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Physics Condensed Matter Materials Science

cond-mat.mtrl-sci Watch Materials Science

Monday 1 June

Materials Science

Stacking-Engineered Switchable Altermagnetism in Topological FeSe bilayer systems

Jie Li, Shifang Li, Mengyang Zhang et al. (+3 more)

Altermagnetism and topological insulators represent two of the most transformative frontiers in modern condensed matter physics, spintronics, and quantum information science. Bringing these two paradigms together opens a largely unexplored route toward fundamentally new quantum phenomena. Here, we predict a topological altermagnetic phase in bilayer tetragonal Fe-based superconductors and reveal it as a highly tunable platform for valley-polarized anomalous Hall physics. Based on first-principles calculations, we show that the characteristic spin-splitting and valley polarization can be effectively tuned via applied strain. Moreover, the resulting valley-polarized anomalous Hall conductivity can be manipulated by shifting the Fermi level. These findings reveal a powerful route for controlling altermagnetism in topological materials and identify a realistic material platform for its experimental realization and technological exploitation.
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All authors Jie Li, Shifang Li, Mengyang Zhang, Pan Zhou, Jianxin Zhong, Ruqian Wu

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

Moire-Engineered Excitonic Landscape and Phonon-Mediated Recombination in Twisted WSe2 Bilayers

Memansa Thapa, Aksa Thomas, Jayalekshmi U. J. et al. (+7 more)

We report light emission from the moire superlattice of a twisted bilayer of tungsten diselenide (WSe2/WSe2) encapsulated in insulating hexagonal boron nitride (hBN). The low-temperature photoluminescence (PL) spectroscopy reveals signatures of moire-potential induced strong interlayer excitonic emission and phonon-assisted recombination, while the twisting significantly suppresses the emission from localized defect-bound excitons. The moire potential redistributes carriers into indirect valleys, thereby enhancing recombination efficiency and stabilizing the interlayer excitons. Our findings establish that precise control of twist angle and dielectric environment provides a new route for engineering excitonic systems for exploring exciton-phonon interactions and associated quantum phenomena in transition metal dichalcogenides.
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All authors Memansa Thapa, Aksa Thomas, Jayalekshmi U. J., Krishna Prasad Bera, Darshit Solanki, Kenji Watanabe, Takashi Taniguchi, Ajay Kumar Shukla, Anindya Das, Ajay Soni

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

Roughness-controlled Tribocharging Governs Friction in Dry Glass Contacts

Liang Peng, Begum Demirkurt, Thibault Roch et al. (+3 more)

Friction is commonly reduced by polishing surfaces, based on the idea that roughness enhances mechanical interlocking and thus friction. Here we show that, for dry glass-glass contacts, increasing nanoscale roughness can instead reduce friction because it suppresses triboelectric adhesion. Using rheometer-based friction measurements in dry nitrogen, super-resolution imaging of the real contact area, soft x-ray discharge, and Faraday-cup electrometry, we demonstrate that sliding generates substantial tribocharges whose electrostatic attraction contributes significantly to friction. As the root-mean-square surface slope h'_rms of the glass ball is increased from 0.01 to 0.09, the real contact area and retained tribocharge both decrease strongly, while the average contact pressure increases by a factor of three; nevertheless, the friction coefficient drops by about 30%. Discharging the interface with soft x-rays largely removes the roughness dependence of friction. Our results show that nanoscale roughness controls tribocharging and electroadhesion in dielectric contacts, inverting the classical relation between roughness and friction and identifying triboelectric effects as a key design parameter for friction control.
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All authors Liang Peng, Begum Demirkurt, Thibault Roch, Albert M. Brouwer, Bart Weber, Daniel Bonn

Materials Science

Charge dynamics in the Weyl semimetals NbIrTe$_4$ and TaIrTe$_4$ under pressure: Signatures of an electronic phase transition

M. Lamp, J. Ebad-Allah, A. Chmeruk et al. (+7 more)

A high-pressure investigation of the Weyl semimetals NbIrTe$_4$ and TaIrTe$_4$ is presented, using infrared spectroscopy supplemented by density functional theory calculations. The experimental optical conductivity spectra as a function of pressure suggest the occurrence of a pressure-induced phase transition at a critical pressure $P_\text{c}=7\text{--}8$ GPa. This transition is most likely electronic in nature, as Raman scattering measurements provide no evidence of a significant structural phase transition. Above $P_\text{c}$ a significant redistribution of spectral weight occurs in the optical conductivity spectrum for both materials. A Drude-Lorentz analysis of the optical data indicates a sharp reduction in the free carrier concentration at $P_\text{c}$, concomitant with the appearance of a low-energy phonon, which was initially screened by free charge carriers. A predominantly electronic origin of the phase transition is supported by the calculated electronic band structure, Fermi surface, and interband optical conductivity as a function of pressure. Our findings provide collective evidence for a pressure-induced, most likely electronic phase transition in both van der Waals materials at $P_\text{c}=7\text{--}8$ GPa, highlighting the tunability of their electronic band structure by hydrostatic pressure.
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All authors M. Lamp, J. Ebad-Allah, A. Chmeruk, N. Bura, R. Schönemann, L. Balicas, S. H. Lee, Z. Q. Mao, L. Chioncel, C. A. Kuntscher

Materials Science

Deep Learning-Accelerated Dynamic Kinetic Monte Carlo Simulation for Hydrogen Transport in Tungsten

Seiki Saito, Keisuke Takeuchi, Hiroaki Nakamura et al. (+5 more)

