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Physics Condensed Matter Materials Science

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Thursday 14 May

Materials Science

Telecom-Wavelength-Compatible Quantum Information Transcription Using Nitrogen-Vacancy Centers

B. Göblyös, S. Kollarics, R. Kucsera et al. (+5 more)

Nitrogen-vacancy (NV) centers in diamond are a leading platform for solid-state quantum sensing and quantum information processing. While most optical studies rely on the visible fluorescence associated with the triplet transitions, the infrared singlet transition near $1042$ nm, which is typically considered dark within the singlet manifold of the NV optical cycle, provides an alternative optical channel. Here, we report wavelength-resolved optically detected magnetic resonance (ODMR) measurements of this infrared emission. We directly observe ODMR contrast in the $1042$ nm emission and analyze its dependence on the magnetic field. The field-dependent spectral dispersion of the ODMR signal demonstrates that the spin-state information encoded in the NV center is transcribed to the infrared singlet emission through the spin-selective intersystem crossing, in close analogy to the visible fluorescence readout. These results establish infrared ODMR as a high-fidelity optical readout pathway. Crucially, by extending spin-state transcription directly into the $1300-1600$ nm range, this work demonstrates a direct, conversion-free interface between diamond spin-qubits and standard telecommunication infrastructure, bypassing the efficiency bottlenecks of active frequency conversion and benefiting from the already well-developed technologies in this range of the electromagnetic spectrum.
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All authors B. Göblyös, S. Kollarics, R. Kucsera, D. Plitt, K. Koltai, B. G. Márkus, L. Forró, F. Simon

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

Compositional and Magnetic Characterisation of Oblique Co and Fe Nanowire Structures Fabricated Using Focused Electron Beam Induced Deposition

Aurys Silinga, Keir Edgar, Stephen McVitie et al. (+4 more)

Focused electron beam induced deposition (FEBID) is an additive manufacturing technique uniquely suited for fabricating functional 3D nanostructures for a range of applications, including spintronic devices. However, the variation of growth dynamics associated with lateral movement of the electron beam results in structures with non-uniform composition when fabricating intricate 3D geometries. Herein, we measure changes in atomic composition and corresponding changes in magnetic induction in 3D ferromagnetic nanostructures with overhanging elements, e.g. bridges or arches. To investigate the effects of electron beam lateral movement, we fabricated Co and Fe nanowire (NW) structures with growth angle relative to the optic axis varying from 0{\deg} to 90{\deg}. The (scanning) transmission electron microscopy techniques of electron energy loss spectroscopy and off-axis electron holography were performed to map the NW elemental composition and magnetic induction as a function of NW growth angle. Comparison of the results reveals a reduction in metal content with increased growth angle in FEBID NWs. The magnitude of metal content reduction can be tuned by controlling electron beam parameters, and ferromagnetic NWs with approximately equal metal content at growth angles from 0{\deg} to 60{\deg} were fabricated by using the lowest viable electron beam voltage and the highest viable beam current to reduce the interaction volume and increase the metal content, respectively.
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All authors Aurys Silinga, Keir Edgar, Stephen McVitie, Kayla Fallon, András Kovács, Rafal E. Dunin-Borkowski, Trevor P. Almeida

Materials Science

Agentic Design of Compositional Descriptors via Autoresearch for Materials Science Applications

Matteo Cobelli and Stefano Sanvito

Autoresearch offers a flexible paradigm for automating scientific tasks, in which an AI agent proposes, implements, evaluates, and refines candidate solutions against a quantitative objective. Here, we use composition-based materials-property prediction to test whether such agents can perform a task beyond model selection and hyperparameter optimization: the design of input descriptors. We introduce Automat, an autoresearch framework where a coding agent based on a large language model generates composition-only descriptors for chemical compounds and evaluates them using a random forest workflow. The agent is restricted to information derivable from chemical formulas and iteratively proposes, implements, and tests chemically motivated descriptor strategies. We apply Automat, with OpenAI Codex using GPT-5.5 as the coding agent, to the prediction of experimental band gaps in inorganic materials and Curie temperatures in ferromagnetic compounds. In both tasks, Automat improves over fractional-composition, Magpie, and combined fractional-composition/Magpie baselines, while producing descriptor families that are chemically interpretable. These results provide a demonstration that autoresearch agents can generate competitive, task-specific materials descriptors without manual feature engineering during the run. They also reveal current limitations, including descriptor redundancy, sensitivity to greedy feature expansion, and the need for explicit complexity control, descriptor pruning, and more sophisticated search strategies.
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Materials Science

N-Graphdiyne as a Tunable Platform for Stabilizing Light Metals toward High-Capacity Reversible Hydrogen Storage

Wael Othman, Ibrahim Alghoul, K-F. Aguey-Zinsou5 et al. (+2 more)

