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Physics Condensed Matter Materials Science

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Sunday 15 March

Materials Science

Atomistic modeling of the hygromechanical properties of amorphous Polyamide 6,6

Karim Gadelrab, Armin Kech and Camilo Cruz

Polyamide 6,6 (PA66) is a key engineering polymer, whose unique mechanical properties arise from strong interchain hydrogen bonding. However, its hygroscopic nature makes it highly sensitive to water uptake, which markedly alters its thermomechanical behavior. Contrary to traditional experimental approaches, this study uses atomistic molecular dynamics (MD) simulations to investigate the role of water in modifying the glass transition temperature (Tg) and the viscoelastic response of amorphous PA66. Simulations capture a nonmonotonic dependence of Tg on water content. At low water concentrations, isolated water molecules bind to amide groups and restrict chain mobility, while beyond ~2.5 wt %, water clustering disrupts the hydrogen bond network and causes a pronounced Tg depression. Analysis of amide group fluctuations reveals a master correlation between local segmental dynamics and bulk density, verifying the known temperature humidity equivalence in terms of density variation. The computed Young's modulus exhibits systematic softening with increasing temperature and water content, consistent with experimental trends, albeit a more pronounced impact of water at low temperatures. Time temperature superposition behavior is observed for both dry and hydrated systems. This work provides molecular scale information on the hygromechanical coupling in PA66 and demonstrates the ability of MD simulations to predict water induced transitions that govern the macroscopic behavior of polyamides.
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Materials Science · Cross-listed from cond-mat.mes-hall

Nanoscale mapping of internal magnetization dynamics reveals how disorder shapes heat generation in magnetic particle hyperthermia

Elizabeth M. Jefremovas, Pauline Rooms, Álvaro Gallo-Córdova et al. (+4 more)

Magnetic particle hyperthermia relies on the efficient conversion of magnetic field energy into heat in biomedical applications, yet the microscopic mechanisms governing heat generation within individual particles remain poorly understood. In this study, AC magnetometry experiments are combined with dynamic micromagnetic simulations to connect microstructural features, magnetization dynamics, and macroscopic heat dissipation. Beyond macroscopic heating metrics, the heat generation is resolved at the intra-particle level, uncovering a heterogeneous landscape of localized ”hot spots” with nanometer spatial and nanosecond temporal resolution. The results demonstrate that grain size acts as a key experimentally tunable parameter, balancing anisotropy disorder and pinning strength, thereby controlling both the magnitude and spatio-temporal distribution of heat release within the particle. In particular, nanoflower architectures composed by larger grains deliver larger heat generation, while the smaller grains offer a deeper intra-particle pinning landscape, which effectively redistributes the heat generation over extended time windows. Together, our results provide a mechanistic framework linking nanoparticle microstructure to magnetic heating and establish design principles for optimizing nanoflowers as magnetic hyperthermia transducers.
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All authors Elizabeth M. Jefremovas, Pauline Rooms, Álvaro Gallo-Córdova, María P. Morales, Frank Wiekhorst, Andreas Michels, Jonathan Leliaert

Materials Science

Gas sensing potential of stacked graphene/h-BN structures: a DFT-based investigation

Martin Siebel, Pavel Rubin and Raivo Jaaniso

Using periodic DFT, we examined the adsorption of NO2, NH3, and O3 on the h-BN side of a graphene/h-BN heterostructure designed as a model gas sensor material. The h-BN overlayer serves both as an active adsorption surface and as protection that may reduce irreversible processes such as graphene oxidation. Two model systems were considered: an extended graphene/h-BN bilayer (B36N36C72) and a graphene sheet partially covered by a smaller h-BN island (B11N11C72). Their electronic structures differ strongly near the Dirac point. In the extended bilayer, the Fermi level remains aligned with that of pristine graphene, indicating negligible charge transfer. In the island-covered system, the Fermi level shifts to lower energies, reflecting electron transfer from graphene to h-BN. These differences lead to distinct adsorption behavior. NO2 binds much more strongly to B11N11C72, forming a chemical bond, while O3 dissociates on this surface but remains intact on the extended bilayer. NH3 unusually acts as an electron acceptor in the island system. Overall, NO2 and O3 substantially increase graphene conductivity, whereas NH3 induces much weaker changes. These results highlight the potential of graphene/h-BN heterostructures for gas sensing.
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Materials Science · Cross-listed from cs.LG

Geometric and Topological Deep Learning for Predicting Thermo-mechanical Performance in Cold Spray Deposition Process Modeling

Akshansh Mishra

This study presents a geometric deep learning framework for predicting cold spray particle impact responses using finite element simulation data. A parametric dataset was generated through automated Abaqus simulations spanning a systematic range of particle velocity, particle temperature, and friction coefficient, yielding five output targets including maximum equivalent plastic strain, average contact plastic strain, maximum temperature, maximum von Mises stress, and deformation ratio. Four novel algorithms i.e. a GraphSAGE-style inductive graph neural network, a Chebyshev spectral graph convolution network, a topological data analysis augmented multilayer perceptron, and a geometric attention network were implemented and evaluated. Each input sample was treated as a node in a k-nearest-neighbour feature-space graph, enabling the models to exploit spatial similarity between process conditions during training. Three-dimensional feature space visualisations and two-dimensional contour projections confirmed the highly non-linear and velocity-dominated nature of the input-output relationships. Quantitative evaluation demonstrated that GraphSAGE and GAT consistently achieved R-square values exceeding 0.93 across most targets, with GAT attaining peak performance of R-square equal to 0.97 for maximum plastic strain. ChebSpectral and TDA-MLP performed considerably worse, yielding negative R-square values for several targets. These findings establish spatial graph-based neighbourhood aggregation as a robust and physically interpretable surrogate modelling strategy for cold spray process optimisation.
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Materials Science

Role of ionic quantum-anharmonic fluctuations on the bond length alternation and giant piezoelectricity of conjugated polymers

Stefano Paolo Villani, Lorenzo Monacelli, Paolo Barone et al. (+1 more)

