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Physics Condensed Matter Materials Science

cond-mat.mtrl-sci Watch Materials Science

Friday 19 June

Materials Science

The FAST Framework: Developing a Data-Efficient Machine Learning Potential to Decode Superionic Transition-Induced Thermophysical and Kinetic Anomalies in UO2 under Extreme Conditions

Fengnian Zhuang, Gaosheng Yan, Hong Chen et al. (+4 more)

Uranium dioxide ($UO_2$) serves as the predominant nuclear fuel globally. Despite its widespread application, evaluating its mechanical, thermophysical, and species transport behaviors under extreme accident scenarios remains a formidable challenge for conventional experimental and computational methods. To address this, we develop a versatile machine learning interatomic potential (MLIP) for $UO_2$ by proposing an efficient training strategy, termed the "FAST" (Fine-tuning via Active-learning and Superionic-Targeting) framework. Our "FAST" framework integrates superionic transition-targeted sampling with active learning-enhanced exploration to efficiently construct a highly compact dataset comprising only 500 configurations for fine-tuning a foundation model. By rigorously accounting for the strong correlation of uranium 5f electrons and antiferromagnetic (AFM) ground state during DFT labeling, we train a robust DFT-level neuroevolution potential (NEP) for $UO_2$. We demonstrate that this NEP exhibits superior predictive capability for various physical properties, encompassing mechanical, defect, thermophysical, and ionic diffusion over an extensive temperature range. Moreover, this NEP accurately captures the anomalous thermophysical and kinetic behaviors triggered by superionic transition. Specifically, it reproduces both the $\lambda$-peak in linear thermal expansion coefficient (LTEC) and "non-Arrhenius" anionic diffusion. Crucially, NEP-based simulations elucidate the microscopic origins underlying these anomalies: the pre-melting of oxygen sublattice and resultant kinetic decoupling between U and O ions.
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All authors Fengnian Zhuang, Gaosheng Yan, Hong Chen, Yi Zhang, Wenshan Yu, Minglong Xu, Shengping Shen

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

Solid-state transcapacitor, a new gain element for logic, memory and interconnects

Amrita Mathuriya, Roza Kotlyar, Neal Reynolds et al. (+9 more)

Today's transistors dictate the voltage and charge scales for both logic and memory. While AI systems are recognized to be limited by memory energy, the dominant share of the energy is expended in the intrachip interconnects whose voltage and charge scales are set by transistors. The energy scaling challenges of transistors can be attributed to simultaneously meeting high current density, high current/impedance modulation, and the inability to lower voltages. Hence, a new logic element that lowers the voltage and charge needs is a priority, not only for lowering logic power but also memory access power. Here, we propose a novel 3-terminal logic element for low energy computing, a solid-state transcapacitor (TCAP). A TCAP is a solid state displacement current modulator realized by a gate which controls the charge-voltage relationship of the channel. Unlike transistors, TCAPs eliminate the dissipative transport current, are not bound by the Boltzmann current modulation limit, and operate with displacement currents limited only by the polarization response and contact resistance. Hence, TCAP circuits may simultaneously overcome the voltage, current density, and current modulation limits of CMOS. We describe a solid state TCAP using a piezoelectric transcapacitor in which a gate-controlled stressor modulates the capacitance of a polar channel via electromechanical coupling. This device achieves inversion and gain, essential for logic, and is functionally equivalent to a 1T-1C memory cell, enabling dense memory. Using voltage scaling, capacitive energy recovery, and high polarization densities of polar materials, the logic based on TCAP offers a pathway to 100 fold lower energy consumption with a delay comparable to ultimately scaled CMOS devices. This approach provides a new potential pathway for low-energy computing beyond the limits of transistors using electro-mechanics and multiferroics.
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All authors Amrita Mathuriya, Roza Kotlyar, Neal Reynolds, Rafael Rios, Alan Kalitsov, Peter B. Meisenheimer, James Clarkson, Noriyuki Sato, Tanay Gosavi, Ramamoorthy Ramesh, Dmitri E. Nikonov, Sasikanth Manipatruni

Materials Science

Interaction between point defects and vertical inversion domain walls in wurtzite AlN

Loris Naudin, Charles Paillard, Laurent Bellaiche et al. (+2 more)

Alloyed aluminium nitride compounds constitute a promising class of ferroelectric materials due to their high remanent electric polarizations, large band gaps and structural compatibility with a growth on Si substrates. Such materials nonetheless possess large coercive fields and polarization-switching mechanisms are still debated. We performed first-principles calculations to investigate the stability of isolated point defects in the vicinity of a vertical inversion domain wall (DW). We found that all studied defects are energetically more stable at or near the DW. Depending on their nature, they can have the opposite effect on the displacement of the DW, which occurs during polarization switching. Finally, we discuss how likely the different defects may be responsible for leaking currents and degraded ferroelectric properties.
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All authors Loris Naudin, Charles Paillard, Laurent Bellaiche, Lionel Calmels, Rémi Arras

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

A Topology-Preserving Python Framework for Reliable Initialization of Star and Cyclic Polymer Architectures in Molecular Dynamics (LAMMPS) Simulations

Oluwatumininu Emmanuel Ayo-Ojo, Akpevweoghene Ogheneowho Ugono and Nkosinathi Dlamini

