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Physics Condensed Matter Materials Science

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Monday 26 January

Materials Science

Functionalities of Au2O, Au2O3, Au2O3-x, and nanosheets, including spontaneous polarization, using DFT and hybrid functional

Yukio Watanabe

We used density functional theories (DFT) to investigate the properties of Au2O and Au2O3-x (x = 00.08) to reveal their remarkable functionalities. Hybrid functional theories accurately estimate the band gap (Eg) of oxides, and the present hybrid functional calculations determined Eg values of 0.96 eV for Au2O and 2.86 eV for Au2O3, which is >300% of the commonly accepted Eg of Au2O3 (0.85 eV). Moreover, we discovered spontaneous polarization (PS) in Au2O3, which is unusually large and advantageous for catalysis. The PS was retained even in 2-nm-thick Au2O3 nanosheets, similar to hyperferroelectric, generating a potential of 0.6 eV despite screening caused by surface reconstruction, which is a novel screening mechanism. Below a thickness of 0.8 nm, the PS vanished, and inversion symmetry emerged at 0.4 nm, suggesting a new approach to finding a paraelectric phase. Au2O was supersoft under shear distortion.
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Materials Science

Magnetic field-induced non-trivial Lifshitz transition in TaCo2Te2

Suman Kalyan Pradhan, Xiaoming Ma, Jicheng Wang et al. (+14 more)

Magnetic-field-driven Lifshitz transitions are typically considered zero-temperature phenomena involving Fermi-surface reconstruction without symmetry breaking. Here, we report an unconventional Lifshitz transition in TaCo2Te2 that emerges exclusively within a narrow finite-temperature window under cooperative tuning by both temperature and magnetic field. Bulk-sensitive transport and thermoelectric measurements demonstrate continuous Fermi-surface renormalization at low temperatures, where the transition is sharply triggered by a critical magnetic field. Crucially, neutron diffraction reveals the absence of structural or magnetic phase transitions, while angle-resolved photoemission spectroscopy shows no spectral anomalies in electronic structure without magnetic field. These observations constrain the mechanism to a Zeeman-driven process invisible to equilibrium probes, establishing a paradigm where Fermi-surface topology is jointly controlled by temperature and magnetic field.
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All authors Suman Kalyan Pradhan, Xiaoming Ma, Jicheng Wang, Weiqi Liu, Yue Dai, Wenxing Chen, Xiaobai Ma, Wenyun Yang, Yu Wu, Zhaochu Luo, Raktim Datta, Arnab Bera, Samik DuttaGupta, Jinbo Yang, Yanglong Hou, Chang Liu, Rui Wu

Materials Science · Cross-listed from physics.optics

Pulse-driven photonic transitions and nonreciprocity in space-time modulated metasurfaces

Zeki Hayran, John B. Pendry, Prasad P. Iyer et al. (+1 more)

Time-varying photonic systems open new possibilities for controlling light, enabling photonic time crystals, time reflection and refraction, frequency conversion, synthetic gauge fields, optical nonreciprocity, among others. These effects emerge from the dynamic modulation of optical properties, which can mediate photonic transitions between eigenstates of different frequencies and/or wavevectors. To achieve such transitions, conventional approaches rely on periodic modulation schemes that demand ultrafast modulation rates and continuous energy input, posing significant practical challenges at optical frequencies. Here, we demonstrate that periodic-modulation-driven photonic transitions within the radiation continuum can be effectively mimicked using a single-period ultrafast pulse modulation, eliminating the need for sustained continuous modulation. By leveraging dispersion engineering in metasurfaces to tailor the density of states in the radiation continuum, we achieve controlled frequency transitions and theoretically demonstrate strong nonreciprocity for free-space waves as a key application. Our findings may guide future experimental research on time-varying photonics using materials such as transparent conductive oxides and semiconductors, expanding the possibilities for ultrafast and reconfigurable optical technologies. More broadly, our work may establish a practical and energy-efficient framework for dynamic photonic systems, with potential applications ranging from spatio-temporal wavefront manipulation to photonic computing and ultrafast signal processing.
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All authors Zeki Hayran, John B. Pendry, Prasad P. Iyer, Francesco Monticone

Materials Science

Thicker amorphous grain boundary complexions reduce plastic strain localization in nanocrystalline Cu-Zr

Esther C. Hessong, Nicolo Maria della Ventura, Tongjun Niu et al. (+6 more)

Amorphous grain boundary complexions have been shown to increase the plasticity of nanocrystalline alloys as compared to ordered grain boundaries. Here, the effect of an important structural descriptor, amorphous complexion thickness, on the plasticity and failure modes of nanocrystalline Cu-Zr is studied with in-situ compression testing, with over 50 micropillars tested. Two model materials were created that differ only in their complexion thickness, with one having a thicker complexion population than the other. The sample with thinner complexions was more likely to experience non-uniform plastic deformation in the form of localized plastic flow or shear banding. In contrast, the sample with thicker complexions displayed more homogeneous plasticity and higher damage tolerance; thicker amorphous complexions suppress localization by absorbing defects. This work demonstrates that increasing complexion thickness can be beneficial for stable plastic flow in nanocrystalline alloys, by improving resistance to strain localization and premature failure.
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All authors Esther C. Hessong, Nicolo Maria della Ventura, Tongjun Niu, Daniel S. Gianola, Hyosim Kim, Nan Li, Saryu Fensin, Brad L. Boyce, Timothy J. Rupert

