Gencer, Oleksandr Dobrovolskiy

Materials Science

Surface Induced Magnetism of CdSe Quantum Dots: A DFT Study

G. Kurian, D. Subedi, A. Aniagboso et al. (+1 more)

Surface induced magnetism of quantum dots is not well understood and has been a subject of considerable controversy because of the complexity of surface chemistry of quantum dot facets coupled with the many degrees of freedom inherently involved in magnetism. We performed spin-polarized colinear density functional theory calculations to study charge and spin densities to determine surface reconstructions in bare as well as passivated quantum dots in controlled way. We find that tricoordinated surface atoms relax contributing no dangling bonds and bi-coordinated atoms dimerize, reducing the population of the dangling bonds affecting the induced magnetism. As a result, bicoordinated rather than tricoordinated surface atoms are responsible for spin polarized surface states. In light of recent advanced experimental tools, we predict dangling bonds that remain, despite passivation, on low index facets with bicoordinated atoms could result in tunable surface magnetism. Our results also shed light on the contradicting experimental results in the literature.
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All authors G. Kurian, D. Subedi, A. Aniagboso, M. D. Mochena

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

Probing La-based nickelates with Ni 1$s$ core-level photoelectron spectroscopy

Daisuke Takegami, Naoki Ito, Koto Fujinuma et al. (+15 more)

We present a comparative Ni core level photoemission study of La$_3$Ni$_2$O$_7$, Nd$_3$Ni$_2$O$_7$, and LaNiO$_3$ using both the Ni $2p$ and the Ni $1s$. We address the challenges in analyzing the widely investigated Ni $2p$ spectra arising from the substantial overlap in energy of the Ni $2p$ with the La $3d$. We show that on the other hand the deep Ni $1s$ core level does provide a clean view on the intrinsic electronic excitations and we highlight its potential to resolve detailed differences in the electronic structure within the strongly correlated Ruddlesden-Popper series La$_{n+1}$Ni$_n$O$_{3n+1}$.
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All authors Daisuke Takegami, Naoki Ito, Koto Fujinuma, Masato Yoshimura, Grace A. Pan, Dan Ferenc Segedin, Qi Song, Hanjong Paik, Charles M. Brooks, Hanjie Guo, Alexander C. Komarek, Takanori Taniguchi, Masaki Fujita, Julia A. Mundy, Takashi Mizokawa, Liu Hao Tjeng, Berit H. Goodge, Atsushi Hariki

Materials Science

Ground-state properties of the $S=3/2$ anisotropic triangular lattice antiferromagnet Na$_3$Cr(PO$_4$)$_2$

A. Magar, Sebin J. Sebastian, Q.-P. Ding et al. (+4 more)

We report the crystal structure and magnetic properties of a $S=3/2$ anisotropic triangular lattice compound Na$_3$Cr(PO$_4$)$_2$ employing single-crystal and powder x-ray diffraction, magnetization, heat capacity, and $^{31}$P nuclear magnetic resonance (NMR) experiments, supported by the band structure calculations. Magnetic susceptibility exhibits a broad maximum around 3.5 K, indicating the presence of a short-range antiferromagnetic order, typical of a low-dimensional spin system. Magnetization and heat capacity manifest an antiferromagnetic long-range ordering at around $T_{\rm N} \simeq 2.6$ K. This was further confirmed by the drastic NMR line broadening and a peak in the nuclear spin-lattice and spin-spin relaxation rates. The isothermal magnetization data exhibit a field-induced spin-flop transition at around $\mu_0H_{\rm SF} \simeq 1.7$ T reminiscent of an anisotropic two-dimensional magnet, before saturating above $\mu_0H_{\rm sat} \simeq 4.5$ T. The saturation field was further upheld by the field-dependent NMR relaxation measurements at low temperatures. The $^{31}$P NMR spectral shape confirms the commensurate antiferromagnetic nature of the ordering below $T_{\rm N}$. Ab initio calculations reveal a significant deformation of the triangular spin lattice, resulting in triangles with two antiferromagnetic couplings of similar strength and a much weaker coupling along the third side of the triangle.
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All authors A. Magar, Sebin J. Sebastian, Q.-P. Ding, Y. Skourski, A. A. Tsirlin, Y. Furukawa, R. Nath