Accurate initialization of polymer architectures remains a critical yet underappreciated determinant of reliability in molecular dynamics simulations of soft matter systems. Errors in coordinate generation and connectivity assignment frequently introduce artificial stresses, topological inconsistencies, and numerical instabilities that propagate throughout simulation trajectories. Here, we present a topology-preserving Python framework for generating star and cyclic polymer architectures with deterministic bond connectivity, exact ring closure, excluded volume enforcement, and spatial-hashing-based overlap detection. The algorithm produces LAMMPS-compatible data files under atom style full without reliance on third-party libraries. We demonstrate that the generated structures exhibit mechanical stability at initialization, suppressed artificial energy spikes, and consistent thermodynamic behavior during equilibration. Benchmark comparisons against naive random placement schemes reveal significant reductions in overlap-induced instabilities and improved reproducibility of structural and dynamical observables. The presented framework establishes initialization as a controlled physical boundary condition rather than a stochastic preprocessing step, thereby enhancing the reliability and reproducibility of polymer molecular dynamics simulations.
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Materials Science

Fine-Tuning a Universal Machine-Learned Interatomic Potential for Oxygen Plasma Interactions with WS$_2$

Jaehong Kwon, Andrew S. Rosen and David B. Graves

Molecular dynamics simulation of plasma-surface interactions requires an interatomic potential that is simultaneously accurate, computationally efficient, and able to describe many elements and bonding types in reactive systems. In principle, a foundation model for machine-learned interatomic potential (MLIP) can meet these demands. We explore the use of the Universal Models for Atoms (UMA) model, developed by Meta FAIR, for the interactions of oxygen plasma species on a multilayer of WS$_2$, a promising 2D material. Starting from the pretrained uma-s-1p1 model under the Open Catalyst 2020 (OC20) task, we apply an iterative fine-tuning loop. Even in the absence of fine-tuning, the pretrained model reproduces the production-scale observables of interest, namely, chemisorbed S and O coverage under 15 eV O$^+$ and O$_2^+$ bombardment. These results were obtained without spin polarization and Hubbard $U$ correction. Nonetheless, fine-tuning with spin polarization and a Hubbard $U$ correction reduces the energy and force mean absolute error (MAE) to $4.5\times10^{-3}$ eV/atom and $0.076$ eV/angstrom, respectively.
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Materials Science · Cross-listed from cond-mat.soft

Perspective: Highly stable vapor-deposited glasses

M.D. Ediger

This article describes recent progress in understanding highly stable glasses prepared by physical vapor deposition and provides perspective on further research directions for the field. For a given molecule, vapor-deposited glasses can have higher density and lower enthalpy than any glass that can be prepared by the more traditional route of cooling a liquid, and such glasses also exhibit greatly enhanced kinetic stability. Because vapor-deposited glasses can approach the bottom of the amorphous part of the potential energy landscape, they provide insights into the properties expected for the ideal glass. Connections between vapor-deposited glasses, liquid-cooled glasses, and deeply supercooled liquids are explored. The generality of stable glass formation for organic molecules is discussed along with the prospects for stable glasses of other types of materials.
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Materials Science · Cross-listed from physics.optics

Mirror-Symmetry-Enforced Photonic Altermagnet

Chong Cao, Xiong-Xiong Xue, Yee Sin Ang et al. (+1 more)

Altermagnets host momentum-dependent spin splitting without net magnetization, a symmetry-enforced band phenomenon whose photonic analogues have so far been realized only in square lattices governed by fourfold rotation. Here we introduce a photonic altermagnet on a hexagonal lattice whose helicity splitting is governed by mirror rather than rotational symmetry. Elliptical chiral elements of alternating handedness, placed at the vertices of a regular hexagon, leave the two opposite-chirality sublattices connected only by chirality reversal combined with a mirror reflection. Full-wave simulations reveal mirror-related splitting of the two opposite-helicity branches in the band structure and isofrequency contours, with the channels exchanged when the ellipse orientation is reversed. Using a finite photonic crystal slab, we show that such splitting separates a linearly polarized beam into handedness-resolved channels, thus enabling beam splitting and direction-selective helicity filtering with target-helicity output fractions above 0.85 and output paths continuously tunable through the ellipse rotation angle. These results extend photonic altermagnetism to a previously unexplored lattice-symmetry class and establish mirror-symmetric chiral textures as building blocks for altermagnetism-inspired on-chip chiral photonics.
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All authors Chong Cao, Xiong-Xiong Xue, Yee Sin Ang, Haiyu Meng

Materials Science

Peripheral Nitrogen Topology as a Defect-Chemical Switch for Electronic and Magnetic States in Graphene: A First-Principles Study of Pyridinic, Pyridazinic, Pyrrolic, and Pyrazolic Configurations

Md. Moktadir Billah Tahmid, Indranil Rudra, Jahid Emon et al. (+1 more)

