Materials Science · Cross-listed from physics.app-ph
Scaling atom-by-atom inverse design with nano-topology optimization and diffusion models
Chun-Teh Chen and Denvid Lau
The mechanical properties of metallic nanostructures are governed not only by
topology but also by
crystal symmetry and face-specific surface physics, which are typically absent from continuum
topology optimization. We develop an atom-by-atom inverse design framework that combines Nano-
Topology Optimization (Nano-TO) with conditional denoising
diffusion probabilistic models. Nano-TO treats each atom as a discrete design variable and evaluates stiffness from the symmetric
curvature of the total energy, removing residual surface-stress bias. A crystallography-aligned multi-shell sensitivity filter stabilizes the optimization and enables designs containing more than 6.5 x 10^5 atoms. Using aluminum nanocantilevers, we identify a surface-physics-driven
topology selection rule: thickness-periodic beams favor brace-dominated trusses, whereas finite-thickness beams favor nearly closed walls that provide efficient shear paths and reduce surface penalties. At sufficiently small scales, these walls become mechanically unstable, and truss-like layouts reappear. In nanopillar studies, atomistic optimization outperforms continuum
topology-optimized designs. Finally, conditional
diffusion models trained on Nano-TO data generate diverse high-performance candidates near the optimization frontier. These results establish nanoscale inverse design as a coupled problem of
topology and surface physics.
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Materials Science
Proton-Transfer Ferroelectrics with Exceptional Switching Endurance
Bibek Tiwari, Yuanyuan Ni and Xiaoshan Xu
Reliable organic ferroelectrics for
memory applications require extreme endurance under repeated electrical switching. Here we demonstrate exceptional fatigue resistance in highly crystalline 2-methylbenzimidazole (MBI) films grown by low-temperature deposition followed by restrained crystallization (LDRC) in a simple Pt/MBI/Pt capacitor geometry. Switching kinetics analyzed using the Kolmogorov-Avrami-Ishibashi (KAI) model reveal characteristic millisecond switching times and quasi-one-dimensional domain growth associated with
proton transfer along hydrogen-bond chains. Guided by these kinetics, we implemented a stringent fatigue protocol designed to maximize switching stress, involving bipolar switching at approximately 2Ec with 5 ms pulses, well beyond the characteristic switching time, for continuous operation over approximately 2 weeks. The remanent polarization exhibits only a minor wake-up (+10% within the first 10^4 cycles) and ultimately returns to approximately its initial value after 10^8 cycles, with testing limited by experimental duration rather than device failure. This robust endurance is achieved in an unengineered structure and contrasts with
polymer ferroelectrics such as P(VDF-TrFE), where comparable performance typically relies on interfacial engineering. The combination of LDRC-enabled high crystallinity and localized
proton-transfer switching, which introduces minimal structural perturbation during polarization reversal, enables this outstanding fatigue tolerance and highlights MBI as a simple, fluorine-free platform for durable organic ferroelectric devices.
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Materials Science · Cross-listed from physics.optics
Coherent multi-dimensional widefield microscopy
Mohammadjavad Azarm, Rizwan Asif, Alessandra Milloch et al. (+14 more)
Understanding how electronic excitations evolve across space and time is essential for revealing the microscopic processes underlying
quantum and optoelectronic materials. However, existing approaches cannot simultaneously resolve ultrafast coherent dynamics with microscopic spatial information: pump-probe microscopy lacks access to
quantum coherence, while two-dimensional electronic spectroscopy (2DES) requires slow point-by-point scanning for spatial resolution. Here we introduce a widefield two-dimensional electronic spectroscopy microscope (2DESM) combining multidimensional coherent spectroscopy with widefield imaging, enabling simultaneous femtosecond temporal and micrometer spatial resolution across a broadband spectral range. Applying 2DESM to hBN-encapsulated WSe2, we directly visualize spatial variations in
exciton coherence and relaxation associated with the local environment, establishing 2DESM as a powerful platform for probing many-body interactions, energy transport, and structure-function relationships in low-dimensional materials and devices.
