Materials Science
SPLIT-PINN: Separable Probability Learning Technique via Physics-Informed Neural Networks for High-Dimensional Probabilistic Modeling
Pouria Behnoudfar, Deekshith Naidu Ponnana, Noah J. Schmelzer et al. (+6 more)
We present a probabilistic modeling framework for incorporating small-scale spatial heterogeneity into macroscopic descriptions of material behavior for polycrystalline metallic materials. Spatially heterogeneous material state fields are represented using probability density functions (PDFs), providing a principled statistical description of microstructural variability and state
evolution across different computational polycrystalline realizations. The framework is built on the inverse identification of a probabilistic transport model, formulated as a Liouville equation with an unknown drift term. To enable accurate, stable, and interpretable inference of this drift field in high-dimensional, transport-dominated settings, we develop a Separable Probability Learning Technique via Physics-Informed Neural Networks (SPLIT-PINN). This method incorporates a marginal-correction drift decomposition, orthogonality constraints, and residual-based adaptive training to enhance well-posedness, numerical stability, and physical consistency without imposing restrictive parametric assumptions. Using SPLIT-PINN, the drift field governing the temporal
evolution of joint state PDFs is inferred directly from data. After
benchmark validation, the framework is applied to physical computational
datasets describing the
evolution of polycrystalline microstructural states, including von Mises stress, dislocation density, and equivalent plastic strain rate. The learned Liouville model, trained on a single
dataset, is subsequently used in forward predictions of the temporal
evolution of joint and marginal PDFs for multiple unseen polycrystal realizations. Quantitative comparisons with reference PDFs demonstrate that the proposed framework yields accurate and robust probabilistic predictions and generalizes effectively across
datasets.
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All authors Pouria Behnoudfar, Deekshith Naidu Ponnana, Noah J. Schmelzer, Janith Wanni, George T. Gray III, Dan J. Thoma, Curt A. Bronkhorst, Nan Chen, Wenxiao Pan
Materials Science
Charge dynamics at nitrogen impurities and nitrogen-vacancy centers in diamond
Chandan Kumar Vishwakarma, J. K. Nangoi, Mark E. Turiansky et al. (+1 more)
The nitrogen-vacancy (NV) center in diamond is the prototype
quantum defect that enables a variety of diamond-based
quantum technologies. However, charge-state instability and spectral
diffusion, often induced by substitutional nitrogen
impurities (N$_{\rm C}$), remain key challenges for device performance. Here, we employ first-principles density functional theory calculations to quantitatively investigate nonradiative carrier capture processes mediated by multiphonon emission at both the NV center and the N$_{\rm C}$
impurity. For relevant cases, we also compute the rates of radiative and thermal emission processes. For N$_{\rm C}^0$ $\to$ N$_{\rm C}^-$, we obtain an electron capture coefficient of $2.2 \times 10^{-8}$ cm$^3$s$^{-1}$ at 300 K. Both the magnitude and temperature dependence are in excellent agreement with experimentally measured capture cross sections. Electron capture at N$_{\rm C}^+$ is even faster, with a capture coefficient of $1.0 \times 10^{-4}$ cm$^3$s$^{-1}$ at 300 K. For the NV center, we find that carrier capture rates involving only the ground states of NV$^0$ and NV$^-$ are negligibly slow. However, capture into the excited states (NV$^{0*}$ and NV$^{-*}$) is significantly faster. In particular, the capture coefficient for the hole capture process NV$^-$ $\to$ NV$^{0*}$ is as large as $1.8 \times 10^{-7}$ cm$^3$s$^{-1}$ and largely temperature-independent. Hole capture at NV$^-$ will thus occur via nonradiative capture into an excited state of NV$^{0}$ followed by fast radiative decay to the NV$^0$ ground state. Similarly, electron capture at NV$^0$ will occur via the NV$^0$ $\to$ NV$^{-*}$ $\to$ NV$^-$ pathway, but with a lower nonradiative capture coefficient ($2.1 \times 10^{-9}$ cm$^3$s$^{-1}$ at 300 K). Our calculated capture coefficients and rates provide essential information for analyzing charge-state dynamics.