Sunday 25 January

Materials Science · Cross-listed from nucl-th

"Observations on the possible electromagnetic nature of nucleon interactions and pions" – historical manuscript from 1969 by B. W. Ninham and C. Pask

Mathias Boström and Drew F. Parsons

This manuscript presents an historical perspective prepared by Barry Ninham and Colin Pask in 1969 on the connection between quantum electrodynamics theory and nucleon interactions. A new theory of strong interactions based on electromagnetic considerations is proposed. Energy and force range magnitudes are correctly given. A new theory of the pion emerges and the pion mass and lifetime are calculated. No strong interaction coupling constant is required.
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Materials Science · Cross-listed from cond-mat.soft

Autonomous Multi-Agent AI for High-Throughput Polymer Informatics: From Property Prediction to Generative Design Across Synthetic and Bio-Polymers

Mahule Roy, Adib Bazgir, Arthur da Silva Sousa Santos et al. (+1 more)

We present an integrated multiagent AI ecosystem for polymer discovery that unifies high-throughput materials workflows, artificial intelligence, and computational modeling within a single Polymer Research Lifecycle (PRL) pipeline. The system orchestrates specialized agents powered by state-of-the-art large language models (DeepSeek-V2 and DeepSeek-Coder) to retrieve and reason over scientific resources, invoke external tools, execute domain-specific code, and perform metacognitive self-assessment for robust end-to-end task execution. We demonstrate three practical capabilities: a high-fidelity polymer property prediction and generative design pipeline, a fully automated multimodal workflow for biopolymer structure characterization, and a metacognitive agent framework that can monitor performance and improve execution strategies over time. On a held-out test set of 1,251 polymers, our PolyGNN agent achieves strong predictive accuracy, reaching R2 = 0.89 for glass-transition temperature (Tg ), R2 = 0.82 for tensile strength, R2 = 0.75 for elongation, and R2 = 0.91 for density. The framework also provides uncertainty estimates via multiagent consensus and scales with linear complexity to at least 10,000 polymers, enabling high-throughput screening at low computational cost. For a representative workload, the system completes inference in 16.3 s using about 2 GB of memory and 0.1 GPU hours, at an estimated cost of about $0.08. On a dedicated Tg benchmark, our approach attains R2 = 0.78, outperforming strong baselines including single-LLM prediction (R2 = 0.67), group-contribution methods (R2 = 0.71), and ChemCrow (R2 = 0.66). We further demonstrate metacognitive control in a polystyrene case study, where the system not only produces domain-level scientific outputs but continually monitors and optimizes its own behavior through tactical, strategic, and meta-strategic self-assessment.
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All authors Mahule Roy, Adib Bazgir, Arthur da Silva Sousa Santos, Yuwen Zhang

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

Advances in ion-doping of Ca-Mg silicate bioceramics for bone tissue engineering

Ashkan Namdar and Erfan Salahinejad

The use of bioceramics as hard tissue substitutes is extensive due to their excellent biocompatible and osteogenic behaviors. Among various bioceramics, Ca-Mg silicates are unique from the viewpoints of osteoinductive and mechanical properties, as well as their outstanding osteoconductive and angiogenic behaviors owing to the release of Si, Ca and Mg. Despite these distinct advantages, different compositions of these bioceramics still require mechanical and biological enhancements for further applications. For this purpose, doping with some ions like F-, Sr2+, Cu2+, Eu2+, Ba+, Ce3+ and some alkali cations has been proved to be a valued approach. This review attempts to bring together areas for the performance improvement of the further researched Ca-Mg silicates (i.e., diopside, akermanite, bredigite and monticellite) and the alteration of these compositions via ion-doping. It is concluded that a correct choice of dopants incorporated at the optimal concentration makes these silicates ideal bone substitutes competing or even superior to calcium phosphates (apatites) and bioglasses which are known as the most prominent bioceramics.
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Materials Science · Cross-listed from cs.LG

Multimodal Machine Learning for Soft High-k Elastomers under Data Scarcity

Brijesh FNU, Viet Thanh Duy Nguyen, Ashima Sharma et al. (+3 more)

Dielectric materials are critical building blocks for modern electronics such as sensors, actuators, and transistors. With rapid advances in soft and stretchable electronics for emerging human- and robot-interfacing applications, there is a growing need for high-performance dielectric elastomers. However, developing soft elastomers that simultaneously exhibit high dielectric constants (k) and low Young's moduli (E) remains a major challenge. Although individual elastomer designs have been reported, structured datasets that systematically integrate molecular sequence, dielectric, and mechanical properties are largely unavailable. To address this gap, we curate a compact, high-quality dataset of acrylate-based dielectric elastomers by aggregating experimental results from the past decade. Building on this dataset, we propose a multimodal learning framework leveraging large-scale pretrained polymer representations. These pretrained embeddings transfer chemical and structural knowledge from vast polymer corpora, enabling accurate few-shot prediction of dielectric and mechanical properties and accelerating data-efficient discovery of soft high-$k$ dielectric elastomers. Our data and implementation are publicly available at: https://github.com/HySonLab/Polymers
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All authors Brijesh FNU, Viet Thanh Duy Nguyen, Ashima Sharma, Md Harun Rashid Molla, Chengyi Xu, Truong-Son Hy

