Materials Science · Cross-listed from physics.comp-ph
qNEP: A highly efficient neuroevolution potential with dynamic charges for large-scale atomistic simulations
Zheyong Fan, Benrui Tang, Esmée Berger et al. (+13 more)
Although electrostatics can be incorporated into machine-learned interatomic potentials, existing approaches are computationally very demanding, limiting large-scale, long-time simulations of electrostatics-driven phenomena such as dielectric response, infrared activity, and field-matter coupling. Here, we extend the neuroevolution potential (NEP), a highly efficient machine-learned interatomic potential, to a charge-aware framework (qNEP) by introducing explicit, environment-dependent partial charges. Each ionic partial charge is represented by a neural network as a function of the local descriptor vector, analogous to the NEP site-energy model. This formulation enables the direct prediction of the Born effective charge tensor for each ion and, consequently, the polarization. As a result, dielectric properties, infrared spectra, and coupling to external electric fields can be evaluated within a unified framework. We derive consistent expressions for the forces and virials that explicitly account for the position dependence of the partial charges. The qNEP method has been implemented in the free-and-open-source GPUMD package, with support for both Ewald summation and particle-particle particle-mesh treatments of electrostatics. We demonstrate the accuracy and efficiency of the qNEP approach through representative applications to water, Li7La3Zr2O12, BaTiO3, and a magnesium-water interface. These results show that qNEP enables accurate atomistic simulations with explicit long-range electrostatics, scalable to million-atom systems on nanosecond time scales using consumer-grade GPUs.
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All authors Zheyong Fan, Benrui Tang, Esmée Berger, Ethan Berger, Erik Fransson, Ke Xu, Zihan Yan, Zhoulin Liu, Zichen Song, Haikuan Dong, Shunda Chen, Lei Li, Ziliang Wang, Yizhou Zhu, Julia Wiktor, Paul Erhart
Materials Science
Frequency- and time-resolved second order quantum coherence function of IDTBT single-molecule fluorescence
Quanwei Li, Yuping Shi, Lam Lam et al. (+2 more)
The frequency- and time-resolved second order
quantum coherence function (g(2)({\tau})) of single-molecule fluorescence has recently been proposed as a powerful new
quantum light spectroscopy that can reveal intrinsic
quantum coherence in excitation energy transfer in molecular systems ranging from simple dimers to photosynthetic complexes. Yet, no experiments have been reported to date. Here, we have developed a single-molecule fluorescence g(2)({\tau})
quantum light spectroscopy (SMFg2-QLS) that can simultaneously measure the fluorescence intensity, lifetime, spectra, and g(2)({\tau}) with frequency resolution, for a single molecule in a controlled environment at both room temperature and cryogenic temperature. As a proof of principle, we have studied single molecules of IDTBT (indacenodithiophene-co-benzothiadiazole), a semiconducting donor-acceptor conjugated copolymer with a chain-like structure that shows a high carrier mobility and annihilation-limited long-range
exciton transport. We have observed different g(2)({\tau}=0) values with different bands or bandwidths of the single molecule IDTBT fluorescence. The general features are consistent with theoretical predictions and suggest non-trivial excited state
quantum dynamics, possibly showing
quantum coherence, although further analysis and confirmation will require additional theoretical calculations that take into account the complexity and inhomogeneity of individual IDTBT single molecular chains. Our results demonstrate the feasibility and promise of frequency- and time-resolved SMFg2-QLS to provide new insights into molecular
quantum dynamics and to reveal signatures of intrinsic
quantum coherence in photosynthetic light harvesting that are independent of the nature of the light excitation.
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All authors Quanwei Li, Yuping Shi, Lam Lam, K. Birgitta Whaley, Graham Fleming
Materials Science
Toward Tunable Magnetic Dirac Semimetals: Mn Doping of Cd$_3$As$_2$
Anthony D. Rice, Ian Leahy, Herve Ness et al. (+8 more)
Magnetic impurities provide a route toward increasing functionality in electronic materials, often enabling new device concepts and architectures. In the case of topological semimetals, dilute
magnetic doping presents a particularly attractive approach for inducing a Dirac to Weyl phase change via time reversal
symmetry breaking. However, efforts to realize changes in the electronic structure have been limited by challenges in incorporating
magnetic impurities into
crystals with sufficiently high electron mobilities to detect them via transport or spectroscopic techniques. Here, we demonstrate incorporation of Mn into Cd$_3$As$_2$ Dirac semimetal thin films grown by molecular beam epitaxy (MBE). Using As-rich growth conditions and [001] oriented thin films, Mn compositions of >10% are achieved. Films contain uniform distributions of Mn with no evidence of secondary phases and exhibit electron mobilities greater than 10,000-30,000 cm$^2$/Vs up to 5% Mn. An
evolution in the magnetization behavior along with the emergence of a second
quantum oscillation frequency at low Mn concentrations provide preliminary evidence of Mn-induced changes in the electronic structure that are consistent with a Weyl phase. This work demonstrates the potential of magnetically doping topological semimetal thin films and a pathway for synthesizing them.