Hydrogen (H2) is a promising carbon-neutral energy carrier. However, its deployment is limited by the lack of lightweight, reversible storage media that operate under practical conditions. Here, we establish nitrogen-doped graphdiyne (N-GDY) as a programmable two-dimensional platform for stabilizing dispersed light-metal dopants and enabling high-capacity physisorption of molecular H2. The computational package involves density functional theory (DFT) combined with ab initio molecular dynamics (AIMD) and Langmuir-based statistical thermodynamic modeling. The results revealed that N-sites of N-GDY bind up to five Li, Na, K, and Ca atoms per primitive cell with binding energies of -2.27, -1.57, -1.80, and -2.13 eV, respectively, exceeding their respective bulk cohesive energies. AIMD simulations at 400 K further confirm the structural robustness of the decorated frameworks and the absence of metal aggregation. The polarised metal centres activate reversible H2 adsorption through electrostatic and dispersion interactions, with average adsorption energies falling within the optimal window (-0.15 to -0.35 eV per H2). Sequential adsorption analysis reveals uptake of up to 25 H2 molecules per primitive cell, achieving intrinsic gravimetric capacities of 13.08, 10.82, 9.23, and 9.15 wt% for Li-, Na-, K-, and Ca-functionalized systems, respectively. Thermodynamic analysis indicates favorable adsorption-desorption behavior under near-ambient conditions, with Li- and Ca-functionalized systems exceeding the 6.5 wt% U.S. Department of Energy's ultimate system-level target when considering intrinsic material capacity. These results identify N-GDY as a chemically tunable scaffold for dispersing lightweight metals and provide a mechanistic design strategy for achieving high-capacity, reversible hydrogen storage in porous two-dimensional materials.
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All authors Wael Othman, Ibrahim Alghoul, K-F. Aguey-Zinsou5, Nacir Tit, Tanveer Hussain

Materials Science · Cross-listed from cond-mat.soft

Kinetic effects on the phase behavior and microstructural transitions of a thermoresponsive polymer solution

Pritha Acharya, Riya Karmakar and Khushboo Suman

The thermoresponsive behavior of Pluronic F127 solutions is governed by temperature-dependent micellization and complex self-assembly of these micelles. This study investigates the effect of thermal stimuli on the kinetics of phase transition of Pluronic systems during heating and cooling cycles. We employ Differential Scanning Calorimetry measurements to investigate the dependence of the micellization temperature on thermal stimuli, revealing that both the micellization temperature and the peak intensity vary systematically with the applied thermal ramp rate. Furthermore, we employ rheological characterization which reveals a sharp sol to soft-solid transition upon heating. Interestingly, we observe a novel multi-step transition during the cooling phase, indicating a more complex reorganization pathway with intermediate metastable states than typically assumed for reversible micellization. Our findings indicate that the characteristic multi-step cooling transition is transient, gradually weakening with successive thermal cycles. We also present a comprehensive mathematical model which accurately captures the kinetics and multiple step transition in viscoelastic parameters. Significantly, the distinct peaks in Small-Angle X-ray Scattering (SAXS) measurements clearly reveal the evolution from a disordered unimers/micelles state at low temperatures to a highly ordered lattice with long-range spatial correlation at elevated temperatures. We also present a comprehensive phase diagram highlighting the critical role of thermal stimuli and pathways in defining the phase behavior of Pluronic system. This work, therefore, offers essential experimental and theoretical insights into the thermally driven self-assembly, transition kinetics, and microstructural evolution of thermoreversible Pluronic solution.
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Materials Science

Tunable Dual-Type Weyl Points in Dirac-Weyl Semimetal CaAgBi

Shenghao Huang, Heng Gao, Hongfei Wang et al. (+1 more)

Dirac-Weyl semimetals host both Dirac and Weyl fermions and the exploration of material candidates with tunable topological properties is essential to realize topological spintronic devices. In this work, we propose CaAgBi as a Dirac-Weyl semimetal with tunable type-I and type-II Weyl points based on first-principle calculations. In addition to the three pairs of Dirac points located along the rotational axis as previously reported, our calculations reveal 18 additional pairs of dual-type Weyl points distributed across three distinct planes: type-I in the $k_z=0$ plane and type-II in the $k_z= \pm 0.0698\,\frac{2\pi}{c}$ planes. The topological features are further confirmed through chirality of the Weyl points as well as the existence of surface Fermi arcs. Moreover, we find that the position and annihilation of Dirac and Weyl points are tunable by the alloy engineering and external strains. The alloy engineering is employed to modulate the positions of Weyl points, revealing different annihilation concentrations for type-I and type-II Weyl points, potentially offering novel experimental strategies for Weyl point manipulation. Under tensile biaxial strain, the Weyl points in the $k_{z}=0$ plane annihilate along the $\Gamma$–$\mathrm{M}$ path at $2.1\%$ strain, whereas the Weyl points in the $k_{z}\neq 0$ planes remain robust within $6\%$ strain. This work provides a versatile platform for manipulating Dirac/Weyl interactions, with spin-orbit coupling (SOC) driven alloy control and strain-selective engineering opening avenues for topological electronics.
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All authors Shenghao Huang, Heng Gao, Hongfei Wang, Wei Ren

Materials Science

Biquadratic exchange coupling effect on the magnetic properties of (Fe/Ti) multilayers

Melissa Yactayo, H. S. Tarazona, O. Copie et al. (+3 more)