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

Large temperature-up-jump simulations of a binary Lennard-Jones system

Aude Y. Amari, Lorenzo Costigliola and Jeppe C. Dyre

This paper presents simulations of the physical aging of a binary Kob-Andersen-type Lennard-Jones liquid following large temperature up-jumps from equilibrated states of high relaxation time. The purpose is to investigate how well the Tool-Narayanaswamy (TN) material-time concept works for this rather extreme case of aging. First the triangular relation of the potential energy is investigated. This is found to be well obeyed, making it possible to define a potential-energy-based material time $\xi$. We proceed to study aging toward equilibrium at the final temperature 0.48 for jumps from the two temperatures 0.43 and 0.37 (primarily), monitoring the following five quantities: the potential energy, the self-intermediate scattering function, the mean-square displacement, the dynamic susceptibility $\chi_4$, and the non-Gaussian parameter $\alpha_2$. The TN material-time prediction is that all time-autocorrelation functions should collapse to only depend on the material-time difference $\xi_2-\xi_1$. This is found to work better for the $0.43\to 0.48$ temperature jump than for the $0.37\to 0.48$ jump. Our findings thus confirm the general understanding that the TN aging formalism works best for systems that are never very far from equilibrium. This raises two questions for future work: Is the collapse significantly improved if each aging quantity is allowed its own material time? Can better collapse be obtained if the material-time is generalized to be locally defined (in order to reflect dynamic heterogeneity)?
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Materials Science

Crystal Representation in the Reciprocal Space

Osman Goni Ridwan, Hongfei Xue, Youxing Chen et al. (+2 more)

In crystallography, a structure is typically represented by the arrangement of atoms in the direct space. Furthermore, space group symmetry and Wyckoff site notations are applied to characterize crystal structures with only a few variables. While this representation is effective for data records and human learning, it lacks one-to-one correspondence between the crystal structure and its representation. This is problematic for many applications, such as crystal structure determination, comparison, and more recently, generative model learning. To address this issue, we propose to represent crystals in a four-dimensional (4D) reciprocal space featured by their Cartesian coordinates and scattering factors, which can naturally handle translation invariance and space group symmetry with the help of structure factors. In order to achieve rotational invariance, the 4D coordinates are then transformed into a power spectrum representation under the orthogonal spherical harmonic and radial basis. Hence, this representation captures both periodicity and symmetry of the crystal structure while also providing a continuous representation of the atomic positions and cell parameters in the direct space. Its effectiveness is demonstrated by applying it to several crystal structure matching and reconstruction tasks.
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All authors Osman Goni Ridwan, Hongfei Xue, Youxing Chen, Harish Cherukuri, Qiang Zhu

Materials Science

Instability-driven mechanically locked states in functional oxide membranes

Varun Harbola, Thomas Emil le Cozannet, Denis Alikin et al. (+10 more)

Mechanical instabilities in thin solids offer a powerful route to engineer nonlinear responses, yet their controlled use in functional crystalline oxides has remained largely unexplored. Notably, by changing the aspect ratio of solids, the energy landscape around equilibrium can be modified to induce non-linearities under lateral stresses through non-lateral deformations. These nonlinear systems can develop multiple local energy minima where the system can settle and switch between states through the application of a driving force. Crucially, recent advances in oxide thin film growth have enabled the fabrication of freestanding oxide membranes, paving a viable path for their use in bistable architecture, particularly at the nanoscale. Here, we demonstrate that freestanding oxide membranes, such as SrTiO3 (STO) and BaTiO3 (BTO), relax into well-defined metastable buckling states when transferred onto lithographically defined cavities. The membrane deformation is determined by the interplay between built-in residual strain, bending stiffness, and cavity geometry, resulting in reproducible bistable states with distinct strain distributions. Using a combination of atomic force microscopy, in-contact Kelvin probe measurements, and finite-element modelling, we reveal that these mechanically locked states directly shape the electromechanical potential landscape of ferroelectric BaTiO3. We further demonstrate reversible snapthrough transitions between mechanically degenerate states, establishing complex oxides as deterministic, geometry-tunable building blocks for nonlinear nanoelectromechanical architectures. Our results illustrate a general strategy for exploiting mechanical instabilities to encode and manipulate functional responses in ultrathin crystalline membranes.
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All authors Varun Harbola, Thomas Emil le Cozannet, Denis Alikin, Shinhee Yun, Edwin Dollekamp, Andrea Roberto Insinga, Rasmus Bjørk, Nikolas Vitaliti, Thomas Sand Jespersen, Katja Isabelle Wurster, Dae-Sung Park, Jochen Mannhart, Nini Pryds

