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Physics Condensed Matter Materials Science

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Friday 30 January

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

Infinite Magnetoresistance and Vortex Coupling in the Pb/BSCCO Heterostructure

Combining superconductivity with spintronics provides exciting opportunities to realize low-dissipation quantum devices. Here we report the synthesis, characterization and magnetotransport measurements of the Pb/Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ (BSCCO) superconducting heterostructures, where an insulating PbO$_{x}$ layer spontaneously forms at the interface. Non-volatile switching between superconducting (logical "0") and normal ("1") states in Pb films by an external field, i.e., infinite magnetoresistance (IMR), can be realized and are attributed to the strong trapping and pinning of vortices in BSCCO. Furthermore, butterfly-shaped hysteresis loops in magnetoresistance, pronounced resistance dips/jumps and thermal reset to superconducting states can be observed and are direct manifestations of the peculiar vortex dynamics in BSCCO and vortex coupling across the Pb/BSCCO interface. Our work demonstrates a simple and effective way to realize IMR through superconducting vortices and opens up new opportunities to study the vortex interactions across the superconducting interfaces.
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All authors Weifan Zhu, Jiamin Yao, Shuntianjiao Ling, Shanyin Fu, Yifu Xu, Pengyue Xiong, Jiawen Zhang, Mengwei Xie, Yanan Zhang, Ye Chen, Huiqiu Yuan, Xin Lu, Qing-Hu Chen, Yang Liu

Materials Science

Atomic-scale Imaging of Iodide-Gold Interactions in Nanoconfined Liquid-Solid Interfaces

Functionalization of nanoporous metallic materials enables the tailoring of surface chemistry and morphology in nanostructured materials, optimising their performance for electrocatalytic and sensor applications. Liquid phase chemical functionalization is governed by liquid solid interfaces. Yet, these interfaces remain poorly understood due to the challenges of characterising the liquid phase at high spatial and chemical resolutions. To elucidate pathways for functionalizing nanoscale metals, it is crucial to measure the distribution of species, including light elements, across the liquid solid interface, capturing both reactants and products. Here, we employ cryogenic atom probe tomography to directly analyse frozen liquid solid reaction interfaces at near atomic resolution. Focusing on the interaction of iodide and sodium ions with nanoporous gold, we observe the formation of iodine containing complexes on gold nanoligament surfaces and subsurfaces. These findings reveal aspects of the gold iodide system that were previously hidden, including the reaction mechanism between iodide and gold atoms on the surface, and the multiple gold iodide complexes forming. Our work demonstrates that cryogenic atom probe tomography can provide unprecedented visualisation and characterisation of nanoscale interfaces during chemical and electrochemical reactions, with potential implications for modern manufacturing, energy technologies, and sustainable materials development.
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All authors Oliver R. Waszkiewicz, Yuxiang Zhou, Baptiste Gault, Finn Giuliani, Mary P. Ryan, Ayman A. El-Zoka

Materials Science

Unlocking the Power of Orbital-Free Density Functional Theory to Explore the Electronic Structure Under Extreme Conditions

Recent advances in X-ray free-electron laser diagnostics have enabled direct probing of the electronic structure under extreme pressures and temperatures, such as those encountered in stellar interiors and inertial confinement fusion experiments, challenging theoretical models for interpreting experimental data. Kohn-Sham density functional theory (KSDFT) has been successfully applied to analyze experimental X-ray scattering measurements, but its high computational cost renders routine application impractical. Orbital-free DFT (OFDFT) is a substantially more efficient alternative, with computational cost scaling linearly with system size and a weak temperature dependence, yet it often lacks the accuracy required for electronic structure description. Overcoming this limitation, we present a non-empirical Kohn-Sham-assisted orbital-free density functional framework for calculations at extreme conditions, which enables efficient OFDFT simulations with KSDFT-level accuracy for electron densities, electron-ion structure factors, and equations of state across a broad range of conditions. Benchmark comparisons with quantum Monte Carlo data for dense hydrogen and validation against Rayleigh weight measurements of hot dense beryllium demonstrate the reliability of the framework and speedups of up to several hundred times compared with KSDFT. We further show that even at temperatures on the order of 100 eV, quantum non-locality remains essential for correctly describing the electronic structure of dense hydrogen.
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All authors Cheng Ma, Qiang Xu, Zhenhao Zhang, Ke Wang, Ying Sun, Wenhui Mi, Zhandos A. Moldabekov, Tobias Dornheim, Jan Vorberger, Sebastian Schwalbe, Xuecheng Shao

Materials Science

Hydrogen at GaN(0001) surface control of Fermi level pinning: Mg activation of p-type conductivity – Nakamura process deciphered