Functionalized conjugated polymers are promising materials for electromechanical applications due to predicted giant piezoelectricity, arising from anomalously large dynamical effective charges and an enhanced response in the proximity of the dimerization phase transition. In this work, we assess the impact of quantum ionic fluctuations on piezoelectricity using the stochastic self-consistent harmonic approximation with a Rice-Mele diatomic chain model, parametrized to reproduce hybrid-functional first-principles calculations of prototypical carbyne. The model's accuracy is validated against first-principles calculations both with and without quantum-anharmonic effects. We find that ionic fluctuations strongly impact the structural properties, with the boundary of the dimerization phase transition shifted by $34\%$. Despite quantum fluctuations in the bond length reaching magnitudes comparable to the average, the strong piezoelectric response persists. The topological enhancement of the effective charges remains robust and is even enhanced by about $\sim20\%$ thanks to a quantum-induced shrinking of the electronic gap. The piezoelectric coefficient remains dominated by the internal relaxation and retains a morphotropic-like character, reaching maximum values near the renormalized boundary, with quantum anharmonicity mainly shifting the optimal enhancement window.
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All authors Stefano Paolo Villani, Lorenzo Monacelli, Paolo Barone, Francesco Mauri

Materials Science

Self-Assembled H2NC Molecular Lattices as a Platform for Tunable Quantum Superlattices

Adrian Bahri, Zhibo Kang, Ziyan Zhu et al. (+3 more)

Compared to van der Waals moiré systems, molecular assembly has emerged as an exciting alternative platform for superlattice engineering via heterointegration. The electronic properties of the self-assembled square lattice monolayer molecular crystal of metal-free naphthalocyanine (H$_2$Nc), in particular the electronic band dispersion and their tunability by metal substrates, remain less explored. Using density functional theory, supported by angle-resolved photoemission and scanning tunneling microscopy, we compare the electronic structure of a free-standing H$_2$Nc monolayer with that of H$_2$Nc lattice assembled on noble metal substrates. In the free-standing film, we identify both nearly flat, molecule-localized states and more dispersive bands, and we show that each can be compactly described by an anisotropic tight-binding Hamiltonian that yields band-resolved hopping anisotropies. We further show theoretically the wide tunability in the inter-site hopping and Coulomb interaction based on dielectric and screening environment, and show two experimental realizations using Ag(100) and Au(111) substrates. On Ag(100), orbital hybridization between molecular frontier states and the substrate drives finite spectral weight at the Fermi level and local interfacial polarization. This hybridization enhances the effective intermolecular hopping roughly thirty-fold, drastically reducing $U/t$. Complementary angle-resolved photoemission spectroscopy resolves substantial interfacial charge redistribution and enhanced bandwidth of the HOMO band, consistent with theoretical predictions. These results clarify how metal substrates and gates convert H$_2$Nc from isolated molecules into a tunable 2D lattice, and highlight molecular superlattices as a promising platform in which the effective interaction parameters can be engineered over a wide range.
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All authors Adrian Bahri, Zhibo Kang, Ziyan Zhu, Eric I. Altman, Yu He, Chunjing Jia

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

Ab Initio Transfer Length Method Simulations of Tunneling Limits in 2D Semiconductors

Tae Hyung Kim, Juho Lee and Yong-Hoon Kim

As semiconductor devices approach the sub-2 nm technology node, identifying the quantum-mechanical limits of contact-resistance scaling becomes imperative; however, the transition from thermionic emission to direct tunneling in this deep nanoscale regime remains experimentally inaccessible and theoretically undefined. Herein, we present a systematic first-principles framework to characterize metal/2D-semiconductor interfaces at the atomic scale and identify their intrinsic contact resistance and tunneling limits. Based on large-scale multi-space density functional theory calculations, we perform ab initio transmission line model (TLM) analyses for monolayer MoS2 contacted by Sc, Ag, Au, and Pd electrodes in both top-contact and edge-contact geometries. This computational procedure reveals a universal transition in resistance scaling from metal-induced gap states-mediated direct tunneling in the sub-10 nm regime to thermionic emission at longer channel lengths. The resulting transition length provides a rigorous first-principles measure of the critical tunneling length, establishing a physically grounded metric for assessing contact quality and the source-to-drain tunneling limit of 2D ballistic transistors. Using the ab initio TLM method, we further identify optimal contact strategies-top contact with low-work-function metals for n-type operation and edge contact with high-work-function metals for p-type operation. Our study introduces a general computational framework for evaluating and comparing 2D semiconductor contacts and offers practical guidelines for engineering low-resistance, scalable contact technologies for next-generation 2D transistors.
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Materials Science

Diagonal Curvature in Second Order Jahn Teller Theory Can Be Negative: An Analytic Proof with First-Principles Confirmation in NH3

Zhian Li, Hanxiang Mi, Xiyue Cheng et al. (+2 more)

We demonstrate that the diagonal curvature in second-order Jahn-Teller theory (SOJTT) can be negative, invalidating its foundational positivity assumption. Using a frozen-phonon many-body expansion, we show no quantum-mechanical principle enforces its positivity; recasting into the Kohn-Sham framework further reveals that phonon-induced eigen-energy changes arise solely from electron-nuclear, Hartree, and exchange-correlation terms, with kinetic-energy contributions canceling identically. First principles calculations on NH3 place the D3h reference configuration at an A2" saddle point; Schwarz-inequality upper-bound analysis confines the HOMO-LUMO mixing contribution to < 0.2% of the total energy drop,while 99.8% originates from the diagonal electron-nuclear term driving N (2s-2pz) electron redistribution. These findings overturn a core SOJTT tenet and establish that spontaneous structural symmetry breaking demands prior verification of a saddle point, not assumed positivity of the diagonal curvature.
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All authors Zhian Li, Hanxiang Mi, Xiyue Cheng, Jurgen Kohler, Shuiquan Deng

Materials Science

Evolution of Phonon Transport Across Structural Phase Transitions in MgAgSb

Luman Shang, Yu Wu, Yufan Liu et al. (+3 more)