In magnetic confinement fusion reactors, hydrogen plasma irradiation causes material saturation and recycling, where hydrogen released from the tungsten wall significantly impacts the peripheral plasma. Kinetic Monte Carlo (kMC) simulations are essential for investigating the dynamic balance between incident and emitted fluxes at the atomic scale. However, standard kMC frameworks are inadequate for handling realistic material complexities, such as polycrystalline structures and dynamic evolution under irradiation, being computationally bottlenecked by continuous transition parameter updates. Conventionally, evaluating migration barriers in disordered systems (e.g., grain boundaries) relies on computationally prohibitive on-the-fly atomistic calculations like the Nudged Elastic Band (NEB) method. Here, we present a deep learning-accelerated Dynamic kMC framework that eliminates this reliance. Our approach integrates a three-stage deep learning pipeline: a pix2pix model for predicting local 3D potential energy distributions, a U-Net for extracting hydrogen trapping sites, and a 3D-CNN for directly evaluating migration barriers. To achieve macroscopic timescales, we implemented a hierarchical spatial index combined with a differential local-update algorithm operating in O(1) complexity. This architecture restricts recalculations to the immediate vicinity of moving atoms, accelerating updates. Demonstrated on a large-scale realistic polycrystalline tungsten model, the framework successfully reproduces preferential hydrogen trapping along grain boundaries, bridging the gap between atomic-scale accuracy and macroscopic timescales for full-scale plasma-wall interaction simulations.
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All authors Seiki Saito, Keisuke Takeuchi, Hiroaki Nakamura, Yasuhiro Oda, Kazuo Hoshino, Yuki Homma, Shohei Yamoto, Yuki Uchida

Materials Science

Giant dielectric permittivity in Nb-doped rutile crystals

D. Nuzhnyy, V. Bovtun, J. Petzelt et al. (+13 more)

Dielectric properties of Nb-doped (~1.5 at%) rutile single crystals were studied in the 10-300 K temperature range (at frequencies below the MHz range down to 0.3 K) in a broad frequency range, up to terahertz and infrared range, to understand the origin of its giant permittivity. The results were fitted, modelled and compared with those of the undoped rutile crystal measured in the terahertz and infrared ranges. The primary effect originates from the near-electrode depletion layer of lower conductivity compared to the bulk (surface barrier-layer capacitor effect), which causes a strong thermally activated relaxation in the MHz dielectric spectra. In the higher frequency range, the main difference between doped and undoped crystals is the presence of an overdamped microwave excitation (central mode) in the doped crystal for both polarizations, persisting down to 10 K and not thermally activated. This accounts for the previously reported permittivity increase, even at 2 K - where all lower-frequency relaxations are frozen - compared to undoped crystals. It also explains why our low-frequency permittivity at 0.3K exceeds the THz value. The origin of this excitation remains unclear and requires further investigations. Doping affects polar phonons only by slightly increasing their damping.
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All authors D. Nuzhnyy, V. Bovtun, J. Petzelt, M. Savinov, M. Kempa, P. Levinský, P. Vaněk, T. Kmječ, T. Ostapchuk, P. Kužel, J. Hlinka, D. Crandles, M. Cosco, Y. Hashimoto, H. Taniguchi, S. Kamba

Materials Science

Interface Symmetry and Electrostatic Stabilization of Strain-Resilient Janus Heterobilayers for Flexible Piezotronics

Surender Kumar, Mostafa Torkashvand, Stefan Velja et al. (+1 more)

The electronic structure of conventional two-dimensional transition metal dichalcogenides (TMDs) is highly sensitive to lattice deformation, often leading to indirect-to-direct band-gap transitions that compromise performance in flexible nanoelectronic applications. Janus TMDs, with their broken mirror symmetry and intrinsic out-of-plane dipoles, offer a promising alternative platform for electrostatic tuning. However, their electronic stability under strain and the role of the chalcogen stacking sequence in their heterostructures remains poorly understood. Here, we study from first principles the strain tolerance and piezoelectric properties of MoSSe/WSSe heterobilayers. By examining different configurations, we demonstrate that the interface chemistry strongly modulates interlayer coupling, dynamic charge redistribution, and dipole interactions. Importantly, the combined effects of intrinsic electric fields and interface electrostatics effectively suppress the strain-induced band-gap transitions typical of conventional TMDs. Moreover, while the in-plane piezoelectric response remains nearly insensitive to the stacking order, the shear piezoelectric coefficient depends heavily on the interfacial symmetry and can be effectively tuned by strain modulation. Our results highlight interfacial engineering as a powerful route to design strain-resilient Janus heterostructures for next-generation flexible optoelectronic, valleytronic, and piezotronic devices.
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All authors Surender Kumar, Mostafa Torkashvand, Stefan Velja, Caterina Cocchi

Materials Science

Iterative Thermodynamic Augmentation of Spatially Resolved Analytic Microscopy for Fast-Diffusing Solutes

Santiago Benito, Louis Becker, Niels Jöns et al. (+1 more)

The spatially resolved quantification of fast-diffusing solutes presents several challenges in analytic microscopy. Given the critical role of interstitially alloyed elements in physical metallurgy, we propose a computational framework that addresses this limitation by augmenting spatially resolved composition maps of substitutional elements with computationally derived interstitial distributions. The underlying methodology is an iterative thermodynamic model: exploiting the stark differences in solid-state diffusion kinetics, the model assumes a state of partial chemical equilibrium exclusively for the mobile interstitial species. An optimization scheme iteratively adjusts an uniform interstitial chemical potential across the mapped microstructure until the integrated local concentration converges with an independently measured bulk value. Ultimately, this approach extracts thermodynamically consistent interstitial concentration maps from robust, low-noise microscopy data, yielding quantitative spatial arrays that are otherwise time- and resource-intensive to obtain at best.
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All authors Santiago Benito, Louis Becker, Niels Jöns, Sebastian Weber