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All authors Chandan Kumar Vishwakarma, J. K. Nangoi, Mark E. Turiansky, Chris G. Van de Walle
Materials Science
Proton-electron coupled catalyst for ionomer-free electrochemical energy conversion
Ao Zhang, Ran Wang, Mohammed O. Bazaid et al. (+14 more)
Efficient electrochemical energy devices are vital to renewable energy technology, yet coordinating the effective flow of electrons, ions, and chemical species continues to be a major challenge. In conventional
proton-exchange membrane fuel
cell (PEMFC) catalyst layers,
proton and electron transport are supplied separately through percolating carbon networks and ionomer binders, rendering the catalyst largely passive and imposing fundamental trade-offs between reactant accessibility, ionic conductivity, and catalyst activity. Here, we introduce a one-dimensional
proton-electron coupled catalyst (PECC) design, a transport-integrated electrocatalyst architecture in which the catalyst itself simultaneously supplies electronic and protonic transport to catalyst active sites. Using this PECC, PEMFCs can have an ionomer-free cathode catalyst layer (CCL), resulting in a dramatic 95% reduction in non-Fickian oxygen transport and boosting power density by 34% and 85% compared to traditional CCLs, with cathode Pt loadings of approximately 0.090 mg/cm^2 and 0.037 mg/cm^2, respectively. Meanwhile, PECC retains 65% of its mass activity and exhibits 32% higher power density than its ionomer-based CCL counterpart after 30k accelerated stressed test. Similar mass transport improvements have been observed in the electrochemical hydrogen pump (EHP) using PECC in the catalyst layers. Molecular dynamics simulations show the PECC's
proton conductivity is 249% higher than Nafion. This PECC catalyst structure addresses core transport problems in PEMFCs, leading to almost 20% improvement in fuel efficiency and opens up new possibilities for designing high-performance, cost-effective electrochemical devices.
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All authors Ao Zhang, Ran Wang, Mohammed O. Bazaid, Shiyi Wang, Ting-Jung Hsiao, Yibo Wang, Antonio Sorrentino, Yang Liu, Yu-Han Joseph Tsai, Boxuan Zhou, Bosi Peng, Zeyan Liu, Xiangfeng Duan, Adam Z. Weber, William A. Goddard III, Seung Soon Jang, Yu Huang
Materials Science
Redox behaviour of Fe impurities in BaTiO$_3$ based on many-body calculations
Zhiyuan Li, Hamza Zerdoumi, Hao Wang et al. (+2 more)
Based on detailed electronic structure and spectroscopy obtained using DFT-based many-body techniques, the redox behavior of Fe
impurities in BaTiO$_3$ is investigated. It is observed that Fe
impurities exhibit a mixed valence nature, comprising mostly Fe$^{2+}$ ($3d^6$) and Fe$^{3+}$ ($3d^5$) configurations, and such configurations can be tuned via oxygen vacancies which favor Fe$^{2+}$. The origin of such a redox behavior can be attributed to the charge transfer caused by shifting of the $d_{3z^2-r^2}$ orbitals. Furthermore, x-ray photoemission spectroscopy is evaluated by solving the Wannier function-derived local atomic
Hamiltonian using the
crystal field multiplet approach, with good agreements with recent experimental measurements.