MgAgSb, a promising thermoelectric material, undergoes reversible phase transitions that drastically alter its thermal transport behavior. Using first-principles calculations, we systematically investigate the lattice thermal conductivity ($\kappa_L$) of its three phases: $\alpha$, $\beta$, and $\gamma$, revealing a progressive increase following $\alpha < \beta < \gamma$. This trend originates from distinct scattering mechanisms. Four-phonon scattering substantially suppresses the particle-like conductivity ($\kappa_p$) in the $\beta$ and $\gamma$ phases, while electron-phonon scattering provides a minor additional reduction. In contrast, the wave-like conductivity ($\kappa_c$) from coherent phonon tunneling is highest in the complex $\alpha$ phase, contributing up to 44% of $\kappa_L$. Notably, the temperature dependence of $\kappa_L$ differs fundamentally between phases: in $\beta$, the weak $\kappa_p$ variation arises from a decreasing Grüneisen parameter with temperature; in $\alpha$, the strong rise in $\kappa_c$ with temperature counteracts the decay of $\kappa_p$. Our findings establish a comprehensive picture of thermal transport in MgAgSb, highlighting the phase-dependent interplay between particle-like and wave-like phonon contributions.
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All authors Luman Shang, Yu Wu, Yufan Liu, Shuming Zeng, Gang Tang, Chenhan Liu

Materials Science

Millimeter-Scale, Atomically Controlled 2D Topological Insulators Revealed by Multimodal Spectroscopy

Woojoo Lee, Qiang Gao, Yufei Zhao et al. (+20 more)

Quantum spin Hall insulators, or synonymously known as 2D topological insulators, are crucial 2D systems hosting topologically protected edge states. The working temperature of this topological quantum phase is dictated by the inverted bandgap. However, the previously identified large-gap 2D topological insulators are either extremely chemically unstable, or cannot be made with atomistic precision over macroscopic scales. Here, we establish two-quintuple-layer Bi2Te3 and MnBi2Te4/Bi2Te3 heterostructures as atomically controlled, millimeter-scale 2D topological insulators, enabled by precision layer-by-layer growth that yields a carpet-like morphology extending coherently over macroscopic distances. This carpet-like growth mode renders the films amenable to mechanical exfoliation and subsequent wet or dry transfer. Multimodal spectroscopies and microscopies reveal the integer-layer tuned electronic structure of (Bi2Te3)n with excellent agreement to theory. Photon-energy-dependent photoemission and time-resolved photoemission identify band inversion and band dynamics, respectively, while scanning tunneling spectroscopy resolves topological edge states, characteristic of the 2D topological insulator phase. Thickness- and photon-energy-dependent photoemission further validates MnBi2Te4/Bi2Te3 as a robust 2D topological insulator. The large inverted gaps of ~100 meV in (Bi2Te3)2 and ~150 meV in MnBi2Te4/Bi2Te3 suggest operation near ambient temperature. These results define a scalable materials platform for next-generation, low-loss quantum and energy-efficient devices.
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All authors Woojoo Lee, Qiang Gao, Yufei Zhao, Hui Li, Albert Tsui, Yichao Zhang, Yunhe Bai, Haoran Lin, Khanh Duy Nguyen, Gabriele Berruto, Gangbin Yan, Jianchen Dang, Tongyao Wu, Hossein Rokni, Thomas S. Marchese, Ying Shirley Meng, Chao-Xing Liu, Xiao-Xiao Zhang, Chong Liu, Pinshane Y. Huang, Mark C. Hersam, Binghai Yan, Shuolong Yang

Materials Science

Emergent giant topological Hall effect in twisted Fe3GeTe2 metallic system

Hyuncheol Kim, Kai-Xuan Zhang, Yu-Hang Li et al. (+3 more)

The topological Hall effect, driven by the exchange interaction between conduction electrons and topological magnetic textures such as skyrmions, is a powerful probe for investigating the topological properties of magnetic materials. Typically, this phenomenon arises in systems with broken global inversion symmetry, where Dzyaloshinskii-Moriya interactions stabilize such textures. Here, we report the discovery of an emergent giant topological Hall effect in the twisted Fe3GeTe2 metallic system, which notably preserves the general global inversion symmetry. This effect manifests exclusively within a narrow window of "magic" twist angles ranging from 0.45{\deg} to 0.75{\deg}, while it is absent identically outside of that range, highlighting its unique and emergent nature. Micromagnetic simulations reveal that this topological Hall effect originates from a skyrmion lattice induced by alternating in-plane and layer-contrasting Dzyaloshinskii-Moriya interactions that result from local inversion symmetry breaking. Our findings underscore twisted Fe3GeTe2 as a versatile platform for engineering and controlling topological magnetic textures in metallic twisted van der Waals magnets, thereby opening up new avenues for next-generation spintronic devices.
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All authors Hyuncheol Kim, Kai-Xuan Zhang, Yu-Hang Li, Giung Park, Ran Cheng, Je-Geun Park

Saturday 14 March

Materials Science

Lightweight phase-field surrogate for modelling ductile-to-brittle transition through phenomenological elastoplastic coupling

P G Kubendran Amos

The ductile-to-brittle transition (DBT) in body-centred cubic systems is a central design constraint for cryogenic structures. Performing parametric studies to enhance the understanding on DBT using fully coupled thermomechanical continuum DBT models is computationally expensive. Therefore, in this work, a lightweight phase-field surrogate is proposed. This surrogate approach captures key DBT-like trends within a standard isothermal two-field (displacement–damage) setting by prescribing temperature dependence through three phenomenological mechanisms: (i) a temperature-dependent degradation exponent $n(T)$ that sharpens stiffness loss from gradual (ductile-like, $n=2.0$ at 293\,K) to abrupt (brittle-like, $n=3.5$ at 77\,K), (ii) temperature-dependent yield stress and elastic modulus to modulate the balance between plastic dissipation and elastic energy storage, and (iii) an effective fracture toughness and driving-force scaling to represent reduced crack-tip shielding at cryogenic temperatures. The model is implemented in FEniCSx using small-strain $J_2$ return mapping and a staggered solution scheme. Simulations of a single-edge-notched specimen over 77–293\,K demonstrate a systematic progression from brittle-like to ductile-like response, characterised by reduced displacement to unstable fracture, a transition from abrupt post-peak load drop to extended softening, and a shift from narrow, localised damage bands with confined plasticity to broader process zones. A sensitivity study comparing four interpolation schemes (linear, smoothstep, exponential, hybrid) shows that the qualitative transition trends are robust, with interpolation primarily affecting intermediate-temperature responses while endpoint behaviours remain unchanged.
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Materials Science · Cross-listed from physics.chem-ph