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All authors Anthony D. Rice, Ian Leahy, Herve Ness, Andrew G. Norman, Karen N. Heinselman, Chun-Sheng Jiang, David Graf, Alexey Suslov, Stephan Lany, Mark Van Schilfgaarde, Kirstin Alberi
Materials Science · Cross-listed from cs.LG
Towards Self-Optimizing Electron Microscope: Robust Tuning of Aberration Coefficients via Physics-Aware Multi-Objective Bayesian Optimization
Utkarsh Pratiush, Austin Houston, Richard Liu et al. (+2 more)
Realizing high-throughput aberration-corrected Scanning Transmission Electron Microscopy (STEM) exploration of atomic structures requires rapid tuning of multipole probe correctors while compensating for the inevitable drift of the optical column. While automated
alignment routines exist, conventional approaches rely on serial, gradient-free searches (e.g., Nelder-Mead) that are sample-inefficient and struggle to correct multiple interacting parameters simultaneously. Conversely, emerging deep learning methods offer speed but often lack the flexibility to adapt to varying sample conditions without extensive retraining. Here, we introduce a Multi-Objective
Bayesian Optimization (MOBO) framework for rapid, data-efficient aberration correction. Importantly, this framework does not prescribe a single notion of image quality; instead, it enables user-defined, physically motivated reward formulations (e.g.,
symmetry-induced objectives) and uses Pareto fronts to expose the resulting trade-offs between competing experimental priorities. By using Gaussian Process regression to model the aberration landscape probabilistically, our workflow actively selects the most informative lens settings to evaluate next, rather than performing an exhaustive blind search. We demonstrate that this active learning loop is more robust than traditional optimization
algorithms and effectively tunes focus, astigmatism, and higher-order aberrations. By balancing competing objectives, this approach enables "self-optimizing" microscopy by dynamically sustaining optimal performance during experiments.
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All authors Utkarsh Pratiush, Austin Houston, Richard Liu, Gerd Duscher, Sergei Kalinin
Materials Science · Cross-listed from cond-mat.soft
Accelerated design of proton exchange membranes for green hydrogen production with artificial intelligence
Huan Tran, Akhlak Mahmood, Harshal Chaudhari et al. (+5 more)
Water electrolysis is an eco-friendly method for hydrogen production that has reached significant levels of technological maturity. Among commercialized water-electrolysis technologies,
proton-exchange membrane electrolyzers offer high current density, fast dynamic response, and compact system design, among other advantages. On the other hand, managing their high capital cost and the “forever-chemistry” nature of Nafion, a perfluorinated
proton-exchange membrane widely used in such devices, remains a major challenge. Searches for fluorine-free replacements for Nafion, pursued largely through physical experimentation, have been active for decades with limited success. In this work, we develop and demonstrate an AI-based strategy for designing
proton-exchange membranes for electrolyzers. Two key components of this strategy are an implementation of the virtual forward-synthesis approach and a set of machine-learning predictive models for essential application-inspired membrane properties; the former generates a vast space of millions of synthesizable
polymers, which are then evaluated and screened by the latter. The strategy is validated against experimental data for known membranes and then applied to design over 1700 synthesizable candidates. This article concludes with a forward-looking
vision in which the strategy could be elevated into an interactive and iterative scheme that is based on large
language models to facilitate materials design in multiple ways.