Materials Science

Hybrid Electronic-Ionic Ferroelectricity in Superlubric van der Waals Heterostructures

Jing Huang, Jun Kang and Daniel Bennett

One strategy to lower the switching barrier in a sliding ferroelectric (sFE) is to insert an incommensurate spacer to reduce sliding friction, creating a superlubric sliding ferroelectric (SL-sFE). However, how polarization survives across the effectively decoupled outer layers remains an open question. We show that SL-sFEs are fundamentally different from conventional sFEs: polarization is not driven by sliding alone, but by an intricate coupling between interlayer sliding and the out-of-plane buckling of the spacer layer. This coupling results in a unique hybrid electronic-ionic polarization arising from asymmetric orbital hybridization. The interplay of these order parameters generates several distinct types of ferroelectric hysteresis, including mixed first- and second-order transitions, multi-step switching, and antiferroelectric-like behavior, establishing SL-sFEs as a distinct class of ferroelectrics.
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Materials Science · Cross-listed from cond-mat.supr-con

Distinguishing Majorana zero modes from trivial defect states in an iron-based superconductor

Dongfei Wang, Jon Ortuzar, Freek Massee et al. (+5 more)

Majorana zero modes, which obey non-Abelian exchange statistics, are promising candidates for topological quantum computation due to their robustness against environmental perturbations. The iron-based superconductor Fe(Te,Se) has been identified as an intrinsic topological superconductor, possibly hosting Majorana zero modes. In this paper, we report the observation of near-zero-energy localized states at multiple structural defects on the Fe(Te,Se) surface, which could be misidentified as Majorana zero modes without additional verification. By using spin-polarized scanning tunneling spectroscopy, we demonstrate that the near-zero-energy localized states on step edges and line defects originate from topologically trivial Yu-Shiba-Rusinov states. In addition, zero-energy bound states are also observed for regions without surface defects. A combined spatial and magnetic field dependent analysis of the spin-resolved tunneling spectra in these regions reveals that this type of zero-energy states cannot be attributed to the presence of Majorana bound states. These findings emphasize the importance of spin-dependent studies of low-energy states for pursuing Majorana zero modes.
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All authors Dongfei Wang, Jon Ortuzar, Freek Massee, Ruidan Zhong, Genda Gu, Wende Xiao, Yugui Yao, Roland Wiesendanger

Materials Science

Lifetime Sample Tracking (LiST): A Data Platform for Materials Science

Anthony Richardella, Isaiah A Moses, Konrad Hilse et al. (+9 more)

The 2D Crystal Consortium Materials Innovation Platform (2DCC-MIP) is an NSF supported national user facility focused on advancing the synthesis of 2D materials, monolayers, surfaces, and interfaces. The need for the facility to organize and share data with users led to the development of an internal data management and analysis engine, the Lifetime Sample Tracking platform (LiST). This infrastructure allows the automated capture, curation, analysis and dissemination of data ranging from experimental materials synthesis parameters and characterization, to theoretical first-principles and ReaxFF molecular dynamics modeling1. The system currently hosts synthesis and property data (accessible via a REST API) on approximately twenty thousand samples produced by the 2DCC grown using a variety of techniques from bulk crystal growth to metal-organic chemical vapor deposition (MOCVD) and molecular beam epitaxy (MBE), among others. Data used in publications can easily be grouped by the system into data packages that are given digital object identifiers (DOIs) for inclusion with each publication. The LiST platform is now being used by groups outside of the 2DCC as a solution for data curation in materials science. Data management tools such as LiST support the materials development process by allowing a closed loop iteration between synthesis, characterization, theory, and targeted materials design. This also enables machine learning (ML) research, artificial intelligence (AI) analysis, and the potential for autonomous synthesis in the future.
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All authors Anthony Richardella, Isaiah A Moses, Konrad Hilse, Frank Santaguida, Kevin Dressler, Ric Wilburn, Saiyyam Kochar, Wesley F. Reinhart, Adri C. T. van Duin, Nitin Samarth, Vincent H. Crespi, Joan M. Redwing

Materials Science · Cross-listed from cs.LG

Toward Controllable Catalyst Inverse Design via Large-Scale Autoregressive Pretraining