Materials Science · Cross-listed from cond-mat.supr-con

Evolution of the intertwining correlated topological phases in iron-based superconductor Fe(Te,Se)

Yue Sun, Shiying He, Zhongyi Zhang et al. (+16 more)

Multiple topological electronic phases can coexist within a single quantum material and induce different topological superconducting states, offering deeper insights into interplay of topological superconducting states and Majorana modes, which may also be influenced and modified by correlation effect. Iron-based superconductors, with both topological states and correlation effect, is an ideal platform to study these phenomena. Here, with high resolution angle resolved photoelectron spectroscopy, we directly resolve two distinct intertwining topological states in iron-based superconductor Co-doped Fe(Te,Se), and study their evolution with electron doping. We identify a region where both topological insulator surface states and topological Dirac semimetal states intersect the Fermi level. The topological states are affected by the strong correlation effect and are isolated from trivial bulk states. The evolution between distinct topological phases offers a good opportunity to study various Majorana modes from different superconducting phases according to theoretical analysis. Our findings establish an ideal platform for exploring the interaction between multiple topological superconducting states and the related Majorana modes.
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All authors Yue Sun, Shiying He, Zhongyi Zhang, Yong Huang, Jingheng Chen, Weixiang Yan, Chunbo Yu, Yuyang Dong, Kohei Aido, Xin Zhou, Zhengtai Liu, Mao Ye, Jishan Liu, Haruhisa Kitano, Zhixiang Shi, Hong Ding, Takeshi Kondo, Xianxin Wu, Peng Zhang

Materials Science · Cross-listed from cond-mat.supr-con

Excitonic-Superconducting Coexistence and Emergent Nematic Superconductivity Driven by Spontaneous Symmetry Breaking

Fei Yang, Ruigang Li, Junwei Liu et al. (+1 more)

Excitonic insulating (EI) and superconducting (SC) orders are generally regarded as mutually exclusive electronic instabilities. Within a self-consistent microscopic theory, we study electronic systems hosting an EI phase in the presence of SC pairing and show that an intrinsic mismatch between electron and hole Fermi surfaces fundamentally reshapes this competition. This mismatch stabilizes FFLO-like electron-hole pairing and drives spontaneous symmetry breaking of the EI state. The resulting symmetry breaking reconstructs the pairing phase space for SC and EI state, such that different regions of the Fermi surface complementarily support either EI or SC correlations, leading to a natural coexistence of the two orders. Notably, the emergent SC state consequently breaks rotational symmetry and develops intrinsic nematic superconductivity, even in the absence of explicit symmetry-breaking fields (such as magnetic fields, spin-orbit coupling, or bare band-structure anisotropy). Our results suggest that candidate materials such as monolayer 1T$'$-MoTe$_2$ and the square-net semimetal NaAlSi may provide promising platforms for observing this phenomenon. More broadly, these findings reveal a unique mechanism by which competing many-body orders generate electronic nematicity, suggesting a broader route toward spontaneous anisotropic electronic states in correlated quantum materials.
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All authors Fei Yang, Ruigang Li, Junwei Liu, Binghai Yan

Materials Science

Polaron Transport in TiO$_{2}$ from Machine Learning Molecular Dynamics

Christian S. Ahart, Denan Li, Jochen Blumberger et al. (+1 more)

Transition metal oxides have attracted much attention as photo(electrochemical)-catalysts but practical applications are typically hampered by their low and anisotropic charge mobility. A deep understanding of excess charge carrier transport in these materials requires a dynamical treatment of nuclear motion that goes well beyond standard approaches. Here we introduce DeepPolaron, a machine learning framework boosting the accessible time scale of first principles molecular dynamics of adiabatic polaron transport by three orders of magnitude at a virtually negligible loss in accuracy. We apply our method to excess electron and hole transport in titanium dioxide rutile and anatase. We find that the excess electron in rutile relaxes to a polaron predominantly localized on a single Ti atom with hopping occurring only along the [001] direction, associated with an activation energy of 39 meV and a room temperature mobility of $4.4 \times 10^{-2}$ cm$^2$/Vs in good agreement with experiment. In contrast the hole polaron in anatase is localized on a single O atom, and due to poor O 2p orbital overlap with first nearest neighbors charge transport occurs primarily to second nearest neighbors, with a large activation energy of 139 meV resulting in a small room temperature mobility of $1.4 \times 10^{-3}$ cm$^2$/Vs. This work provides a finite temperature first-principles characterization of small polaron transport in rutile and anatase, with a methodology that is directly transferable to other small polaron forming materials and interfacial charge-transfer processes.
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All authors Christian S. Ahart, Denan Li, Jochen Blumberger, Shi Liu

Materials Science

Hydrogen trapping and interfacial decohesion at the {\alpha}-Al2O3(0001)/Fe(110) interface