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All authors Mohammadjavad Azarm, Rizwan Asif, Alessandra Milloch, Francesco Proietto, Donna Datta, Ambrine Lanseur, Sreyan Raha, Filippo Fabbri, Federica Bianco, Fabrizio Preda, Antonio Perri, Suman Chatterjee, Ziliang Ye, Giulio Cerullo, Stefania Pagliara, Gabriele Ferrini, Claudio Giannetti
Materials Science · Cross-listed from cond-mat.mes-hall
Theoretical Prediction of Three-Dimensional $sp^2$-free Graphyne-Based Nanomaterials via Density Functional Theory
Djardiel da S. Gomes, Alexandre F. Fonseca and Marcelo L. Pereira Jr
The search for carbon-based materials with tailored dimensionality and properties remains an important topic in materials science, particularly for applications in electronics, photonics, and nanomechanics. Among the emerging platforms in this context, graphyne (GY) represents a class of two-dimensional (2D) carbon allotropes composed of benzene rings connected by acetylenic linkages, yielding networks containing both $sp$- and $sp^2$-hybridized carbon atoms. By analogy with the transformation of $sp^2$ carbon networks such as
graphene into $sp^3$-bonded diamond through interlayer covalent bonding, we construct three-dimensional (3D) GY-derived frameworks (3DGY) by covalently connecting stacked $\alpha$-, $\beta$-, and $\gamma$-GY sheets via out-of-plane acetylene bridges. This approach converts the original $sp^2$ nodes into $sp^3$ centers while preserving the $sp$ character of the acetylenic segments, producing fully $sp$-$sp^3$ carbon networks. Structural relaxation shows that the $\alpha$-derived framework does not converge to a stable configuration within this scheme, whereas the $\beta$- and $\gamma$-3DGY phases form stable architectures. Density functional theory (DFT) calculations, combined with ab initio molecular dynamics (AIMD) simulations, confirm the energetic, thermal, and dynamical stability of these two systems and are further used to investigate their structural, mechanical, electronic, and optical properties. Mechanical analysis reveals anisotropic elastic behavior, whereas electronic structure calculations show indirect band gaps of approximately 0.15 eV for $\beta$-3DGY and 1.65 eV for \gamma-3DGY. Optical calculations further reveal anisotropic responses, with absorption extending from the infrared to the visible. These results identify \beta-3DGY and \gamma-3DGY as new three-dimensional carbon allotropes with distinct mechanical, electronic, and optical properties.
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Materials Science
Active learning-enabled multi-objective design of thermally conductive and mechanically compliant polymers
Yuhan Liu, Jiaxin Xu, Renzheng Zhang et al. (+2 more)
Polymers are attractive in applications like flexible electronics and thermal interface materials due to their mechanical compliance and processability. However, conventional
polymers have low thermal conductivity (TC), limiting their heat dissipation performance. Identifying
polymers that simultaneously achieve high intrinsic TC and mechanical flexibility (i.e., low modulus) remains a challenge. Here, we develop an active learning (AL) framework based on multi-objective
Bayesian optimization (MOBO) to discover
polymers exhibiting both high TC and low bulk modulus. Initially, a high-throughput molecular dynamics (MD) pipeline generated an initial
dataset, and independent Deep Kernel Learning (DKL) surrogate models were trained for TC and bulk modulus to predict properties and uncertainties. Using the parallel noisy expected hypervolume improvement (qNEHVI) acquisition function, the framework iteratively screens a larger unlabeled
polymer database, systematically recommends new
polymer candidates for MD evaluation, and updates the DKL models with newly acquired data. Ultimately, six candidates were identified on the Pareto front, representing optimal trade-offs between TC and modulus. Interpretability analysis further revealed molecular features associated with these trade-offs, and synthesizability assessment supported the practical relevance of the selected candidates. By combining MD simulations with AL-enabled MOBO, our workflow mitigates data scarcity, reduces development time, and provides actionable guidance for designing multifunctional
polymers tailored for different applications.
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All authors Yuhan Liu, Jiaxin Xu, Renzheng Zhang, Meng Jiang, Tengfei Luo
Materials Science
Quantum Saturation of the Electro-Optic Effect
Aiden Ross, Sankalpa Hazra, Albert Suceava et al. (+4 more)
Future
quantum computing architectures require electro-optic materials that maintain a strong, stable performance at cryogenic temperatures. In conventional electro-optic materials, large electro-optic coefficients are often confined to narrow temperature windows near structural phase transitions, where small changes in temperature lead to large changes in the electro-optic response. Using thermodynamic analysis, phase-field simulations, experimental growth and cryogenic optical measurements we show that
quantum fluctuations can be harnessed to overcome this trade-off. By tuning the ferroelectric phase boundaries down to 0 K,
quantum fluctuations induce a saturation regime in which a large electro-optic response becomes nearly temperature-independent below 25 K. We demonstrate that the phase boundaries can be tuned through either strain in BaTiO3 or through chemical composition in Ba1-xCaxTiO3, leading to a large, temperature insensitive, cryogenic electro-optic effect comparable to bulk BaTiO3 at room temperature; the performance exceeds BaTiO3-on-Si by over an order of magnitude. These findings establish a general design principle for engineering high-performance electro-optic materials for cryogenic applications.
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All authors Aiden Ross, Sankalpa Hazra, Albert Suceava, Dylan Sotir, Darrell G. Schlom, Venkatraman Gopalan, Long-Qing Chen
Materials Science
Structural Chart of Copper-Silver Nanoalloys through machine learning
Manoj Settem, Emanuele Telari, Antonio Tinti et al. (+2 more)
Nanoalloys (or
alloy nanoparticles) are an important class of materials that are promising for their functional properties. However, designing synthesis protocols to control their structure and chemical ordering is rather challenging. Part of this difficulty stems from the lack of information on their metastable and stable structures. Here, we develop a general computational framework to construct a structural chart of nanoalloys using 38-atom AgCu nanoalloys as a model system. Initially, the
equilibrium structural distribution is sampled using parallel tempering combined with molecular dynamics (PTMD). Using a machine learning (ML) based approach, the vast number of sampled configurations are classified into various structural classes. This ML approach produces a single three-dimensional map in which all structures and compositions can be visualized and discriminated. Finally, a finite-temperature structural chart is constructed which provides information on the dominant structures across the entire range of compositions and temperatures. In addition, the structural chart reveals significant differences in thermal stability between nanoalloys and bulk
alloys. The presented framework provides an effective route to compute and map the vast structural and chemical space of multicomponent nanoparticles, paving the way to the rational design of functional nanoalloys.