Dong Hyeon Mok, Jonggeol Na and Seoin Back

Inverse design of heterogeneous catalysts remains challenging because catalyst surfaces exhibit substantial structural complexity with coupled surface-adsorbate interactions across a vast chemical space that is difficult to explore efficiently through conventional screening alone. Although machine learning-based high-throughput screening has accelerated catalyst discovery, its efficiency inevitably declines as the search space grows, motivating the development of generative models that can directly construct catalysts with target properties. Here, we present a conditional catalyst generative model based on the Generative Pretrained Transformer architecture with a numerical embedding layer that enables the generation of catalyst structures conditioned on both categorical and continuous properties within a single autoregressive framework. The model was pretrained on 133 million catalyst structures and subsequently fine-tuned on approximately 460,000 optimized structures with associated categorical properties and binding energies for conditional generation. The resulting model achieved 98% structural validity, 95% optimization validity, and high categorical condition fidelity, with a 93 % joint match rate for adsorbate type and composition. For binding energy conditioning, the match rate of approximately 20% represents a four-fold improvement over the baseline training distribution, and the generated distributions shift systematically toward the target values, enabling a 1.5 to 4-fold improvement in screening efficiency for reaction-targeted catalyst discovery without additional fine-tuning. These results show that large-scale autoregressive pre-training, combined with explicit property conditioning, provides a practical route toward controllable catalyst generation and accelerated catalysts discovery.
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Materials Science

Coexistence of Donor and Acceptor Hydrogen States in n-Type InN

Masaki Kobayashi, Yudai Yamashita, Kazuyuki Hirama et al. (+1 more)

Hydrogen often exhibits amphoteric behavior in semiconductors, but its role is in n-type InN remains unresolved. Wurtzite InN is a narrow-gap semiconductor with high electron mobility and is therefore attractive for high-speed electronics and optoelectronic applications. Here we use hard x-ray photoemission spectroscopy (HAXPES) to probe hydrogen-related electronic structure in as-grown and post-annealed InN thin films prepared at different grown temperatures. Post annealing, which reduces the concentration of hydrogen impurities in the films, shifts the core-level spectra toward lower binding energy, consistent with a chemical-potential shift associated with the passivation of electron carriers. In the valence-band spectra, an acceptor-like in-gap feature near the valence-band maximum is suppressed after annealing. Together with the established donor-like behavior of hydrogen in InN, these results suggest that acceptor H- states coexist with donor H+ states in InN. The coexistence of these opposite hydrogen charge states provides a microscopic picture of hydrogen-driven compensation in InN and highlights the amphoteric nature of hydrogen even in a highly n-type semiconductor.
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All authors Masaki Kobayashi, Yudai Yamashita, Kazuyuki Hirama, Yoshitaka Taniyasu

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

Dispersive mode coupling in $p$-doped semiconductor nanomechanical resonators

Ankang Liu, Mahmoud T. Elewa and Mark I. Dykman

Dispersive coupling between vibrational modes with different frequencies is a major nonlinear dynamical effect. We show that in $p$-doped semiconductors such coupling is strongly enhanced. Moreover, the coupling parameters increase with the order of the nonlinearity. The doping-induced dispersive coupling becomes much stronger than the intrinsic one already for moderately strong doping. Its dependence on the hole density is nonmonotonic, and the temperature dependence becomes nonmonotonic for higher densities. Relevant mesoscopic frequency fluctuations are briefly discussed. The results are applied to Si resonators, where doping is used to compensate the temperature dependence of a clock mode, whereas another low-frequency mode is used as a thermometer to enable temperature stabilization.
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Monday 15 June

Materials Science · Cross-listed from cs.AI

Steering topology distributions for unified generative design of architected metamaterials

Haolin Li, Yuyang Miao, Menglei Li et al. (+9 more)

Architected metamaterials derive their functions from structure, creating vast opportunities to program physical responses through topology design. However, existing design methods are often tailored to individual design problems, making limited use of topology knowledge for effective and broadly applicable design as objectives, constraints, and physical functions change. Here we introduce Generative Topology Optimization (GenTO), a unified framework that turns a learned topology prior into a reusable design engine. GenTO trains a diffusion model on a large full-order topology dataset and then iteratively steers the resulting topology distribution toward task-specific high-performing regions using user-defined physical objectives and constraints. This shifts the object of optimization from a single structure to a task-adapted topology distribution. Across topology design problems spanning thermal extremization, multi-objective morphology control, property-targeted auxetic design, and vibration transmission design, GenTO reuses pretrained topology priors for heterogeneous tasks, preserves structural diversity, and reaches high-performing solutions supported by numerical benchmarks and experimental validation. These results establish reusable topology knowledge as a unified principle for effective and scalable architected metamaterial design.
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All authors Haolin Li, Yuyang Miao, Menglei Li, Jinshuai Bai, Liyuan Wang, Xin Liu, Bo Gao, Jiantao Liu, Danilo Mandic, Zahra Sharif Khodaei, M.H.Aliabadi, Weiqiu Chen