Ab initio calculations were used to disentangle the mystery of Nakamura activation of p-type in Mg doped MOVPE grown gallium nitride, the key process leading to the 2014 Nobel Prize in Physics. Calculations were used to obtain the equilibrium state of the hydrogen atom deep in the GaN bulk and at the GaN(0001) surface. It was shown that the H position within bulk GaN depends on the Fermi level: in n-type GaN, it is located in the channel, whereas in p-type GaN, it is attached to the N atom, breaking one of the GaN bonds. In contrast, at the GaN(0001) surface, H is attached in the on-top position for any hydrogen coverage; for low and high H-coverage, the Fermi level is pinned at the Ga - broken bond state and at the valence band maximum (VBM), respectively. The diffusion path from the bulk to the surface was obtained when the Fermi level was high and low, the barrier was zero, and $\Delta E_{bar} \approx 1.717 eV$, which effectively blocked hydrogen escape into the vapor. Thus, high H coverage, that is, high hydrogen pressure in the vapor, prevents H from escaping from the bulk to the surface, whereas at low coverage (low hydrogen pressure), the process is barrierless. It is therefore proven that the hydrogen escape control step in the Nakamura process is the transition of hydrogen from the bulk to the surface, which is controlled by the position of the Fermi level at the surface. Molecular hydrogen desorption from the surface is easy for high H coverage and difficult for low, thus opposite to observed experimentally thus this process is not the determining step in activation. A full thermodynamic estimate of the maximal partial pressure of hydrogen in the vapor, corresponding to the transition of the Fermi level from the Ga-broken bond state to the VBM, was used to establish the maximal hydrogen pressure limit for the p-type Mg activation process.
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All authors Konrad Sakowski, Pawel Strak, Pawel Kempisty, Izabella Grzegory, Stanislaw Krukowski

Materials Science

Role of quasi-Fermi levels in Si- and Mg-related optical absorption in nitride laser diodes (LDs): material context

Optical absorption and reabsorption of light emitted from active regions in nitride laser diodes (LDs) have been shown to reduce the light extraction efficiency of these devices. It was proven that the presence of Si and Mg may considerably increase the optical absorption. This effect is much stronger in the high-energy (short-wavelength) range of the spectrum. The absorption increase is directly related to the ionization of the Si donor and Mg acceptor levels, which are controlled by the electron and hole quasi-Fermi levels. It is shown that the absorption may be increased because of the higher ionization of Mg caused by the compensation in the p-type region and the high ionization of Si in the n-type region. It was explained theoretically why optical efficiency is increased by removal of doping in waveguides. It was also shown that good material quality leads to a low absorption level, especially in the Mg-doped p-type part of the device.
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All authors Konrad Sakowski, Cyprian Sobczak, Pawel Strak, Izabella Grzegory, Robert Czernecki, Jacek Piechota, Agata Kaminska, Stanislaw Krukowski

Materials Science

Resolving Structural Avalanches in Amorphous Carbon with Arclength Continuation

Plastic deformation in amorphous solids is carried by localized shear transformations that self-organize into avalanches. In amorphous carbon modeled with a machine-learned interatomic potential, we find that the energetics and organization of these avalanches can be resolved by systematically following the underlying energy landscape. With a pseudo-arclength numerical continuation framework, we decompose avalanches into constituent shear transformations and determine their strain-dependent energetics. Our analysis shows that, prior to onset, avalanches have a latent structure that consists of well-separated local minima. We further demonstrate that arclength continuation yields an event driven framework for following avalanche dynamics, eliminating time-step effects on statistical avalanche properties such as distributions of stress drops.
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All authors Fraser Birks, Ibrahim Ghanem, Lars Pastewka, James Kermode, Maciej Buze

Materials Science · Cross-listed from stat.CO

A Framework for the Bayesian Calibration of Complex and Data-Scarce Models in Applied Sciences

In this work, we review the theory involved in the Bayesian calibration of complex computer models, with particular emphasis on their use for applications involving computationally expensive simulations and scarce experimental data. In the article, we present a unified framework that incorporates various Bayesian calibration methods, including well-established approaches. Furthermore, we describe their implementation and use with a new, open-source Python library, ACBICI (A Configurable BayesIan Calibration and Inference Package). All algorithms are implemented with an object-oriented structure designed to be both easy to use and readily extensible. In particular, single-output and multiple-output calibration are addressed in a consistent manner. The article completes the theory and its implementation with practical recommendations for calibrating the problems of interest. These guidelines – currently unavailable in a unified form elsewhere – together with the open-source Python library, are intended to support the reliable calibration of computational codes and models commonly used in engineering and related fields. Overall, this work aims to serve both as a comprehensive review of the statistical foundations and (computational) tools required to perform such calculations, and as a practical guide to Bayesian calibration with modern software tools.
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Materials Science · Cross-listed from cond-mat.mes-hall

Gate-tuneable single-photon emitters in WSe2 monolayer created via AFM nanoindentation on rigid SiO2/Si substrates