Materials Science · Cross-listed from quant-ph

Colour Centre Formation in Silicon-On-Insulator for On-Chip Photonic Integration

Arnulf J. Snedker-Nielsen, David R. Gongora, Magnus L. Madsen et al. (+12 more)

Colour centres in silicon have great potential as single photon sources for quantum technologies. Some of them - like the T centre - also possess optically-active spins that enable spin-photon interfaces for generating entangled photons and multi-spin registers. This paper explores the generation of several types of colour centres in silicon for mass-manufacturable silicon-on-insulator quantum devices. We investigate how different processes in the device development affect the presence of the quantum emitters, including thermal annealing and fabrication steps for optical nanostructures. The study reveals coupled formation dynamics between different colour centres, identifies optimal parameters for annealing processes, and reports on the sensitivity to annealing duration and nanofabrication procedures for photonic integrated circuits. Furthermore, we discern stable optical signals from colour centres in silicon which have not been identified before.
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All authors Arnulf J. Snedker-Nielsen, David R. Gongora, Magnus L. Madsen, Christian H. Christiansen, Eike L. Piehorsch, Mathias Ø. Augustesen, Elvedin Memisevic, Sangeeth Kallatt, Rodrigo A. Thomas, Mark Kamper Svendsen, Peter Krogstrup Jeppesen, Marianne E. Bathen, Lasse Vines, Peter Granum, Stefano Paesani

Materials Science · Cross-listed from physics.optics

Experimental Realization of Optimized Ternary Mirror Coatings

V. Pierro, M. Granata, C. Michel et al. (+9 more)

We report on the first experimental realization of multi-material dielectric mirror coatings designed through a multi-objective optimization algorithm to simultaneously minimize thermal noise and optical losses. We validate this design strategy by fabricating and characterizing two distinct ternary systems: a SiNx -based proof-of-concept and a Ti:GeO2 -based system targeting lower optical losses. The performance of the SiN x coating shows remarkable agreement with predictions, demonstrating a noise amplitude spectral density reduction of 0.82 with respect to current reference coatings, and validating our design-to-fabrication pipeline. The Ti:GeO2 -based system achieves the crucial goal of sub-ppm absorption; its measured thermal noise, however, is higher than the theoretically predicted level of 0.71, extrapolated from single-layer material characterization. A dedicated tolerance analysis confirms that this discrepancy is not attributable to random thickness errors, emphasizing that further studies of the manufacturing process are needed to fully exploit this combination of materials. This work establishes a robust methodology for producing complex, high-performance optical coatings tailored for precision experiments.
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All authors V. Pierro, M. Granata, C. Michel, L. Pinard, B. Sassolas, D. Forest, N. Demos, S. Gras, M. Evans, I. M. Pinto, G. Avallone, V. Granata

Materials Science

An AI-ready fine-tuning framework for accurate machine-learning interatomic potentials in solid-solid battery interfaces

Xiaoqing Liu, Xinyu Yu, Yangshuai Wang et al. (+6 more)

Atomistic modeling of solid-solid battery interfaces is essential for understanding electro-chemo-mechanical coupling, but the complex interfacial chemistry and heterogeneous environments pose major challenges for quantum-accurate, data-efficient modeling. Herein, we propose an approach of fine-tuning with integrated replay and efficiency (FIRE), a general framework for universal machine-learning interatomic potentials by combining efficient configurational sampling with a replay-argumented continual strategy, achieving quantum-level accuracy at moderate cost. Across six solid-solid battery interface systems, FIRE consistently achieves root-mean-square errors in energy below 1 meV/atom and in force near 20 meV/angstrom, marking an order-of-magnitude improvement over existing models while requiring only 10% of the original datasets. In addition, the fine-tuned model successfully reproduces key mechanical and electrochemical properties of the materials, in close agreement with experimental data. The FIRE offers a generalizable and data-efficient approach for developing accurate interatomic potentials across diverse materials, enabling predictive simulations beyond the reach of first-principles methods.
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All authors Xiaoqing Liu, Xinyu Yu, Yangshuai Wang, Zhe-Tao Sun, Zedong Luo, Kehan Zeng, Teng Zhao, Shou-Hang Bo, Zhenli Xu

Materials Science

An autonomous living database for perovskite photovoltaics

Sherjeel Shabih, Hampus Näsström, Sharat Patil et al. (+16 more)

Scientific discovery is severely bottlenecked by the inability of manual curation to keep pace with exponential publication rates. This creates a widening knowledge gap. This is especially stark in photovoltaics, where the leading database for perovskite solar cells has been stagnant since 2021 despite massive ongoing research output. Here, we resolve this challenge by establishing an autonomous, self-updating living database (PERLA). Our pipeline integrates large language models with physics-aware validation to extract complex device data from the continuous literature stream, achieving human-level precision (>90%) and eliminating annotator variance. By employing this system on the previously inaccessible post-2021 literature, we uncover critical evolutionary trends hidden by data lag: the field has decisively shifted toward inverted architectures employing self-assembled monolayers and formamidinium-rich compositions, driving a clear trajectory of sustained voltage loss reduction. PERLA transforms static publications into dynamic knowledge resources that enable data-driven discovery to operate at the speed of publication.
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All authors Sherjeel Shabih, Hampus Näsström, Sharat Patil, Asmin Askin, Keely Dodd-Clements, Jessica Helisa Hautrive Rossato, Hugo Gajardoni de Lemos, Yuxin Liu, Florian Mathies, Natalia Maticiuc, Rico Meitzner, Edgar Nandayapa, Juan José Patiño López, Yaru Wang, Lauri Himanen, Eva Unger, T. Jesper Jacobsson, José A. Márquez, Kevin Maik Jablonka