The Python Simulations of Chemistry Framework: 10 years of an open-source quantum chemistry project

Qiming Sun, Matthew R Hermes, Xiaojie Wu et al. (+100 more)

Over the past decade, the Python-based Simulations of Chemistry Framework (PySCF) has developed into a widely used open-source platform for electronic structure theory and quantum chemical method development. This article reviews the major advances since the previous overview in 2020, covering new modules and methodology, infrastructure changes, and performance benchmarks.
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All authors Qiming Sun, Matthew R Hermes, Xiaojie Wu, Huanchen Zhai, Xing Zhang, Abdelrahman M. Ahmed, Juan José Aucar, Oliver J. Backhouse, Samragni Banerjee, Peng Bao, Nikolay A. Bogdanov, Kyle Bystrom, Frédéric Chapoton, Ning-Yuan Chen, Ivan Yu. Chernyshov, Helen S. Clifford, Sander Cohen-Janes, Zhi-Hao Cui, Yann D. Damour, Nike Dattani, Linus Bjarne Dittmer, Sebastian Ehlert, Janus Juul Eriksen, Francesco A. Evangelista, Simon A. Ewing, Ardavan Farahvash, Kevin Focke, Yang Gao, Kevin E. Gasperich, Nathan Gillispie, Jonas Greiner, Matthew R. Hennefarth, Jan Hermann, Christopher Hillenbrand, Joonatan Huhtasalo, Basil Ibrahim, Bhavnesh Jangid, Alireza Nejati Javaremi, Andrew J. Jenkins, Yu Jin, Daniel S. King, Derk Pieter Kooi, Jo S. Kurian, Henrik R. Larsson, Bryan Tak Gwong Lau, Seunghoon Lee, Susi Lehtola, Chenghan Li, Hao Li, Jiachen Li, Rui Li, Shuhang Li, Aleksandr O. Lykhin, Ankit Mahajan, Nastasia Mauger, Pablo del Mazo-Sevillano, Jonathan Moussa, Kousuke Nakano, Verena A. Neufeld, Linqing Peng, Hung Q. Pham, Peter Pinski, Pavel Pokhilko, Zhichen Pu, Yubing Qian, Stephen Jon Quiton, Wanja T. Schulze, Thais R. Scott, Aniruddha Seal, James D. Serna, James E. T. Smith, Kori E. Smyser, Terrence Stahl, Chong Sun, Kevin J. Sung, Egor Trushin, Shiv Upadhyay, Ethan A. Vo, Thijs Vogels, Shirong Wang, Tai Wang, Xiao Wang, Xubo Wang, Yuanheng Wang, Mark Williamson, Junjie Yang, Hong-Zhou Ye, Chia-Nan Yeh, Haiyang Yu, Jincheng Yu, Victor Wen-zhe Yu, Chaoqun Zhang, Dayou Zhang, Yichi Zhang, Zijun Zhao, Zehao Zhou, Andrew J. Zhu, Tianyu Zhu, Timothy C. Berkelbach, Laura Gagliardi, Sandeep Sharma, Alexander Sokolov, Garnet Kin-Lic Chan

Materials Science

Digital Hydrogen Platform (DigHyd): A Rigorously Curated Database for Hydrogen Storage Materials Empowered by AI-Assisted Literature Mining

Seong-Hoon Jang, Di Zhang, Xue Jia et al. (+8 more)

Solid-state hydrogen storage materials are promising candidates for safe and compact hydrogen storage; however, data-driven discovery in this field remains limited by the availability of large-scale, well-curated datasets. Here, we present the Digital Hydrogen Platform (DigHyd: www.dighyd.org), a rigorously curated database comprising $>4,000$ experimental literature sources and $>30,000$ data entries on hydrogen storage materials, constructed through AI-assisted literature mining combined with human-in-the-loop validation. In addition to gravimetric hydrogen storage density ($w$), DigHyd also covers thermodynamic parameters, specifically the enthalpy ($\Delta H$) and entropy ($\Delta S$) changes associated with hydrogenation reactions, primarily defined as $M + \frac{1}{2} {\rm H}_2 \rightleftarrows M{\rm H}$. These parameters were obtained by manually analyzing multi-temperature pressure-composition-temperature (PCT) data using van't Hoff analysis. By focusing on $\Delta H$ and $\Delta S$ rather than fixing equilibrium pressure at a single temperature, DigHyd enables flexible evaluation of equilibrium behavior under application-specific operating conditions. Statistical analyses reveal distinct distributions of thermodynamic parameters across material classes, together with broad compositional variability within representative hydride systems. Furthermore, both physically interpretable symbolic regression and black-box XGBoost models achieve comparable predictive performance for $w$ and equilibrium pressure at room temperature ($P_{\rm eq,RT}$), demonstrating internal consistency and learnable composition-property relationships within the curated dataset. Overall, DigHyd provides a rigorously curated thermodynamic dataset that serves as a reliable basis for data-driven analyses of hydrogen storage materials and supports systematic exploration of structure-property relationships.
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All authors Seong-Hoon Jang, Di Zhang, Xue Jia, Hung Ba Tran, Linda Zhang, Ryuhei Sato, Yusuke Hashimoto, Toyoto Sato, Kiyoe Konno, Shin-ichi Orimo, Hao Li

Materials Science

Effects of uniaxial strain on monolayer transition-metal dichalcogenides revisited

Igor Evangelista, Abdul Saboor, Muhammad Zubair et al. (+6 more)