Materials Science

Characterization of ultrathin nickel films deposited by thermal laser evaporation

David S. Catherall, Yifei Yan, Finley B. Donachie et al. (+2 more)

Thermal laser evaporation is a physical vapor deposition technique of increasing interest because of its ability to evaporate essentially any solid element, even the most refractory such as W. However, many films deposited by this method, especially non-epitaxial films, remain to be characterized; further, key system components such as the laser delivery system have not been described in detail. Here, we present the evaporation and characterization of ultrathin Ni films deposited with a home-built thermal laser evaporation system. The system employs a continuous-wave 1 kW fiber laser (1070 nm) focused to sub-millimeter diameter onto a Ni target rod mounted inside an ultrahigh-vacuum chamber. The laser heats the target to a temperature high enough to produce vapor for film deposition; for Ni, this temperature is around the melting point of 1725 K. We report the characterization of the surface roughness, composition, and room-temperature electrical properties of the films along with the design of the major components of our system. This work advances the growing consensus regarding the potential of thermal laser evaporation for thin film deposition and epitaxy and provides the necessary design information to facilitate broader adoption of the technique.
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All authors David S. Catherall, Yifei Yan, Finley B. Donachie, Azmain A. Hossain, Austin J. Minnich

Materials Science

Robust Spin Splitting and Strain-Controlled Optical Response in Monolayer CrC2N4 for Valleytronic and Optoelectronic Applications

Md. Samrat, Vivek Chowdhury, Sake Wang et al. (+1 more)

Monolayer CrC2N4 recently emerged as a promising two-dimensional semiconductor, yet its spin-orbit-coupled (SOC) physics and strain-tunable optical response remained largely unexplored. Here, we investigated the electronic, valley, charge-transfer, and optical properties of pristine and biaxially strained monolayer CrC2N4 using first-principles calculations. The monolayer exhibited a direct band gap at the K/K' valleys. SOC produced valley contrasting out-of-plane spin polarization, yielding a moderate valence band spin splitting of 51.9 meV and a small conduction band spin splitting of 1.7 meV. Orbital-resolved analysis showed that the edge states were mainly governed by Cr-d and N-p hybridization, while Bader analysis indicated polar-covalent bonding through charge transfer toward N atoms. Biaxial strain in the range of -4% to +4% tuned the band gap from 1.987 to 1.421 eV and drove an indirect-to-direct gap transition near -1% strain. Tensile strain enhanced the Berry curvature and red-shifted the optical response toward the visible-near-infrared region. These results suggested monolayer CrC2N4 as a promising platform for strain-engineered valleytronic and optoelectronic device applications.
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All authors Md. Samrat, Vivek Chowdhury, Sake Wang, Ahmed Zubair

Materials Science

Dislocation-templated antiferromagnetic domains in epitaxial NiO

Alexandra Fonseca Montenegro, Justin Michel, Fengyuan Yang et al. (+1 more)