Materials Science

Scattering analysis of nano-scale chiral structures in optical vortex using Method of Moments

Chenxu Wang, Hideki Kawaguchi, Hiroaki Nakamura et al. (+2 more)

This paper presents a full 3D Method of Moments (MoM) simulation for analysis of scattering from nano-scale chiral ribbon structures under optical vortex illumination to aim to investigate electromagnetic mechanism of circular dichroism (CD) and optical vortex dichroism (VD). Both twist and helical nano-ribbons are modeled as dispersive materials scatterer. CD and VD are evaluated quantitatively by differences in scattering power. Numerical results demonstrate that angular momentum of optical light induces dichroic response effectively.
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All authors Chenxu Wang, Hideki Kawaguchi, Hiroaki Nakamura, Koichi Matsuo, Masahiro Katoh

Materials Science

Environmental Breakdown of Topological Interface States in Armchair Graphene Nanoribbon Heterostructures

David M T Kuo

We theoretically investigate the stability and transport properties of topological interface states (IFs) in 9-7-9 and 15-13-15 armchair graphene nanoribbon heterostructures (AGNRHs) laterally embedded in boron nitride (BN) sheets. Two configurations, $n$-BNNR/AGNRH/$n$-BNNR and $n$-BNNR/AGNRH/$n$-NBNR, corresponding to same-topology and reverse-topology BN environments, are examined within a tight-binding framework. Using a bulk boundary perturbation approach, we show that in BNNR/AGNRH/BNNR the IFs are destroyed by chirality breaking induced by symmetric BN environments at both interfaces. In contrast, the IFs in the reverse-topology structure remain robust against lateral interface interactions from BN atoms. Transport calculations further demonstrate that the surviving IFs in BNNR/AGNRH/NBNR exhibit the characteristic behavior of topological double quantum dots, with an enhanced interdot hopping strength compared with vacuum boundary conditions. These results reveal that BN environments can either suppress or reinforce topological interface states, depending critically on the topology of the surrounding nanoribbons.
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Materials Science · Cross-listed from cond-mat.mes-hall

Emergent Nodal Spheres and Weyl Fermions via Spin-Texture Coupled to Thin Film Orbital Dirac Semimetals

Pritam Chatterjee and Anirudha Menon

We consider the minimal coupling of a thin film Dirac semimetal Hamiltonian to a generic spin-texture. A simple unitary transformation gauges away the spatial dependence in the exchange term, leading to the generation of effective corrections to the Dirac dispersion. A full function's worth of freedom is obtained as a result. Choosing different pitch vectors, we show that many novel phenomena arise in such systems. For example, a linear pitch vector leads to the generation of a Weyl semimetal – we observe the anomalous Hall effect and the chiral magnetic effect. The anomalous Hall coefficient requires a non-zero pitch vector whereas the CME is proportional to the exchange coupling. The band structure of the model in the presence of a magnetic field shows a Lifshitz-like transition driven by the exchange coupling. The introduction of a suitable time-dependent pitch vector leads, at the level of the leading-order Floquet effective Hamiltonian, to the emergence of a nodal sphere in momentum space. We further show that, in the full driven problem, a closed quasienergy degeneracy structure persists, continuously connected to this nodal sphere, and constrained by the operator algebra of the Floquet expansion.
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Materials Science

Electrical and Structural Response of Nine-Atom-Wide Armchair Graphene Nanoribbon Transistors to Gamma Irradiation

Kentaro Yumigeta, Muhammed Yusufoglu, John G. Federici et al. (+6 more)

Materials and devices used in space and advanced energy systems are continuously exposed to high-energy photons and particles, leading to gradual changes in their structural and electronic properties. Gamma-ray exposure is particularly critical because their strong penetrating power allows them to traverse conventional shielding and device packaging. Real-time monitoring of exposure-induced changes in compact, chip-integrated devices remains limited despite the availability of external radiation detectors. Atomically precise graphene nanoribbons (GNRs) present an attractive platform for probing such effects due to their structural uniformity, tunable electronic properties, and exceptional sensitivity of charge transport to even subtle lattice modifications. Here, we investigate the structural and electronic response of atomically precise GNRs under gamma irradiation. Nine-atom-wide armchair GNRs (9-AGNRs) were synthesized via a bottom-up on-surface approach, integrated into field-effect transistors (FETs), and characterized before and after exposure using Raman spectroscopy and electrical transport measurements. Raman spectroscopy indicates preservation of the primary GNR lattice structure, accompanied by subtle spectral changes suggestive of irradiation-induced oxidation or local lattice perturbations. While these measurements do not indicate severe structural damage, electrical transport measurements reveal a pronounced degradation in device performance, demonstrating the strong susceptibility of GNRFETs to gamma-ray exposure. This pronounced response may be attributed to Anderson localization of charge carriers, potentially arising from enhanced quantum interference in atomically narrow, quasi-one-dimensional GNRs. These results highlight the potential of GNR-based nanoelectronic devices for sensing and monitoring under extreme operational conditions.
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All authors Kentaro Yumigeta, Muhammed Yusufoglu, John G. Federici, Elena T. Hughes, Ahmet Mert Degirmenci, Jon T. Njardarson, Kelly Simmons-Potter, Barrett G. Potter, Zafer Mutlu