Single-photon emitters (SPEs) hosted by two-dimensional (2D) semiconducting materials are envisioned for next-generation quantum applications. However, SPE creation in 2D semiconductors on rigid substrates like SiO2/Si via nanoindentation is a technological gap, critical for interfacing SPEs with photonic circuits and cavities. Here, we report a protocol for deterministically creating SPEs in monolayer WSe2 on SiO2/Si substrates using a sharp diamond AFM (atomic force microscope) tip. A displacement-controlled indentation process is developed, allowing indent depths > 150 nm necessary for creating SPEs. Sharp defect peaks (~200 {\mu}eV) are observed in cryogenic (4K) photoluminescence (PL) spectrum at nanoindented sites and are stable upto ~ 120K. 76% of sites exhibit sharp defect-bound peaks confirmed by power-dependent, temperature-dependent, and time-resolved PL (TRPL). AFM and PL mapping link these peaks to indent periphery. The peaks show sub-linewidth spectral jitter, no blinking, and single-photon nature in second-order autocorrelation measurements. SPEs can be switched on/off, and background emissions suppressed using electrical gating. Gate-voltage dependent TRPL indicate that SPE dynamics can be tuned, depending on nature of SPE, pointing the way to higher-purity SPEs. Our work is directly applicable to other 2D materials and photonic circuit/cavity compatible rigid substrates and is a significant step for scalable SPE technologies.
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All authors Ajit Kumar Dash, Sanket Jugade, Manavendra Pratap Singh, Hardeep, Tilly Guyot, Cora Crunteanu-Stanescu, Indrajeet Dhananjay Prasad, Yunus Waheed, Sumitra Shit, Sébastien Roux, Santosh Kumar, Cedric Robert, Xavier Marie, Akshay Naik, Akshay Singh

Materials Science

Fully Compensated Lines in Ferrimagnets

We generalize the classic Néel diagram and identify another type of ferrimagnetic phase that remains fully magnetically compensated below the Curie temperature, forming a continuous line of compensated points. It exhibits zero net magnetization while retaining non-relativistic, eV-scale reciprocal spin splitting. We further find a persistently enhanced intrinsic switching field over a broad temperature range near the fully compensated phase. Proximity to the compensated line is achieved by minimizing the net local moment while balancing exchange interactions with respect to the number of equivalent atoms in each sublattice. The resulting extended Néel diagram provides practical design rules for engineering fully compensated ferrimagnetic phases via targeted chemical substitution that combines atoms with robust and weak local moments, as demonstrated through density functional theory and Monte Carlo simulations for GdCo$_5$-type ferrimagnets.
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All authors Qais Ali, Anna Grünebohm, Halil Ibrahim Sözen, Tilmann Hickel, Jörg Neugebauer, Eduardo Mendive-Tapia

Materials Science

Magnetization reversal and anisotropies in buffered transition-metal alloys thin films

Interest in planar Hall effect (PHE) sensors has re-emerged in recent years due to their promising potential for a wide range of applications, particularly in biotechnology. Sensor sensitivity can be enhanced by lowering the effective anisotropy field; however, this favors magnetic domain formation during magnetization reversal, leading to hysteretic responses. Therefore, precise control of magnetic anisotropy and magnetization reversal is essential to balance sensitivity and stability in PHE sensors. In this work, we investigate the magnetic anisotropy and magnetization reversal mechanisms of Ni-Fe- and Co-Fe-based multilayers grown on various metallic buffer layers and deposited with and without an external magnetic field, in order to evaluate the effects of the buffer layers and field-assisted deposition on the resulting magnetic anisotropy. NiFe films exhibit a dominant uniaxial anisotropy mainly determined by the applied field during growth, with an anisotropy constant of approximately $3,\mathrm{kerg,cm^{-3}}$, largely independent of the buffer layer. In contrast, the magnetic anisotropy of CoFe films is dominated by the buffer layer, resulting in a biaxial magnetic response. In particular, Ag-buffered films deposited under an external magnetic field exhibit a biaxial anisotropy with values up to $14.88,\mathrm{kerg,cm^{-3}}$. The magnetization reversal mechanism of each system was deduced from the analysis of the angular dependence of the coercive field.
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Materials Science

Ferroelectric switching at edge dislocations in BaTiO$_3$ modelled at the atomic scale

Ferroelectric switching governs the functional properties of ferroelectric perovskites. It is widely accepted that this switching depends on domain nucleation and pinning and that these processes can be controlled by the defect structure. However, an atomistic picture of the influence of one important class of defects - dislocations on ferroelectric switching is missing. This is an important gap in knowledge as dislocations cannot be avoided at interfaces and can also be engineered by plastic deformation at high temperatures. Using atomistic simulations, we show how the cores of $\langle100\rangle$ edge dislocations in BaTiO$_3$ can either act as nucleation centers for ferroelectric switching or pin walls depending on the direction of the applied field. The coupling between electric field and polarization is strongest when the field is applied parallel to the Burgers vector of the dislocation.
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Materials Science

Long-distance spin transport in frustrated hyperkagome magnet Gd3Ga5O12

Transport of spin angular momentum over large distance has been a long sought-after goal in the field of spintronics. While the majority of the research effort has been devoted to the spin transport properties of magnetically ordered materials, spin transport in magnetically frustrated materials has received little attention. Here, we report an anomalous state in frustrated hyperkagome magnetic insulator Gd3Ga5O12, where spin angular momenta can be transported over a long distance of 480 {\mu}m, far exceeding the transport distance of any diffusive spin current in magnetically ordered materials, to the best of our knowledge. Monte Carlo simulations reveal significant spin fluctuations, spin-spin correlations and an absence of conventional magnons in such anomalous state; while the response of the anomalous state to perturbation is found to be akin to an overdamped forced oscillator. We find close relation of such state to the correlated “director” state in the material. Our result provides an effective electrical technique to characterize spin-spin correlations and frustrations; it also unveils the potential of frustrated magnets as powerful channel materials for spin transport.
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All authors Di Chen, Bingcheng Luo, Lei Xu, Zian Xia, Linhao Jia, Shaomian Qi, Congkuan Tian, Kangyao Chen, Hang Cui, Guangyi Chen, Shili Yan, Miaoling Huang, Jian Cui, Ya Feng, Zhentao Wang, Jiang Xiao, Jianhua Zhang, Ryuichi Shindou, X.C. Xie, Jian-Hao Chen