Youngseok Hwang, Norihito Sakaguchi and Yuji Kunisada

Hydrogen embrittlement and tritium leakage pose critical challenges for fusion reactor structural components, rendering {\alpha}-Al2O3/Fe interfaces vital as tritium permeation barriers. Here, the thermodynamic stability, trapping energetics, and hydrogen-induced decohesion at the {\alpha}-Al2O3 (0001)/Fe(110) interface were systematically investigated using density functional theory. Single-hydrogen incorporation reveals that the Fe-hollow site is the most stable trapping region, owing to local free volume and heterogeneous interfacial bonding. Multi-hydrogen analysis demonstrates that trapping behavior is concentration-dependent; increasing hydrogen concentration progressively reduces the available free volume and increases local lattice distortion. As a result, simulated cleavage processes show a monotonic decrease in cleavage energy with accumulation. At high hydrogen concentrations, cleavage energy turns negative, indicating spontaneous interfacial exfoliation. These quantitative insights clarify the atomistic degradation mechanisms of protective oxide scales, offering a theoretical framework for optimizing high-performance permeation barriers in fusion-relevant steels.
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Materials Science · Cross-listed from cond-mat.soft

Resonant Coupling and the Non-Phononic Flat Band in Amorphous Solids

Matteo Baggioli and Bingyu Cui

Recent experiments and simulations provide compelling evidence for the emergence of a non-phononic flat band in the dynamical structure factor of two- and three-dimensional amorphous solids. This feature has been suggested to be connected to the excess in the reduced vibrational density of states of glasses, commonly known as the boson peak, and displays several apparently universal characteristics. First, it is nearly dispersionless, with an energy close to the boson-peak frequency. Second, its intensity is negligible below a critical wave vector of the order of the first diffraction peak. Third, its reduced intensity exhibits a strong correlation with the static structure factor. Here, we revisit the resonant-coupling model, a single-mode harmonic realization of the soft-potential scenario in which acoustic phonons interact with single frequency quasi-localized vibrations. We show that, under minimal phenomenological assumptions, this framework naturally reproduces the main features of the observed flat band and clarifies its connection to the boson peak.
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Materials Science

Altermagnetism in MnF$_2$: Band Splitting and Its Physical Consequences

Igor Solovyev

MnF$_2$ is widely regarded as a candidate altermagnet, but the magnitude and implications of its altermagnetic band splitting remain debated. Using electronic-structure calculations, we construct minimal models that capture the magnetic and electronic properties of MnF$_2$. These models show that the parameters governing the chiral magnon splitting and the spin splitting of the electronic bands are relatively small. Moreover, the electronic system lies in the strong-coupling regime, where most magnetic properties are controlled by the ratio $t/U$ between the characteristic hopping amplitude $t$ and the large on-site Coulomb repulsion $U$. Consequently, all exchange interactions scale as $1/U$, so a small altermagnetic hopping $\delta t$ produces only a proportionally small exchange term. Upon doping, the altermagnetic contribution to the anomalous Hall effect is likewise suppressed, being smaller than the conventional (non-altermagnetic) contribution by a factor of order $\delta t/U$. In contrast, the behavior of the conductivity tensor $\hat{\sigma}(\omega)$ at $\hbar \omega \sim U$ differs qualitatively, because $\delta t$ enters the energies of interband optical transitions directly rather than through the reduced ratio $\delta t/U$. This contribution strongly reshapes $\hat{\sigma}(\omega)$, leading to a dramatic enhancement of the magneto-optical response.
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Sunday 31 May

Materials Science · Cross-listed from cs.AI

Self-Revising Discovery Systems for Science: A Categorical Framework for Agentic Artificial Intelligence

Fiona Y. Wang and Markus J. Buehler

Scientific discovery is not only answer generation but revision of the representational regime in which evidence, artifacts, operations, and verifiers are typed. We develop a category-theoretic account of agentic discovery for materials science. In a fixed regime b with schema category S_b, the system state is a copresheaf I_t: S_b -> Set, and provenance is the category of elements \int_{S_b} I_t. Fixed-regime operation is an update on such states, endofunctorial only when provenance-preserving refinements are specified and preserved. Discovery is instead a verified regime transition u: S_b -> S_b': old artifacts are preserved, transported by the left Kan extension Lan_u I_t, and compared with the post-transition state to identify residual content beyond functorial transport. This separates retrieval, search, and discovery without subjective novelty. We instantiate the framework in two systems. In Builder/Breaker, a protein-mechanics world model is revised under a Minimum Description Length gate; the accepted law expresses within-chain flexibility as all-mode elastic compliance conditioned by slow collective-mode participation, or mode-conditioned compliance. In CategoryScienceClaw, typed skills, artifacts, open needs, workflow mutation, gates, stress tests, and public discourse become a proof-carrying knowledge-computation graph. A fiber-network example records candidate models, rejected alternatives, an AIC gate, perturbation tests, and an accepted orientation-tensor anisotropic stiffness surrogate over an isotropic fiber-count descriptor. Together, the cases show how category theory can be both a mathematical language for discovery and an engineering specification for self-revising AI discovery systems.
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Materials Science · Cross-listed from cond-mat.mes-hall

Quantum Statistics and Structural Topology Govern Thermal Transport in Two-Dimensional Monolayer Amorphous Carbon

Gizem Kurt and Haldun Sevincli

We investigate the quantum thermal conductivity (TC) of two-dimensional monolayer amorphous carbon (MAC). We employ three distinct amorphization algorithms to generate various possible MAC configurations, ranging from Zachariasen-type continuous random networks to nanocrystallites embedded in random networks. The local bond order parameter, q3, is used to quantify the amorphousness of the structures, and TC is computed as functions of q3 and temperature. This framework enables us to assess how structural topology, degree of amorphization, and quantum statistics contribute to heat conduction in a two-dimensional amorphous solid. At room temperature, TC values are predicted to range between 3.5 to 10 W/m/K, in agreement with recent experiments. Analysis of vibrational modes reveals that, while the modes of these 2D amorphous structures fall into the usual categories, namely, propagons, diffusons, and locons, their polarization characteristics display distinct behavior. Owing to the fully quantum mechanical framework, we examine both low- and high-temperature characteristics of this 2D amorphous system. By examining the classical limit, we show that classical treatments substantially overestimate the TC of MAC; namely, the quantum TC is less than half of the classical value at room temperature and up to nearly an order of magnitude lower at low temperatures.
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Materials Science · Cross-listed from cond-mat.mes-hall