This work explores the static and dynamic magnetic properties of weakly antiferromagnetically coupled Fe/Ti superlattices, emphasizing the link between magnetic behavior and structural characteristics. HRTEM and XRD analyses confirm alternating Fe and Ti layers with rough interfaces, especially in upper layers. Magnetic measurements reveal two-step hysteresis loops and a temperature and thickness-dependent interlayer exchange coupling (IEC). A macrospin model incorporating bilinear and biquadratic coupling reproduces the experimental data and supports a phase diagram analysis identifying non-collinear configurations. The results underscore the impact of structural imperfections and highlight the crucial role of biquadratic exchange in Fe/Ti/Fe multilayers.
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All authors Melissa Yactayo, H. S. Tarazona, O. Copie, J.-C. Rojas-Sánchez, J. Quispe-Marcatoma, C. V. Landauro

Materials Science

Methane hydrate nucleation frustration and dimensional reduction of structural order under nanoconfinement

Jose Torres-Arenas, Ángel M. Fernández-Fernández, Martín Pérez-Rodríguez et al. (+1 more)

Methane hydrate nucleation under nanoconfinement remains poorly understood due to the complex interplay between geometric restriction and molecular ordering. Here, we investigate the structural organization of water-methane systems confined between silica planar slit pores with widths ranging from 1 to 5 nm and temperatures between 250 and 295 K. Three-dimensional radial distribution functions reveal a clear suppression of hydrate-like ordering at strong confinement (below 2 nm), indicating frustrated nucleation. In contrast, projected two-dimensional correlations exhibit pronounced in-plane structural organization, evidencing a confinement-induced reduction in the dimensionality of molecular order.
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All authors Jose Torres-Arenas, Ángel M. Fernández-Fernández, Martín Pérez-Rodríguez, Manuel M. Piñeiro

Materials Science · Cross-listed from cs.LG

Lang2MLIP: End-to-End Language-to-Machine Learning Interatomic Potential Development with Autonomous Agentic Workflows

Wenwen Li, Yuki Orimo and Nontawat Charoenphakdee

Developing machine learning interatomic potentials (MLIPs) for complex materials systems remains challenging because it requires expertise in atomistic simulations, machine learning, and workflow design, as well as iterative active learning procedures. Existing automated pipelines typically assume a fixed sequence of stages or depend on domain experts, which limits their adaptability to heterogeneous materials systems where the optimal curriculum is not known in advance. To lower the barrier to developing MLIPs for non-experts, we propose Lang2MLIP, a multi-agent framework that takes natural-language input and formulates end-to-end MLIP development as a sequential decision-making problem solved by large language models (LLMs). At each step, a decision-making agent observes the current dataset, model, evaluation results, and execution log, and then automatically selects an appropriate action to improve the model. This removes the need for a predefined pipeline and enables the agent to self-correct by revisiting earlier subsystems when new failures arise. We evaluate this approach on a solid electrolyte interphase (SEI) system with multiple components and interfaces. These results suggest that LLM-based multi-agent systems are a promising direction for automating MLIP development and making it more accessible to non-experts.
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Materials Science

Probing the Chirality of Trigonal Selenium and Tellurium by Spin and Orbital Hall Effects

Yuting Xiong, Yingjie Hu, Wei Ren et al. (+1 more)

Chiral crystals exhibit enantiomer-dependent transport phenomena that generate pure spin or orbital currents, while the handedness sensitivity of spin and orbital Hall conductivities (SHC/OHC) remains insufficiently understood. Using first-principles calculations, we demonstrate that trigonal selenium and tellurium – prototypical chiral semiconductors – exhibit opposite signs of the SHC/OHC tensor elements $\sigma_{yx}^{S_y}$ and $\sigma_{yx}^{L_y}$ between their left- and right-handed enantiomers. This behavior originates from the mirror operation relating the two structures, described by space groups $P3_221$ (left-handed) and $P3_121$ (right-handed). Although both enantiomers share identical band structures and four nonzero SHC/OHC tensor components, $\sigma_{yx}^{S_y}$ and $\sigma_{yx}^{L_y}$ reverse sign due to the antisymmetric transformation of the spin/orbital Berry curvature under the $M_{xy}$ mirror operation. More generally, for mirror-related enantiomorphic structures, selected SHC/OHC tensor components can exhibit symmetry-governed sign reversal. For trigonal Se and Te, the calculated signs of these components can be directly correlated with the left- and right-handed structures under the chosen coordinate convention. These results clarify the symmetry origin of handedness-dependent SHC/OHC and suggest a possible route for correlating measurable SHC/OHC signals with structural handedness in specific chiral materials.
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All authors Yuting Xiong, Yingjie Hu, Wei Ren, Heng Gao

Materials Science

Accurate computation of the electron-phonon interaction contribution to the total energy

Shilpa Paul, Mogadalai Pandurangan Gururajan, Amrita Bhattacharya et al. (+1 more)