Controlling antiferromagnetic domains is essential for spintronics, yet predictable manipulation remains challenging due to their lack of net magnetization. Here, we utilize scanning electron microscopy electron channeling contrast imaging (ECCI) to observe the formation of nanoscale antiferromagnetic domains in epitaxial NiO/MgO(001) at interface dislocations. Thermal cycling across the Néel temperature reveals that while domain contrast vanishes in the paramagnetic phase, the features re-emerge at identical spatial locations upon cooling. Diffraction-vector-dependent ECCI imaging, governed by a relative tilt contrast model, indicates that the domains stem from localized rhombohedral distortions of volumetric twin-type $T$-domains. These $T$-domains are stabilized by the long-range shear stress field of interface misfit dislocations (MDs). By tracking a film thickness series from 23 to 46~nm, we resolve a transition in oxide relaxation mechanics from primary $60^\circ$ interface MDs along $\langle110\rangle$ to a cross-slipped network of pure edge $90^\circ$ MDs deviated toward $\langle100\rangle$. We demonstrate that ECCI identifies the Burgers vector and line direction of these MDs via strict $\vec{g} \cdot (\vec{b} \times \vec{u})$ invisibility criteria, and an Eshelby interaction energy model accurately predicts the asymmetric nucleation of specific $T$-domains along MD flanks. Quantitative image analysis shows $T$-domain volume fractions track the spatial configuration of the evolving MD networks, providing a framework for defect-engineering antiferromagnetic textures using one-dimensional defects.
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All authors Alexandra Fonseca Montenegro, Justin Michel, Fengyuan Yang, Roberto C. Myers

Materials Science

General Method for Evaluation of Stop-Bands of Periodic Structures with Symmetric Unit Cells

Alexander Hvatov, Mariia Krasikova, Aleksandra Pavliuk et al. (+1 more)

The mirror symmetries of a periodic unit cell are exploited to decompose the standing-wave eigenproblem at the high-symmetry vertices of the Brillouin zone into four independent sub-problems on a quarter-cell, each governed by Neumann (sound-hard) or Dirichlet (sound-soft) boundary conditions. Sorting and pairing the resulting eigenfrequencies by index along each segment of the irreducible Brillouin zone boundary yields an explicit formula for the stop-band intervals without computing the full dispersion diagram. The decomposition is exact, following directly from the representation theory of the little group at each high-symmetry point. It applies to any unit cell whose material distribution is invariant under the mirrors normal to the cell faces. The method is validated on two configurations: a phononic crystal of lead cylinders in an epoxy matrix, analyzed using the plane-wave expansion, and a lattice of coupled C-shaped Helmholtz resonators, analyzed using finite-element analysis. For both systems, the reconstructed stop-band boundaries agree with the full Floquet dispersion calculation to within 1% for the lowest bands, requiring eigenvalue solutions at only three discrete wavevectors. Avoided crossings within a Brillouin zone segment can cause bands to exhibit non-monotone behavior, rendering the pairing rule approximate; the spectral conditions for this are identified. Flat bands common to both boundary-condition types are identified as bound states in the continuum.
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All authors Alexander Hvatov, Mariia Krasikova, Aleksandra Pavliuk, Steffen Marburg

Materials Science

Physics-Informed Attention Mechanism and Generalization Capability of Deep Learning-Based Grain Growth Evolution Prediction

Pungponhavoan Tep and Marc Bernacki

Machine Learning (ML) models for grain growth prediction are typically trained on idealized synthetic data, yet practical applications require generalization to conditions outside the training distribution. This study evaluated the Out-Of-Distribution (OOD) generalization capability of the trained model from our previous study across three test cases, including experimental microstructures, microstructures characterized by a bimodal grain size distribution, and abnormal grain growth. To further probe whether physics-informed architectural design could improve robustness under these different conditions, a boundary-masked attention mechanism was proposed specifically for grain growth, constraining attention to grain boundary pixels. Both the baseline and the proposed physics-informed attention model were evaluated without retraining or fine-tuning on the OOD data. Both models successfully generalized to all three test cases, yet the boundary-masked attention mechanism provided substantial improvements, with the most notable gains for microstructures characterized by a bimodal grain size distribution, where Structural Similarity Index Measure (SSIM) improved from \num{0.6221} to \num{0.7609} and mean grain size ($\overline{R}$) error decreased from \SI{8.75}{\percent} to \SI{3.57}{\percent}. The attention heatmap analysis revealed that the boundary-masked attention model learned to concentrate attention on large grain boundaries in a manner consistent with curvature-driven grain growth physics, emerging from training without being explicitly encoded into the architecture. These results indicate that models trained on synthetic data can generalize to diverse OOD conditions without retraining, and that physics-informed attention may improve accuracy when the boundary morphology matches the training domain.
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Materials Science