Materials Science

Optimizing spin-based terahertz emission from magnetic heterostructures

Terahertz radiation pulses can be generated efficiently through femtosecond laser excitation of a ferromagnetic/nonmagnetic heterostructure, wherein an ultrafast laser-induced spin current results in an electromagnetic THz pulse due to spin-charge conversion. It is, however, still poorly understood how the THz emission amplitude and its bandwidth can be optimized. Here, we perform a systematic analysis of the THz emission from various magnetic heterostructures. The dynamics of the spin current is described by the semiclassical, superdiffusive spin-transport model and the energy dependence of the spin Hall effect of hot electrons is taken into account, leading to emission profiles for Co(2 nm)/Pt(4 nm) bilayer in good agreement with experiment. To identify the optimal {conditions} for THz emission, {we study} the properties of the emitted THz wave profile by systematically varying the layer thicknesses of metallic bilayers, their interfacial spin-current transmission properties, their materials' dependence, and influence of the pump laser-pulse width, allowing us to give optimization guidelines. We find that thin nonmagnetic layer thicknesses of 5-6 nm provide the largest bandwidth in the case of Co/Pt and that the peak frequency of the THz emission depends only on the geometry of the emitter and not on the laser pulse width. The THz bandwidth {is conversely found to} depend on several factors such as exciting laser pulse width, layers' thicknesses, and interface transmission-reflection properties, with the limitation that an increase in the bandwidth by tuning the interface properties comes with a trade-off in the energy efficiency of the emitter. Lastly, we propose a double pulse excitation protocol of a trilayer system that could provide broadband THz emission with a large bandwidth. {Our results contribute to establishing guidelines for optimizing spintronic THz generation.
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All authors Francesco Foggetti, Francesco Cosco, Peter M. Oppeneer, Henri Jaffrés, Niloufar Nilforoushan, Juliette Mangeney, Sukhdeep Dhillon

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

Combining quasi-static and high frequency experiments for the viscoelastic characterization of brain tissue

Mechanical models of brain tissue are a beneficial tool to simulate neurosurgical interventions, disease progression, or brain development. However, the accuracy and predictive capacity of such a model relies on a precise experimental characterization of the tissue's mechanical behavior. Such a characterization is yet limited by inconsistent or contradictory experimental responses reported in the literature, particularly when measurements are performed in different time or length scales. Although brain tissue has been extensively investigated in previous studies, the combination of experimental findings from different scales has received limited attention. In this study, we combine ex vivo mechanical responses of porcine brain tissue obtained at different time scales in a mechanical model. We investigated the mechanical behavior of three different brain regions in the quasi-static domain with multi-modal large strain rheometer measurements and at high frequencies with magnetic resonance elastography (MRE). A comparative analysis of the mechanical parameters obtained from both experimental techniques demonstrated consistent regional variations in the viscoelastic behavior across the two domains. However, the mechanical behavior changes from a higher elasticity in the quasi-static and low frequency domain to a dominating viscosity at high frequencies. Based on the quasi-static and the high frequency behavior, we calibrated a fractional Kelvin-Voigt model and consequently unified the two responses in a single mechanical model to obtain a comprehensive characterization of the tissue's mechanical behavior.
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All authors Laura Ruhland, Nina Reiter, Silvia Budday, Kai Willner

Materials Science

Incorporating Gibbs free energy into interatomic potential fitting

We develop a method to fit high-temperature Gibbs free energy data for the development of interatomic potentials for atomic systems. The approach is based on Hamiltonian thermodynamic integration, enabling the identification of suitable potential parameters such that the system's free energy matches a specified target. The method can be readily combined with conventional fitting techniques for properties such as elastic tensors and liquid pair distribution functions. We validate the effectiveness of the approach using the Uhlenbeck-Ford model and embedded-atom method potentials for pure Ni phases and binary Fe1-xOx liquids under high-pressure and high-temperature conditions. Our framework provides an efficient strategy for incorporating free energy into interatomic potential fitting.
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Materials Science

Turning Insulators into Accelerators: Deciphering the Interfacial Conductivity Boost in ZrO2-Li2ZrCl6 Composites through Machine Learning Molecular Dynamics Simulations