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All authors Zhiyuan Li, Hamza Zerdoumi, Hao Wang, Ruiwen Xie, Hongbin Zhang
Materials Science
Ab-initio Crystal Structure Determination from Powder X-Ray Diffraction
Kaixiang Su, Osman Goni Ridwan, Hongfei Xue et al. (+1 more)
Determining
crystal structures from powder X-ray diffraction (PXRD) has been a significant challenge in materials science, particularly when experimental data contain noise or the target structure has a high complexity. While recent AI generative models show promise for rapid structure generation, they predominantly employ data-driven approaches to learn direct mappings between PXRD patterns and
crystal structures, often failing on complex or out-of-distribution cases. In this work, we present a hybrid ab-initio approach that decomposes structure determination into a two-stage optimization problem: (1) discrete selection of space group
symmetry, unit
cell parameters, and Wyckoff site combinations; and (2) continuous optimization of atomic coordinates within the selected Wyckoff positions. By integrating AI-based techniques for peak profile analysis, density estimation and energy minimization with physics-informed constraints, our method systematically overcomes limitations of purely data-driven PXRD solvers. We demonstrate that this hierarchical optimization framework enables robust structure determination even for challenging cases with high structural complexity or limited experimental data quality. Our approach provides a principled pathway for incorporating crystallographic knowledge into AI models for more reliable and generalizable
crystal structure determination.
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All authors Kaixiang Su, Osman Goni Ridwan, Hongfei Xue, Qiang Zhu
Materials Science · Cross-listed from cond-mat.supr-con
Theoretical study of superconductivity in freestanding infinite-layer nickelate membranes under pressure: mitigation of excess correlation enhances $T_c$
Mahiru Seki, Reo Kono, Naotaka Tanaka et al. (+5 more)
We theoretically investigate a freestanding membrane of infinite-layer nickelate Nd$_{0.85}$Sr$_{0.15}$NiO$_2$ under pressure by constructing a seven-orbital effective model based on first-principles calculations. By performing the fluctuation exchange (FLEX) approximation, we demonstrate that the seven-orbital model explains a monotonic increase in $T_c$ reported in a recent experiment. This enhancement of superconductivity is attributed to the mitigation of excessively strong electron correlations caused by exceptionally low valence of Ni atom. Furthermore, we examine the dynamical stability of the
crystal structure under pressure through
phonon calculation.
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All authors Mahiru Seki, Reo Kono, Naotaka Tanaka, Kensei Ushio, Daiki Nakaoka, Masayuki Ochi, Kazuhiko Kuroki, Hirofumi Sakakibara
Materials Science
Application and Performance Assessment of Annealing Methods for Electrostatic-Energy-Based Configuration Search in Mixed Crystals
Tack Saquai, Kenta Hongo, Ryo Maezono et al. (+1 more)
In first-principles design of solid solutions and disordered materials, exhaustive evaluation of all possible substitutional configurations is often impractical because the number of site occupations increases exponentially. Here, we develop a framework for pre-screening mixed-
crystal configurations using annealing methods, where the Ewald electrostatic energy is used as the objective function. Substitutional occupations are represented by binary variables, allowing the Ewald energy to be mapped onto an Ising-type
Hamiltonian and the search for low-energy configurations to be formulated as a combinatorial optimization problem. We implement this formulation using simulated annealing (SA) and
quantum annealing (QA), and
benchmark their performance against exhaustive search. For the small-scale system CaYAlO$_4$, SA achieved a speed-up of about 30 times, while QA achieved a speed-up of more than 100 times; both methods identified all lowest-energy configurations. For the medium-scale system $\beta$-KSbF$_4$ and the large-scale Ba-doped SiAlON system, SA achieved speed-ups of about 200-300 times while robustly identifying the lowest-energy structures. In contrast, QA was effective for the small-scale case but showed limited speed-up for medium-scale problems and missed some low-energy configurations due to chain breaks. These results indicate that SA is currently the most robust and general-purpose approach for rapid pre-screening of mixed-
crystal configurations based on electrostatic energy. The proposed formulation can be implemented automatically using publicly available libraries and provides a practical route for accelerating candidate-structure generation before first-principles calculations.