Defect and heteroatom engineering offer powerful routes for tuning the electronic and magnetic properties of graphene, yet the role of specific peripheral nitrogen topologies around graphene voids remains insufficiently understood. Here, spin-polarized first-principles calculations were performed to investigate how four heterocyclic – like peripheral nitrogen configurations – pyridinic, pyridazinic, pyrrolic, and pyrazolic modify the structural stability, charge redistribution, electronic structure, and magnetic response of graphene containing a central void. Among the four peripheral N configurations, the pyridinic N provides the most favorable structural-energetic balance among the investigated motifs. Bond-length analysis reveals that nitrogen topology strongly controls local lattice reconstruction. Charge-density, charge-density-difference, and Bader analyses demonstrate that the peripheral N atoms act as electron-accumulating centers and reshape the local electronic environment around the vacancy rim. Spin-resolved band structures show that pyridinic, pyridazinic, and pyrrolic configurations retain metallic or near-metallic defect-state character, whereas pyrazolic graphene opens a narrow band gap. Magnetic analysis further reveals that pyrazolic graphene is spin-compensated, with zero net magnetization, unlike the other systems, which possess finite spin-polarized moments. Spin-density and SPDOS analyses indicate that the magnetism originates from N-modulated vacancy-edge states involving both N 2p and neighboring C 2p orbitals. These findings establish peripheral nitrogen topology not merely as a structural defect descriptor, but as a deterministic defect-chemical switch, offering a metal-free route to pattern active spintronic and semiconducting domains directly into the graphene lattice through controlled vacancy-edge nitrogen coordination.
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All authors Md. Moktadir Billah Tahmid, Indranil Rudra, Jahid Emon, Mohammad Jane Alam Khan

Materials Science

Machine learning metallic glass critical cooling rates through elemental and molecular simulation based featurization

Lane E. Schultz, Benjamin Afflerbach, Paul M. Voyles et al. (+1 more)

We have developed a machine learning model for critical cooling rates for metallic glasses based on computational properties. We compare results for features derived from easy-to-compute functions of elemental properties to more complex physically motivated properties using ab initio, machine-learning potentials, and empirical potential molecular dynamics methods. The established approach enables property acquisition across a diverse range of alloys. Analysis of various features for 34 alloys from 20 chemical systems shows that the best model for critical cooling rates was learned from one elemental property-based feature and three simulated features. The elemental property-based feature is an ideal entropy value based on alloy stoichiometry. The simulated features were acquired from estimates of energies above the convex hull, changes in heat capacity, and the fraction of icosahedra-like Voronoi polyhedra. Models were assessed through a demanding cross validation test based on repeatedly leaving out full chemical systems as test sets and had an $R^2$ of 0.78 and a mean average error of 0.76 in units of $[log_{10}(K/s)]$. We demonstrate with Shapley additive explanation analysis that the most impactful features have physically reasonable influence on model predictions. The established methodology can be applied to other high-throughput studies of material properties of diverse compositions.
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All authors Lane E. Schultz, Benjamin Afflerbach, Paul M. Voyles, Dane Morgan

Materials Science

Bulk Photovoltaic Effect in Two-Dimensional Perovskite Oxides

Chunmei Zhang, Jian Zhou and Liang Si

Perovskite oxides ABO$_3$ host a rich interplay of charge, spin, lattice, and orbital degrees of freedom, giving rise to diverse quantum phenomena. In low-dimensional ABO$_3$, reduced symmetry can induce exotic quantum effects such as the two-dimensional electron gas and unconventional superconductivity. Using first-principles density functional theory, tight-binding modeling, and symmetry analysis, we show that ultrathin two-dimensional (2D) ABO$_3$ films – exemplified by SrTiO$_3$ – naturally break inversion symmetry, producing a spontaneous out-of-plane bulk photovoltaic (BPV) effect. This differs from previous studies on in-plane BPV current signals and is more applicable and experimentally detectable. Such an effect is highly tunable via thickness, strain, surface termination, crystallographic orientation, and Moiré twisting. These findings are broadly applicable to a wide range of 2D perovskite and other layer-resolved oxides.
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Materials Science · Cross-listed from math.NA

An FFT-based solver with general boundary conditions for stationary diffusion problems based on Chebyshev collocation

Juan M. Quecedo and Javier Segurado

An efficient and robust FFT-based solver is proposed for diffusion-type problems with general Neumann and Dirichlet boundary conditions, based on a Chebyshev collocation framework. The method combines Chebyshev polynomial approximations with FFT-based operators to provide a matrix-free implementation of the discrete differential operator at the Chebyshev-Gauss-Lobatto points. The linear system of equations resulting from the Chebyshev discretization is solved using LGMRES. To overcome convergence problems on fine grids, a hierarchical refinement strategy based on modal prolongation is proposed, enabling the solution of very large 3D problems. The methodology is applicable to homogeneous and heterogeneous domains, as well as to linear and nonlinear constitutive equations. The accuracy of the proposed method is analyzed by solving the Poisson equation in homogeneous 1D and 3D domains with general boundary conditions, using manufactured analytical solutions as references. Convergence to the analytical solution is achieved in a few iterations, with smaller errors than those obtained using DCT/DST approaches. Discretizations of up to $256^3$ are achieved thanks to the hierarchical refinement strategy. In the case of heterogeneous domains, the accuracy and efficiency obtained are similar to those of a standard periodic FFT approach. It is found that the computational complexity of the method preserves the FFT scaling, of order $n\log n$, in all the cases studied.
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Materials Science · Cross-listed from cs.LG