Halide solid-state electrolytes have emerged as promising candidates for all-solid-state lithium batteries due to their high oxidative stability and deformability, yet their moderate ionic conductivity remains a bottleneck. While incorporating ionically insulating ZrO2 nanoparticles (Nat. Commun. 2023, 14, 2459) has been experimentally shown to enhance the ionic conductivity of Li2ZrCl6, the atomistic origin governing this interfacial phenomenon remains unclear. Here, we bridge the spatiotemporal gap in modeling complex heterostructures by developing an accurate machine-learned force fields based on neuroevolution potential, enabling large-scale molecular dynamics simulations of ZrO2/Li2ZrCl6 heterostructures. By systematically investigating four representative low-lattice-mismatch ZrO2/Li2ZrCl6 interfaces, we identify spontaneous interfacial amorphization driven by space-charge effects upon surface cleavage, trapping Li+ and leading to under-coordinated Li+ polyhedrons with pronounced geometric distortion. These distorted amorphous interfacial regions exhibit markedly enhanced Li+ hopping activity, significantly outperforming the bulk lattice, provided that local mobile Li+ inventory is not depleted by surface charge redistribution. This work establishes a computational framework for training validated machine-learned force fields for interfaces and provides mechanistic understandings of the interfacial conductivity boost in the insulator-conductor composites, guiding the rational design of electrolytes toward next-generation solid-state batteries.
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All authors Boyuan Xu, Chen Qian, Liyi Bai, Chenlu Wang, Feng Ding, Qisheng Wu

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

Electronic Origin of Density Wave Orders in a Trilayer Nickelate

The discovery of superconductivity in Ruddlesden-Popper nickelates has established a new frontier in the study of high-temperature superconductors. However, the underlying pairing mechanism and its relationship to the material's electronic and magnetic ground states remain elusive. Since unconventional superconductivity often emerges from a complex interplay of magnetic correlations, elucidating the magnetic ground state of the nickelates at ambient pressure is crucial for understanding the emergence of superconductivity under high pressure. Here, we combine high-resolution angle-resolved photoemission spectroscopy with tight-binding model simulation to investigate the electronic structure of the representative trilayer Ruddlesden-Popper nickelate La$_4$Ni$_3$O$_{10}$. We provide the first experimental evidence of band splitting induced by interlayer coupling and further resolve the momentum-dependent density wave gap structures along all the Fermi surfaces. Our findings identify the mirror-selective Fermi surface nesting as the origin of the interlayer antiferromagnetic spin density wave and demonstrate the dominant role of Ni-3d$_{z^2}$ orbitals in the low-energy physics of La$_4$Ni$_3$O$_{10}$. These results provide a fundamental framework for understanding the magnetic interactions and high-temperature superconductivity mechanism in the Ruddlesden-Popper nickelate family.
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All authors Jiangang Yang, Jun Zhan, Taimin Miao, Mengwu Huo, Qichen Xu, Yinghao Li, Yuyang Xie, Bo Liang, Neng Cai, Hao Chen, Wenpei Zhu, Mingkai Xu, Shenjin Zhang, Fengfeng Zhang, Feng Yang, Zhimin Wang, Qinjun Peng, Hanqing Mao, Xintong Li, Zhihai Zhu, Guodong Liu, Zuyan Xu, Jiangping Hu, Xianxin Wu, Meng Wang, Lin Zhao, X. J. Zhou

Materials Science

Thermal and Microstructural Simulations of Photonic Sintering of Oxide Ceramics: A Two-Scale Scheme

Photonic sintering (PS) offers an ultra-fast, contact-free alternative to conventional sintering and has demonstrated its potential for enhancing the sinterability of acceptor-doped barium zirconate (BZY) ceramics. However, a central challenge in the PS process lies in achieving precise control over thermal self-stabilization in the presence of complex microstructural effects arising from photonic-ray–induced thermal profiles. To elucidate the interplay among thermal fields, microstructural evolution, and PS process parameters, this study establishes a two-scale, non-isothermal simulation framework. The framework integrates macroscopic heat-transfer simulations, incorporating effective heat conduction and photonic-ray–induced volumetric heating in the porous media, with microscopic non-isothermal phase-field sintering simulations that resolve microstructure evolution under local thermal profile. Scale bridging is achieved through a temperature field transferring and mapping that satisfies Hill-Mandel condition between the macroscopic and microscopic simulations, while maintaining synchronization between their asynchronous time-stepping schemes. After calibrating model parameters against experimental measurements, the framework successfully reproduces the experimentally observed porosity inhomogeneity along the sample depth. The influence of enhanced localized mass transport is further examined through a parametric investigation of surface and grain boundary diffusivities. Overall, the proposed framework demonstrates its feasibility and physical interpretability in establishing process-microstructure relationships for the scalable fabrication of high-performance protonic ceramics.
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All authors Junlong Ma, Yangyiwei Yang, Julian N. Ebert, Wolfgang Rheinheimer, Bai-Xiang Xu

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

Electronic band structure, phonon dispersion, and magnetic triple-q state in GdGaI

We theoretically investigate the physical properties of the magnetic van der Waals material GdGaI. Using first-principles calculations, we compute the phonon dispersion of GdGaI and show no imaginary phonons, suggesting that phonon-driven phase transitions are unlikely to occur in GdGaI. Our band calculation reveals that the electronic bands near the Fermi energy are composed of Gd 5d and Ga 4p orbitals. We construct a tight-binding model that incorporates the Gd 5d and Ga 4p orbitals to investigate the magnetic structure. We introduce Kondo coupling between electrons in Gd 5d orbitals and localized spins in Gd 4f orbitals and present the modified band structure when localized spins form a magnetic order characterized by three q vectors that connect the valence and conduction bands. We discuss the origin of the spin order based on the Ruderman-Kittel-Kasuya-Yosida mechanism and suggest that Coulomb interactions acting on electrons near the Fermi level can contribute to the ordering of localized spins.
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All authors Tatsuya Kaneko, Ryota Mizuno, Shu Kamiyama, Hideo Miyamoto, Masayuki Ochi