Using hybrid density functional calculations including spin-orbit coupling, we compute the strain evolution of the band structure of monolayer 1H-phase transition-metal dichalcogenides, MX$_2$ (M= Mo, W; X= S, Se, Te), emphasizing an accurate reproduction of the quasiparticle band gap (as opposed to the excitonic optical gap). We show that tensile uniaxial strain applied along either the armchair or zigzag directions leads to a pronounced reduction of the fundamental gap, with the conduction-band edge generally exhibiting the stronger strain response. Both the conduction-band electron valleys (CBM) and the valence-band hole valleys (VBM) remain degenerate under uniaxial strain, while simultaneously drifting away from the high-symmetry $K$ point under strain ("valley drift"), such that the band extrema occur at nearby off-symmetry wave vectors. A minimal tight-binding model rationalizes the valley drift and the unequal electron- and hole-valley drift rates in the presence of strain, leading to indirect band gaps. In particular, for MoS$_2$ the indirectness increases with tensile strain, providing a natural explanation for the experimentally observed decrease in photoluminescence intensity under uniaxial deformation. These results provide quantitative guidance for tailoring band structures for optoelectronic and quantum-defect applications.
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All authors Igor Evangelista, Abdul Saboor, Muhammad Zubair, Intuon Chatratin, Ruiqi Hu, Dai Q. Ho, Shoaib Khalid, Ioanna Fampiou, Anderson Janotti

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

The stripe state at 1/8 Ba doping hosts optimal superconductivity in La-214 cuprates under low in-plane stress

V. Sazgari, S.S. Islam, M. Lamotte et al. (+20 more)

The cuprate system La$_{2-x}$Ba$_{x}$CuO$_{4}$ (LBCO) exhibits a pronounced sensitivity to in-plane uniaxial stress, particularly near the 1/8 doping anomaly, where stripe order strongly suppresses bulk superconductivity. While previous studies have focused on compositions close to 0.125, the commensurate $x$=0.125 phase remains largely unexplored under symmetry-selective lattice tuning. Here, we combine muon-spin rotation (${\mu}$SR), AC susceptibility, and electrical resistivity to investigate superconductivity, spin-stripe order, and structural response in LBCO-0.125 under in-plane uniaxial stress applied 45$^\circ$ to the Cu-O bond direction. Complementary resistivity measurements on $x$=0.115 and 0.135 track the evolution across both sides of the anomaly. We observe a giant enhancement of the bulk superconducting transition temperature in LBCO-0.125, increasing from 5 K to 37 K under 0.5 GPa. While the onset temperature of spin-stripe order decreases only modestly, the magnetic volume fraction is reduced by about a factor of two, with local order preserved. Simultaneously, the resistivity peak associated with the LTT phase is fully suppressed across all dopings. These results demonstrate that suppression of the LTT phase and reduction of the static spin-stripe-ordered volume fraction are crucial for the development of optimal three-dimensional superconductivity. Strikingly, the composition $x$=0.125, with the most robust stripe stability and the lowest ambient-pressure $T_{\rm c}$ develops the highest $T_{\rm c}$ under stress, reaching a zero-resistance state at 37 K and an onset of the superconducting transition as high as 46 K. This behavior indicates that stripe-related interactions enhance pairing strength, while static stripe order competes with superconductivity primarily at the level of phase coherence rather than pairing itself.
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All authors V. Sazgari, S.S. Islam, M. Lamotte, J.N. Graham, O. Gerguri, P. Kràl, I. Maetsu, T. Shiroka, G. Simutis, R. Khasanov, R. Sarkar, A. Steppke, N.A. Shepelin, M. Müller, M. Bartkowiak, M. Janoschek, J. Chang, H.H. Klauss, T. Adachi, G.D. Gu, J.M. Tranquada, H. Luetkens, Z. Guguchia

Materials Science

Vacuum Wannier Functions for First-Principles Scattering and Photoemission

Tyler Wu and Tomás Arias

We establish a first-principles theory of vacuum Wannier functions unifying tight-binding and nearly-free-electron descriptions across solid-vacuum interfaces. Analytic solutions for canonical Wannier functions in arbitrary dimension and disentangled functions in 1D motivate a numerically verified 3D Wannier close-packing principle, enabling dense k-space construction of full Born-series scattering states at interfaces and thus predictive photoemission calculations without semiempirical vacuum potentials. Applications to graphene and h-BN reveal corrections beyond the first-Born approximation.
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Materials Science

Linear dichroic soft X-ray microscopy of ferroelectric stripe domains in epitaxial K$_\mathbf{0.6}$Na$_\mathbf{0.4}$NbO$_\mathbf{3}$

M. Schneider, T. A. Butcher, S. Wagner et al. (+19 more)

Functional properties of ferroelectric thin films are governed by domains that can be engineered by epitaxial strain. Soft x-ray microscopy can image domain structures with elemental and electronic sensitivity, but hitherto its application to strain-stabilized domains has been hindered by the absorption of soft x-rays in epitaxial substrates. Here, it is demonstrated how this limitation can be overcome by locally back-thinning the (110) TbScO3 substrate of epitaxial K$_{0.6}$Na$_{0.4}$NbO$_{3}$ ferroelectric thin films to achieve soft x-ray transparency at the O K-edge around 530 eV. Strain-induced ferroelectric stripe domains with periods down to 44 nmwere resolved by scanning transmission x-ray microscopy and coherent diffractive imaging by exploiting the x-ray linear dichroism of hybridized O 2p-Nb 4d states, providing sensitivity to in-plane polarization components under normal incidence. The results establish soft x-ray microscopy for nanoscale imaging of epitaxial ferroelectric domain structures and open perspectives for time-resolved studies thereof.
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All authors M. Schneider, T. A. Butcher, S. Wagner, D. Metternich, C. Klose, E. Malm, R. Battistelli, V. Deinhart, J. Fuchs, S. Wittrock, T. Karaman, K. Puzhekadavil Joy, M. Patra, F. Büttner, S. Wintz, M. Weigand, C. M. Günther, D. Engel, P. Gaal, J. Schwarzkopf, B. Pfau, S. Eisebitt

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

Superhydrides on the way to ambient pressure: weak localization and persistent X-ray photoconductivity in BaSiH$_{8}$

Dmitrii V. Semenok, Di Zhou, Sven Luther et al. (+15 more)