Atomistic Language Models Understand and Generate Materials

Sathya Edamadaka, Krithik Ramesh, Ju Li et al. (+1 more)

Atomistic structure and natural language have long been modeled separately, with language models either calling atomistic models as tools or being fine-tuned on lossy textual encodings that discard atomistic information. We introduce Atomistic Language Models (ALMs) to pursue native multimodality, in which a single language backbone understands atomistic structures, generates materials from natural language, and optimizes crystal structures as instructed by text. By unifying a pretrained atomistic encoder, large language model, and denoising diffusion model through purely continuous projectors and staged training, ALMs achieve state-of-the-art results on crystal structure prediction and de novo generation. ALMs are enabled by a continuous bridge that maps language model embeddings directly into the steering space of atomistic diffusion, and are assisted by Text-to-Crystal Feynman-Kac (T2C-FK), a particle-based sampler that scores partial denoising trajectories to enforce stoichiometric targets at inference time. To evaluate the ability of ALMs to optimize and generate materials from natural-language prompts and 3D atom-coordinate inputs, we introduce ALM Bench, the first benchmark for text-conditioned crystal generation and optimization. Code, training data, and model weights will be released soon.
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All authors Sathya Edamadaka, Krithik Ramesh, Ju Li, Rafael Gómez-Bombarelli

Materials Science

Floquet-induced anisotropic magnetoresistance and anomalous Hall effect in 2D $d$-wave altermagnets with Rashba spin-orbit coupling

Mohsen Yarmohammadi, Pieter M. Gunnink, Jairo Sinova et al. (+1 more)

Altermagnets (AMs) combine momentum-dependent spin splitting with zero net magnetization, making them promising for spintronics. Periodic driving enables dynamic symmetry engineering beyond static, material-specific control. We show that Floquet engineering in 2D $d$-wave AMs with out-of-plane Néel order and Rashba spin-orbit coupling unlocks equilibrium-forbidden transport responses. Monochromatic driving produces purely out-of-plane magnetization, yielding longitudinal anisotropic magnetoresistance (AMR) and an anomalous Hall effect, whereas bichromatic driving generates both in-plane and out-of-plane magnetizations and additionally activates transverse AMR via the second harmonic of the secondary beam. Comparable static magnetic fields would require hundreds of tesla, avoided in Floquet driving. These effects persist across linear, circular, and mixed light polarizations and are tunable via light parameters. Our results establish multi-color Floquet engineering for controlling magnetization and symmetry-protected transport in AMs.
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All authors Mohsen Yarmohammadi, Pieter M. Gunnink, Jairo Sinova, James K. Freericks

Materials Science

Strain induced magnetic phase transitions in Fe3GeTe2 monolayer

Anjali Jyothi Bhasu, Satish Kumar, Mátyás Török et al. (+11 more)

We investigate the magnetic properties of a monolayer of Fe3GeTe2 as a function of the lattice constant by combining first-principles calculations with atomistic spin dynamics simulations. The calculated magnetic exchange interactions reveal a competition between ferromagnetic and antiferromagnetic couplings, with the latter being significantly strengthened under compressive strain. Stochastic Landau-Lifshitz-Gilbert simulations reveal a substantial decrease in the Curie temperature with decreasing lattice constant, and predict a transition of the magnetic ground state from a ferromagnetic configuration to a conical spin-spiral state. We introduce a simple spin-model which explains the stabilization of the spiral phase due to competing exchange interactions. We found multiple magnetic phase transitions involving ferromagnetic, conical spin-spiral, and planar Neel states, depending on both the lattice constant and the temperature. The absence of Dzyaloshinskii-Moriya interactions is found to significantly reduce the Neel temperature, while leaving the Curie temperature largely unaffected. Our findings reveal the importance of lattice distortions in controlling complex magnetic phases and their evolution with temperature.
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All authors Anjali Jyothi Bhasu, Satish Kumar, Mátyás Török, Dániel Tibor Pozsár, Bendegúz Nyári, László Udvardi, Gabriel Martínez-Carracedo, Balázs Nagyfalusi, Amador García-Fuente, Jaime Ferrer, Zoltán Tajkov, László Oroszlány, Levente Rózsa, László Szunyogh

Materials Science

Atomistic Mechanisms of Hard Carbon Formation from Polyvinylidene Chloride

Litong Wu, Zitong Wu, Zakariya El-Machachi et al. (+1 more)

Hard carbons are a class of disordered materials with widespread application in energy storage. Despite decades of research, their atomistic formation mechanisms have remained elusive, due to the difficulty of both in situ experimental characterization and first-principles simulations. Here, we describe the formation mechanism of hard carbon from the thermal decomposition of polyvinylidene chloride (PVDC), using first-principles-quality simulations with a bespoke machine-learned interatomic potential model. Our results indicate a two-stage process, consisting of (i) radical-mediated dehydrochlorination, which generates reactive unsaturated carbon sites, and (ii) progressive carbon-carbon cross-linking followed by thermally activated rearrangement into an extended sp$^{2}$-bonded network. We provide an atomistic account of non-hexagonal ring motifs emerging during pyrolysis, supporting the empirically-derived theory that these motifs induce the intrinsic curvature that frustrates graphitic ordering in hard carbons.
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All authors Litong Wu, Zitong Wu, Zakariya El-Machachi, Volker L. Deringer