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All authors Manoj Settem, Emanuele Telari, Antonio Tinti, Riccardo Ferrando, Alberto Giacomello
Materials Science
Ferromagnetic Spin Glass State and Anomalous Hall Effect in Topological Semimetal Candidate Mn2Sb2Te5
M.M. Sharma, Ankush Saxena, S.M. Huang et al. (+3 more)
Materials that intrinsically possess both magnetism and topological states represent a key frontier of
quantum materials research. Recently, Mn2(Bi/Sb)2Te5 has emerged as a promising candidate for hosting topological surface states coupled with intrinsic
magnetic order, making it a potential
magnetic Weyl semimetal. In this study, we investigate the
magnetic and transport properties of Mn2Sb2Te5 single
crystals. The magnetization measurements reveal a
spin glass state with field-induced ferromagnetism. Although heat capacity measurement indicates the absence of long-range order, the intrinsic magnetization in Mn2Sb2Te5 significantly affects its electrical properties, as demonstrated by the anomalous
Hall effect. This work provides valuable insights into the magnetism and the electronic properties of Mn2Sb2Te5, establishing Mn2(Bi/Sb)2Te5 system as a compelling platform for exploring the interplay between magnetism and non-trivial band
topology, enabling emergent
quantum phases and novel transport responses not accessible in non-
magnetic systems.
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All authors M.M. Sharma, Ankush Saxena, S.M. Huang, Santosh Karki Chhetri, Jin Hu, V.P.S. Awana
Materials Science
Ultrafast Sintering
Jian Luo
This Perspective critically assesses recent advances in ultrafast sintering and highlights open scientific questions and emerging technological opportunities. Mechanistic studies of flash sintering indicate that the flash event initiates as a coupled thermal and electrical runaway, while rapid densification is enabled by ultrahigh heating rates and elevated sintering temperatures. Building on this understanding, ultrafast sintering has been realized without passing electric currents through the specimens via multiple approaches, including rapid thermal annealing (using intense infrared heating), ultrafast high-temperature sintering (in which specimens are sandwiched between graphite felt heaters), blacklight sintering (employing blue
laser or intense ultraviolet irradiation), atmospheric-pressure
plasma sintering, and induction ultrafast sintering (utilizing skin currents in direct induction heating or no current in the specimens in susceptor-heating mode). Reactive ultrafast synthesis and sintering have also been demonstrated. Although several hypotheses have been proposed, the mechanisms governing ultrafast sintering and its kinetics warrant further investigation. In particular, reactive ultrafast synthesis and sintering of compositionally complex ceramics are scientifically intriguing to understand while also presenting technological opportunities. The expanding range of ultrafast sintering methods provides a versatile platform for high-throughput materials discovery, especially in the rapidly growing field of high-
entropy and compositionally complex ceramics, which feature vast compositional spaces to explore.
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Materials Science · Cross-listed from cond-mat.supr-con
Magnetic flux distribution, quasiparticle spectroscopy, and quality factors in Nb films for superconducting qubits
Amlan Datta, Bicky S. Moirangthem, Kamal R. Joshi et al. (+6 more)
Niobium is a practical material platform for superconducting microwave
circuits; however, device-level performance can vary significantly depending on film growth and processing conditions. We compare three epitaxial Nb films grown on $c-$plane sapphire substrates under nominally identical conditions, except for the deposition temperature. To correlate internal quality factors, $Q_{\mathrm {i}}$, with material properties, we combine magneto-optical imaging of
magnetic flux distribution with quasiparticle spectroscopy via measurements of the London penetration depth, $\lambda(T)$. In the low-$Q_{\mathrm i}$ film, there is a lesser ability to screen the
magnetic field and an irregular temperature variation of $\lambda(T)$, implying the existence of localized in-gap states. High $Q_{\mathrm i}$ films show the opposite trend. We conclude that our measurements provide an efficient method for characterizing and optimizing superconducting films for
quantum informatics applications.