Machine learning insights into band gap properties in halide-based perovskites

Chadawan Khamdang and Mengen Wang

Halide perovskites show great promise for applications in optoelectronic devices. The lead-free perovskites are attracting increasing interest due to their low toxicity and motivate the exploration of alternative compositions and structures, including A$_2$BX$_6$, A$_2$BB$^\prime$X$_6$, A$_3$B$_2$X$_9$, and A$_4$BX$_6$. Accurate predictions of a wide range of band gap energies are important for designing new materials. It is also desired to generate a direct relationship between the structural and elemental descriptors and the band gap energies. In this work, we develop machine learning models to predict band gap energies across various types of halide perovskites based on atomic and structural properties. Algorithms including ensemble tree-based methods, random forest regression (RFR), gradient boosted regression trees (GBRT), and extreme gradient boosting (XGB) showed strong predictive accuracy. We also analyzed feature importance to identify key descriptors, including B-site and X-site elemental properties, as well as the number of A- and B-site atoms, as primary factors influencing band gap energies. These results improve our understanding of the ML models and provide guidance for designing new halide perovskite materials.
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Materials Science · Cross-listed from cond-mat.str-el

Exotic magnetism and persistent spin dynamics in a frustrated Jeff = 1/2 triangular lattice antiferromagnet

M. Barman, K. Jaksetič, M. Pregelj et al. (+3 more)

The delicate interplay between competing degrees of freedom, anisotropy, and frustration-induced strong quantum fluctuations in pseudospin-$J_{\rm eff}=1/2$ rare-earth triangular-lattice antiferromagnets offers a promising platform for the experimental realization of exotic states with nontrivial low-energy excitations. Here, we present thermodynamic, inelastic neutron scattering (INS), and muon spin relaxation ($\mu$SR) investigations of the frustrated magnet K$_3$NdTe$_2$O$9$, in which Nd$^{3+}$ ions constitute a structurally perfect triangular lattice with no detectable site disorder. The experiments reveal the realization of a Kramers doublet ground state with $J{\rm eff}=1/2$ moments, well separated from the first excited state, which interact antiferromagnetically with an exchange interaction of $\sim$0.6 K between the Nd$^{3+}$ moments in the triangular plane. The absence of oscillations and the so-called 1/3 plateau in the zero-field $\mu$SR asymmetry down to 50 mK rules out long-range magnetic ordering and spin freezing on the $\mu$SR time scale, respectively. The temperature dependence of the zero-field $\mu$SR relaxation rate is well described by the Orbach relaxation mechanism, indicating the existence of fluctuating moments in the ground state of this frustrated magnet. Our results demonstrate exotic magnetism and persistent spin dynamics down to 50 mK. These observations establish this new family of frustrated rare-earth triangular-lattice antiferromagnets as a promising venue for the experimental realization of nontrivial quantum states with exotic low-energy excitations.
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All authors M. Barman, K. Jaksetič, M. Pregelj, M. D. Le. P. J. Baker, A. Zorko, P. Khuntia

Materials Science

Chiral Phonons Enable Ultrafast Magnetization Switching via Magnetoelastic Coupling

Weiwei He, Muhammad Hamza Asim, Mara Strungaru et al. (+3 more)

Phonons are desirable for current-free energy-efficient spin manipulation and harnessing their chirality to achieve ultrafast magnetization switching remains actively pursued. Here we demonstrate that terahertz-driven chiral phonons enable faster magnetization switching than linear phonons through the purely magnetoelastic coupling that transfers both energy and angular momentum. Only one phonon handedness efficiently transfers angular momentum to the spin system, which we explain by a large fictitious kinematic Barnett-like field at THz frequencies that destabilizes spin precession for the opposite chirality. Considering different regions of the spinwave spectrum, we find that switching conditions can be realized near the {\Gamma}-point where strong energy transfer and spinwave excitation dominate, and near the P-point which offers minimal energy loss. Our results establish phonon chirality as a decisive and previously overlooked parameter in spin-lattice dynamics within the magnetoelastic coupling mechanism, offering a promising avenue for ultrafast low-energy spintronic devices.
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All authors Weiwei He, Muhammad Hamza Asim, Mara Strungaru, Roy Chantrel, Min Yi, Oksana Chubykalo-Fesenko

Materials Science

Evolution of Nonlinear Ion Transport in Nanopore Arrays: Ionic Conductance, Current Rectification, and Osmotic Power