Quantized orbital and spin Hall transport: interplay between $sp$-hybridization, altermagnetism and spin-orbit coupling

Saikat Saha, Banasree Sadhukhan and Tanay Nag

We here explore the emergence of orbital and spin Hall effects, originating beyond the $L$-$S$ coupling, and investigate the interplay between inter-orbit hybridization, relativistic Rashba spin-orbit coupling (SOC), and non-relativistic SOC, namely altermagnetic (AM) order, in a two-dimensional model Hamiltonian. The orbital (spin) Hall responses are remarkably found to be quantized within a window of Fermi energy when the strength of AM order (Rashba SOC) exceeds (falls below) the scale set by $sp$-hybridization. Importantly, orbital and spin Hall quantizations are independent of Rashba SOC and AM order, respectively, while the uniform profiles of finite orbital and vanishingly small spin moments of bands around the Fermi energy. The microscopic origin of such quantization comes from the Fermi surface-activated orbital and spin Berry curvatures. The extent of the quantized regime is strongly controlled by the intra-orbital coupling strength. As the temperature increases, the quantization is significantly compromised in the spin Hall case. We extend our analysis to the orbital and spin Nernst coefficients where the pronounced dip-peak structures signal the existence of the quantization leading to experimental relevance.
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Materials Science

Flat interface between amorphous ices and the role of MDA-like intermediate states in the LDA-HDA transformation

Anastasiia Shupletsova and Vladimir Stegailov

The pressure-induced transformation between low-density amorphous ice (LDA) and high-density amorphous ice (HDA) is a prototypical polyamorphic transition, yet its microscopic mechanism - and in particular the nature of intermediate amorphous (IA) states - has long remained unresolved. We present the first characterisation of a flat LDA||HDA interface, determining its equilibrium thickness and showing its link to medium-density amorphous ice (MDA). Interestingly, the thickness of the interfacial layer remains constant under compression, while its position shifts reversibly into the LDA region - an elastic response that exhibits kinetic hysteresis upon decompression, reminiscent of memory effects. For high-precision discrimination of amorphous ices, we use a neural network classifier based on SOAP (Smooth Overlap of Atomic Positions) descriptors. The systematic description of the local structure emphasizes the importance of orientational information from the hydrogen bond network. Furthermore, this approach enables molecular dynamics analysis of the LDA-to-HDA transformation, directly mapping the spatial distribution of intermediate structures relative to growing HDA domains and the surrounding LDA matrix, and revealing that MDA-like IA configurations are not a distinct bulk phase but rather localise at the LDA-HDA interface.
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Materials Science

Resonant Raman scattering in bilayer 3R-MoS$_{2}$

Chinmay K. Mohanty, Kacper Walczyk, Tomasz Woźniak et al. (+5 more)

Raman scattering is a powerful spectroscopic technique widely employed to investigate light-matter interactions and lattice dynamics in two-dimensional materials. Here, we investigate the temperature-dependent resonant Raman response of bilayer 3R-MoS$_2$. The study combines multi-wavelength Raman spectroscopy, photoluminescence measurements, and density functional theory calculations to track the evolution of excitonic transitions and resonance conditions. We observe contributions from both zone-centre and finite-momentum phonons, a pronounced quenching of the Stokes intensity at low temperatures followed by saturation, the emergence of anti-Stokes scattering above 130~K, and a strong deviation of the effective phonon temperature from the lattice temperature induced by resonance effects. These results demonstrate that the Raman response is governed by the interplay between incoming and outgoing resonance processes, providing deeper insight into exciton-phonon coupling in van der Waals materials.
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All authors Chinmay K. Mohanty, Kacper Walczyk, Tomasz Woźniak, Chengcheng Jiang, Adam Babiński, Clement Faugeras, Zhaolong Chen, Maciej R. Molas

Materials Science

High-quality Nano-patterning of Oxide Interfaces Using Transferred Gold Mask

Qing Xiao, Yanling Liu, Changjian Ma et al. (+7 more)

Complex oxide interfaces, such as $\mathrm{SrTiO_3}$ and $\mathrm{KTaO_3}$ based heterostructures, host rich correlated phenomena with strong potential for advanced device applications. However, these interfaces are extremely susceptible to contamination and defect formation during nanofabrication, which often compromises device performance. Here, we present a solvent-free method for patterning oxide interfaces by employing high-resolution transferable thin metal masks in conjunction with oxygen-enriched $\mathrm{Ar^+}$ ion milling, which enables a clean and well-controlled nanofabrication process. Transport measurements demonstrate that the fabricated devices preserve their intrinsic properties, including high carrier mobilities, with negligible degradation compared to the pristine interfaces. This technique offers a convenient and robust route for engineering high-performance oxide electronic devices with precisely tailored transport characteristics.
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All authors Qing Xiao, Yanling Liu, Changjian Ma, Danqing Liu, Zhiyuan Qin, Qianyi Zhao, Chengyuan Huang, Mengke Ha, Zhenhao Li, Guanglei Cheng

Materials Science

Orbital Hall effect-driven spin-orbit torque enhancement in Ti-based systems via rare-earth interface engineering