The standard Hamiltonian of a coupled electron-phonon system is based on second-order perturbation theory. The EPI contribution in the standard Hamiltonian consists of two terms, the EPI contribution to the band-structure energy and the partial-Fan-Migdal (FM)-occupied contribution. Within the non-adiabatic approximation, we derive a new expression for the partial-FM-occ contribution and show that it has the structure of a higher-order term, and not a second-order term. Along similar lines, we derive new expressions for the computation of the partial-FM-occ term. The new expressions for the partial-FM-occ term must be preferred over the standard expressions, in theoretical and computational studies, because they incorporate the complete physics underlying this term. Unlike the EPI contribution to individual eigenstates, the EPI contribution to the total energy must be computed in the non-adiabatic approximation for all materials, Infra-red (IR) active and IR-inactive. We report the computation of the standard Hamiltonian, for the first time, for Carbon polymorphs (diamond and hexagonal lonsdaleite) by including the EPI contribution to the total energy. This is the most accurate ab initio total energy reported till date. The present work also opens the way to compute the ab initio free-energy more accurately at finite temperatures by including the EPI contribution.
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All authors Shilpa Paul, Mogadalai Pandurangan Gururajan, Amrita Bhattacharya, Tiramkudlu R. S. Prasanna

Materials Science

High-Pressure Crystal Structure Database

Zhenyu Wang, Qingchang Wang, Junwen Duan et al. (+7 more)

High-pressure research is a productive route to new structures and emergent properties. However, crucial high-pressure structural information remains highly fragmented across individual publications and heterogeneous computational repositories. This fragmentation creates a major bottleneck for data-driven materials design. To bridge this gap, we introduce the High-Pressure Crystal Structure Database (HPCSD), a traceable, pressure-resolved repository that integrates experimental and theoretical high-pressure structures. HPCSD is constructed from two complementary data streams: elemental high-pressure phases and a searchable configuration space of stable and metastable phases generated via CALYPSO crystal structure prediction. To ensure rigorous comparability, all retained structures underwent re-optimization under a unified density functional theory (DFT) framework , with continuous enthalpy curves systematically generated specifically for the elemental phases across their stability fields. The initial release encompasses 77,346 consistently evaluated structural entries spanning 89 elements. An analysis reveals that pressure-induced polymorphism is ubiquitous and exhibits pronounced family-dependent trends. Structural diversity is strongly influenced by an element's electronic adaptability , with the greatest structural complexity emerging at intermediate rather than highest pressures. By providing standardized, reusable, and rigorously evaluated high-pressure structural data, HPCSD establishes a robust infrastructure to accelerate experimental phase identification, facilitate cross-study thermodynamic comparisons, and support the development of machine-learning interatomic potentials and generative models for high-pressure systems.
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All authors Zhenyu Wang, Qingchang Wang, Junwen Duan, Heng Ge, Xiaoshan Luo, Pengyue Gao, Wei Zhang, Jian Lv, Yanchao Wang, Yanming Ma

Materials Science

Shaping Maximally Localized Wannier Functions via Discrete Adiabatic Transport

Yuji Hamai and Katsunori Wakabayashi

Maximally localized Wannier functions (MLWFs) are conventionally constructed by iteratively minimizing a spread functional over a high-dimensional gauge landscape. In this work, we present a non-variational constructive algorithm that unifies gauge smoothing and the eigenvalue problem of the projected position operator into a single deterministic framework. We demonstrate that discrete adiabatic transport across band degeneracies emerges naturally as an integral part of the solution procedure for the position eigenvectors. In this transport-aligned gauge, the Bloch overlaps exhibit an approximately linear phase dependence, allowing the Wannier centers to be extracted via deterministic fixed-point iterations and self-consistent updates rather than spread-functional minimization. Benchmark calculations for one- and two-dimensional systems yield spreads and orbital shapes in good agreement with standard minimization schemes. Furthermore, this analytical approach transparently isolates the physical origin of the $\mathcal{O}(L)$ mesh-dependent spread scaling ($L$ being the boundary seam resolution) observed in graphene, demonstrating that it is an intrinsic geometric manifestation of non-commuting projected position operators forcing finite gauge defects to accumulate along a one-dimensional boundary seam.
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Materials Science

Strain-Enhanced Hydrogen Evolution, Electrical, Optical, and Thermoelectric Properties of the Multifunctional 2D CrSi2N4 Monolayer

Rao Uzair Ahmad, Fahd Sikandar Khan and Nasir Javed

First-principles density functional theory (DFT) is employed to evaluate the structural, electronic, optical, thermoelectric, and electrocatalytic properties of monolayer CrSi2N4. Its symmetric N-Si-N-Cr-N-Si-N septuple-layer structure exhibits dynamic, thermal (300 K), and mechanical stability, supported by a -8.76 eV/atom cohesive energy. PBE and HSE06 functionals reveal an indirect bandgap of 0.58 eV and 2.16 eV, respectively, driven by localized Cr-3d and N-2p states. The monolayer features 15.57 static dielectric constant and maximum absorption coefficients of 0.9 X 10^6 cm-1 (visible) and 1.4 X 10^6 cm-1 (deep-UV). Semiclassical Boltzmann calculations predict an outstanding room-temperature n-type thermoelectric power factor of 3.5 x mW/mK2. For hydrogen evolution (HER), the basal plane yields a baseline hydrogen adsorption free energy ({\Delta}GH) of 1.05 eV at the N-site. Applying +5% expansive biaxial strain improves HER kinetics, reducing {\Delta}GH to 0.46 eV. Thus, CrSi2N4 is a resilient, tuneable candidate for waste-heat recovery, photodetectors, and sustainable electrocatalysis.
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Materials Science