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All authors Huan Tran, Akhlak Mahmood, Harshal Chaudhari, Kuldeep Mamtani, Chiho Kim, Rampi Ramprasad, Anand N. Krishnamoorthy, Abhirup Patra
Materials Science · Cross-listed from physics.app-ph
Twisting Kelvin Cells for Enhanced Vibration Control
Lukas Kleine-Wächter, Anastasiia O. Krushysnka, Romain Rumpler et al. (+1 more)
This work investigates the propagation of elastic waves in periodic Kelvin-
cell chains, focusing on
symmetry-breaking
geometric modifications induced by twisting the
cell's faces. By imposing such twists, the original
lattice topology is preserved, while mirror
symmetries are strategically broken through modifying a single
geometric parameter, allowing wave characteristics to be adjusted without additional resonators or mass augmentation. The complex-valued Bloch-Floquet analysis reveals that twisting activates two distinct wave attenuation mechanisms: Bragg-type band gaps associated with periodicity-induced scattering, and polarization-dependent band gaps arising from longitudinal-torsional mode coupling and avoided crossings. To obtain qualitative and quantitative insight into these mechanisms, a simplified analytical model with coupled translational and rotational degrees of freedom is considered. The finite-element wave transmission calculations are experimentally validated on SLA-printed three-
cell specimens, for which wave attenuation reaches up to 20 dB within the predicted band-gap frequencies. Note that high prediction accuracy requires accounting for viscoelastic material behavior, underscoring the importance of material behavior on the wave propagation characteristics. Overall, the findings show that modest
geometric modifications to a classical Kelvin-
cell lattice can enhance wave-filtering behavior, offering a tractable design strategy for vibration control in lightweight architected
lattices.
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All authors Lukas Kleine-Wächter, Anastasiia O. Krushysnka, Romain Rumpler, Gerhard Müller
Materials Science
MAD-SURF: a machine learning interatomic potential for molecular adsorption on coinage metal surfaces
Manuel González Lastre, Joakim S. Jestilä, Rubén Pérez et al. (+1 more)
Predicting how organic molecules adsorb, assemble, and interact on metal surfaces is central to surface chemistry and molecular electronics, particularly in the context of interpreting high-resolution scanning probe microscopy. Yet, the application of first-principles simulations to interfaces is hampered by the computational cost for evaluating the electronic structure for the large number of atoms typically involved. We hereby present MAD-SURF, a machine learning interatomic potential specifically tailored for molecular adsorption on coinage metal surfaces. Trained on a broad
dataset spanning diverse molecules, adsorption motifs, surfaces, molecular dynamics trajectories and non-covalent aggregates, MAD-SURF achieves accuracy comparable to the underlying DFT reference while enabling simulations orders of magnitude faster than density functional theory. The model reliably reproduces energies, forces and adsorption geometries across the three coinage metal substrates. We demonstrate its capabilities on experimentally characterized systems, including organic monolayers, polycyclic aggregates, flexible biomolecules and the long-range herringbone reconstruction of gold. By merging accuracy, speed, and generalizability, MAD-SURF offers a practical framework for accelerating atomistic simulations and advancing data-driven workflows in surface science.
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All authors Manuel González Lastre, Joakim S. Jestilä, Rubén Pérez, Adam S. Foster
Materials Science
A New Layered Kagome Strip Structure Na2Co3(AsO4)2(OH)2: Static and Dynamic Magnetic Properties
Duminda S. Liurukara, Emily D. Williams, Tianran Chen et al. (+6 more)
One-dimensional kagome strip chains share much of the same frustrated structural motif as two-dimensional kagome antiferromagnets, making them valuable for deepening our understanding of kagome
lattice magnetism. In this paper, we report the hydrothermal synthesis and detailed structural and property characterization of Na2Co3(AsO4)2(OH)2, a striped kagome system. The
crystal structure was characterized using single
crystal X-ray diffraction, which reveals that Na2Co3(AsO4)2(OH)2 crystallizes in the monoclinic
crystal system C2/m. The structure features a one-dimensional kagome strip
lattice built from Co2+ ions and undergoes an
antiferromagnetic transition at TN = 14 K. The
magnetic ground state at zero field was characterized using
neutron powder diffraction. Below the
magnetic transition, Na2Co3(AsO4)2(OH)2 orders into an
antiferromagnetic structure with a k-vector (0.5, 0.5, 0.5). In the proposed model, the Co1 moment is predominantly confined to the ac-plane while the Co2 moment is primarily aligned along the b-axis. Two flat bands were observed in the inelastic
neutron spectra below the
magnetic transition at 5 and 10 meV. Inelastic
neutron spectra were modeled with a Heisenberg
Hamiltonian including three nearest-neighbor exchange interactions (J1, J2, J3) and strong single-ion anisotropy to stabilize the observed
magnetic structure. Our study highlights the complexity of the Co2+-based kagome strip
magnetic lattice compound Na2Co3(AsO4)2(OH)2, which provides an excellent platform to broaden our understanding of the frustrated kagome
magnetic lattice space.