Materials Science

Synthesis of Monolayer Ice on a Hydrophobic Metal Surface

Understanding water-metal interactions is central to disciplines spanning catalysis, electrochemistry, and atmospheric science. Monolayer ice phases are well established on hydrophilic surfaces, where strong water-substrate interactions stabilize ordered hydrogen-bond networks. In contrast, their formation on hydrophobic metals has been deemed ther-modynamically unfavourable, with water typically assembling into amorphous films, three-dimensional crystallites, or interlocked bilayer ice. Here, we demonstrate the synthesis of a monolayer ice phase on the hydrophobic Au(111) surface using a low-energy-electron-assisted growth method. Combined experimental characterizations including low-energy electron diffraction, angle-resolved photoemission spectroscopy, and X-ray photoelectron spectroscopy, complemented by first-principles calculations, prove that the monolayer ice phase composes of intact water molecules. This approach provides a generalizable strategy for stabilizing ordered two-dimensional ice on inert substrates and offers new insight into the interplay between water and low-energy electrons at hydrophobic interfaces.
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All authors Qiaoxiao Zhao, Meiling Xu, Dong Li, Zhicheng Gao, Yudian Zhou, Wenbo Liu, Jingyan Chen, Peng Cheng, Sheng Meng, Kehui Wu, Yanchao Wang, Lan Chen, Baojie Feng

Thursday 29 January

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

A complete phase-field fracture model for brittle materials subjected to thermal shocks

Brittle materials subjected to thermal shocks experience strong temperature gradients that in turn give rise to mechanical stresses that can be large enough to induce fracture. This work presents a complete model for phase-field fracture for coupled thermo-mechanical problems, wherein the bulk material properties, the material strength, and the fracture toughness are specified independently. The capabilities of the model are assessed across a wide span of scenarios in thermo-mechanical fracture, from the propagation of large pre-existing cracks to crack nucleation under spatially uniform states of stress. In particular, we revisit the controlled quenching of glass plates, and demonstrate how the model captures experimentally observed crack patterns across a range of thermal loads. Ceramic disks subjected to infrared radiation are also examined, with the model reproducing both straight cracks in notched specimens and branching in intact specimens. Finally, ceramic pellets subjected to rapid power pulses are examined, with the model explaining experimental transitions from intact to fractured pellets and the important role of material strength. The results demonstrate that the complete phase-field model unifies the treatment of distinct fracture scenarios under thermal shock, surpassing classical approaches and enabling more reliable prediction of brittle fracture in extreme environments.
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Materials Science · Cross-listed from cs.NE

MolLIBRA: Genetic Molecular Optimization with Multi-Fingerprint Surrogates and Text-Molecule Aligned Critic

We study sample-efficient molecular optimization under a limited budget of oracle evaluations. We propose MolLIBRA (MultimOdaLity and Language Integrated Bayesian and evolutionaRy optimizAtion), a genetic algorithm based framework that pre-ranks candidate molecules using multiple critics before oracle calls: (i) an ensemble of Gaussian process (GP) surrogates defined over multiple molecular fingerprints and (ii) a pretrained text-molecule aligned encoder CLAMP. The GP ensemble enables adaptive selection of task-appropriate fingerprints, while CLAMP provides a zero-shot scoring signal from task descriptions by measuring the similarity between molecular and text embeddings. On the Practical Molecular Optimization (PMO) benchmark with a budget of 1,000 evaluations (PMO-1K), MolLIBRA-L, our variant with a language-model-based candidate generator, attains the best Top-10 AUC on 14/22 tasks and the highest overall sum of Top-10 AUC across tasks among prior methods.
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All authors Masahi Okada, Kazuki Sakai, Hiroaki Yoshida, Masaki Okoshi, Tadahiro Taniguchi

Materials Science

Towards Agentic Intelligence for Materials Science

The convergence of artificial intelligence and materials science presents a transformative opportunity, but achieving true acceleration in discovery requires moving beyond task-isolated, fine-tuned models toward agentic systems that plan, act, and learn across the full discovery loop. This survey advances a unique pipeline-centric view that spans from corpus curation and pretraining, through domain adaptation and instruction tuning, to goal-conditioned agents interfacing with simulation and experimental platforms. Unlike prior reviews, we treat the entire process as an end-to-end system to be optimized for tangible discovery outcomes rather than proxy benchmarks. This perspective allows us to trace how upstream design choices-such as data curation and training objectives-can be aligned with downstream experimental success through effective credit assignment. To bridge communities and establish a shared frame of reference, we first present an integrated lens that aligns terminology, evaluation, and workflow stages across AI and materials science. We then analyze the field through two focused lenses: From the AI perspective, the survey details LLM strengths in pattern recognition, predictive analytics, and natural language processing for literature mining, materials characterization, and property prediction; from the materials science perspective, it highlights applications in materials design, process optimization, and the acceleration of computational workflows via integration with external tools (e.g., DFT, robotic labs). Finally, we contrast passive, reactive approaches with agentic design, cataloging current contributions while motivating systems that pursue long-horizon goals with autonomy, memory, and tool use. This survey charts a practical roadmap towards autonomous, safety-aware LLM agents aimed at discovering novel and useful materials.
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All authors Huan Zhang, Yizhan Li, Wenhao Huang, Ziyu Hou, Yu Song, Xuye Liu, Farshid Effaty, Jinya Jiang, Sifan Wu, Qianggang Ding, Izumi Takahara, Leonard R. MacGillivray, Teruyasu Mizoguchi, Tianshu Yu, Lizi Liao, Yuyu Luo, Yu Rong, Jia Li, Ying Diao, Heng Ji, Bang Liu