From spin splitting to projected mass in altermagnetic Chern matter

Gyanti Prakash Moharana

Altermagnetic spin splitting alone does not define Chern matter. The relevant object is the exchange mass projected onto Hall-active surface, valley, orbital or interface sectors. We formulate this projected-mass criterion for compensated magnetic topology. The resulting two-channel $(C,\mathcal{A})$ diagnostic separates hidden compensated Hall responses from additive altermagnetic quantum anomalous Hall phases in a global insulating gap. It also guides interface, thickness and materials design strategies.
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Materials Science

Chiroptical Ternary Entropy Harvesting from Self-Assembled Block Copolymer Nanopatterns

Wookjin Jung, Serin Jeong, Kyulim Kim et al. (+3 more)

Nanoscale fabrication inevitably produces local stochasticity that is commonly treated as a defect, but can instead be harnessed as a material resource for information security. Here we report a chiroptical platform for ternary entropy harvesting based on stochastic Au nanopatterns formed by block copolymer self-assembly. By transducing fabrication-induced stochastic microstates into handedness-dependent optical responses through chiroptical mapping, our platform enables native ternary digitization rather than conventional binary encoding, allowing physically harvested ternary random sequences to be used for key generation. This raises the information density to log2(3) = 1.585 bits per trit, approximately 58.5% higher than the binary limit, enabling more entropy to be harvested from a limited physical footprint. The harvested outputs exhibit near-balanced symbol populations, negligible spatial and inter-sample correlations, Shannon entropy approaching the ternary ideal, and resistance to statistical and machine-learning-based prediction. These results establish self-assembled chiroptical nanostructures as a scalable platform for cryptographic key generation, secure edge devices, and distributed Internet-of-Things platforms.
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All authors Wookjin Jung, Serin Jeong, Kyulim Kim, Dongkyu Lee, Sang Ouk Kim, Jihyeon Yeom

Materials Science

Ward identities and orbital magnetization in current density functional theory

Giovanni Vignale, Junren Shi, Di Xiao et al. (+1 more)

We revisit the derivation of the orbital magnetization formula for periodic crystals in current density functional theory (CDFT)[1]. Our new derivation computes the linear response of the energy density to a periodic magnetic field in the long-wavelength limit. We unveil a Ward identity which connects the current vertex to the derivative of the Kohn-Sham self-energy. The result of Ref.[1] is confirmed: the orbital magnetization of the interacting solid can be computed exactly (in principle) from the self-consistent eigenfunctions and eigenvalues of the Kohn-Sham equation of CDFT.
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All authors Giovanni Vignale, Junren Shi, Di Xiao, Qian Niu

Materials Science

Depletion-mode N-polar AlN-based high electron mobility transistors with improved on/off ratios

Xu Yang, Sheng Zhang, Ke Wei et al. (+4 more)

We report N-polar AlN-based high-electron mobility transistors (HEMTs) with a GaN channel thickness of 5.2 nm on N-polar AlN on sapphire. The threshold voltage is around -2.4 to -3.0 V with saturation currents over 240 mA/mm and on/off ratios as high as 10,000, much higher than previously reported N-polar AlN-based HEMTs. The high on/off ratio is attributed to the use of an abrupt AlN/GaN heterostructure with a dedicated AlN transition layer, together with improved gate leakage. The high frequency properties as well as the on-resistance of ~20 Ohm mm are all limited by the 2000 Ohm/square sheet resistance of the channel layer.
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All authors Xu Yang, Sheng Zhang, Ke Wei, Xinhua Wang, Xinyu Liu, Itsuki Furuhashi, Markus Pristovsek

Materials Science

Unified definition of ferroelectricity

Wei Luo, Shihan Deng, Hongjun Xiang et al. (+1 more)

Recent theoretical and experimental advances in quantum ferroelectrics suggest that ferroelectricity can also emerge in non-polar space group, highlighting the limitations of conventional polar space group criteria in identifying ferroelectric materials. Here, we introduce a unified definition based on switchable polarization differences between energetically equivalent states, which naturally encompasses conventional and quantum ferroelectrics. Guided by this principle, we implement a high-throughput screening strategy that systematically identifies both conventional and quantum ferroelectrics among experimentally synthesized materials. In particular, we identify a new type of quantum ferroelectric in which the quantized polarization arises from arbitrary ionic displacements, in contrast to previous quantum ferroelectrics (including both fractional and integer quantum ferroelectrics) where quantized polarization results from fractional or integer ionic displacements. Notably, we find that materials such as Ba3I6 and Cs2PdC2 exhibit low switching barriers and robust insulating behavior, highlighting their experimental viability. Our results reconcile conventional and quantum ferroelectrics, expand the accessible materials landscape, and provide a practical roadmap for discovering next-generation ferroelectrics with advanced switchable functionalities.
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All authors Wei Luo, Shihan Deng, Hongjun Xiang, Laurent Bellaiche

Materials Science

Machine-learning-identified two-dimensional van der Waals multiferroics for four-state nonvolatile memory