Materials Science · Cross-listed from physics.optics

Bounds on the Topological Charge of Photonic Systems

F. R. Prudencio, I. Souza and M. G. Silveirinha

Topology has become a central concept in understanding physical phenomena, leading to important advances in condensed matter and photonics. Recent work has established a universal upper bound on the energy gap of Chern insulators in electronic systems, revealing a fundamental connection between topology, quantum geometry, and optical absorption. Here, we generalize this framework to photonic systems, deriving rigorous upper bounds on gap Chern numbers without requiring explicit topological analysis. Our approach enables the estimation of the topological charge of band gaps in both dispersive and nondispersive regimes.
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Materials Science

Room-Temperature Noncolinear Ferroelectricity in van der Waals WO$_2$Cl$_2$ with a Wide Bandgap

Yu Xing, Ning Ding, Zhipeng Wang et al. (+21 more)

Low-dimensional ferroelectrics are attractive for their promising prospects in nanoelectronics. Compared with widely-used ferroelectric perovskites, most low-dimensional ferroelectrics exhibit several inborn weaknesses such as small bandgaps (mostly <2 eV, i.e. semiconductors-like) or faint polarizations (e.g. $<1$ $\mu$C/cm$^2$ for sliding ferroelectrics even if their bandgaps can be large). Here we experimentally demonstrate the room-temperature ferroelectricity of van der Waals WO$_2$Cl$_2$ . The well-tested d0 rule inherited from ferroelectric perovskites leads to a large dipole (~3 eÅ) from the off-center displacement of W$^6+$ ion and a wide bandgap of 2.80 eV. Its ferroelectricity is proved by multiple characterizations including second harmonic generation, piezoresponse force microscopy, and ferroelectric hysteresis loops. More interestingly, the exotic noncollinear dipole order is directly observed at the atomic level by integrated differential phase contrast scanning transmission electron microscopy. Our work paves an alternative route for low-dimensional ferroelectrics to pursue excellent ferroelectric performance and distinct physics of polarity.
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All authors Yu Xing, Ning Ding, Zhipeng Wang, Zhiwen Pan, Lei Guo, Guowei Du, Yangrui Liu, Xiaoxing Cao, Ran Su, Mengting Jiang, Xuezhi Ma, Xiyu Chen, Junchao Zhang, Xinyu Yang, Haoran Ye, Honghong Yao, Rui Feng, Dexiang Chen, Le-Ping Miao, Yumeng You, Zejun Li, Dongsheng Song, Linglong Li, Shuai Dong

Materials Science

SALMON 2.3: Implementation of divide-and-conquer ground-state initialization for large-scale real-time TDDFT

Shunsuke Yamada and Tomohito Otobe

In large-scale real-time time-dependent density functional theory (TDDFT), preparing the ground-state electronic structure can be more expensive than the subsequent time propagation, limiting simulations of nonequilibrium electron dynamics in realistic systems containing thousands of atoms. This bottleneck is especially important for disordered materials, liquids, nanostructures, and heterogeneous condensed-matter systems, where nonlinear and strong-field phenomena such as high-harmonic generation and light-induced phase transitions require explicit real-time treatment. SALMON is an open-source first-principles code for light-matter interaction simulations based on real-time TDDFT on real-space grids, supporting massively parallel calculations with MPI combined with OpenMP or GPU acceleration. In SALMON 2.3, we implement a divide-and-conquer density functional theory (DC-DFT) scheme and combine it with a postprocessing method that reconstructs spatially extended Kohn-Sham orbitals of the entire system. These reconstructed global orbitals are used directly as initial states for the standard real-time, real-space TDDFT module of SALMON. The resulting workflow connects efficient DC-DFT ground-state preparation to conventional real-time TDDFT. The DC-DFT self-consistent-field procedure exhibits linear scaling with system size, addressing a major bottleneck in large-scale electron-dynamics simulations while retaining the robustness and broad applicability of SALMON's established time-propagation scheme. We describe the computational procedure, parallelization strategy, and input/output design. Weak-scaling tests using Si supercells on Fugaku confirm the linear-scaling behavior. Accuracy tests for a 512-atom amorphous Si system and a bulk H2O liquid system containing 4134 atoms demonstrate that the workflow enables practical large-scale real-time TDDFT simulations.
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Materials Science · Cross-listed from cond-mat.mes-hall

Propagating edge and interfacial states in corrugated graphene: Robustness and configurability

Adel Belayadi, Dawei Zhai and Nancy Sandler

Periodically strained graphene provides a versatile platform to realize moiré-like electronic structures. We show that the interplay between strain-induced pseudomagnetic field and a displacement-field-controlled scalar potential enables the formation of isolated narrow bands. Some of the low-energy bands are topological, carrying valley-opposite Chern numbers. Remarkably, despite a vanishing total Chern number, propagating in-gap edge states emerge in various nanoribbon geometries that preserve valley symmetry. We elucidate the distinct mechanisms responsible for edge states in the zero-energy and higher-energy gaps and demonstrate their robustness against disorders, despite lacking conventional topological protection. Leveraging these properties, we propose device architectures in which a displacement field switches the zero-energy gap and its associated edge channels on and off. Furthermore, split-gate geometries generate topological interfacial states that coexist with the edge modes and can be spatially reconfigured. These results establish strain superlattices as a powerful platform for engineering topological electronic states and electronic transport.
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Materials Science