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All authors Amlan Datta, Bicky S. Moirangthem, Kamal R. Joshi, Anthony P. Mcfadden, Florent Lecocq, Raymond W. Simmonds, Makariy A. Tanatar, Matthew J. Kramer, Ruslan Prozorov
Materials Science
AlphaDiffract: Automated Crystallographic Analysis of Powder X-ray Diffraction Data
Nina Andrejevic, Ming Du, Hemant Sharma et al. (+6 more)
Materials identification and structural understanding from powder X-ray diffraction (PXRD) data is a long-standing challenge in materials science, fundamental to discovering and characterizing novel materials. A prerequisite for full structure solution is the accurate determination of the
crystal lattice, including
lattice parameters and crystallographic
symmetries. Traditional methods for this are iterative and typically require expert input, and while existing deep learning approaches have shown promise, a robust, single-shot method for comprehensive
lattice determination from experimental data remains a key goal. Here, we introduce AlphaDiffract, a deep learning framework that achieves state-of-the-art performance in predicting the
crystal system, space group, and
lattice parameters directly from PXRD patterns. AlphaDiffract utilizes a 1D adaptation of the ConvNeXt architecture, a modern convolutional neural network that integrates key design principles from
transformers, coupled with dedicated prediction heads for each crystallographic property. The model is trained on the largest-to-date physics-based
dataset of over 31 million simulated diffraction patterns, generated by augmenting 312,267 curated structures from the ICSD and Materials Project databases. Crucially, it demonstrates strong generalization to experimental data, achieving 81.7%
crystal system accuracy and 66.2% space group accuracy on the RRUFF
dataset while additionally predicting all six
lattice parameters. By providing a unified model for rapid and accurate
lattice determination from PXRD data, AlphaDiffract represents a significant step forward in leveraging deep learning for high-throughput materials discovery.
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All authors Nina Andrejevic, Ming Du, Hemant Sharma, James P. Horwath, Aileen Luo, Xiangyu Yin, Michael Prince, Brian H. Toby, Mathew J. Cherukara
Materials Science · Cross-listed from physics.app-ph
Laser-Enhanced Contact Optimization in Silicon Photovoltaics: Mechanisms, Reliability, and Predictive Process Design
Donald Intal and Abasifreke U. Ebong
Laser-enhanced contact optimization (LECO) has emerged as an important method for simultaneously reducing contact resistivity and metallization-induced recombination in advanced crystalline silicon
solar cells, thereby enabling concurrent gains in fill factor and open-
circuit voltage, particularly in TOPCon devices. However, broader industrial transferability remains constrained by the need to preserve these gains within a narrow process window and by unresolved, architecture-dependent questions regarding the kinetic stability of some LECO-modified interfaces. LECO is therefore examined in this review as a coupled multiphysics process that links localized electrothermal activation and microstructural
evolution to device-level electrical signatures through an instantaneous regime map and a reliability classification based on time-dependent drift. A predictive workflow is outlined that couples transient electrothermal modeling with reduced state metrics, including effective
diffusion depth and local areal energy density, and propagates calibrated thresholds across the recipe space. The framework separates stable optimization from marginal activation and latent damage, while explaining why fine-line scaling and copper-containing contact stacks can tighten stability margins through current localization and
diffusion-barrier constraints. These insights provide a basis for reliability-aware process-window design and future digital-twin-assisted optimization of LECO for scalable, high-efficiency silicon photovoltaics.
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Materials Science
Reliable and High Performance IGZO and In2O3 Transistors via Channel Capping
C. W. Cheng, J. Smith, K. Mashooq et al. (+13 more)
A device and process strategy for achieving reliable indium gallium zinc
oxide and indium
oxide transistors compatible with a 400oC BEOL thermal budget and without performance degradation is demonstrated by fully exploiting intrinsic
oxide material properties. An indium
oxide transistor with a novel amorphous In2O3 mixed with SiO2 capping layer exhibits a positive threshold voltage, high extrinsic saturation mobility 33.1 cm2/V.s ,and only a 5mV Vt shift after positive-bias stress at 3 MV/cm for 1000s at room temperature, superior to conventional SiO2 encapsulation.
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All authors C. W. Cheng, J. Smith, K. Mashooq, P. Solomon, R. Watters, T. Philicelli, D. Piatek, C. Lavoie, M. Hopstaken, L. Gignac, B. Khan, M. BrightSky, G. Gionta, P. Hashemi, V. Narayanan, M. M. Frank
Materials Science
Experimental Insights into the Limiting Mechanism of Vacancy Transport in Sodium Metal Anodes for Solid State Batteries
Ansgar Lowack, Rafael Anton, Bingchen Xue et al. (+4 more)
Ceramic solid-state batteries with sodium (Na) metal electrodes promise enhanced safety and energy density compared to contemporary secondary batteries. However, the critical delamination of the Na metal electrode during discharge - when vacancies accumulate at the Na/ceramic interface - remains to be understood and avoided. The study investigates the underlying mechanism by applying a linear current ramp between two Na metal electrodes separated by a ceramic solid electrolyte to provoke vacancy buildup. Above a critical current density $j_\mathrm{crit}$ the anode voltage no longer increases linearly but in an exponential fashion. Arrhenius analysis of $j_\mathrm{crit}(T)$ for the three solid electrolytes $\mathrm{Na_{1.9}Al_{10.67}Li_{0.33}O_{17}}$, $\mathrm{Na_{3.4}Zr_2Si_{2.4}P_{0.6}O_{12}}$, and $\mathrm{Na_5SmSi_4O_{12}}$ yields an activation energy $E_\mathrm{A}$ of $0.13$ to $0.15\,\mathrm{eV}$. This exceeds the activation energy of $0.053\,\mathrm{eV}$ for the diffusive vacancy migration in bulk Na significantly. Further, $E_\mathrm{A}$ is insensitive to anode microstructure variation. Both observations rule out bulk
diffusion as the transport bottleneck. A thin tin-sodium
alloy interlayer lowers $E_\mathrm{A}$ to $(0.10\pm0.01)\,\mathrm{eV}$, implicating interfacial thermodynamics as rate-limiting. Sodiophilic, Na-conducting interlayers and low-tension interfaces emerge as key pathways to stable, high-rate Na-SSBs at practical stack pressures.