Zhibin Tan, Tao Wang and Hao Jin

Two-dimensional (2D) van der Waals (vdW) multiferroics offer an attractive platform for four-state nonvolatile memory by combining switchable ferroelectric polarization and magnetization within a single material system. However, their development is hindered by the scarcity of synthesizable candidates and the lack of non-destructive readout schemes. Here, we combine machine-learning screening with first-principles calculations to explore the 2D vdW ABC$_2$X$_6$ family and identify a set of high-confidence multiferroic candidates. Among them, AuCrP$_2$S$_6$ monolayer emerges as a representative system with a ferromagnetic ground state, a sizable out-of-plane polarization of 7.46 pC/m, and a moderate ferroelectric switching barrier of $\sim$130 meV/f.u. Moreover, the nonlinear optical response mediated by the bulk photovoltaic effect (BPVE) in AuCrP$_2$S$_6$ provides a dual-channel probe of the ferroic orders, in which the polarization direction governs the photocurrent sign while the magnetic order selects the spin channel via robust exchange splitting. This intrinsic coupling enables the non-destructive readout of four logic states within a single atomic layer, thereby providing a practical blueprint for next-generation multistate optoelectronic memory.
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Wednesday 13 May

Materials Science · Cross-listed from q-bio.NC

Sensing Intelligence as a Trainable Metamaterial Property

Kyungmi Na, Yifei Li, Xinyi Yang et al. (+1 more)

In biological systems, sensing is not performed by the brain alone: the body deforms, vibrates, and filters external stimuli before they are transduced into neural signals. In engineered systems, this processing burden is placed largely on electronics and computation, while the mechanical body is usually designed only for strength and stability. Here, we present sensing intelligence as a trainable property of the body. We show that the geometry of a metamaterial can be optimized to reshape external stimuli into internal signals that are easier for a neural network to interpret. Rather than hand-designing this physical preprocessing, we let the neural network train its own body for sensing by backpropagating the sensing loss to the body's design parameters through differentiable simulation. Across numerical and experimental sensing scenarios, the optimized body improves sensing accuracy by up to fivefold or reduces the number of required electronic sensors by nearly an order of magnitude.
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All authors Kyungmi Na, Yifei Li, Xinyi Yang, Bolei Deng

Materials Science · Cross-listed from cs.AI

NIMO Controller: a self-driving laboratory orchestrator based on the Model Context Protocol

Naruki Yoshikawa and Ryo Tamura

Self-driving laboratories (SDLs) are attracting increasing attention as a means of accelerating scientific discovery; however, developing SDL software remains technically demanding. To improve accessibility, orchestration software frameworks have been proposed to coordinate SDL components, but many existing frameworks are primarily designed for human interaction and lack standardized interfaces for direct integration with AI agents. In this work, we propose an SDL software architecture based on the Model Context Protocol (MCP), in which all SDL functionalities are exposed through MCP servers. Following this design principle, we introduce NIMO Controller, an MCP-based SDL orchestrator that integrates the experimental planning software NIMO. It provides a visual programming interface automatically generated through MCP-based tool discovery, allowing human users to design experimental workflows without writing code. The same MCP backend is also accessible to AI agents, providing a unified interface through which both human users and AI agents can interact with SDL components. AI agents can invoke MCP tools directly or generate NIMO workflows from natural language instructions. We evaluated the agentic workflow generation performance of various LLMs and conducted a user study using a color-matching SDL.
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Materials Science

Carrier-density dependence of magnetotransport in correlated Dirac semimetal CaIrO$_3$

Rinsuke Yamada, Jun Fujioka, Minoru Kawamura et al. (+8 more)

We report the carrier density dependence of the magnetotransport property in the correlated Dirac semimetal CaIrO$_3$. In the dilute carrier density region ($n_{\rm H}$ $\sim 2.2 \times 10^{16} \,$$\rm{cm}^{-3}$) at $2 \, \mathrm{K}$, the mobility exceeds $1.0 \times 10^{5} \,$$\rm{cm}^{2}/\rm{Vs}$ at $2 \, \mathrm{K}$, and the transverse magnetoresistance (MR) reaches $2,000 \,$% at $12 \, \mathrm{T}$. The analysis of quantum oscillations and Hall conductivity shows that the Fermi velocity is nearly independent of the cross-sectional area of the Fermi surface, or equivalently the carrier density, supporting a $k$-linear dispersion of the Dirac node. The field dependence of magnetoresistivity is nearly $B$-linear in the moderate carrier density region ($n_\mathrm{H} \geq 4 \times 10^{16}\,$cm$^{-3}$), but scales with $B^{\alpha}$ ($\alpha > 2$) in the lower carrier density region. The variation of magnetoresistivity is likely affected by the enhanced long-range Coulomb interaction in the quantum limit, where Dirac electrons are subject to the magnetic confinement.
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All authors Rinsuke Yamada, Jun Fujioka, Minoru Kawamura, Tatsuya Okawa, Yoshio Kaneko, Shiro Sakai, Motoaki Hirayama, Ryotaro Arita, Kiyohiro Adachi, Daisuke Hashizume, Yoshinori Tokura

Materials Science

A Neural-Network Framework to Learn History-Dependent Constitutive Laws and Identifiability of Internal Variables

Mayank Raj, Lianghao Cao, Andrew Stuart et al. (+1 more)