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All authors Tack Saquai, Kenta Hongo, Ryo Maezono, Tom Ichibha
Materials Science · Cross-listed from cond-mat.supr-con
Nonunitary triplet superconductivity in the Z2 topological metal SrPd2As2
Aarti, Dibyendu Samanta, Kartik Panda et al. (+9 more)
In Z2 topological metals, nontrivial band
topology and strong
spin-orbit coupling (SOC) impose
symmetry constraints that can stabilize unconventional superconducting states, even when thermodynamic probes indicate an isotropic gap. Here, we investigate the superconducting ground state of such a material, SrPd2As2, using
muon spin rotation and relaxation (muSR), first-principles calculations, and Ginzburg-Landau analysis. Transverse-field muSR indicates a fully gapped superconducting state below Tc = 0.94 K, while zero-field muSR detects spontaneous internal
magnetic fields below Tc, establishing time-reversal
symmetry (TRS) breaking. Electronic structure calculations identify SrPd2As2 as a Z2 topological metal with surface states crossing the
Fermi level. Standard anisotropic Migdal-Eliashberg calculations predict a nodal gap and overestimate Tc, indicating that a purely
phonon-mediated pairing mechanism is insufficient. We resolve this apparent contradiction by showing that the interplay of SOC, tetragonal
symmetry, and an open
Fermi surface
topology stabilizes a nonunitary triplet superconducting state whose
symmetry-imposed nodes lie in momentum-space regions devoid of electronic states. This yields a fully gapped thermodynamic response while naturally breaking TRS. Our results establish SrPd2As2 as a clean platform for bulk nonunitary triplet pairing and a promising candidate for intrinsic topological superconductivity.
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All authors Aarti, Dibyendu Samanta, Kartik Panda, Devashibhai Adroja, Daloo Ram, Zakir Hossain, Rhea Stewart, Adrian Hillier, Amitava Bhattacharyya, Samar Layek, Sudeep Kumar Ghosh, Vivek Kumar Anand
Materials Science
Techno-economic Analysis of Light Isotope-enriched Elements for Lightweighting Applications
Wenbo Bao, Zhihao Yang, Taeyoung Wang et al. (+2 more)
Lightweighting is critical to mass-sensitive applications such as aircraft and space transportation. Conventional lightweight strategies often rely on new designs of materials and structures. An alternative approach is to enrich the lightest stable isotopes in an element to reduce the elements atomic mass while having little effect on structural and chemical properties. However, the economic feasibility of this concept remains unclear. Here we present a techno-economic analysis of light isotope-enriched elements for lightweighting applications by estimating isotope enrichment cost and the economic gain from mass reduction. The enrichment cost is scaled from established large-scale processes. Twelve common aerospace-relevant elements are considered, including Li, B, C, Mg, Cl, Ti, Ni, Fe, Cu, Zn, Mo, and Sn. We find that nine elements, especially Li, B, Zn, Ni, Mo, and Sn, show potentially attractive economic benefit at moderate enrichment levels, whereas C, Mg, and Fe provide little or no benefit. With the optimized enrichment levels, an Airbus A380 is expected to save approximately USD 700 K over a 30-year operational lifetime, a SpaceX Falcon 9 could save USD 516 K, and a SpaceX Starship is expected to save USD 2.37 million over its whole lifetime. While the exact enrichment cost needs to be further investigated, these results provide an initial screening of promising candidate elements and highlight isotopic mass reduction as a potential drop-in lightweighting strategy.
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All authors Wenbo Bao, Zhihao Yang, Taeyoung Wang, Joseph F. Wild, Yuan Yang
Materials Science
Multi-Source Domain Transfer Learning for Accurate Property Prediction in Two-Dimensional Materials
Huiyang Zhang, Xinyu Chen, Qionghua Zhou et al. (+1 more)
Machine learning has revolutionized materials discovery, but data scarcity remains a critical bottleneck for complex functional properties. As emerging systems, two-dimensional (2D) materials possess limited overall data volumes. Evaluating their diverse functional properties requires time-consuming simulations, hindering unified high-throughput screening. Furthermore, restrictions in known structural prototypes lead to highly fragmented data distributions. To address these challenges, we propose a multi-source domain transfer learning framework to extract generalizable and complementary knowledge from diverse crystalline systems. To mitigate data scarcity, the framework employs a shared feature extractor that integrates
adversarial transfer learning with maximum mean discrepancy, mapping
crystal structures into a domain-invariant latent space while preserving underlying physical correlations. To resolve distribution fragmentation, a sample-adaptive weighted ensemble strategy is subsequently utilized to dynamically aggregate predictions from multiple source domains. Relying solely on
crystal structures, the framework predicts 2D carrier mobilities with an R2 score exceeding 0.90. The framework successfully screened 55 novel high-mobility 2D
semiconductors, which were validated via first-principles electron-
phonon coupling analysis, confirming their exceptional transport properties and stability. This work can potentially accelerate machine learning-assisted materials design and discovery with less data restriction.