Chih-Yuan Lin and Marija Drndić

Understanding the ionic transport and scaling behaviors in nanopore arrays is essential for bridging fundamental ion physics and blue energy applications. By fabricating sub-3 nm and sub-20 nm diameter nanopore arrays (NPAs) spanning from few pores to N ~ 10000, we systematically investigate ionic conductance, ion current rectification, and osmotic energy conversion. We report the ionic conductance scaling laws and nonlinearity with nanopore number, with stronger deviations from linearity at lower salt concentrations. Experimental evidence reveals that surface-charge-governed conductance and ion current rectification progressively weaken with increasing N and even vanish as the NPA scales up to N ~ 10000, resulting in an underestimation of surface charge density. In a sub-3 nm densely packed array (separation ~ 25 nm), the conductance exhibits an anomalous power-law dependence on concentration, deviating markedly from the single nanopore characteristics, attributed to the strong pore interactions. Furthermore, osmotic power harvesting measurements reveal a substantial reduction in power density upon scaling, with decreases of up to three orders of magnitude over the same range. To elucidate the underlying mechanism, we developed rigorous 3D modeling showing that the nonlinear behavior originates from concentration polarization at pore entrances and suppressed electric field across NPAs, collectively hindering ion transport. Our work provides insight into nonlinear ion-transport scaling and reveals fundamental differences between transport phenomena in single nanopores and nanopore arrays.
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Materials Science · Cross-listed from physics.chem-ph

Hydrogen Chemisorption and Current-Induced Spin Polarization on NbP

Luis Martinez-Gomez and Raphael F. Ribeiro

Topological semimetals have been proposed as electrocatalytic platforms because their surface states can connect adsorbate bonding with interfacial charge and spin responses. Here we investigate hydrogen chemisorption on NbP(001) using density functional theory and Wannier-based analyses of surface spectra, chemical bonding, and current-induced spin polarization. Comparing calculations with and without spin–orbit coupling allows us to examine nodal-line-derived surface states and Weyl Fermi arcs on the same surface. Spin–orbit coupling leaves the adsorption thermodynamics essentially unchanged but reorganizes how hydrogen bonds with the Nb- and P-derived surface orbitals. The characteristic Fermi-arc branches persist after adsorption, with H-derived spectral weight appearing within the same near-Fermi-level surface manifold. Together, these results show that chemisorbed hydrogen participates in the spin-textured surface electronic response. The accompanying adsorbate-local current-induced spin polarization points toward opportunities to connect surface chemistry with electrically controlled spin phenomena in topological semimetals.
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Materials Science · Cross-listed from cond-mat.supr-con

Dynamical Steering and Unambiguous Signature of Majorana Corner Modes in Altermagnetic Josephson Junctions

Yu-Xuan Li and Tao Zhou

Dynamical manipulation of Majorana zero modes and their unambiguous distinction from topologically trivial states remain paramount challenges in topological quantum computation. Here, we propose a phase-biased altermagnetic Josephson junction as a versatile platform for generating and controlling Majorana corner configurations. Moving beyond conventional global parameter tuning that merely toggles the topological phase in situ, our platform utilizes the macroscopic superconducting phase difference and the Néel-vector orientation as independent control knobs to dynamically reshape the boundary mass. This synergistically enables the deterministic spatial relocation of Majorana corner modes (MCMs) among selected corners of a fixed device geometry. Crucially, this spatial reconfiguration yields a definitive experimental fingerprint: a control-correlated conductance switching. As the MCMs are relocated, the quantized zero-bias peak perfectly emerges at the target corner while simultaneously vanishing at the initial one. This macroscopically phase-locked spatial correlation effectively eliminates false positives from trivial Andreev bound states, establishing a control-correlated diagnostic and a promising route toward future Majorana braiding architectures.
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Materials Science

High-entropy Fe$_2$VAl-based thermoelectric modules with improved conversion efficiency

Michael Parzer, Geoffrey Roy, Fabian Garmroudi et al. (+4 more)