Reducing the stabilization pressure of superhydrides represents one of the most important challenges in hydrogen-saturated compound chemistry. Moving in this direction, we studied the Ba-Si-H system at 0-142 GPa using transport measurements, 1H nuclear magnetic resonance, single-crystal and powder X-ray diffraction in the temperature range of 4-317 K. We synthesized the previously predicted cubic BaSiH$_{8}$ at pressures of 18-31 GPa. Remarkably, we demonstrate that BaSiH$_8$ remains stable upon decompression to ambient conditions and can be recovered from the diamond anvil cell. Obtained Ba-Si polyhydrides exhibit metallic and superconducting properties ($\textit{T$_c$}$ = 9 K, $\textit{B$_{c2}$}$(0)=13-16 T) at 142 GPa. However, at pressures below 50 GPa, these hydrides behave as degenerate semiconductors (bandgap < 0.4 meV) or poor metals with weak electron localization, negative magnetoresistance, photovoltaic effect, and persistent photoconductivity in the X-ray and visible range. Our work demonstrates the high-pressure synthesis of Ba-Si polyhydrides that remain stable upon decompression to ambient conditions, overcoming a critical bottleneck in superhydride chemistry and establishing a foundation for practical applications in hydrogen storage.
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All authors Dmitrii V. Semenok, Di Zhou, Sven Luther, Toni Helm, Hirokazu Kadobayashi, Yuki Nakamoto, Katsuya Shimizu, Kirill S. Pervakov, Andrei V. Sadakov, Oleg A. Sobolevskiy, Vladimir M. Pudalov, Simone Di Cataldo, Roman Lucrezi, Lilia Boeri, Michele Galasso, Frederico G. Alabarse, Ivan A. Troyan, Viktor V. Struzhkin

Materials Science

Non-isothermal flow of Al-, Co- and Cu-based alloys made in different spatial configurations or structural states: model and experimental study

A.D. Berezner, V.A. Fedorov, N.S. Perov et al. (+4 more)

The universal generalising approach for non-isothermal behaviour of different alloys has been provided together with the novel deformation modelling. Strong correlation between the model approach and experimental results is shown that permits estimation of main applied parameters such as the linear thermal expansion coefficient and others. Necking contours and critical thickness at corrugation for ribbon and rod specimens are also calculated. Fractal analysis of corrugation folds (their main size) has been carried out for polycrystalline and amorphous ribbon specimens. Structural peculiarities at the plastic deformation stage are investigated with microscopy.
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All authors A.D. Berezner, V.A. Fedorov, N.S. Perov, J.C. Qiao, V.E. Gromov, M.Yu. Zadorozhnyy, G.V. Grigoriev

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

Systematically Improvable Numerical Atomic Orbital Basis Using Contracted Truncated Spherical Waves

Yike Huang, Zuxin Jin, Linfeng Zhang et al. (+1 more)

To solve the Kohn-Sham equation within the framework of density functional theory, we develop a scheme to construct numerical atomic orbital (NAO) basis sets by contracting truncated spherical waves (TSWs). The contraction minimizes the trace of the kinetic operator in the residual space, generalizing the spillage minimizing scheme [M. Chen et al., J. Phys. Condens. Matter 22, 445501 (2010); P. Lin et al., Phys. Rev. B 103, 235131 (2021)]. In addition to the systematic improvability inherited from previous schemes, the use of TSW instead of plane waves as the expansion basis bridges reference states and NAOs more effectively, and eliminates spurious interactions between periodic images, thereby enabling better transferability through the inclusion of extensive reference states. Benchmarks demonstrate that the constructed NAO achieves satisfactory precision for various properties of both molecules and bulk systems, including total energy, bond length, atomization energy, lattice constant, cohesive energy, band gap, and energy-level alignment. By incorporating unoccupied states, the improved transferability in describing the conduction band is demonstrated to be effective and substantial.
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All authors Yike Huang, Zuxin Jin, Linfeng Zhang, Mohan Chen

Materials Science

Generative Inverse Design of Cold Metals for Low-Power Electronics

Kedeng Wu, Yucheng Zhu, Yan Chen et al. (+6 more)

Cold metals are a class of metals with an intrinsic energy gap located close to the Fermi level, which enables cold-carrier injection for steep-slope transistors and is therefore promising for low-power electronic applications. High-throughput screening has revealed 252 three-dimensional (3D) cold metals in the Materials Project database, but database searches are inherently limited to known compounds. Here we present an inverse-design workflow that generates 3D cold metals using MatterGPT, a conditional autoregressive Transformer trained on SLICES, an invertible and symmetry-invariant crystal string representation. We curate a training set of 26,309 metallic structures labeled with energy above hull and a unified band-edge distance descriptor that merges p-type and n-type cold-metal characteristics to address severe label imbalance. Property-conditioned generation targeting thermodynamic stability and 50-500 meV band-edge distances produces 148,506 unique candidates; 92.1% are successfully reconstructed to 3D structures and down-selected by symmetry, uniqueness and novelty filters, followed by high-throughput DFT validation. We identify 257 cold metals verified as novel with respect to the Materials Project database, with gaps around the Fermi level spanning 50-500 meV. First-principles phonon, electronic-structure, and work-function calculations for representative candidates confirm dynamical stability and contact-relevant work functions. Our results demonstrate that SLICES-enabled generative transformers can expand the chemical space of cold metals beyond high-throughput screening, providing a route to low-power electronic materials discovery.
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All authors Kedeng Wu, Yucheng Zhu, Yan Chen, Bizhu Zhang, Shuyu Liu, Xiaobin Deng, Yabei Wu, Liangliang Zhu, Hang Xiao

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

Crystal structure, magnetic and resonant properties of decorated spin kagome system (CsCl)Cu$_5$As$_2$O$_{10}$

Ilya V. Kornyakov, Marina V. Likholetova, Irina E. Lezova et al. (+8 more)

We report the synthesis and investigation of the crystal structure and physical properties of the averievite-like arsenate, $(\mathrm{CsCl})\mathrm{Cu}_5\mathrm{As}_2\mathrm{O}_{10}$. Just above room temperature, this compound undergoes a structural phase transition from the high-temperature trigonal $P\bar{3}m1$ $(a=b=a_0$ and $c=c_0)$ to the low-temperature monoclinic $I2/a$ phase $(a \approx \sqrt{3}a_0$, $b=a_0$, $c \approx 2c_0$ and $\beta \approx 90.6^\circ)$. According to thermodynamic and nuclear magnetic resonance measurements, it experiences a phase transition into a canted antiferromagnetic state at $T_N = 21~\mathrm{K}$. The density functional theory calculations place the energy scale of kagome exchange interaction parameter in $(\mathrm{CsCl})\mathrm{Cu}_5\mathrm{As}_2\mathrm{O}_{10}$ in between those in V- and P-analogs.
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All authors Ilya V. Kornyakov, Marina V. Likholetova, Irina E. Lezova, Sergey V. Krivovichev, Harald O. Jeschke, Yasir Iqbal, Alexey V. Tkachev, Sergey V. Zhurenko, Andrey A. Gippius, Larisa V. Shvanskaya, Alexander N. Vasiliev