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All authors Huiyang Zhang, Xinyu Chen, Qionghua Zhou, Jinlan Wang
Materials Science
Termination-Dependent Surface States and Magnetic Fingerprints of Chiral Helimagnet Cr1/3TaS2
Bo Liang, Xue Li, Congcong Le et al. (+36 more)
Chiral helimagnets based on intercalated transition-metal dichalcogenides, characterized by nano-scale
spin ordering, provide a powerful route to engineer
chiral spin textures (e.g. the topologically protected
magnetic solitons) and emergent electronic functionality at reduced dimensions, where surface and interface states often dominate device operation. However, despite growing interest, direct experimental studies of termination-dependent surface electronic structures and their temperature-driven
magnetic evolution remain largely unexplored, hindering a microscopic understanding of the electronic states that is crucial for the development of low-dimensional spintronic devices. Here, for the first time, taking Cr1/3TaS2 as a representative example, we systematically investigate the termination-dependent surface electronic states of the
chiral helimagnets and uncover their distinct temperature
evolution across the
magnetic transition (TC~142K) by combining high-resolution ARPES with a micro-focused beam and surface-state-resolved first-principles calculations. The TaS2-terminated surface hosts folded monolayer-like TaS2 bands under the $\sqrt3\times\sqrt3$ superlattice potential and a shallow triangular electron pocket at the superlattice $\bar K$ point arising from Cr-Ta orbital hybridization. In contrast, the Cr-terminated surface exhibits reconstructed hole pockets with pronounced
magnetic band splitting. This splitting disappears above TC and closely follows the
chiral helimagnetic order parameter, providing a direct spectroscopic fingerprint of
chiral helimagnetic order. In addition, multiple ultranarrow Cr-d-derived surface flat bands are resolved. These findings establish Cr1/3TaS2 as a model system in which surface electronic states are strongly coupled to
chiral magnetism, opening new opportunities for
chiral spintronic and valleytronic micro/nanodevices.
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All authors Bo Liang, Xue Li, Congcong Le, Zirui Wu, Wenpei Zhu, Neng Cai, Yong-Chang Lau, Xianxin Wu, Jiayu Liu, Zhanfeng Liu, Hongen Zhu, Tongrui Li, Zhicheng Jiang, Yu Huang, Wenchuan Jing, Xun Ma, Qi Jiang, Hang Li, Zhihao Cai, Xuezhi Chen, Gexing Qu, Yiwei Cheng, Bing-Jie Chen, Zhengtai Liu, Dawei Shen, Mao Ye, Shengtao Cui, Zhe Sun, Koji Miyamoto, Taichi Okuda, Kenya Shimada, Yaobo Huang, Zhenhua Chen, Lin Zhao, Baojie Feng, Xinguo Ren, Wenhong Wang, Xingjiang Zhou, Guodong Liu
Materials Science
Colossal Type-II Multiferroic Polarization Driven by Collinear Spin Orders
Chengxi Huang, Xinhai Tu, Jintao Jiang et al. (+2 more)
Achieving strong magnetoelectric coupling (MEC) together with large ferroelectric polarization remains a central challenge in type-II multiferroics. In conventional
spin-driven multiferroics, the induced polarization is usually mediated by
spin-orbit coupling (SOC) or
spin-
lattice coupling (SLC). Since many representative systems are based on 3d transition-metal ions, where SOC is relatively weak and SLC-induced
lattice distortions are often limited, their polarizations are typically much smaller than those of proper ferroelectrics. Moreover, electric polarizations in type-II multiferroics are generally induced by spiral
spin orders stabilized by competing
magnetic interactions, which often leads to relatively low
magnetic transition temperatures. In this Letter, using
spin-group
symmetry, we propose an SOC- and SLC-independent route to MEC in collinear 3d
magnetic systems. We show that, even for a noncentrosymmetric
lattice structure, different collinear
magnetic configurations can either forbid or allow electric polarization, indicating direct
magnetic control of polarization and hence strong MEC. The first-principles calculations excluding SOC on monolayer 2H-VS2 support this picture: a collinear stripy
antiferromagnetic order induces an in-plane ferroelectric polarization up to 25.00 {\mu}C/cm2, about two orders of magnitude larger than that of typical type-II multiferroics. Furthermore, our microscopic model suggests that the induced polarization originates from SOC-independent p-d hybridization governed by electronic hopping. Our results suggest a possible route toward type-II multiferroics combining strong MEC with large electronic polarization in collinear 3d
magnetic systems.