The identification of constitutive laws is ubiquitous in engineering: in modeling of materials where experimental data are fitted to mathematical models or learning surrogate models to beat the FE\textsuperscript{2} computational cost of multiscale numerical simulations. However, these models of constitutive laws, unless equipped with a potential formulation, are not necessarily consistent with (a) the second law of thermodynamics; (b) stability of the material under extreme applied strain; and (c) the mathematical theory underpinning the existence of solutions of the governing equation. In this work, we present a causal and energetic formulation, consistent with aforementioned properties, of learning a history-dependent constitutive law. This characterization of the class of internal variables sheds light on the equivalence class of equivalent surrogate models for the constitutive law. We show that the internal variables that are learned from the data are unique up to a linear transform. The framework is deployed to learn the Taylor-averaged response of a polycrystalline magnesium unit cell. We achieve 2% relative error in the prediction of the Taylor-averaged response.
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All authors Mayank Raj, Lianghao Cao, Andrew Stuart, Kaushik Bhattacharya

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

Observation of Switchable Chiral Magnons in an Altermagnet

Zheyuan Liu, Hodaka Kikuchi, Zijun Wei et al. (+8 more)

Chiral magnons, the quanta of handed spin waves, transport spin angular momentum without energy loss due to Joule heating. The recently discovered altermagnets were proposed to host chiral magnons arising from a non-relativistic exchange mechanism, similar to that in ferromagnets but without net magnetization, offering a stray-field-free platform for efficient magnon spin-current manipulation. In this work, we directly observed chiral magnons in the altermagnetic prototype MnTe using polarized inelastic neutron scattering. Furthermore, the magnon chirality was found to be reversibly switched by magnetic-field control, establishing a robust foundation for functional altermagnetic magnonics.
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All authors Zheyuan Liu, Hodaka Kikuchi, Zijun Wei, Shinichiro Asai, Mechthild Enderle, Ursula B. Hansen, Vasile O. Garlea, Manh D. Le, Gøran J. Nilsen, Igor A. Zaliznyak, Takatsugu Masuda

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

Switchable Surface Linear Photogalvanic Effect in the Magnetic Weyl Semimetal Co3Sn2S2

Niket Shah, Aymen Nomani, Kai Chen et al. (+2 more)

We investigate the linear photogalvanic effect (LPGE) on the surface of the magnetic Weyl semimetal Co3Sn2S2 using a Green's-function and diagrammatic formalism. While the LPGE vanishes in the centrosymmetric bulk, it is symmetry-allowed on the surface where inversion symmetry is broken. We show that unitary crystal symmetries on the surface produce characteristic sign reversals of the total photocurrent at certain polarization angles upon flipping the magnetization. We further find that the intrinsic contribution to the LPGE is strongly constrained by an antiunitary mirror symmetry, which forces several nonlinear response tensor elements to vanish. In contrast, the extrinsic contribution is not subject to these constraints and displays a large magnitude which, we argue, is due to the enhanced density of states associated with Fermi-arc surface states. The current exhibits an approximately linear temperature dependence and a low-frequency power-law scaling, |jy| proportional to omega^-2.2, with weak temperature dependence of the scaling exponent. Our results identify Co3Sn2S2 as a promising platform for experimentally accessing symmetry-controlled nonlinear transport in realistic systems and for applications in magnetically controlled optoelectronic devices.
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All authors Niket Shah, Aymen Nomani, Kai Chen, Hridis K. Pal, Pavan Hosur

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

Monolithic axial InGaAs quantum dot emitters in GaAs-based nanowires via Sb-mediated facet engineering

Hyowon W. Jeong, Aris Koulas-Simos, Imad Limame et al. (+6 more)

GaAs-based nanowires hosting active quantum heterostructures provide a promising route toward monolithic integration of single-photon sources on silicon, a key requirement for scalable quantum photonics. However, ultrathin axial quantum-emitter formation is often hindered by facet-dependent growth dynamics and rotational twins, which induce lateral overgrowth and compromise interface abruptness. Here, we develop InGaAs-based quantum emitters by tailoring facet evolution via dilute Sb incorporation, which efficiently suppresses twins and promotes confined axial insertion at the growth-front facet. This approach significantly enhances the probability of obtaining abrupt, few-nanometer-thin quantum dots at the nanowire tip. Single-nanowire optical spectroscopy reveals intense, spatially localized emission from the active region with lifetimes as short as (0.51 $\pm$ 0.02) ns, and second-order photon-correlation measurements consistently exhibit pronounced antibunching with $g^{(2)}(0)<0.4$, confirming single-photon emission. These results establish a strong correlation between twin density and axial heterostructure formation, identifying defect control as a key factor in realizing monolithically integrated nanowire single-photon sources.
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All authors Hyowon W. Jeong, Aris Koulas-Simos, Imad Limame, Markus Döblinger, Sang Kyu Kim, Chirag C. Palekar, Jonathan J. Finley, Stephan Reitzenstein, Gregor Koblmüller

Materials Science

Circularity in Perovskite-Based Tandem Photovoltaics for Terawatt-Scale Deployment

Abderrahime Sekkat, Shiling Dong, Jenny Baker et al. (+4 more)