Rohiteswar Mondal, Chennoju Raghu, Animesh Baral et al. (+2 more)

Orbital currents in light metals offer large orbital Hall conductivities, yet translating this into practical spin-orbit torque efficiency is hindered by fundamental limitations. In this work, we introduce a Gd interlayer between a Ti orbital source and a Co ferromagnet to enhance the orbital torque efficiency. Ferromagnetic resonance-based spin (orbital) pumping measurements identify an optimal Gd thickness of around 4 nm, where the orbital-to-spin conversion efficiency reaches its maximum. The Ti-thickness dependence of the inverse orbital Hall effect signal confirms a bulk orbital Hall origin in Ti and yields a qualitative orbital diffusion length exceeding 20 nm. Spin-torque ferromagnetic resonance measurements demonstrate a fivefold enhancement of the SOT efficiency in Ti(20 nm)/Co compared to a Gd(4 nm)/Co reference. Interestingly, the trilayer Ti/Gd/Co architecture exhibits a spin (orbital) torque efficiency greater than 1, which is higher than that of the bilayer Ti/Co and Gd/Co structures, irrespective of Ti thickness. These results establish rare-earth interlayer engineering as a viable route to enhanced orbital torque efficiency for next-generation spin-orbitronic devices.
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All authors Rohiteswar Mondal, Chennoju Raghu, Animesh Baral, Arabinda Haldar, Chandrasekhar Murapaka

Materials Science

How Can Machine Learning Accelerate CALPHAD Free Energy Modeling?

Chen Shen, Muhammad Waqas Qureshi, Mark Asta et al. (+2 more)

The CALPHAD framework provides a rigorous basis for thermodynamic modeling, yet its ability to predict new chemistries is restricted by limited data and by functional forms that rely heavily on composition alone. Here, we show that machine learning (ML) can address these challenges through a hybrid strategy that learns Redlich-Kister (RK) interaction coefficients directly from physically informed elemental descriptors. Using formation energies of 14-element FCC alloys generated by a universal machine-learning interatomic potential (MLIP), we benchmark three classes of models: (1) composition-based RK and ML models, (2) descriptor-based ML models, and (3) a combined ML-augmented RK approach (ML4RK). Leave-one-element-out tests highlight complementary strengths. RK models, class (1), remain the most data-efficient when binary information is available, while descriptor-based ML models, class (2), enable genuine zero-shot extrapolation to elements absent from the training set. By embedding elemental descriptors into the RK framework, the hybrid approach unifies these regimes and enables prediction of interaction parameters for otherwise unknown or data-scarce binaries, class (3). This work demonstrates a physically grounded and data-efficient route to extend CALPHAD models by combining the transferability of ML with the physical grounding, interpretability, data efficiency, and robustness of thermodynamic formalisms.
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All authors Chen Shen, Muhammad Waqas Qureshi, Mark Asta, Izabela Szlufarska, Dane Morgan

Materials Science

Statistical admissibility and long-wavelength structural convergence determine representative support in granular materials

Christian Tantardini, Fernando Alonso-Marroquin, Abdullah Alqubalee et al. (+1 more)

Representative elementary areas and volumes provide the scale bridge between resolved granular microstructure and continuum-scale material properties, yet they are still commonly selected from the apparent stabilization of a single scalar observable. Such plateaus can be false indicators of representativeness when statistically incompatible regions are averaged together or when long-wavelength structural correlations remain unresolved. We introduce a general representative-support framework for granular materials based on three sequential requirements: statistical admissibility of the sampled domain, persistent convergence of the apparent field mean and the low-wavenumber covariance spectrum, and validation against independent effective properties. The concept is tested on seven large-area backscattered-electron images of Arabian dune sands and mineral-resolved QEMSCAN maps. The structure-only criterion identifies a representative elementary area of $1536$ pixels, corresponding to approximately $2.01~\mathrm{mm}$. Without property-specific fitting or recalibration, the same physical scale transferred to the QEMSCAN grid $(\approx 2.04~\mathrm{mm})$ coincides with the onset of weak size dependence in apparent thermal conductivity, elastic stiffness, and directional Young's moduli. Thus, the representative scale inferred from long-wavelength granular organization independently predicts the convergence of distinct constitutive responses. The results show that representative support should be assigned only after both statistical compatibility and long-range structural convergence have been established. Although demonstrated here on two-dimensional dune-sand sections, the criterion is formulated for granular materials generally and has a direct mathematical extension to three-dimensional voxelized volumes.
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All authors Christian Tantardini, Fernando Alonso-Marroquin, Abdullah Alqubalee, Eduardo Garzanti

Materials Science

Giant enhancement in spin-to-charge conversion in Bi2Se3/NiFe heterostructure via interface engineering

Sourav Rajat Subhra Maitra, Poulami Manna, Ravi Prakash Singh et al. (+2 more)