Saturday 24 January

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

Universal rapid machine learning models for predicting unconvoluted and convoluted X-ray Absorption Spectra

Fei Zhan and Zhi Geng

X-ray absorption near edge structure (XANES) is an essential tool for elucidating the atomic-scale, local three-dimensional (3D) structure of given materials and molecules. The rapid computation of XANES based on molecular 3D structures constitutes a vital element of quantitative XANES analysis. Here, we present an XANES prediction model. It takes 3D structures as input and generates either unconvoluted XANES or convoluted spectra as output, demonstrating excellent generalizability across diverse instrumental broadening. This model has validated its predictive capability for both hard X-ray XAS (exemplified by K-edges of 3d 4d metals and lanthanides) and soft X-ray XAS (using S K-edge as examples). Adopting the model, XANES spectra of multiple elements can be predicted using a single unified model. A highly efficient 3D structure fitting algorithm based on this unconvoluted XANES prediction model, aiming to serve as an online data analysis method suitable for XAS beamlines.
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Materials Science · Cross-listed from eess.IV

In-situ On-demand Digital Image Correlation: A New Data-rich Characterization Paradigm for Deformation and Damage Development in Solids

Ravi Venkata Surya Sai Mogilisetti, Partha Pratim Das, Rassel Raihan et al. (+1 more)

Digital image correlation (DIC) has become one of the most popular methods for deformation characterization in experimental mechanics. DIC is based on optical images taken during experimentation and post-test image processing. Its advantages include the capability to capture full-field deformation in a non-contact manner, the robustness in characterizing excessive deformation induced by events such as yielding and cracking, and the versatility to integrate optical cameras with a variety of open-source and commercial codes. In this paper, we developed a new paradigm of DIC analysis by integrating camera control into the DIC process flow. The essential idea is to dynamically increase the camera imaging frame rate with excessive deformation or deformation rate, while maintaining a relatively low imaging frame rate with small and slow deformation. We refer to this new DIC paradigm as in-situ on-demand (ISOD) DIC. ISOD DIC enables real-time deformation analysis, visualization, and closed-loop camera control. ISOD DIC has captured approximately 178% more images than conventional DIC for samples undergoing crack growth due to its dynamically adjusted frame rate, with the potential to significantly enhance data richness for damage inspection without consuming excessive storage space and analysis time, thereby benefiting the characterization of intrinsic constitutive behaviors and damage mechanisms
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All authors Ravi Venkata Surya Sai Mogilisetti, Partha Pratim Das, Rassel Raihan, Shiyao Lin

Materials Science · Cross-listed from cond-mat.stat-mech

A Local Structural Basis to Resolve Amorphous Ices

Quinn M. Gallagher, Ryan J. Szukalo, Nicolas Giovambattista et al. (+2 more)

Phases with distinct thermodynamic properties must differ in their underlying microscopic configurations. While ordered phases are readily distinguished by unit cells and space groups, the local structural basis differentiating amorphous phases is less apparent. Here, using a new probabilistic data-driven framework applied to molecular simulations of water, we identify local collective variables that discriminate low-density and high-density amorphous (LDA and HDA) ices and characterize pressure-induced transitions between them. As expected, descriptors related to local density effectively distinguish LDA and HDA; however, phase identity is surprisingly encoded within the first coordination shell. Furthermore, the pressure-induced LDA–HDA transformation proceeds through redistribution between LDA- and HDA-like local environments with no evidence for intermediate structures, consistent with a first-order-like phase transition. This contrasts with the gradual structural evolution observed in other amorphous systems, such as metallic glasses. Critically, local hydrogen density reveals pronounced structural hysteresis between compression and decompression pathways, which is not apparent in orientational order parameters, demonstrating that the microscopic interpretation of amorphous transformations depends fundamentally on descriptor choice. These findings are robust across force fields and provide a general strategy for characterizing disordered phases lacking obvious distinguishing features.
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All authors Quinn M. Gallagher, Ryan J. Szukalo, Nicolas Giovambattista, Pablo G. Debenedetti, Michael A. Webb

Materials Science

Non-monotonic roughness evolution in film growth on weakly interacting substrates

Dmitry Lapkin, Ismael S. S. Carrasco, Catherine Cruz Luukkonen et al. (+5 more)