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All authors Chengxi Huang, Xinhai Tu, Jintao Jiang, Xiangang Wan, Erjun Kan
Materials Science
Light-Driven Ferroic Switching Enables Reversible Control of Hydrogen Adsorption Thermodynamics
Xueqing Wan, Zhenlong Zhang, Charles Paillard et al. (+5 more)
Reversible ultrafast switching of surface thermodynamics is highly desirable for hydrogen storage and catalysis yet remains elusive at the nanoscale. Here we demonstrate that photoinduced ferroic-order switching in two-dimensional ionic ferroelectric monolayers enables rapid, reversible control of hydrogen binding. In TiGeSe$_3$, carrier-density-driven redistribution of transition-metal 3d orbital occupations triggers a sequential
evolution from the ferroelectric ground state to paraelectric phases with staggered or Zig-Zag
antiferromagnetic order. This switch continuously tunes the hydrogen adsorption free energy from 0.33 to 1.11 eV, shifting the interface from near-thermoneutrality to spontaneous desorption. Nonadiabatic dynamics indicate that electron-
phonon coupling promotes nonthermal H release, while picosecond carrier recombination rapidly restores the initial ferroic order, closing an ultrafast reversible cycle. Generality is further validated in AgBiP$_2$Se$_6$ and CuInP$_2$S$_6$, establishing ferroic order as an optically addressable knob for dynamic thermodynamic reconfiguration beyond static design.
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All authors Xueqing Wan, Zhenlong Zhang, Charles Paillard, Jian Zhou, Jinyang Ni, Chuanlu Yang, Zhijun Jiang, Laurent Bellaiche
Materials Science
Dilute Magnetism and Edge-State Engineering in Monolayer SnO
Yuya Fukuta, Souren Adhikary, Kazuhito Tsukagoshi et al. (+1 more)
Tin monoxide (SnO) is a p-type
oxide semiconductor whose electronic properties can be widely modified via atomic-scale engineering. Using density functional theory, we investigate the electronic and
magnetic properties of transition-metal (TM = Mn, Fe, Co and W) doped SnO monolayer within a large supercell. We find that all dopants induce finite localized
magnetic moments, primarily originating from $d$-orbitals of the
impurity atoms. We show that these localized
magnetic states give rise to nearly dispersionless bands in the vicinity of the
Fermi energy (taking Co doped SnO as an example). In addition, we investigate dimensional effects by constructing nanoribbon geometries of SnO monolayer. The ribbons exhibit intrinsic edge-localized states that are largely independent of ribbon width. For
chiral nanoribbons oriented along a low-
symmetry direction of the square
lattice, we find that oxygen-rich edges are thermodynamically most stable and remain semiconducting, whereas Sn-terminated edges host metallic one-dimensional conduction channels. Our results demonstrate that transition-metal doping and edge engineering provide effective routes to tailor the electronic properties of SnO monolayer, making it a promising candidate for future spintronic and nanoelectronic applications.