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All authors Duminda S. Liurukara, Emily D. Williams, Tianran Chen, Stuart Calder, V. Ovidiu Garlea, C. Charlotte Buchanan, Dustin A. Gilbert, Joseph W. Kolis, D. A. Tennant
Materials Science · Cross-listed from physics.data-an
McSAS3: improved Monte Carlo small-angle scattering analysis software for dilute and dense scatterers
Brian Richard Pauw and Ingo Breßler
McSAS3 is the refactored successor to the original McSAS Monte Carlo small-angle scattering analysis software. It is intended to be integrated in automated data processing pipelines, but can also be used to process individual (batches of) scattering data. McSAS3 comes with a graphical user interface (McSAS3GUI), complete with guides, examples and
videos. McSAS3GUI will help to generate and test the three configuration files that McSAS3 needs for data read-in, Monte Carlo optimization and histogramming. The user interface can also be used to process individual files or batches, and can be augmented with machine-specific use templates. The Monte Carlo (MC) approach is able to fit most practical scattering patterns extremely well, resulting in form-free model parameter distributions. Theoretically, these can be distributions on any model parameter, but in practice the MC-optimized parameter is usually a (volume-weighted) size distribution, in absolute volume fraction for absolute-scaled data.
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Materials Science
On-surface dehydrogenative lateral homo-coupling and aromatization of n-octane on Pt(111)
D. Arribas, E. Tosi, V. Villalobos-Vilda et al. (+14 more)
Aliphatic hydrocarbons, such as normal alkanes, constitute a naturally abundant source of carbon atoms. Of special interest is the formation of cyclic and aromatic products from aliphatic reactants. Combining scanning tunneling microscopy and ab initio calculations, we investigate the thermal induced aromatization of linear n octane molecules on the catalytic Pt(111) surface and the reactions of intermolecular homocoupling between them at temperatures above 600 K. The cycloaromatization of individual n octane molecules requires bending the linear adsorbates prior to their dehydrogenation and the formation of an intramolecular C-C bond, yielding adsorbed benzene rings. In addition, the Pt(111) surface catalyzes a homocoupling reaction by initiating the formation of a C-C bond between the dehydrogenated methyl ends of the chemisorbed n octane molecules and then propagating along the carbon backbone in a zipper like fashion. Our findings provide molecular level insight into the heterogeneous catalytic processes underlying the generation of aromatic products and stable on surface polycyclic species.
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All authors D. Arribas, E. Tosi, V. Villalobos-Vilda, B. Cirera, I. Palacio, A. Sáez-Coronado, P. Lacovig, A. Baraldi, L. Bignardi, S. Lizzit, C. Sanchez-Sanchez, A. Gutiérrez, J. A. Martín-Gago, M. Garnica, J. I. Martínez, P. L. de Andres, P. Merino
Materials Science · Cross-listed from stat.CO
The generalised balanced power diagram: flat sections, affine transformations and an improved rendering algorithm
Felix Ballani
The generalised balanced power diagram (GBPD) is regarded in the literature as a suitable
geometric model for describing polycrystalline microstructures with curved grain boundaries. This article compiles properties of GBPDs with regard to affine transformations and flat sections. Furthermore, it extends an
algorithm known for power diagrams for generating digital images, which is more efficient than the usual brute force approach, on GBPDs.
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Materials Science · Cross-listed from math.OC
Global Optimization of Atomic Clusters via Physically-Constrained Tensor Train Decomposition
Konstantin Sozykin, Nikita Rybin, Andrei Chertkov et al. (+5 more)
The global optimization of atomic clusters represents a fundamental challenge in computational chemistry and materials science due to the exponential growth of local minima with system size (i.e., the curse of dimensionality). We introduce a novel framework that overcomes this limitation by exploiting the low-rank structure of potential energy surfaces through Tensor Train (TT) decomposition. Our approach combines two complementary TT-based strategies: the algebraic TTOpt method, which utilizes maximum volume sampling, and the probabilistic PROTES method, which employs generative sampling. A key innovation is the development of physically-constrained encoding schemes that incorporate molecular constraints directly into the discretization process. We demonstrate the efficacy of our method by identifying global minima of Lennard-Jones clusters containing up to 45 atoms. Furthermore, we establish its practical applicability to real-world systems by optimizing 20-atom carbon clusters using a machine-learned Moment Tensor Potential, achieving geometries consistent with
quantum-accurate simulations. This work establishes TT-decomposition as a powerful tool for molecular structure prediction and provides a general framework adaptable to a wide range of high-dimensional optimization problems in computational material science.