Materials Science · Cross-listed from cs.CV

Efficient Semi-Automated Material Microstructure Analysis Using Deep Learning: A Case Study in Additive Manufacturing

Sanjeev S. Navaratna, Nikhil Thawari, Gunashekhar Mari et al. (+3 more)

Image segmentation is fundamental to microstructural analysis for defect identification and structure-property correlation, yet remains challenging due to pronounced heterogeneity in materials images arising from varied processing and testing conditions. Conventional image processing techniques often fail to capture such complex features rendering them ineffective for large-scale analysis. Even deep learning approaches struggle to generalize across heterogeneous datasets due to scarcity of high-quality labeled data. Consequently, segmentation workflows often rely on manual expert-driven annotations which are labor intensive and difficult to scale. Using an additive manufacturing (AM) dataset as a case study, we present a semi-automated active learning based segmentation pipeline that integrates a U-Net based convolutional neural network with an interactive user annotation and correction interface and a representative core-set image selection strategy. The active learning workflow iteratively updates the model by incorporating user corrected segmentations into the training pool while the core-set strategy identifies representative images for annotation. Three subset selection strategies, manual selection, uncertainty driven sampling and proposed maximin Latin hypercube sampling from embeddings (SMILE) method were evaluated over six refinement rounds. The SMILE strategy consistently outperformed other approaches, improving the macro F1 score from 0.74 to 0.93 while reducing manual annotation time by about 65 percent. The segmented defect regions were further analyzed using a coupled classification model to categorize defects based on microstructural characteristics and map them to corresponding AM process parameters. The proposed framework reduces labeling effort while maintaining scalability and robustness and is broadly applicable to image based analysis across diverse materials systems.
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All authors Sanjeev S. Navaratna, Nikhil Thawari, Gunashekhar Mari, Amritha V P, Murugaiyan Amirthalingam, Rohit Batra

Materials Science

Nitrogen-Vacancy-Mediated Magnetism in Sputtered GdN Thin Films

Pankaj Bhardwaj, Jyotirmoy Sarkar, Bubun Biswal et al. (+11 more)

Among rare-earth nitrides (RENs), gadolinium nitride (GdN) stands out as a promising material for spintronics owing to its distinctive combination of semiconducting behavior, strong exchange interactions, and intrinsically soft ferromagnetism. Its relatively high Curie temperature and large saturation magnetization make it an attractive candidate for device concepts such as non-volatile memory elements and spin-based transistors, motivating efforts toward low-cost, uniform, and compositionally controlled thin-film growth. In this work, we deposited GdN thin films on SiO2/AlN substrates using DC sputtering under reactive nitridation conditions, with thicknesses varying from 18 to 180 nm, and systematically investigated their structural and magnetic properties. The films exhibit soft ferromagnetic ordering, characterized by a coercive field of approximately 200 Oe and a Curie temperature (Tc) near 70 K. Structural analysis reveals lattice distortions and local strain associated with nitrogen-vacancy defects, whose concentration varies with film thickness. Our theoretical studies establish a direct correlation between the observed Raman modes of the GdN lattice and the reduced magnetization induced by nitrogen vacancies. These vacancies give rise to defect-mediated ferromagnetism, leading to a measurable enhancement of Tc from 68 K to 82 K across the studied thickness range. The observed magnetic behavior is well described by the bound magnetic polaron (BMP) model, confirming that nitrogen vacancies are key contributors to ferromagnetic ordering while preserving the soft-magnetic character intrinsic to GdN. This study underscores the pivotal role of defect engineering in optimizing GdN thin films for spintronics applications.
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All authors Pankaj Bhardwaj, Jyotirmoy Sarkar, Bubun Biswal, Subhransu Kumar Negi, Arijit Sinha, Anirudh Venugopalrao, Sharath Kumar C, Sreelakshmi M Nair, R. S. Patel, Deepshika Jaiswal Nagar, Abhishek Mishra, Srinivasan Raghavan, Umesh Waghmare, Dhavala Suri

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

Eccentricity valley Hall effect

Jin Cao, Shen Lai, Cong Xiao et al. (+2 more)

Valleytronics harnesses the valley degree of freedom – energy-degenerate extrema in the electronic band structure – for information storage and processing. Valley Hall effect (VHE) is a cornerstone of valleytronics, enabling electric generation of pure valley currents. While extensively studied in systems with valleys located at time-reversal-breaking points, here, we shift the paradigm to valleytronic platforms with time-reversal-invariant valleys (TRIVs), revealing a novel phenomenon: eccentricity VHE. Unlike conventional VHE, the valley Hall angle for eccentricity VHE is an intrinsic geometric property, governed solely by the eccentricity of the valley Fermi surface, rendering it highly robust against variations in temperature or carrier density. Eccentricity VHE emerges universally across all 25 layer groups supporting TRIVs. We demonstrate these distinctive features in monolayer GeS$_{2}$ via first-principles calculations, predicting a significant valley Hall angle of 0.74. This effect can be detected through nonlocal transport measurements exhibiting characteristic scaling behavior, or, in certain cases, through valley-layer coupling. Our findings reveal a critical overlooked facet of valley Hall physics, transcend the established VHE paradigm, and significantly broadens the scope of valleytronics.
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All authors Jin Cao, Shen Lai, Cong Xiao, Qian Niu, Shengyuan A. Yang

Materials Science

Research Paradigm of Materials Science Tetrahedra with Artificial Intelligence

Shiyun Zhang, Yibo Yao, Haoquan Long et al. (+4 more)