Quasi-1D Spin Textures: From Chiral Soliton Lattice to Fan State

M. Winter, A. Pignedoli, A. S. Sukhanov et al. (+18 more)

In most helimagnets, an applied magnetic field aligns the propagation direction of a helical spin texture with the field, resulting in a conical state and obscuring the unwinding process. Here, we access a complementary regime in the anisotropic chiral magnet Mn$_{1.4}$PtSn, where crystal symmetry constrains the propagation direction of the spin modulation. Using resonant elastic X-ray scattering in a vector magnet, we track the evolution of quasi-one-dimensional spin textures that propagate along a chiral crystallographic axis while the magnetic field is applied perpendicular to this direction. Together with micromagnetic simulations, our measurements reveal a transformation from the zero-field $\pi$-chiral soliton lattice into a fan-like state. In this state, the propagation direction remains transverse to the applied field, while the spins oscillate about the field direction. During magnetization, the modulation length decreases continuously with the field and approaches the field-polarized state. Simulations indicate that magnetostatic interactions in finite samples play a key role in stabilizing this behavior. Our results provide evidence for a fan-like regime in a chiral magnet and highlight how field orientation can be used to control one-dimensional spin textures.
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All authors M. Winter, A. Pignedoli, A. S. Sukhanov, M. Azhar, A. Tahn, B. Achinuq, J. R. Bollard, V. Ukleev, C. Luo, F. Radu, S. Wintz, M. Weigand, A. Mistonov, P. Vir, J. Geck, C. Felser, G. van der Laan, T. Hesjedal, K. Everschor-Sitte, B. Rellinghaus, M. C. Rahn

Thursday 18 June

Materials Science

Deciphering Noise in tip–sample Interactions: Insights into Nanoscale Dynamics

Jaime Colchero and Juan F. González-Martínez

Noise sets the fundamental limits of resolution and sensitivity in Dynamic Atomic Force Microscopy (DAFM). While thermal fluctuations are conventionally assumed to be the dominant noise source, this work demonstrates that tip–sample interactions in ambient conditions introduce a non–thermal noise component that significantly exceeds the thermal background. Using a model system of sodium dodecyl sulfate (SDS) on graphite, we characterize this noise through force spectroscopy, 3D imaging modes, and Kelvin Probe Force Microscopy (KPFM). This interaction–induced noise arises from the stochastic formation and rupture of nanoscopic liquid necks, serving as a direct fingerprint of local wettability and dissipative dynamics. Crucially, we find that this “noise channel” provides chemical contrast that is distinct from and complementary to the electrostatic potential mapped by KPFM. By deciphering the physical origin of these fluctuations, we establish that noise is not merely an instrumental artifact but a rich spectroscopic signal, and we propose that Frequency Modulation (FM–DAFM) offers a superior approach to decouple these dissipative effects for high–resolution imaging.
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Materials Science

Persistent structural distortions and absent superconductivity in trilayer nickelate thin films

Abigail Y. Jiang, Maria Bambrick-Santoyo, Lopa Bhatt et al. (+14 more)

A new family of high-temperature superconductors was recently discovered in the $n=2,3$ Ruddlesden-Popper nickelates, where superconductivity emerges concomitant with suppression of parent density waves and structural octahedral rotations under hydrostatic pressure. Intriguingly, compressive strain mimics the structural effects of pressure in the $n=2$ phase, yielding ambient-pressure superconductivity. However, analogous strain-stabilized superconductivity has not been realized in the $n=3$. Here, we use atomically-precise synthesis, transport, picoscale electron microscopy, and synchrotron X-ray diffraction to probe $n=3$ La$_4$Ni$_3$O$_{10}$ thin films. Although compressive strain suppresses density wave order, we do not observe superconductivity even under the largest strain state. Importantly, we identify a structural distortion unique to strained $n=3$ thin films that may inhibit superconductivity: persistent, layer-inequivalent octahedral rotations around the $c$-axis. Our results highlight key differences between the $n=3$ and $n=2$ systems, suggesting that ambient-pressure superconductivity in the $n=3$ may require new methods beyond epitaxial strain engineering.
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All authors Abigail Y. Jiang, Maria Bambrick-Santoyo, Lopa Bhatt, Kyeong-Yoon Baek, Yi-Feng Zhao, Dan Ferenc Segedin, Ari B. Turkiewicz, Jenna Hatmin, Grace A. Pan, Suchismita Sarker, Donald A. Walko, Charles M. Brooks, David A. Muller, Berit H. Goodge, Hua Zhou, Antia S. Botana, Julia A. Mundy

Materials Science

Silicon Nanostructures for Biosensing: From Field-Effect Transistors to Photonic Resonators, and the Long Road to the Clinic

Ang Liu, Jun Cao, Zhihao Sun et al. (+1 more)