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All authors Konstantin Sozykin, Nikita Rybin, Andrei Chertkov, Anh-Huy Phan, Ivan Oseledets, Alexander Shapeev, Ivan Novikov, Gleb Ryzhakov
Materials Science · Cross-listed from cond-mat.mes-hall
Electrostatic Screening Modulation of Graphene's Electronic Structure and the Helical Wavefunction Dominated Topological Properties
Yaorui Tan, Xiang Chen, Yunhu Zhu et al. (+4 more)
This study examines electrostatic screening effects in
graphene using tight binding calculations based on the Binding energy and Bond Charge model and a modified version of it. The results indicate that the modified BBC potential decays in an exponential manner with distance, which suppresses electron electron interactions. The hopping integrals exhibit a pronounced decrease over distance and shift with parameter variation. A band gap opens once the parameter exceeds a certain threshold. The density of states shows a prominent peak near the
Fermi level, whereas the low-energy region remains largely unchanged. The low energy helical wave functions in
graphene display topological characteristics, including pseudospin momentum locking and a {\pi} Berry phase, resulting in distinctive transport properties. By avoiding the Coulomb singularity, the model offers valuable insights for the engineering of screening in two-dimensional systems and the design of topological devices.
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All authors Yaorui Tan, Xiang Chen, Yunhu Zhu, Xiaowu Yang, Zhongkai Huang, Chuang Yao, Maolin Bo
Materials Science
First-principles study of bulk stacking, $J_{\rm eff}$ picture, magnetic Hamiltonian, $g$ factors, and structural distortions of $\alpha$-RuCl$_3$
Seung-Ju Hong, Tae Yun Kim and Cheol-Hwan Park
$\alpha$-RuCl$_3$ is a candidate Kitaev material that exhibits zigzag
antiferromagnetic ordering below 7 K. One contentious issue regarding this material is its bulk structure in the low-temperature phase. Recently, it has become generally accepted from experiments that the low- and high-temperature structures belong to the $R\bar{3}$ and $C2/m$ space groups, respectively. However, there was no theoretical study supporting the $R\bar{3}$-type structure as the low-temperature structure. In this study, we use constrained density functional theory to show that the $R\bar{3}$ structure is lower in energy than the $C2/m$ structure, in agreement with experimental observations. Then, we show that the conduction band minimum states are almost of the $J_\textrm{eff}=1/2$ and $m_\textrm{eff}=-1/2$ character, if we set the angular momentum quantization axis to be parallel to the Néel vector; this is the first analysis of the $J_\textrm{eff}$ picture for $\alpha$-RuCl$_3$ from this perspective. In addition, we compute the anisotropic
magnetic exchange parameters and $g$ factors of monolayer $\alpha$-RuCl$_3$, thereby providing a comprehensive understanding of its magnetism. Our results demonstrate that both second-nearest-neighbor exchange interactions and
magnetic moments not captured by the conventional atomic orbital projection method are necessary for accurate description of the magnetism in $\alpha$-RuCl$_3$. Moreover, the calculated $g$ factors are in fairly good agreement with experimental measurements, especially the small anisotropy between their in-plane and out-of-plane components. Finally, we examine the effects of structural distortions from a perfect RuCl$_6$ octahedron, already present in bulk $\alpha$-RuCl$_3$ without any external perturbation, on the
magnetic properties. (The abstract is cut here due to the word limit; see the pdf file for the full abstract.)