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All authors Ansgar Lowack, Rafael Anton, Bingchen Xue, Kristian Nikolowski, Cornelius Dirksen, Mareike Partsch, Alexander Michaelis
Materials Science · Cross-listed from cond-mat.mes-hall
Comment on 'Observation of Shapiro Steps in the Charge Density Wave State Induced by Strain on a Piezoelectric Substrate'
D.Yu. Saltykova, M.V. Nikitin, V.Ya. Pokrovskii et al. (+5 more)
In their Letter Fujiwara et al. (10.48550/arXiv.2511.09888. 2025) report a high-quality experiment demonstrating the synchronization of the CDW sliding in NbSe3 whiskers (nanowires) with surface acoustic waves (SAWs). The SAWs are induced in the conventional LiNbO3 piezoelectric substrates through application of rf voltage to an interdigital transducer (IDT). When a SAW mode is excited, Shapiro steps (ShSs) appear on the I-V curves, while no ShSs are observed when the frequency is shifted from the resonance. This gives clear evidence of synchronization of the CDW with the acoustic modes.
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All authors D.Yu. Saltykova, M.V. Nikitin, V.Ya. Pokrovskii, S.G. Zybtsev, V.V. Kolesov, V.V. Kashin, I.E. Kuznetsova, I.A. Nedospasov
Materials Science
Virtual materials testing of ASSB cathodes combining AI-based stochastic 3D modeling and numerical simulations
Anina Dufter, Sabrina Weber, Orkun Furat et al. (+7 more)
The performance of all-solid-state battery (ASSB) cathodes strongly depends on their microstructure. Optimizing the cathode morphology can therefore enhance effective macroscopic properties such as ionic and electronic conductivity. The search for optimized microstructures can be facilitated by virtual materials testing: By integrating image analysis and
stochastic microstructure modeling to generate a wide range of realistic 3D microstructures and evaluate their effective macroscopic properties by means of numerical simulations, thereby reducing the need for extensive physical experiments. This approach allows for the investigation of structure-property relationships through parametric regression models that incorporate relevant geometrical descriptors of microstructures such as volume fractions, mean geodesic tortuosities, specific surface areas, and constrictivities. By linking these geometrical descriptors to macroscopic properties, virtual materials testing provides quantitative insight into how microstructure influences material performance. In the present paper, this framework is applied for ASSB cathodes. In addition, by systematically varying model parameters, a broad range of 3D microstructures can be generated, which remain close to the original cathode morphology while inducing targeted changes in selected geometrical descriptors. The resulting database enables the calibration of regression models whose predictive performance is assessed by comparing predicted and simulated effective properties such as the ionic and electronic conductivity, thereby quantifying how accurately combinations of geometrical descriptors can explain and predict variations in effective macroscopic properties.
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All authors Anina Dufter, Sabrina Weber, Orkun Furat, Johannes Schubert, René Rekers, Maximilian Luczak, Erik Glatt, Andreas Wiegmann, Anja Bielefeld, Volker Schmidt
Materials Science · Cross-listed from physics.optics
Unveiling nanolaser physics: Non-Perturbative Measurement of the Lasing-Mode Photon Population at the Sub-Picoseconds and Nanometer Scale
Cléo Santini, Thi Huong Ngo, Luiz H. G. Tizei et al. (+13 more)
Semiconducting nanowire
lasers (NWLs) constitute nanometer-scale modular and tunable light sources hence an essential component for integrated opto-electronics. However, improving and optimizing NWL operation requires characterization of their near-field and dynamics at the nanometer scale, which is hampered by the light diffraction limit. In this article, we show how to non-perturbatively measure the absolute number of
photons in the nanolaser cavity above the lasing threshold with sub-picosecond resolution using a GaN nanowire nanolaser, as well as map the lasing mode spatial profile at the nanoscale. This technique, based on the simultaneous measurements of the
photon induced near-field electron microscopy (PINEM) and the
photons far-field, allows for the complete nanoscale and time-resolved characterization of a NWL in operation while monitoring its macroscopic optical properties.