Thin film deposition on weakly interacting substrates exhibits a unique growth mode characterized by initially strong island formation and rapidly increasing roughness, which reaches a maximum and subsequently decreases as the film returns to a smooth morphology. Here we show this rough-to-smooth growth mode experimentally for two molecular systems with substantially different geometries, namely, the effectively spherical buckminsterfullerene (C$_{60}$) and the disk-like 1,4,5,8,9,11-hexaazatriphenylenehexacarbonitrile (HATCN). This growth mode is explained by a geometrical model that captures the basic mechanisms of multilayer island growth, island coalescence, and formation of a continuous film. Additionally, kinetic Monte Carlo simulations with minimal ingredients demonstrate that this mode generally occurs for weakly interacting substrates, providing quantitative estimates of parameters that characterize adsorbate-adsorbate and adsorbate-substrate interactions. Both the model and simulations accurately describe the experimental data and highlight the generic nature of the phenomenon, independently of the details of the interactions and the molecular flux, which opens up a path for controlling nanoscale film roughness.
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All authors Dmitry Lapkin, Ismael S. S. Carrasco, Catherine Cruz Luukkonen, Oleg Konovalov, Alexander Hinderhofer, Frank Schreiber, Fábio D. A. Aarão Reis, Martin Oettel

Materials Science

Complex spin dynamics induced metamagnetic phase transitions in Dirac semimetal EuAuBi

Lipika, Shobha Singh, Anyesh Saraswati et al. (+8 more)

We report a comprehensive investigation of the physical properties of the Dirac semimetal compound EuAuBi single crystals, using neutron diffraction, magnetization, electrical transport, and specific heat measurements. EuAuBi crystallizes in a hexagonal structure with space group P63mc (No. 186). First-principles calculations using density functional theory characterize it as a Dirac semimetal, with a notable band-crossing in proximity to the Fermi level (EF ) along the {\Gamma}-A direction. The crystal exhibits three distinct magnetic phases at 4 K (TN1), 3.5 K (TN2), and 2.8 K (TN3)as observed from magnetic and specific heat measurements. However, zero-field neutron diffraction resolves only two magnetic phases: a commensurate antiferromagnetic phase and a canted antiferromagnetic phase. Field-dependent ac and dc magnetization measurements uncover field-induced non-trivial spin textures in the magnetic field range 1.5 to 3 T, manifested as a tilted plateau in the magnetization curves. The interplay between conduction carriers and these spin textures is further evidenced by unique features in the magnetic field-dependent longitudinal resistivity in the system. Finally, we present a comprehensive magnetic phase diagram of EuAuBi, highlighting diverse spin alignments present in the material. EuAuBi thus emerges as a rare material system in which both momentum-space and real-space Berry curvature effects may coexist, providing a unique opportunity to investigate their interplay.
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All authors Lipika, Shobha Singh, Anyesh Saraswati, Vikas Chahar, Yan Sun, Pascal Manuel, Devashibhai Adroja, Walter Schnelle, Nitesh Kumar, Jhuma Sannigrahi, Kaustuv Manna

Materials Science

Non-Enzymatic Glucose sensing properties of NiO nanostructured flower decorated Exfoliated Graphite Electrodes

Piyush Choudhary, Chhavi Chetiwal, Chandra Prakash et al. (+2 more)

Nanostructured transition metal oxides (TMO) are extensively explored materials for non-enzymatic glucose sensors. TMOs such as Iron oxides( {\alpha}-Fe2O3, {\gamma}-Fe2O3, Fe3O4, etc.), NiO, CuO, Cr2O3, etc. have been utilized as electrocatalysts for glucose determination. Tremendous efforts have been put into identifying the impact of different morphologies of these materials on the glucose-sensing performance. The larger surface area of the flower and wire-shaped catalysts make them better performing amongst other morphologies. Interestingly, it is important to note that most of such studies are on standard Glassy Carbon electrodes. Further to enhance the Electrochemically active surface area (ECSA) of the electrode, Carbon nanomaterials such as reduced Graphene Oxide (r-GO) and Carbon Nanotubes (CNTs) are used as additives. Exfoliated Graphite paper electrodes offer better electrochemical characteristics than GCE electrodes due to their much larger ECSA. This study presents the non-enzymatic glucose sensing properties of NiO nanoflower-decorated Exfoliated Graphite electrodes. The amperometric detection of glucose shows a linear increase in current over a physiologically relevant wide range of 0-10 mM. The electrodes offer a better sensitivity of 304.12 microA per mM per cm square and a Limit Of Detection (LOD) of 100 microM. In addition, the electrodes showed high selectivity towards glucose in the presence of other interfering species such as Ascorbic acid, Fructose, Sucrose, and NaCl.
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All authors Piyush Choudhary, Chhavi Chetiwal, Chandra Prakash, Vijay K. Singh, Ambesh Dixit

Materials Science

Resistive-Switching Dynamics in Poly(3-hexylthiophene-2,5-diyl) Thin Films under Perforated Bottom Electrode