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Materials Science · Cross-listed from physics.flu-dyn
Spontaneous epicuticular charging affects droplet dynamics on living leaves
Mihir Durve, Serena Armiento, Benham Kamare et al. (+3 more)
How water droplets move and slide on leaves influences plant ecophysiological and abiotic interactions, as well as the design of advanced bio-inspired wetting materials. Despite cross-disciplinary relevance, current descriptions of the in situ dynamics of droplets on living leaves focus almost exclusively on surface structure and chemistry, treating the leaf as a static, electrically neutral substrate. Here, three decades after the mechanistic discovery of the Lotus effect, we show that a yet 'hidden' force due to instantaneous electrical phenomena affect the dynamic droplet motion on living leaves. Using high-speed motion tracking and precision charge measurements, we show that droplets sliding on the pristine epicuticular wax layer on superhydrophobic Colocasia esculenta leaves strongly charge affecting its dynamics, previously observed only on synthetic (highly electronegative fluorinated) surfaces. Droplets accumulate charges of Qp,D1 = -0.02 to -0.15 nC per 30 uL droplet on pristine leaves. However, we specifically demonstrate the crucial role of the epicuticular wax layer plasticity: by a structural modification that decreases its roughness amplitude, the same leaves gain an impressive 30-40 fold enhancement in charge transfer (reaching Qt,D1 = -2.8 to -5.2 nC) slowing the droplet by half due to an estimated electrostatic force of 11 uN dominating the resistive forces. The charge accumulation is surface-history-dependent and charge quantities per droplet are surprisingly similar or even exceeding those recently reported from artificial surfaces. Our findings prove that electrostatic charging is a fundamental component of droplet-leaf interactions, opening new research directions from charge-affected leaf ecology to sustainable materials for droplet-based energy harvesting by tuning surface treatments and, moreover,...
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All authors Mihir Durve, Serena Armiento, Benham Kamare, Sauro Succi, Barbara Mazzolai, Fabian Meder
Materials Science
NuMagSANS: a GPU-accelerated open-source software package for the generic computation of nuclear and magnetic small-angle neutron scattering observables of complex systems
Michael P. Adams and Andreas Michels
We present NuMagSANS, a GPU-accelerated software package for calculating
nuclear and
magnetic small-angle
neutron scattering (SANS) cross sections and correlation functions. The program allows users to import position-dependent
nuclear density and magnetization data, providing a large flexibility for analyzing the scattering signatures of complex systems, particularly
magnetic materials. Full rotational control of the sample is supported, allowing a comprehensive exploration of angular-dependent scattering features. NuMagSANS includes a versatile library of approximately 100 response functions that encompass two-dimensional SANS cross sections, correlation functions, and azimuthally averaged quantities. These capabilities allow users to gain detailed insight into the structural and
magnetic characteristics of their samples. GPU acceleration ensures rapid computations, even for large data sets, making NuMagSANS a powerful and efficient tool for advanced SANS analysis.
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Materials Science
Unusual Dual Flat Bands and two-dimensional Dirac-node Arc State in Kagome Metal Ni3In2S2
Bo Liang, Yichen Liu, Jie Pang et al. (+36 more)
Kagome materials are at the frontier of condensed matter physics. An ideal kagome
lattice features only one geometrically frustrated flat band spanning the entire momentum space and a single Dirac cone at the Brillouin-zone corners. However, for the first time, here we observe unusual flat-band and Dirac physics in the newly discovered "322" kagome material Ni3In2S2 by combining high-resolution synchrotron- and
laser-based angle-resolved photoemission spectroscopy with a micro-focused beam, scanning tunneling microscopy, and first-principles calculations. We resolve two distinct electronic flat-band states located in close proximity to the
Fermi level: a robust Topological Surface Flat Band at ~40 meV below the
Fermi level on the Sulfur-terminated surface, originating from weak topological
insulator states, and a kagome
lattice-derived flat band at ~100 meV binding energy with an ultranarrow bandwidth (~5 meV). Instead of the single Dirac cone, the Indium-terminated surface hosts a rare two-dimensional Dirac-node arc state, where the gapless Dirac nodes extend along an open one-dimensional line crossing the Brillouin-zone boundary, exhibiting sharp linear dispersion, exceptionally high
Fermi velocity, and pronounced circular dichroism. These findings establish Ni3In2S2 as a unique topological kagome metal in which multiple flat-band states of different physical origin coexist with an unusual Dirac-node arc, opening an avenue for discovering flat-band–driven and
topology-enabled
quantum phenomena.