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All authors Cléo Santini, Thi Huong Ngo, Luiz H. G. Tizei, Aurélie Lloret, Tom Fraysse, Sebastien Weber, Adrien Teurtrie, Virginie Brändli, Sebastien Chenot, Denis Lefebvre, Stéphane Vézian, Hugo Lourenço-Martins, Christelle Brimont, Benjamin Damilano, Thierry Guillet, Sophie Meuret
Materials Science · Cross-listed from cond-mat.dis-nn
Generative Inversion of Spectroscopic Data for Amorphous Structure Elucidation
Jiawei Guo and Daniel Schwalbe-Koda
Determining atomistic structures from characterization data is one of the most common yet intricate problems in materials science. Particularly in amorphous materials, proposing structures that balance realism and agreement with experiments requires expert guidance, good interatomic potentials, or both. Here, we introduce GLASS, a generative framework that inverts multi-modal spectroscopic measurements into realistic atomistic structures without knowledge of the potential energy surface. A score-based model learns a structural prior from low-fidelity data and samples out-of-distribution structures conditioned on differentiable spectral targets. Reconstructions using pair distribution functions (PDFs), X-ray absorption spectroscopy, and diffraction measurements quantify the complementarity between spectral modalities and demonstrate that PDFs is the most informative probe for our framework. We use GLASS to rationalize three contested experimental problems: paracrystallinity in amorphous silicon, a
liquid-
liquid phase transition in sulfur, and ball-milled amorphous ice. In each case, generated structures reproduce experimental measurements and reveal mechanisms inaccessible to diffraction analysis alone.
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Materials Science · Cross-listed from cond-mat.mes-hall
Symmetry-enabled tunable square-lattice Hubbard models in $\Gamma$-valley moiré bilayers
Rui Shi, Kejie Bao, Huan Wang et al. (+1 more)
Square-
lattice moiré systems provide a promising route for
quantum simulation of Hubbard physics, yet electrically tunable realizations of the hopping ratio $t'/t$ have so far been limited to specific valley configurations. A natural question is whether the same tunability can be extended to the more broadly occurring $\Gamma$-valley systems. Here we identify a
symmetry-controlled route for realizing electrically tunable square-
lattice Hubbard models in $\Gamma$-valley twisted homobilayers. At small twist angles, an emergent layer-exchange
symmetry separates the low-energy states into flat bands localized on two nested square sublattices, suppressing inter-sublattice hopping. An interlayer displacement field breaks this
symmetry and induces controllable hybridization between the sublattices, enabling continuous tuning of the $t'/t$ ratio over a wide range while preserving an effective single-band description. We further establish a formal correspondence between $\Gamma$- and M-valley moiré systems, revealing them as different
symmetry limits of a unified framework for tunable square-
lattice Hubbard models. Our results uncover a general
symmetry principle underlying displacement-field tunability and extend electrically controllable square-
lattice Hubbard physics to a broad family of $\Gamma$-valley materials.
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All authors Rui Shi, Kejie Bao, Huan Wang, Jing Wang
Materials Science
Field-induced spin-flip and spin-flop transitions in NdFeO3
Mariana M. Gomes, Rui Vilarinho, E. Miranda et al. (+14 more)
Magnetic control of correlated
spin systems is central to the development of next-generation
spin-based technologies. Rare-earth orthoferrites provide an interesting platform in which exchange coupling between rare-earth 4f and transition-metal 3d moments generates competing
magnetic interactions and multiple metastable states. Here, we show that the orientation of the applied
magnetic field drives different
magnetic phase transition sequences in NdFeO3 across a broad temperature range. Using Raman and polarized terahertz spectroscopies, supported by magnetization and specific-heat measurements, we track the temperature- and field-dependent
evolution of the different
magnetic phases and the successive
spin rearrangements, driven by 4f - 3d
magnetic anisotropic interactions. For fields applied along the crystallographic c-axis, a
spin-reorientation transition is followed by
spin-flop and
spin-flip processes, producing an unexpectedly complex
magnetic phase sequence at low temperatures. Below 8 K, precursor effects associated with ordering of the Nd-sublattice strongly modify the transition pathway. Our results demonstrate how anisotropic 4f-3d coupling enables
magnetic-field control of coupled
spin excitations and provide a route to accessing novel
spin configurations in rare-earth orthoferrites.
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All authors Mariana M. Gomes, Rui Vilarinho, E. Miranda, Ana S. Silva, Christelle Kadlec, Filip Kadlec, Miroslav Lebeda, Petr Proschek, Matus Mihalik jr., Marian Mihalik, Diparkan Jana, Fadi Choueikani, Clement Faugeras, José Antonio Paixão, Ester de Prado, Stanislav Kamba, Joaquim Agostinho Moreira
Materials Science
Open Quantum System Theory of Muon Spin Relaxation in Materials
Elvis F. Arguelles and Osamu Sugino
We present a non-Markovian theory of
muon spin relaxation that treats the implanted
muon as an open
quantum spin coupled to a temporally correlated local
magnetic environment. Using a Schwinger-Keldysh influence-functional formulation, we derive a
stochastic equation of motion for the
muon spin, in which the fluctuation kernel is fixed by the local-field correlation tensor, while the retarded
memory torque is introduced through an effective phenomenological backaction kernel. In the appropriate limits, the theory reduces to standard Kubo-Toyabe descriptions. This enables quantitative, global analysis of zero-field (ZF) and weak longitudinal-field (LF) $\mu$SR spectra beyond the strong-collision approximation. Applied to $\mathrm{Li}_{0.73}\mathrm{CoO}_2$, the model supports a decomposition into a quenched width and a Li-driven dynamical component within the adopted parametrization, and yields fluctuation rates approximately consistent with activated behavior over the intermediate-temperature window. The fitted
memory parameter is most visible in the crossover between quasi-static and fast-fluctuation limits.