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All authors Yuya Fukuta, Souren Adhikary, Kazuhito Tsukagoshi, Katsunori Wakabayashi
Materials Science
Systematic comparison of approximations and functionals in first-principle calculations of aluminum-based III-V ferroelectric nitrides
Alejandro Mercado Tejerina, Peng Chen, Keisuke Yazawa et al. (+3 more)
We revisit first-principles predictions of structural, ferroelectric, and electronic properties in aluminum-based III-V nitride
alloys, focusing on Al1-xScxN and Al1-xBxN. Using density functional theory within a unified 48-atom supercell framework, we systematically assess the role of chemical disorder and exchange-correlation approximations by comparing the virtual
crystal approximation (VCA) and special quasirandom structures (SQS), as well as PBE, PBESol, SCAN, and SCAN+rVV10 functionals. We demonstrate that, even amongst the similar PBE and PBESol functionals, big quantitative and qualitative differences emerge. In particular, the VCA or SQS PBESol (a popular functional) strongly underestimate the stability domain of the ferroelectric wurtzite phase in Al1-xScxN compared to SQS PBE or SQS SCAN. We demonstrate that the 5-fold coordinated hexagonal phase predicted in 2002 by Farrer and Bellaiche [Phys. Rev. B 66, 201203] is a low-energy metastable state between the four-fold coordinated ferroelectric wurtzite phase and the six-fold coordinated rocksalt phase near the transition point upon increasing the Sc content. In contrast, Al1-xBxN shows a much faster destabilization of the wurtzite ferroelectric phase, with bond breaking which strongly distorts the wurtzite structure (with enhanced polarization) and eventually favor a zincblende phase and a threefold coordinated hexagonal layer phase. Our analysis highlights the critical importance of both local disorder and exchange-correlation treatment in predicting the functional properties of III-V nitride ferroelectrics. Overall, SQS combined with SCAN provides the most consistent theoretical framework for understanding and optimizing emerging nitride-based ferroelectric materials.
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All authors Alejandro Mercado Tejerina, Peng Chen, Keisuke Yazawa, Andriy Zakutayev, Laurent Bellaiche, Charles Paillard
Materials Science
Ultrafast Magneto-optical Fingerprints of Altermagnetism in MnTe
Xu Yang, Xingkai Cheng, Zhuo Deng et al. (+9 more)
Recently identified altermagnets exhibit a distinctive dual-space nature: they possess
spin-split electronic bands akin to ferromagnets in momentum space while maintaining the fully compensated magnetization of antiferromagnets in real space. This inherent duality, originating from the same
crystal symmetry, gives rise to various intriguing physical phenomena unique to altermagnets. Consequently, a robust and efficient experimental signature capable of revealing this dual character is critically needed. The magneto-optical Kerr and Voigt effects, given their high sensitivity to ferromagnetism and antiferromagnetism, respectively, are ideally suited to probe this duality. Here, using time-resolved pump-probe magneto-optical measurements, we report the coexistence of pronounced Kerr and Voigt effects in the altermagnet MnTe. Combining the magnetization measurement and first-principles calculations, we demonstrate that the Kerr effect originates from the intrinsic Berry
curvature of altermagnetism distribution in momentum space, while the Voigt effect arises from an anisotropic permittivity induced by the in-plane Néel order in real space, directly revealing the dual-space nature of altermagnets. Furthermore, the transient Kerr signal exhibits faster relaxation dynamics than the transient Voigt signal, underscoring their distinct origins in Berry
curvature and Néel order, respectively. These findings establish transient magneto-optical responses as distinctive fingerprints of altermagnetism and position altermagnets as promising platforms for manipulating magneto-optical phenomena in ultrafast
spin optoelectronics.
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All authors Xu Yang, Xingkai Cheng, Zhuo Deng, Yu-Han Gao, Qing-Lin Yang, Zheng Chang, Peng-Tao Yang, Hong-Mei Feng, Xiang-Qun Zhang, Wei He, Junwei Liu, Zhao-Hua Cheng