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All authors Bo Liang, Yichen Liu, Jie Pang, Hanbin Deng, Taimin Miao, Wenpei Zhu, Neng Cai, Tiantian Zhang, Jiayu Liu, Zhicheng Jiang, Zhanfeng Liu, Hongen Zhu, Yuliang Li, Tongrui Li, Mingkai Xu, Hao Chen, Xiaolin Ren, Chaohui Yin, Yingjie Shu, Yiwen Chen, Yu-Tian Zhang, Zhengtai Liu, Dawei Shen, Mao Ye, Fengfeng Zhang, Shenjin Zhang, Shengtao Cui, Zhe Sun, Koji Miyamoto, Taichi Okuda, Kenya Shimada, Lihong Yang, Jia-Xin Yin, Lin Zhao, Zuyan Xu, Haijun Zhang, Youguo Shi, X. J. Zhou, Guodong Liu
Materials Science
Effect of ballistic re-solution on the nucleation kinetics of precipitates in diluted binary alloys under irradiation. Part 2: Cr-rich alpha' precipitates in Fe-Cr alloys
M.S. Veshchunov
On the base of a critical analysis of existing models for nucleation of new phase precipitates in metastable binary
alloys, a new kinetic model of homogeneous nucleation and growth of alpha'-phase precipitates in Fe-Cr
alloys was developed within the framework of the Reiss kinetic theory of binary nucleation. The model was further modified to account for the influence of ballistic re-solution on the kinetics of nucleation and growth of alpha' precipitates, following the general approach proposed in Part 1. The model was used for qualitative interpretation of the results of recent tests, in which the stability of alpha' precipitates in Fe-15Cr
alloys under irradiation was studied.
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Materials Science
Effect of ballistic re-solution on the nucleation kinetics of precipitates in diluted binary alloys under irradiation. Part 1: Stoichiometric gamma' precipitates in Ni-Al alloys
M.S. Veshchunov
A modification of classical nucleation theory is carried out as applied to solid solutions under irradiation, taking into account the influence of ballistic re-solution on the nucleation kinetics of pure unary (single-component) and stoichiometric binary precipitates. The effects of excessive point defects formed under steady irradiation conditions and operating alongside the ballistic re-solution mechanism are incorporated into the new model for a consistent description of the nucleation of incoherent and coherent particles. The developed model was applied to interpret the results of Nelson, Hudson and Mazey (NHM) tests, in which the stability of gamma' phase (Ni3Al) precipitates in diluted Ni-Al
alloys under irradiation was studied.
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Materials Science · Cross-listed from cond-mat.mes-hall
Voltage-controlled topological spin textures in the monolayer limit
Yangliu Wu, Bo Peng, Zhaozhuo Zeng et al. (+10 more)
The physics of phase transitions in low-dimensional systems has long been a subject of significant research interest. Long-range
magnetic order in the strict two-dimensional limit, whose discovery circumvented the Mermin-Wagner
theorem, has rapidly emerged as a research focus. However, the demonstration of a non-trivial topological
spin textures in two-dimensional limit has remained elusive. Here, we demonstrate the out-of-plane electric field breaks inversion
symmetry while simultaneously modulating the electronic band structure, enabling electrically tunable
spin-orbit interaction for creation and manipulation of topological
spin textures in monolayer CrI3. The realization of ideal two-dimensional topological
spin textures may offer not only an experimental testbed for probing the Berezinskii-Kosterlitz-Thouless mechanism, but also potential insights into unresolved
quantum phenomena including superconductivity and superfluidity. Moreover, voltage-controlled
spin-orbit interaction offers a novel pathway to engineer two-dimensional
spin textures with tailored
symmetries and
topologies, while opening avenues for skyrmion-based next-generation information technologies.
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All authors Yangliu Wu, Bo Peng, Zhaozhuo Zeng, Chendi Yang, Haipeng Lu, Peiheng Zhou, Jianliang Xie, Difei Liang, Linbo Zhang, Peng Yan, Haizhong Guo, Renchao Che, Longjiang Deng
Materials Science · Cross-listed from cond-mat.supr-con
Direct observation of vortex liquid droplets in the iron pnictide superconductor CaKAs$_4$Fe$_4$ at $0.5T$_c$
Oscar Bou Marqués, Jose A. Moreno, Pablo García Talavera et al. (+7 more)
Type-II
superconductors under
magnetic fields are in a
quantum coherent non-dissipative state as long as
vortices remain pinned. Dissipation appears when
vortices depin, eventually driven by thermal fluctuations. This can be associated to a melting transition between a
vortex solid and a
vortex liquid. This transition is almost always observed very close to T$_c$ when probed by macroscopic experiments. However, it remains unclear how the
vortex solid responds to thermal fluctuations at the scale of individual
vortices far from the melting transition. Here we use scanning tunneling microscopy (STM) to visualize
vortices in CaKAs$_4$Fe$_4$ (T$_c \approx$ 35 K). We find
vortex liquid droplets-localized regions in space where
vortices strongly fluctuate due to thermal exctiation-at temperatures as low as 0.5\,T$_c$. Our results show that the onset of dissipation at the local scale occurs at temperatures considerably below T$_c$ in type-II
superconductors.