Thermoelectric (TE) materials enable the direct conversion of heat into electricity and are attractive for sustainable energy applications. For practical deployment, TE materials must combine high efficiency with low cost, non-toxicity, and scalability. In this work, we optimize the TE performance of low-cost and robust Fe$_2$VAl-based full-Heusler compounds through high-entropy engineering: a synergistic combination of heavy-element doping and controlled off-stoichiometry results in substitutional disorder on all lattice sites, triggering one of the lowest lattice thermal conductivities, $\kappa_\text{L}\sim2.3$ W m$^{-1}$ K$^{-1}$, reported so far for full-Heusler systems. The resulting materials exhibit improved values of the average figure of merit $zT_\text{ave}\approx 0.3$ from $300-500$ K. To demonstrate reproducibility and technological relevance, a full TE module (TEM) based on the optimized alloys was fabricated and characterized. Scaled-up material batches were synthesized by hot pressing, exhibiting TE properties in excellent agreement with laboratory-scale samples, with only slightly increased resistivities in absence of post-annealing treatments. Owing to the excellent mechanical workability of Fe$_2$VAl-based materials, the TEM legs were directly brazed onto copper electrodes, enabling robust module fabrication. A ($6\times 6$)-leg TEM was assembled and systematically characterized. The device exhibits the highest output power and one of the highest conversion efficiencies reported to date for Fe$_2$VAl-based generators over the broad temperature range of $300-673$ K, underscoring the potential of this material system for scalable TE energy harvesting.
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All authors Michael Parzer, Geoffrey Roy, Fabian Garmroudi, Pawel Ziolkowski, Thomas Konegger, Ernst Bauer, Pascal J. Jacques

Materials Science · Cross-listed from math.NA

Phase-field digital image correlation for integrated displacement and damage measurements

Dingxiang Zhu and Ye Lu

This work presents a novel digital image correlation (DIC) framework for full-field measurements of displacement, strain, and damage, based on a phase field (PF) approach. The idea is to take advantage of the ability of the PF method to track complex crack morphologies and to provide a natural way in DIC to perform damage and crack measurements from experimental speckle images, in addition to displacement and strain fields. Moreover, incorporating the damage variable into DIC can improve the displacement accuracy near the crack tip, and can avoid the need of user-defined masks when dealing with cracked samples, which is advantageous when cracks become complex and the manual application of masks becomes challenging. The theoretical formulation of the proposed framework, namely PF-DIC, was presented in detail in the paper, along with a finite element implementation. Numerical examples have demonstrated the capability of the proposed PF-DIC in terms of capturing different types of cracks while providing similar measurement accuracy to that of masked DIC. Additionally, it is shown that the PF-DIC can be easily adapted to selectively identify critical cracks under specific loading conditions or mechanisms for damage assessment and diagnostic purposes. The proposed DIC framework can be used to characterize material defects, support structural health monitoring, and enable a potential unification of PF simulations and experimental fracture measurements
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Materials Science

Data-Driven Micromechanical Characterization and Mapping of Shale Rocks Using High Speed Nanoindentation

Shaziya Ahmed Banu, Xukai Zhang, Samah A. Mahgoub et al. (+4 more)

This study investigates the potential of high-speed nanoindentation in collaboration with data analytics and phase volume fractions to achieve micromechanical characterization of heterogeneous rocks. While micromechanical characterization can be performed using mechanical testing alone, integrating chemical analysis-such as elemental mapping techniques-provides essential phase identification. This enables more accurate interpretation of phase-specific mechanical properties. However, incorporating chemical analysis increases the complexity of the process. Hence, this study proposes data-driven micromechanical characterization and mapping of heterogeneous rocks based primarily on mechanical data and limited dependence on chemical analysis. In this study, Mancos shale rock is analyzed using high-speed nanoindentation to determine the mechanical properties at the microscale. Subsequently, a suite of unsupervised statistical learning techniques, such as Uniform Manifold Approximation and Projection (UMAP) with k-means Clustering, Gaussian Mixture Model (GMM), Dirichlet Process Mixture Model (DPMM), and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), are applied to the nanoindentation data. Additionally, an automated image processing and segmentation technique was developed and tested. The results from each technique have been systematically compared against the conventional chemo-mechanical approach using two metrics: weighted error and spatial error. Based on the results, UMAP with k-means clustering is the most appropriate technique, while DBSCAN, DPMM, and image segmentation techniques are more suitable as secondary approaches. This study demonstrates the capability of high-speed nanoindentation combined with machine learning techniques for micromechanical characterization with reduced analytical complexity and improved workflow efficiency.
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All authors Shaziya Ahmed Banu, Xukai Zhang, Samah A. Mahgoub, Christopher C. Walker, George M. Pharr, Arash Noshadravan, Sara Abedi