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

Plasticity, hysteresis, and recovery mechanisms in spider silk fibers

Spider silk is a remarkable biomaterial with exceptional stiffness, strength, and toughness stemming from a unique microstructure. While recent studies show that silk fibers exhibit plasticity, hysteresis, and recovery under cyclic loading, the underlying microstructural mechanisms are not yet fully understood. In this work, we propose a mechanism explaining the loading-unloading-relaxation response through microstructural evolution: initial loading distorts intermolecular bonds, resulting in a linear elastic regime. Upon reaching the yield stress, these bonds dissociate and the external load is transferred to the polypeptide chains, which deform entropically to allow large deformations. Unloading is driven by entropic shortening until a traction free state with residual stretch is achieved. Subsequently, the fiber recovers as chains reorganize and bonds reform, locking the microstructure into a new stable equilibrium that increases stiffness in subsequent cycles. Following these mechanisms, we develop a microscopically motivated, energy-based model that captures the macroscopic response of silk fibers under cyclic loading. The response is decoupled into two parallel networks: (1) an elasto-plastic network of inter- and intramolecular bonds governing the initial stiffness and yield stress, and (2) an elastic network of entropic chains that enable large deformations. The model is validated against experimental data from Argiope bruennichi dragline silk. The findings from this work are three-fold: (1) explaining the mechanisms that govern hysteresis and recovery and linking them to microstructural evolution; (2) quantifying the recovery process of the fiber, which restores and enhances mechanical properties; and (3) establishing a predictive foundation for engineering synthetic fibers with customized properties.
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Materials Science · Cross-listed from physics.bio-ph

Effects of PLGA coating on biological and mechanical behaviors of tissue engineering scaffolds

Scaffolds have a key role in the clinical success of tissue engineering for the regeneration of damaged tissues. Their bio-performance is often described as the extent to which they can provide an extracellular matrix-like environment for cells embedded where their function and growth can effectively continue. For this purpose, tissue engineering scaffolds should exhibit biodegradability, biocompatibility, bioactivity, delivery, and mechanical performance. The use of polymer coatings, especially poly(lactic-co-glycolic acid) (PLGA), on tissue engineering scaffolds has been found to be one of the most effective methods to improve the scaffold properties. This paper reviews the techniques used to coat tissue engineering scaffolds with PLGA and its effects on the mechanical characteristics, biodegradability, biocompatibility, Molecular delivery, and osteointegration of the scaffolds. It is concluded that apart from apatite-formation ability, all bio-functionalities can be tuned through PLGA coatings. This reflects the great potential of this modification approach to be used in tissue regeneration and therapeutic delivery applications.
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Materials Science

Nanoscale mapping of phase-transformation pathways in medium-Mn TRIP steel by multimodal STEM

The mechanical response of third-generation advanced high-strength steels is governed by phase transformations at the nanoscale, yet the coupled evolution of chemistry and crystallography remains poorly resolved. Here we apply a correlative scanning transmission electron microscopy approach that enables simultaneous mapping of lattice structure, crystallographic orientation, and phase distribution at 10 nanometre resolution in a medium-manganese TRIP steel. We combine nano-beam electron diffraction and energy-dispersive X-ray spectroscopy maps to characterize an industrial medium-manganese steel containing 7.15 weight percent Mn. Tensile testing of a rolled steel sample was performed, and lamellae were extracted from deformed and undeformed regions. Manganese-resolved energy-dispersive X-ray spectroscopy provides a chemical fingerprint that, when combined with nano-beam electron diffraction based phase segmentation, enables robust ferrite-martensite separation and phase-resolved lattice-parameter refinement. The phase fractions of ferrite, austenite, and martensite are quantified together with their corresponding lattice parameters, accompanied by measurable shifts in grain-size distributions and crystallographic texture in the deformed regions. Kernel average misorientation maps reveal systematically lower local misorientation in ferrite than in martensite. This multimodal workflow provides a transferable framework for quantitative, phase-resolved analysis of complex multiphase alloys at the nanoscale.
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All authors Marc Raventós-Tato, S. Leila Panahi, Núria Bagués, David Frómeta, Oleg Usoltsev, Núria Cuadrado, Joaquín Otón

Materials Science

Hydrogen in Brownmillerite Perovskites: First-Principles Insights into Energetics and Induced Electronic-Magnetic Changes