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All authors Oscar Bou Marqués, Jose A. Moreno, Pablo García Talavera, Mingyu Xu, Juan Schmidt, Sergey L. Bud'ko, Paul C. Canfield, Isabel Guillamón, Edwin Herrera, Hermann Suderow
Materials Science
Understanding Interface Stability in RENi2/Ni through First-Principles Calculations
Yuta Yahagi and Yumi Katasho
Crystallographic orientation analysis revealed that DyNi2 grew epitaxially on Ni, whereas NdNi2 does not. To elucidate the microscopic origin of this contrasting behavior, we constructed atomistic models of Ni/Rare-earth (RE)Ni2 interfaces with well-defined crystallographic
alignment and performed first-principles calculations based on density functional theory (DFT). The computed interfacial energies exhibit a clear correlation with
lattice mismatch: larger mismatch leads to higher interfacial energy and reduced interface stability. Consequently, Ni/DyNi2 exhibits a significantly lower interfacial energy than Ni/NdNi2, consistent with experimental observations. A comparison between interfacial and strain energies for Ni/RENi2 (RE = Sc, Y, Nd, Gd, Dy, and Lu) reveals that the elemental dependence of interfacial stability is dominated by elastic strain rather than chemical bonding. Based on this insight, we developed a simple regression model using the absolute
lattice mismatch as a descriptor, enabling qualitative predictions of stability for Ni/RENi2 interfaces with RE other than those examined in DFT.
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Materials Science
Accurate semiempirical analytical formulas for spontaneous polarization by crystallographic parameters of SrTiO3-BaTiO3 system by ab initio calculations
Yukio Watanabe
Spontaneous polarizations (PSs) of BaTiO3 and SrTiO3 under various conditions are calculated ab initio using different exchange-correlation functionals. The extensive theoretical sets of PS vs. ion positions are found to lie on a single curve, despite the chemical differences and the wide variations of PS and
lattice parameters. This uncovers accurate simple analytical formulas of PS of SrTiO3-BaTiO3 system expressed by ion positions; a single formula predicts both macroscopic and atomic-scale PS of SrTiO3, BaTiO3 and SrTiO3-BaTiO
alloys. The accuracy of the formula is demonstrated by the application to experiments, BaTiO3-SrTiO3 (-CaTiO3)
alloys, Sr4Ti4O12 with PS // a-axis, a parallel domain, and a headon domain. In addition, the present results verify empirically that oxygen displacement is the primary identifier and the origin of PS of SrTiO3 and BaTiO3 and indicate that BaTiO3 and SrTiO3 may transforms into new state by an extremely large strain, e.g., -3%. Furthermore, the earlier prediction of headon domain without aid of defects was confirmed. The present procedures for finding formulas can be applied to other materials.
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Materials Science · Cross-listed from cond-mat.soft
Programming Nonlinear Interfacial Mechanics of Synthetic Cells: Lipid Geometry and DNA Nanostructures
Kazutoshi Masuda and Miho Yanagisawa
Soft interfaces formed by lipid membranes are fundamental to living
cells, synthetic
cells, and membrane-based soft materials. However, a quantitative framework linking molecular organization with nonlinear interfacial mechanics remains elusive. Here, we establish an analytical framework that captures the nonlinear elastic response of lipid-membrane-coated synthetic
cells under micropipette aspiration. Incorporating both area stretching and
curvature bending enables the model to quantitatively reproduce the complete pressure-displacement response within the small-deformation regime. This approach reduces interfacial mechanics to two parameters: the in-plane area-stretching modulus and an out-of-plane bending-related term. Using this unified framework, we experimentally demonstrate that nonlinear interfacial mechanics can be programmed by altering the molecular geometry and effective dimensionality of adsorbed elements. The lipid molecular shape and
curvature-dependent packing regulate in-plane stiffness, while DNA nanostructures, the other adsorbed element, introduce an orthogonal control axis via dimensionality: isolated motifs primarily enhance area stretching, whereas three-dimensional network architectures markedly reinforce bending resistance. Together, these results establish a general molecular design principle for programming interfacial mechanics and provide a quantitative foundation for engineering mechanically tunable synthetic
cells and soft interfaces.
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