Silicon has a unique combination of properties that makes it one of the best material choices for biosensor platforms: it is inexpensive, its native oxide is atomically smooth, its fabrication processes are CMOS-compatible and have been refined for more than three decades, and it can support many transduction mechanisms in biosensor design. Over the past thirty years, researchers and engineers have used silicon nanostructures to produce ion-sensitive transistors, ultrasensitive nanowire field-effect biosensors, refractive-index-based porous silicon films, microring photonic resonators, suspended cantilevers, luminescent quantum dots, and solid-state nanopores. These device families have demonstrated successful sensing capabilities at the single-molecule, single-virus, or sub-femtomolar level under laboratory conditions; however, they have rarely been widely deployed in clinical assays. This gap is mainly caused by several well-characterized bottlenecks: for nanowire BioFETs, device variability and Debye screening; for porous silicon, fouling, pore wetting, and surface stability; for silicon photonics, thermal drift, spectral readout, and packaging; and across all platforms, calibration, reproducibility, and validation in real biofluids. In this review, we trace the development of silicon biosensors from their early stages to their current state, search and organize the literature focusing on the three most mature platforms and a set of emerging directions, summarize and compare the performance and bottlenecks of different platforms, and argue that progress over the next decade will come primarily from integrated readout, interface engineering, and systematic benchmarking rather than from the discovery of new silicon nanostructures.
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All authors Ang Liu, Jun Cao, Zhihao Sun, Jingsong Shang

Materials Science

Magnetic Anisotropy and Metamagnetic Transitions in Er3Pt2Sb4.55 with A Distorted Square Net Lattice

Dylan Correll, Chaoguo Wang and Xin Gui

Magnetic materials with square-net sublattices are of great interest due to its potential to realize magnetic frustration. Here we report the crystal growth and structural, magnetic, thermodynamic and electronic transport properties of a new rare-earth-based intermetallic compound, Er3Pt2Sb4.55(5). The new material possesses a distorted square-net framework of Er. Magnetic properties measurements suggest anisotropic behavior, long-range antiferromagnetic ordering and metamagnetic transitions based on a Jeff = 1/2 Er3+ motif. A magnetic structure is proposed based on the observed magnetic and thermodynamic properties. This new material expands the R3Pt2Sb4+x family with distorted square-net lattice of rare-earth elements and offers a new opportunity to study the relationship between magnetic ordering, crystal-electric field effect and crystal structure in rare-earth-based compounds.
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Materials Science

Boosting lattice polarization Mixing the perspectives of geometry optimization and cell-augmentation

Pegah Azizi, Rahul Dev Kundu, Xiaojia Shelly Zhang et al. (+1 more)

Topologically polarized mechanical metamaterials enjoy a special built-in asymmetry that manifests as a preferred localization of edge states on selected edges. While this property has been shown for a few ideal Maxwell lattices, we currently lack systematic criteria to design families of structural systems exhibiting polarization. Here, we propose a framework to design polarized structural configurations enabled by topology optimization (TO), using both band and mode morphological properties as drivers of the optimization algorithm. Through the lens of TO, we are able to tap into a vast design space, unlocking geometric freedom far beyond what is achievable with canonical lattice architectures. At the same time, we elucidate important criteria that need to be satisfied, beyond the optimization outcome, to ensure robustness of the achieved polarization against perturbations of the edge morphology. These results provide the inspiration to loop back into the realm of ideal lattices in search of new configurations characterized by extreme polarization. The peculiar shape and connectivity of the TO-generated lattice offer a blueprint for identifying a new family of Maxwell trusses based on augmented kagome geometry. We demonstrate the achievement of strong polarization signatures up to a three-count edge state mismatch. For all the cases studied, we show agreement between theory, simulations, and experiments, which include laser vibrometry wave measurements on a waterjet-cut specimen and static tests on a 3D-printed prototype.
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All authors Pegah Azizi, Rahul Dev Kundu, Xiaojia Shelly Zhang, Stefano Gonella

Materials Science

Controllable Quantum Spin Hall Phases in Bi$_2$Te$_3$-Family van der Waals Heterobilayers

Emmanuel V. C. Lopes, Pedro H. Sophia, Felipe Crasto de Lima et al. (+1 more)

The tunability and control of topological edge/surface states are crucial for the development of new device applications. In this work, by combining first-principles calculations and Wannier-based tight-binding methods, we show the emergence of quantum spin Hall phases in van der Waals heterostructures formed by stacking two trivial quintuple layers from the Bi$_2$Te$_3$ family. We demonstrate the tunability of the edge states under interlayer strain and external electric field effects, suggesting the possibility of switching topological edge states on/off by external control. Additionally, the quantum spin Hall edge channels remain robust against interlayer twist, highlighting their stability against external perturbations. Our results provide a new way to create and manipulate two-dimensional topological phases in systems based on Bi$_2$Te$_3$ family, which can be valuable for practical applications, such as topological field effect transistors and spintronic devices.
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All authors Emmanuel V. C. Lopes, Pedro H. Sophia, Felipe Crasto de Lima, Adalberto Fazzio

Materials Science

A Defect-Free Model of Amorphous Silicon with Pristine Electronic Structure

Louise A. M. Rosset, Chinonso Ugwumadu, Stephen R. Elliott et al. (+2 more)