Topological insulators provide a promising platform for spintronic applications owing to their spin-momentum-locked surface states and efficient spin-to-charge conversion. Among these, Bi2Se3 has been the subject of intensive investigation due to its large bulk bandgap and single Dirac cone band structure. However, spin-to-charge conversion strongly depends on the quality of the topological insulator/ferromagnet interface. Here, we investigate spin transport and spin-to-charge conversion in sputter-deposited Bi2Se3/Ti/NiFe heterostructures at room temperature. The topological insulator layer is deposited on a CMOS-compatible silicon substrate. Low-temperature magnetoresistance measurements are conducted to establish the existence of a surface conducting channel in the deposited topological insulator layer. Pure spin current is injected into the Bi2Se3 layer through the titanium spacer layer via spin pumping induced by the spin precession in microwave-driven ferromagnetic resonance of the ferromagnetic film. Spin pumping studies are carried out by varying the thickness of the Bi2Se3 layer. The Bi2Se3 thickness dependence of the Gilbert damping reveals a pronounced 55% enhancement at a thickness of 4 nm, consistent with the hybridization of the top and bottom surface states of the topological insulator layer. The spin Hall angle, a parameter that quantifies the spin-to-charge conversion efficiency, exhibits an approximately one-order-of-magnitude enhancement upon insertion of the Ti spacer compared with Bi2Se3/NiFe heterostructures without the spacer. The significant enhancement of the spin Hall angle is attributed to Ti, which inhibits interdiffusion between the Bi2Se3 and NiFe layers, thereby protecting the topological surface states. Our findings highlight the role of titanium spacers in topological spintronics applications.
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All authors Sourav Rajat Subhra Maitra, Poulami Manna, Ravi Prakash Singh, Chandrasekhar Murapaka, Arabinda Haldar

Materials Science

A literature-grounded scientific reasoning framework for defect-engineered TiO$_{2}$ photocatalysts

F. J. Dominguez-Gutierrez and E. Wierzbicka

Defect-engineered TiO$_2$ photocatalysts are extensively investigated for photocatalytic hydrogen evolution; however, the highly heterogeneous nature of the literature, including inconsistent descriptors, diverse synthesis protocols, non-uniform activity metrics, and incomplete mechanistic reporting, limits the applicability of conventional machine-learning approaches based solely on statistical regression. Here, we present a literature-grounded large language model (LLM)-assisted scientific reasoning framework for defect-engineered TiO$_2$ photocatalysts integrating curated literature data, mechanistic rule extraction, and retrieval-augmented reasoning. A harmonized database was constructed from experimentally relevant publications specifically selected for hydrogen-evolution-related defect engineering in TiO$_2$, covering polymorph-dependent behavior, hydrogenation conditions, Ti$^{3+}$ defect states, oxygen vacancies, illumination conditions, and photocatalytic activity descriptors. In parallel, mechanistic evidence sentences and publications-defined scientific rules were encoded into a structured reasoning layer enabling explainable inference beyond black-box prediction. The resulting framework combines structured experimental descriptors, semantic literature retrieval, and mechanistic interpretation to generate confidence-aware recommendations for optimal defect-engineering conditions. For example, the AI agent identified a consistent optimal anatase hydrogenation window centered at ~500 $\deg$C under H$_2$-containing atmospheres for approximately 1 h, supported by mechanistic evidence linking balanced Ti$^{3+}$/oxygen-vacancy populations with enhanced photocatalytic hydrogen evolution.
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Materials Science

Topological Surface States and Anisotropic Magnetotransport in SnSb$_6$Te$_{10}$

Mohit Mudgal, Subhajit Mandal, Bishal Das et al. (+11 more)

We have investigated the electronic structure and magnetotransport properties of SnSb$_6$Te$_{10}$ single crystals using density functional theory (DFT), synchrotron-based angle-resolved photoemission spectroscopy (ARPES), and quantum transport measurements. Our DFT calculations reveal a clear spin-orbit coupling driven band inversion between the Sb-$p$ and Te-$p$ states together with a non-trivial $\mathbb{Z}_2$ topological invariant. The calculated surface-state dispersion and hexagonally warped Fermi surface contours agree well with the ARPES measurements. Temperature-dependent transport measurements indicate dominant electron-phonon scattering, while Hall measurements confirm hole-type carriers with carrier density of the order of $10^{21}$ cm$^{-3}$. Both transverse and longitudinal magnetotransport exhibit weak antilocalization behavior, while Shubnikov-de Haas oscillations observed for $H \parallel c$ yield a Berry phase close to $\pi$, consistent with Dirac-like surface states. Furthermore, angle-dependent magnetotransport measurements reveal pronounced anisotropy associated with an anisotropic Fermi surface topology and mixed bulk-surface transport behavior. Our combined theoretical and experimental results establish SnSb$_6$Te$_{10}$ as a strong topological insulator and a promising platform for investigating topological transport phenomena in layered telluride systems.
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All authors Mohit Mudgal, Subhajit Mandal, Bishal Das, Priyanka Meena, Amarjyoti Choudhury, Vishnu Kumar Tiwari, Yogendra Kumar, Vivek Kumar Malik, Tulika Maitra, Kiyohisa Tanaka, Shinichiro Ideta, Kenya Shimada, Aftab Alam, Jayita Nayak

Materials Science · Cross-listed from cs.AI

Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach

An Vuong, Minh-Hao Van, Chen Zhao et al. (+1 more)

AI for materials science is a critical topic within AI for science, aiming to accelerate materials discovery and produce accurate property predictions. Bilayer 2D material stacking is essential for exploring new materials with novel functions and inherent phenomena, enabling the creation of new 2D bilayers for diverse real-world applications. Research on bilayer vdWs materials has made significant progress from experimental and computational perspectives. Various bilayer materials have been successfully synthe sized experimentally and the increasing utilization of high-throughput computing technology has con structed several computational two-dimensional materials databases. However, the use of AI to model bilayer stacking and predict new properties remains underexplored, necessitating further research studies. In this work, we propose a novel multimodal learning approach to study the interfaces between dissimilar materials that jointly enable new or multiple functions, and to predict new properties arising from the vertical integration (stacking) of different functional material layers under given configurations. Comprehensive experiments demonstrate the effectiveness and efficiency of our approach compared to baseline methods. Our code is available at https://github.com/AnVuong123/bimat ml.
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All authors An Vuong, Minh-Hao Van, Chen Zhao, Xintao Wu