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Materials Science
Formation of Ag and Au Plasmonic Nanoparticles by Ion Implantation in Ga$_2$O$_3$ thin films
Inês Freitas, Ana Sofia Sousa, Duarte Magalhães Esteves et al. (+6 more)
Gallium
oxide (Ga$_2$O$_3$) is a wide-bandgap
semiconductor with exceptional electrical and optical properties, making it a promising material for optoelectronic and sensing applications. In this work, we demonstrate for the first time the formation of plasmonic silver (Ag) and gold (Au) nanoparticles embedded in Ga$_2$O$_3$ thin films via ion implantation. Ga$_2$O$_3$ films deposited by RF sputtering on sapphire substrates were implanted with Ag or Au ions at 150 keV and a nominal fluence of 5 $\times$ 10$^{16}$ ions/cm$^2$, followed by thermal annealing between 200 and 700 {\deg}C. Rutherford backscattering spectrometry (RBS) measurements revealed saturation effects during implantation, resulting in lower incorporated fluences, as well as out-
diffusion with post-implantation annealing. Transmission electron microscopy confirmed the formation of metallic nanoparticles with a distribution consistent with the metal profiles measured by RBS. Optical absorption measurements showed a pronounced localized surface plasmon resonance (LSPR) band in the Ag-implanted films, visible even in the as-implanted state and red-shifting with increasing annealing temperature, while Au-implanted films exhibited a distinct LSPR peak only after annealing at $\geq$500 {\deg}C. The observed LSPR shifts with annealing are attributed primarily to changes in the Ga$_2$O$_3$
matrix rather than a change in nanoparticle size. These results establish ion implantation as a viable approach for integrating plasmonic nanostructures into Ga$_2$O$_3$.
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All authors Inês Freitas, Ana Sofia Sousa, Duarte Magalhães Esteves, Mamour Sall, Ângelo Rafael Granadeiro da Costa, Joana Madureira, Sandra Cabo Verde, Katharina Lorenz, Marco Peres
Materials Science
Fine-tuning of universal machine-learning interatomic potentials for high-entropy alloys with application to 2D (Mo,Ta,Nb,W,V)S$_2$
Chun Zhou and Hannu-Pekka Komsa
High-
entropy alloy (HEA) materials and their two-dimensional counterparts (2D-HEAs) have recently attracted
attention due to their tunable properties and catalytic potential, yet their chemical complexity makes direct density functional theory (DFT) calculations computationally prohibitive. The complexity also makes training of machine-learning interatomic potentials (MLIPs) challenging, but this could possibly be overcome by employing universal MLIPs as starting point. In this work, we investigate the applicability of universal MLIP models for 2D transition metal dichalcogenide HEAs and develop effective fine-tuning strategies. Training structures are systematically generated and selected, and the performance of universal and fine-tuned models are benchmarked against DFT. We find that all universal MLIPs employed in this work yield unsatisfactory mixing energies without fine-tuning. Applied to the experimentally synthesized (Mo,Ta,Nb,W,V)S$_2$ system, fine-tuned models based on enumerated structures can achieve near-DFT accuracy in predicting mixing energies while enabling Monte-Carlo simulations and random structure sampling at scales inaccessible to DFT.
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Materials Science
Mechanical Origin of High-Temperature Thermal Stability in Platinum Oxides
Fangyuan Ma, Mengzhao Sun, Xuejian Gong et al. (+3 more)
Platinum
oxides are vital catalysts, but their limited thermal stability hinders applications. Recent studies have uncovered a structural transition in two-dimensional platinum
oxides that significantly enhances their thermal resilience by several hundred Kelvin. Herein, we demonstrate that this enhanced stability stems from the mechanical robustness of the elastic network at the atomic scale. Prior to the transition, an over-constrained
lattice generates localized states of self-stress through an incommensurate Moiré pattern with the platinum substrate, reducing thermal endurance. After the transition, the
oxide shifts to a mechanically flexible structure with balanced degrees of freedom and constraints. The isostatic network, together with the platinum substrate, forms a commensurate Moiré superlattice that relaxes elastic energy and enhances stability. These findings highlight the fundamental role of network connectivity in governing thermal stability, and provide a design principle for catalysts in extreme environments.