Amorphous silicon (a-Si) is understood to be the canonical continuous random network material, ideally defined by fully fourfold coordination. Here, we show that a defect-free ('ideal') model of a-Si from machine-learning-driven molecular-dynamics simulations [L. A. M. Rosset et al., Nat. Commun. 16, 2360 (2025)], subsequently evaluated with hybrid-level density-functional theory computations, can accurately reproduce the experimentally observed electronic bandgap. We compare this model with one resulting from the Wooten-Winer-Weaire (WWW) bond-switching approach and with other recent approximants to ideal a-Si. More broadly, our work provides a platform for studies of band tails, optical properties, and transport in a-Si.
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All authors Louise A. M. Rosset, Chinonso Ugwumadu, Stephen R. Elliott, David A. Drabold, Volker L. Deringer

Materials Science · Cross-listed from cs.CE

Interpretable Meta-Learning for Multi-Objective Chemical Search

Antonio Varagnolo, Yulia Pimonova, Michael G. Taylor et al. (+2 more)

Navigating the vast space of synthetically accessible molecules demands surrogate models that are interpretable and capable of handling multiple competing objectives at the same time. Deep learning approaches struggle to satisfy them under the computational constraints of quantum-level chemistry. Here, we introduce a modular pipeline that combines interpretable linear meta-learning models and adaptive-confidence uncertainty quantification into an Efficient Global Optimization (EGO) framework for multi-objective molecular discovery. For the first time, linear meta-learning is deployed in a multi-objective chemical search setting: by training across chemical objectives and cheap auxiliary properties, the meta-learned surrogates acquire transferable chemical knowledge that adapts rapidly to new objectives from limited data. Evaluated empirically on a real large scale search for spin-crossover metal-organic complexes, the baseline performs 78% worse in Pareto sense than the meta-learning alternative. We also address the calibration challenges inherent to active search. Since optimal candidates typically lie precisely in the distributional tails, standard uncertainty estimates fail. We introduce an adaptive confidence-tuning algorithm that dynamically recalibrates the exploration-exploitation trade-off as the molecular search evolves. Empirically, dynamic confidence tuning further dominates over 50% of the statically calibrated front.
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All authors Antonio Varagnolo, Yulia Pimonova, Michael G. Taylor, Raphaël Pestourie, Nicholas E. Lubbers

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

Polymer-polymer interdiffusion: effects of entanglements and a polymeric source

Avraham Moriel and Howard A. Stone

Many industrial applications and biological scenarios involve the interdiffusion of two polymeric species. Motivated by biological subcellular source-driven processes, we study polymer-polymer interdiffusion problems in the absence or the presence of a polymeric source, for both unentangled and entangled scenarios. Utilizing a two-fluid formalism, we arrive at scaling relations, self-similar reductions, and analytical solutions, which are confirmed with one- and two-dimensional numerical simulations. The introduction of a source term breaks the self-similar structure, modifying the boundary conditions and the domain of integration. Nevertheless, we show that the front characteristics of the diffusing droplet exhibit similar spatial structures as in the absence of a source. Our results allow deeper understanding of polymer-polymer interdiffusion and nonlinear transport, especially in the presence of a source.
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Materials Science · Cross-listed from physics.optics

Plasma Etch Process Optimization for Photonic-Grade Diamond-on-Insulator Substrates and Thickness Evaluation using Colorimetry

Tianyin Chen, Alessio Miranda, Leyla Rami et al. (+2 more)

Diamond color-center qubits integrated with photonic circuits can be initialized, manipulated, entangled, and read individually with high fidelity, making them attractive for large-scale modular quantum computers, quantum networks, and distributed quantum sensing. However, the limited size of heteroepitaxially grown single-crystal diamond (SCD) and photonic-grade diamond-on-insulator (DOI) substrates remains a challenge for integration with existing manufacturing processes. Here, we develop a plasma etch recipe to thin direct-bonded (100) SCD membranes (<50 $\mu$m) into large-area, thin-film DOI substrates, and demonstrate free-standing photonic chiplets fabricated from the resulting DOI. The ICP-RIE recipe preserves diamond bonding, provides sufficient micromasking and surface-quality control, and enables thin-film DOI manufacture. We thin a 10 $\mu$m diamond plate bonded to SiO$_2$/Si and obtain a photonic-grade DOI substrate with diamond thickness $\leq$300 nm. The DOI film is around 300 nm thick over 0.5 $\times$ 0.5 mm$^2$, with surface roughness < 0.5 nm, while the bonding interface remains intact. Diamond photonic chiplets are fabricated on this DOI substrate using a standard two-step lithography process, without complex thin-film transfer, under-etching, or pedestal formation. We also present a colorimetric study of diamond visibility on SiO$_2$ and quantify color differences across thicknesses in common colorimetric spaces. This analysis enables automatic diamond-thickness extrapolation from standard optical microscope images with 5 nm resolution, in good agreement with white-light interferometry (WLI) measurements. The DOI substrate and colorimetric thickness-evaluation method provide an effective fabrication platform and reliable validation route for scalable manufacturing of diamond nanophotonic devices, opening a path toward large-scale integrated quantum systems.
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All authors Tianyin Chen, Alessio Miranda, Leyla Rami, Ryoichi Ishihara, Salahuddin Nur