The classical material tetrahedron that represents the Structure-Property-Processing-Performance-Characterization relationship is the most important research paradigm in materials science so far. It has served as a protocol to guide experiments, modeling, and theory to uncover hidden relationships between various aspects of a certain material. This substantially facilitates knowledge accumulation and material discovery with desired functionalities to realize versatile applications. In recent years, with the advent of artificial intelligence (AI) techniques, the attention of AI towards scientific research is soaring. The trials of implementing AI in various disciplines are endless, with great potential to revolutionize the research diagram. Despite the success in natural language processing and computer vision, how to effectively integrate AI with natural science is still a grand challenge, bearing in mind their fundamental differences. Inspired by these observations and limitations, we delve into the current research paradigm dictated by the classical material tetrahedron and propose two new paradigms to stimulate data-driven and AI-augmented research. One tetrahedron focuses on AI for materials science by considering the Matter-Data-Model-Potential-Agent diagram. The other demonstrates AI research by discussing Data-Architecture-Encoding-Optimization-Inference relationships. The crucial ingredients of these frameworks and their connections are discussed, which will likely motivate both scientific thinking refinement and technology advancement. Despite the widespread enthusiasm for chasing AI for science, we must analyze issues rationally to come up with well-defined, resolvable scientific problems in order to better master the power of AI.
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All authors Shiyun Zhang, Yibo Yao, Haoquan Long, Dingwen Tao, Guangming Tan, Wei-Hua Wang, Yuan-Chao Hu

Materials Science

Giant Full-Space Anomalous Hall Effect Induced by Non-Coplanar Spin State in Mn-Rich Mn3Sn

Yiming Liu, Xin Liu, Jiayao Zhu et al. (+6 more)

Antiferromagnets are promising candidates for next-generation spintronic devices owing to their negligible stray fields and ultrafast spin dynamics. The noncollinear antiferromagnet $\mathrm{Mn}_{3}\mathrm{Sn}$ exhibits a large anomalous Hall effect (AHE). However, its specific noncollinear spin configuration leads to the forbiddance of the anomalous Hall conductivity from the (0001) basal plane, $\sigma_{(0001)}$, limiting practical applications. Here, using first-principles density functional theory, we demonstrate that Mn enrichment in $\mathrm{Mn}_{3}\mathrm{Sn}$ drives a magnetic transition from the coplanar $120^\circ$ spin configuration to a non-coplanar state with moments tilted toward the $c$-axis. This transition is primarily mediated by four-spin ring exchange interaction in the local triangular lattice, which breaks the time-reversal symmetry and generates a giant intrinsic anomalous Hall conductivity over the full three-dimensional space in $\mathrm{Mn}_{3}\mathrm{Sn}$. We predict that $\sigma_{(0001)}$ reaches as high as $\sim\!-468~\Omega^{-1}\cdot\mathrm{cm}^{-1}$, and an enhanced $\sigma_{(01\bar{1}0)}$ of $\sim\!-229~\Omega^{-1}\cdot\mathrm{cm}^{-1}$ is expected in light Mn self-doping of $\mathrm{Mn}_{3}\mathrm{Sn}$ ($\mathrm{Mn}_{3.125}\mathrm{Sn}_{0.875}$). Unlike previously reported mechanisms relying on external magnetic fields or strain, our approach exploits intrinsic compositional tuning to stabilize a non-coplanar magnetic ground state for realizing a strong full-space AHE in antiferromagnets, providing another viable pathway toward high-performance, low-power spintronic devices.
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All authors Yiming Liu, Xin Liu, Jiayao Zhu, Fengxian Ma, Li Ma, Dewei Zhao, Guoke Li, Congmian Zhen, Denglu Hou

Materials Science

Cobalt Binary Compounds for Advanced Interconnect Materials

Gyungho Maeng and Yeonghun Lee

The industrial standard copper (Cu) interconnects face a substantial resistivity increase at thinner linewidths, posing a well-known challenge to limit overall device performance. To address this issue, we have evaluated the potential properties of cobalt (Co) based binary compounds as replacements for Cu. Co is considered as a promising alternative due to its potential for enhanced reliability and low resistivity at sub-nanoscale dimensions. Furthermore, the combination of elements provides a possibility to engineer novel properties, transcending the limitations of elemental metals and expanding the search space for next-generation interconnects. In this study, a high-throughput screening method was used to identify several Co-based binary compounds with superior electronic transport and reliability at reduced thickness. The findings demonstrate that specific Co-based binary compounds hold significant potential to overcome the performance limitations of scaled interconnects.
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Materials Science

Revealing Hydroxide Ion Transport Mechanisms in Commercial Anion-Exchange Membranes at Nano-Scale from Machine-learned Interatomic Potential Simulations

Jonas Hänseroth, Muhammad Nawaz Qaisrani, Mostafa Moradi et al. (+2 more)

Hydroxide ion transport in anion-exchange membranes fundamentally limits the efficiency of alkaline water electrolysis for green hydrogen production, yet the atomic-scale transport mechanisms remain poorly understood due to the computational challenges associated with modeling ion dynamics. Given that anion-exchange membranes enable alkaline electrolysis with abundant catalysts while avoiding perfluoroalkyl and polyfluoroalkyl materials, a deeper mechanistic understanding of hydroxide transport in these systems is essential for advancing sustainable hydrogen production. Here, we show that large-scale molecular dynamics simulations with fine-tuned machine-learned interatomic potentials provide atomistic insight into hydroxide mobility in a commercial membrane over tens of nanoseconds and over ten nanometer. We find that increasing water content transforms isolated water clusters into a connected hydrogen-bond network that enables long-range proton transfer. Under dry conditions hydroxide ions are trapped near positively charged groups and transport is strongly hindered, whereas well-hydrated membranes exhibit extended proton migration and diffusion coefficients approaching those of dilute aqueous solutions. The simulations reproduce experimental trends in diffusion and activation energies. Our results establish a direct link between nano-scale structure and macroscopic transport. Beyond mechanistic insight, the presented simulation framework enables predictive, simulation-guided optimization of membrane chemistry and architecture, opening a pathway toward the rational design of more efficient anion-exchange membranes for green hydrogen technologies.
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All authors Jonas Hänseroth, Muhammad Nawaz Qaisrani, Mostafa Moradi, Karl Skadell, Christian Dreßler