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All authors Fangyuan Ma, Mengzhao Sun, Xuejian Gong, Jun Cai, Zhujun Wang, Di Zhou
Materials Science
Ultrafast optical route to coupled ferroelectric and altermagnetic switching
Yuhao Gu, Yu-Hui Song, Peng-Jie Guo et al. (+5 more)
Exploring novel magnetoelectric coupling mechanisms to achieve control of ferroelectric polarization and magnetism is highly significant for both fundamental science and electronic device applications. Although extensive studies have been conducted on electrical switching of magnetism in multiferroic materials, simultaneous ultrafast
laser switching of ferroelectric polarization and altermagnetism remains unexplored. In this letter, we propose that the ultrafast
laser can be used to switch ferroelectric polarization and altermagnetism concurrently in charge-order-induced altermagnetic ferroelectrics. Building on this idea, we further demonstrate that such dual switching can be realized in charge-order-induced altermagnetic ferroelectric LiV$_2$F$_6$ by
symmetry analysis and time-dependent density functional theory (TDDFT) calculation. Given that LiV$_2$F$_6$ has already been experimentally synthesized, our work not only provides an ideal material platform for experimentally realizing simultaneous switching of ferroelectric polarization and altermagnetism but also holds potential application value in future ultrafast spintronic devices.
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All authors Yuhao Gu, Yu-Hui Song, Peng-Jie Guo, Yihao Wang, Zhe Li, Ze-Feng Gao, Huan-Cheng Yang, Zhong-Yi Lu
Materials Science
Profound impacts of interlayer interactions in bilayer altermagnetic V2S2O
Siqi Xu, Qilong Cui, Shaowen Xu et al. (+6 more)
Two-dimensional altermagnets exhibit exceptional potential for low-power spintronics via nonrelativistic
spin splitting and zero net magnetization. Here, we systematically investigate the influence of interlayer interactions on the electronic,
magnetic and
quantum transport properties of
bilayer vanadium oxysulfide (V2S2O), a prototypical layered altermagnet, using DFT and NEGF calculations. Our results reveal that interlayer interactions predominantly modulate the p-orbital derived top valence bands, inducing a profound competitive valence band maximum position between Gamma-point pz and X/Y-point pxy orbitals, with an energy difference as small as 9 meV. Furthermore, interlayer interactions suppress the piezomagnetic effect and impose additional requirements on the type of strain for the
bilayer system, compared to its monolayer counterpart. Out-of-plane external electric fields effectively weaken interlayer coupling by enlarging the energy difference of Gamma/X-Y top valence bands to 170 meV.
Quantum transport simulations on a
bilayer Au/V2S2O/Au two-probe device demonstrate the presence of pronounced
spin current. Interlayer interactions reduce the transmission
spin polarization from nearly 100% (monolayer) to 60% (
bilayer) for energies above the
Fermi level. Notably, gate-voltage modulation exhibits significant asymmetry in controlling charge-to-
spin current conversion efficiency, originating from the out-of-plane
symmetry breaking induced by the electrode geometry. Specifically, a positive gate voltage markedly enhances the contribution of the bottom layer to the overall
spin polarization, while a negative gate voltage induces a marginal reduction of transmission
spin polarization, attributed to the inherently weak polarization contribution of the bottom layer. These findings provide essential insights for the design and optimization of multilayer altermagnetic spintronics.
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All authors Siqi Xu, Qilong Cui, Shaowen Xu, Xianbo Chenwei, Jiahao Zhang, Ruixue Li, Yuan Li, Gaofeng Xu, Fanhao Jia
Materials Science
Experimental investigation of magnetic properties of MnFeCo$_{4}$Si$_{2}$ discovered by GNoME
Shuhei Naganuma and Jiro Kitagawa
AI-driven inorganic materials research has garnered significant
attention due to its ability to reduce the time, labor, and cost associated with experiments. An AI model known as GNoME, recently developed by Google DeepMind, is particularly fascinating because it is integrated with the Materials Project open database. The experimental verification of compounds identified by GNoME is a crucial process for advancing AI-driven materials research. Here, we focus on the
magnetic compound MnFeCo$_{4}$Si$_{2}$ (Materials ID: mp-3203253), which possesses a layered-like structure. Consistent with the GNoME prediction, MnFeCo$_{4}$Si$_{2}$ crystallizes in a rhombohedral structure with a single-phase nature. We have characterized its
magnetic properties and determined that MnFeCo$_{4}$Si$_{2}$ is a soft ferromagnet with a Curie temperature of 1039 K.
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Materials Science
Hydrogenation-induced gigantic resistance decrease of palladium films deposited by high pressure magnetron sputtering
Yusuke Ikeda, Takuya Kawada and Yuki Shiomi
We demonstrate a pronounced decrease in the electrical resistance of highly disordered palladium (Pd) films deposited under a high working Ar pressure using a compact film coating system. The resulting resistance change ratio of up to $1/335$ is predominant among those reported previously. Film characterization suggests two primary mechanisms responsible for this significant resistance reduction: atomic force microscopy observation indicates improved electrical contacts among Pd grains, and X-ray diffraction measurement demonstrates hydrogenation-induced crystallization of Pd. These findings offer a simple scheme to enhance hydrogen sensor performance and can contribute to a more comprehensive understanding of the hydrogenation process in Pd.
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