Saturday 30 May

Materials Science · Cross-listed from quant-ph

Topological Edge States from Molecular Chirality: A General Framework for Dimerized Dipolar Arrays

Muhammad Arsalan Ali Akbar, Mohsin Raza and Sabre Kais

We establish a general theoretical framework for realizing topological edge states in dimerized arrays of chiral dipolar molecules and demonstrate that molecular handedness provides a natural and tunable route to SSH-like topology in an interacting one-dimensional setting. Starting from an effective spin-$\tfrac{1}{2}$ model generated by Stark-dressed chiral molecules, we introduce bond dimerization and show that the chirality-induced Dzyaloshinskii–Moriya interaction amplifies the effective hopping amplitudes and enlarges the bulk topological gap relative to an achiral chain of equivalent dipole strength. Using self-consistent mean-field theory with periodic- and open-boundary calculations, we map out the trivial, critical, and topological regimes through bulk spectra, complex-plane winding, and boundary-localized probability densities. A central result is that the two in-gap boundary modes carry opposite molecular chirality: the left edge state localizes on a left-handed molecule and the right edge state on a right-handed molecule, a stereochemical labeling with no analogue in conventional SSH implementations. The two-leg ladder extension supports a richer four-band bulk structure and a rung-split edge sector whose robustness is characterized by a continuous sweep of the interchain coupling. All results are expressed in dimensionless units of the reference hopping scale $t_0$, making the framework directly applicable to any dipolar molecular platform – from bialkali polar molecules at MHz coupling scales to future arrays of ultracold chiral polyatomic species. These findings establish dimerized chiral molecular arrays as a controllable and chirality-addressable platform for quasi-one-dimensional topological quantum matter.
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Materials Science

Benchmark Dataset for Catalysis on 2D MXenes

Pavlo Melnyk, Anmar Karmush, Mårten Wadenbäck et al. (+4 more)

Merging first-principles calculations with machine learning (ML), we aim to accelerate the exploration of catalytic behaviour in novel materials. We focus on two-dimensional (2D) Ti$_2$CT$_y$ MXenes, whose versatile surface chemistry makes them particularly compelling candidates for catalysis. Resolving their composition and structure under realistic conditions exceeds the reach of standard density functional theory (DFT) due to computational cost. To address this challenge, we generate a comprehensive dataset of 50,000 DFT calculations for training and 10,000 for testing, encompassing both Ti$_2$CT$_y$ MXene configurations and molecular systems, along with an additional test dataset with 1000 genuinely new, larger systems to investigate how well models generalise. We train and validate widely used and competitive machine learning interatomic potential (MLIP) models, including EquiformerV2, MACE, MatRIS, and UPET, that accurately predict atomic forces and formation energies – quantities that DFT must repeatedly compute for structural and catalytic investigations – for these 2D materials. This combined DFT-ML framework achieves computational acceleration on the order of approximately $1-4 \cdot 10^3$ (on a CPU) while maintaining desired-level accuracy (approximately +/- $10$ meV/A for forces and approximately +/- $1$ meV for per-atom energies), paving the way for more efficient investigations of MXene catalytic behaviour. Moreover, we perform an extensive qualitative evaluation of the trained models, showcasing the importance of comprehensive simulation-based comparison beyond benchmark metrics. The dataset and the trained models with the code are available at https://huggingface.co/datasets/CatalystAnonymous/catalyst_mxenes.
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All authors Pavlo Melnyk, Anmar Karmush, Mårten Wadenbäck, Ania Beatriz Rodríguez-Barrera, Johanna Rosen, Michael Felsberg, Jonas Björk

Materials Science

Catalytic precursor dissociation in Hot-Wire CVD and comparing a-Si:H growth under continuous and pulsed silane flow conditions

Swati Goyal, Karam Veer Singh, Rajiv O. Dusane et al. (+1 more)

Hot-wire Chemical vapor deposition (HWCVD) of hydrogenated amorphous silicon (a-Si:H) thin films utilizes the dissociation of silane (SiH4) precursor over heated tungsten or tantalum filaments (\geq 1600 {\deg}C). In this work, assuming catalytic dissociation mechanism, we present kinetic model for SiH4 dissociation and the resulting a-Si:H film growth. Our model calculations showed that for an identical dose of the introduced SiH4 precursor, a-Si:H thickness was considerably higher for the pulsed SiH4 flow as compared to the continuous SiH4 flow. The pulsed SiH4 flow is represented by time intervals t_ON and t_OFF, where the SiH4 flow rate (F_(SiH_4)) is at the set-point and zero, respectively. In agreement with our model calculations for an introduced 75 cm^3 (STP) SiH4 dose, the resulting a-Si:H film thickness was 175 \pm 5 nm under continuous precursor flow, whereas it considerably increased to 425 \pm 8 nm when this SiH4 dose was split into 15 shorter pulses (t_ON =15s ; t_OFF = 60s). Moreover, these a-Si:H films deposited using pulsed SiH4 flow exhibited improved electrical properties, with a dark conductivity ({\sigma_d}) of 1.1 \times 10^-11 S/cm and a photoconductivity ({\sigma_ph}) of \sim 5.8 \times 10^-5 S/cm, compared to films deposited under continuous SiH4 flow ({\sigma}_d \sim 2.5 \times 10^-10 S/cm and {\sigma}_ph \sim 3.5 \times 10^-6 S/cm).
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All authors Swati Goyal, Karam Veer Singh, Rajiv O. Dusane, Triratna P. Muneshwar