As photovoltaics (PVs) scale from one to multiple terawatts over the next decade, ensuring sustainable deployment is urgently required. Crystalline silicon (c-Si) PVs, the current industry standard, will generate an estimated 160 million tonnes of waste by 2050, and there remains complex technoeconomic challenges associated with their recycling. Metal-halide perovskite (MHP)-based tandem PVs not only promise higher power conversion efficiencies than single-junction c-Si devices, but also offer intrinsic advantages for circularity, including simpler device architectures, low-temperature processing, and more accessible materials recovery routes. At this pivotal juncture when perovskite PVs begin to enter the market, this review examines the critical circularity challenges that must be addressed: substitution of scarce raw materials, scalable recycling protocols, cost-effective stack delamination, safe lead sequestration, and policy frameworks to encourage circularity across the device lifecycle with effective incentives. By integrating the materials, technoeconomic and policy dimensions that go beyond conventional lifecycle assessments, we outline actionable strategies to co-optimize device performance and sustainability. This review aims to guide researchers, policymakers, and industry stakeholders in steering perovskite-based tandem PVs towards a circular and responsible commercialization pathway within the global clean-energy transition.
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All authors Abderrahime Sekkat, Shiling Dong, Jenny Baker, Matt Burnell, Tapas Mallick, Ruy S. Bonilla, Robert L. Z. Hoye

Materials Science

Engineering topological flat bands in $\Gamma$-valley moiré systems with Ising-type SOC: twisted 1T-ZrS$_2$ and 1T-SnSe$_2$

Hanqi Pi, Yves H. Kwan, Haoyu Hu et al. (+8 more)

Twisted moiré superlattices hosting topological flat bands provide a platform to explore the interplay between topology and correlations. Here we investigate topological band structures in $\Gamma$-valley moiré systems based on 1T-ZrS$_2$ and 1T-SnSe$_2$. Using large-scale ab initio calculations and continuum modelling, we demonstrate that both materials exhibit an approximate spin-$U(1)$ symmetry and host isolated topological moiré valence bands, including quantum spin Hall and high spin Chern states. By constructing a hierarchy of $\Gamma$-valley moiré continuum models, we show that isolated moiré bands carry a trivial $C_3$ symmetry indicator when the low-energy physics is described by a single effective orbital and a single layer-hybridized branch, either bonding or antibonding. Topological bands therefore arise from inter-branch and/or inter-orbital coupling. Moreover, we determine interaction-driven phase diagrams using Hartree–Fock and exact diagonalization, finding various phases tunable by twist angle, interaction strength, and displacement field. We identify specific conditions under which fractional Chern insulators are favored. Together with previous work showing that the moiré conduction bands of 1T-ZrS$_2$ and 1T-SnSe$_2$ realize $M$-valley twisting and host quasi-one-dimensional physics, our results establish these systems as ideal platforms for strongly correlated moiré physics and provide a systematic framework for understanding topological band structures in $\Gamma$-valley moiré materials.
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All authors Hanqi Pi, Yves H. Kwan, Haoyu Hu, Yi Jiang, Dumitru Călugăru, Jie Shan, Kin Fai Mak, Miguel M. Ugeda, Dmitri K. Efetov, Maia G. Vergniory, B. Andrei Bernevig

Materials Science

Rongzai agent: A Large Language Model-Based Autonomous Assistant for Rietveld Refinement of Neutron Diffraction Data

Qingmeng Li, Hao Wang, Dongbo Xiong et al. (+11 more)

Neutron diffraction (ND) is an indispensable technique for determining atomic positions (especially light elements) and thus serves as a critical probe for revealing microscopic structures in materials science. However, traditional Rietveld refinement of ND data relies heavily on manual operation of specialized software, which is time-consuming, labor-intensive, and highly dependent on user expertise, severely hindering automated analysis. The automation of Rietveld refinement has long been a long-standing and challenging problem in crystallography. To address this challenge, this paper presents the Dr.Sai-Rongzai agent, an autonomous refinement assistant based on a large language model (LLM), a specialist knowledge base, and the GSAS-II refinement engine, achieving for the first time an intelligent refinement that integrates knowledge-driven decision-making. The agent accomplishes a fully automated workflow from natural language task parsing to autonomous decision-making, execution of refinement strategies, and report generation. Evaluation on five representative samples shows that the Rongzai agent achieves lower Rwp values than human specialists on three samples (2.88% vs. 4.42%, 5.06% vs. 5.40%, 7.60% vs. 9.00%), while on the other two samples its results are very close to those of the specialists. The agent is currently deployed at the China Spallation Neutron Source (CSNS) and is open for external user registration, providing an intelligent and user-friendly analytical tool for materials research. This work fully leverages the cutting-edge advantages of LLM, offers a new path to solve the long-standing problem of automated refinement, takes a key step toward intelligent and fully automated crystallographic analysis, and holds great potential to accelerate AI for Science discoveries in neutron-based materials characterization.
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All authors Qingmeng Li, Hao Wang, Dongbo Xiong, Jiajun Zhong, Wenhai Ji, Hao Hu, Yiyu Zhang, Bolun Zhang, Hong Wang, Yongfeng Zhu, Rong Du, Zhengde Zhang, Fazhi Qi, Junrong Zhang