Hydrogen uptake in brownmillerite perovskites A2B2O5 offers an (electro)chemically accessible route to tune functional properties, but mechanistic understanding and design rules for hydrogen-responsive oxides remain limited. Here we employ density functional theory (DFT) to quantify how H absorption affects electronic structure, magnetic exchange, and anisotropy in representative Sr2Fe2O5 and Sr2Co2O5 oxides. We find that hydrogenation introduces a localized electron that stabilizes near the proton, with B-site-dependent preference. The resulting lattice distortions and redistribution of charge density modify exchange coupling and cant the Neel vector, giving rise to weak ferromagnetism. We also show that absorption energies are highly sensitive to proton-electron arrangements and magnetic order, varying by up to 1 eV across different settings. This sensitivity demands consistent treatment of charge localization and spin states, together with careful choice of computational parameters. Extending to a variety of experimentally reported A2B2O5 compositions, we identify candidates with favorable H uptake and uncover a trend linking more favorable absorption to a higher B-site d-electron count. We also demonstrate that the preferred proton absorption site in these materials is governed by local O-O separations and lattice flexibility, which describe the ability of the framework to accommodate proton-induced distortions. Finally, benchmarks of universal machine-learning interatomic potentials reveal uncertainties of about 1 eV for site-resolved absorption energies, motivating descriptor-based surrogate models and targeted DFT validation. Together, these results establish practical design rules for hydrogen-responsive oxides relevant to iono-electronic devices, sensors, and electrically tunable spin functionality.
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Materials Science

Chiral and Clock phases in Twisted Dipolar Clusters

We study samples and a dipolar model of magnetic rods arranged on twisted polygonal clusters in terms of the twist angle. We find that the relative twist between polygons induces noncollinear chiral phases, ranging from flux vortex closure to hedgehog like radial configurations. Chirality, quantified in terms of a bond order parameter, is an emergent property that behaves here as an Ising variable. The chiral configurations of the systems can be understood in terms of chirality and clock index order parameters, whose evolution with twist occurs through discontinuous switching of the magnetic textures. Within a fixed Ising chiral sector, the clock index, rooted in the $C_N$ invariance of the polygons, distinguishes chiral textures that share chirality. As the twist increases, it continuously shifts the preferred relative clock phase, but the N-fold anisotropy only allows discrete orientations; the competition produces a tilted N-fold energy landscape whose global minimum hops discontinuously between clock sectors. As the number of sites in the polygon grows, the resulting response displays a nonlinear crossover from rigid, Ising-like behavior to an almost $\rm U(1)$-invariant regime, governed by a twist-induced suppression of the emergent $Z_N$ clock anisotropy. Guided by symmetry considerations and the outcomes of the numerical minimization, we developed a Landau phenomenological description that is compatible with both the Ising-type chirality and the $Z_N$ clock anisotropy.
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Materials Science · Cross-listed from cs.LG

SCALAR: Quantifying Structural Hallucination, Consistency, and Reasoning Gaps in Materials Foundation Models

Large language models are increasingly applied to materials science reasoning, yet their behavior under physically structured distribution shifts remains poorly understood. We introduce SCALAR (Structural Consistency And Logic Across Regimes), a benchmark for evaluating geometric scale generalization and its connection to structural hallucination, consistency, and reasoning in materials foundation models. Given canonical crystal representations, models must reason about derived nanoparticle structures obtained through supercell expansion and geometric truncation across length scales spanning a few atoms to over 18,000 atoms, totaling $\approx$100,000 structures from DFT-validated unit cells. SCALAR defines three tasks. (i) CIF to property prediction. (ii) A Chain-of-Thought variant with explicit physics-grounded reasoning. (iii) Inverse retrieval identifying crystals from candidates given target properties. Outputs are evaluated via structured metrics capturing numeric error, hallucination, cross-prompt consistency, monotonic reasoning, output validity, and retrieval regret. Experiments across diverse foundation models reveal large, model-dependent shifts under explicit reasoning, often reducing hallucination and error, but frequently destabilizing consistency or validity. These results demonstrate that geometric scale generalization cannot be inferred from accuracy alone. Supplementary materials are available at https://github.com/KurbanIntelligenceLab/SCALAR.
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All authors Can Polat, Erchin Serpedin, Mustafa Kurban, Hasan Kurban

Materials Science

Analysis of some solid amorphous inorganic structures and the boson peak phenomenon with a computational random graph approach

In this study, a new alternative model algorithm has been proposed for assembling amorphous structures, unifying the bosonic paradigm applicable at low temperatures with crystalline models relevant at room and higher temperatures. Physical meaning of main model parameters is determined together with an explanation for the appearing bosonic peak using the random graph theory. Numerically, statistical atomic distribution in a multiphase amorphous system is provided without the melting simulation of base crystals, and the mean energy function has been determined analytically. The calculated table data are in good agreement with neutronography measurements of the actual amorphous alloy in its solid state. Programme optimisations were also implemented, and we outlined several effective steps to achieve the higher processing speed. The proposed programme code can be used for potential test assembling and simulations of amorphous systems with sorting by the optimal atomic content or proportion (i.e. glass forming ability).
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All authors A. Berezner, M. Rybakov, M. Sidlyar, V. Fedorov