Sirsendu Ghosh and Pramod Kumar

The effect on the resistive switching (RS) mechanism in organic semiconductor (OSC), Poly(3-hexylthiophene-2,5-diyl) (P3HT), due to the presence of the perforated bottom electrode (PBE) is investigated. The simulation shows a high local electric field at the edges of a patterned bottom electrode (BE), which can increase the probability of metal filament formation due to high current density, suggesting that the use of a PBE can assist the RS mechanism. RS involves switching from the high resistive state (HRS) to the low resistive state (LRS) known as the "SET" process at higher positive bias, and returning to HRS from LRS is known as the "RESET" process, which can be achieved at a negative bias. Various switching mechanisms are segregated from each other by the obtained current response to applied voltage. RS due to the formation of complete metal filaments between the top and bottom electrodes showed Ohm's law behaviour. On the other hand, a slope of approximately 2 in the log-log plot signifies that the space charge limited current (SCLC) dominates the device, and hence RS comes from incomplete metal filament formation or some changes in the P3HT polymer itself. Similarly, high current density can transform the molecular arrangement from crystalline to an amorphous state due to joule heating, which leads to an intermediate OFF state. The high current density joule heating RS are from HRS to LRS, which is opposite to the metal filament based RS, hence it is called an inverted RS. The optical images of the fresh device and after multiple cycles indicate the metal percolation inside the OSC responsible for the RS. EDX spectrum at LRS in a cross-sectional transmission electron microscope (TEM) confirms the top metal percolation through the OSC and touches the BE. Therefore, the metal filament formation is the fundamental reason for these observed switching behaviours in P3HT.
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Materials Science

Catalog of phonon emergent particles and chiral phonons: Symmetry-based classification and materials database investigation

Houhao Wang, Dongze Fan, Hoi Chun Po et al. (+2 more)

Chirality and topology are fundamental and ubiquitous in nature. Symmetry has proven to be a powerful tool for predicting topological phonons. However, to date, topological phonon emergent particles (EMPs) have not been systematically cataloged in material databases. Moreover, traditional symmetry methods are often inadequate for predicting chiral phonons, because realistic calculations can yield negative results even when symmetry analysis permits phonon chirality. Here, we first establish a complete symmetry-based classification: given any space group and Wyckoff positions (WYPOs) occupied by atoms, the number of occurrences of all (co-)irreducible representations ((co-)irreps) (that can host EMPs) can be unambiguously known without omission prior to expensive and parameter-dependent calculation. Moreover, whether a phonon mode (belonging to one (co-)irrep) is chiral can also be determined from the occupied WYPOs. We then perform a materials database investigation identifying over 25 million EMPs at high-symmetry points and along high-symmetry lines and computing the concrete value of phonon angular momentum for each mode. We demonstrate two main applications: identifying ideal materials with surface chirality momentum locking and identifying materials with giant phonon magnetic moment. All computational data are compiled into a website: http://phonon.nju.edu.cn, which is expected to stimulate future studies on topological and chiral phonons.
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All authors Houhao Wang, Dongze Fan, Hoi Chun Po, Xiangang Wan, Feng Tang

Materials Science

Predicting Interface Structure using the Minima Hopping Method with a Machine Learning Interatomic Potential

Chang-Ti Chou, Menghang Wang, Chao Yang et al. (+4 more)

Predicting atomic-scale interfacial structures remains a central challenge in materials science due to their structural complexity and the difficulty of direct comparison between computational and experimental results. In this study, we present an efficient approach for interface structure prediction that integrates the Minima Hopping Method (MHM) with the state-of-the-art machine learning interatomic potential (MLIP), Allegro. We demonstrate that the MHM-Allegro approach provides a robust and computationally efficient route for predicting interfacial structures in the benchmark system SrTiO3 Sigma 3 (112)[110] tilt grain boundaries (GBs), consistently identifying the lowest-energy configurations across different stoichiometries. Furthermore, we introduce a strategy for constructing defect-representative training datasets without explicitly including defective configurations, achieving excellent extrapolative performance in interface predictions. The predictive capability is further validated through direct comparison with experimental observations of the SrTiO3 Sigma 5 (310)[001] GB, where the predicted atomic configurations show strong agreement with experimental measurements. This work represents a significant step toward bridging the gap between ab initio predictions and experimentally observed interfacial structures.
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All authors Chang-Ti Chou, Menghang Wang, Chao Yang, Peter A. van Aken, Nicola H. Perry, Boris Kozinsky, Christopher M. Wolverton

Materials Science

Unsupervised segmentation and clustering workflow for efficient processing of 4D-STEM and 5D-STEM data

Serin Lee, Stephanie M. Ribet, Arthur R. C. McCray et al. (+3 more)

Four-dimensional scanning transmission electron microscopy (4D-STEM) enables mapping of diffraction information with nanometer-scale spatial resolution, offering detailed insight into local structure, orientation, and strain. However, as data dimensionality and sampling density increase, particularly for in situ scanning diffraction experiments (5D-STEM), robust segmentation of structurally consistent behavior across sequential measurements becomes essential for efficient and physically meaningful analysis. Here, we introduce a clustering framework that identifies crystallographically distinct domains from 4D-STEM datasets. By using local diffraction-pattern similarity as a metric, the method extracts closed contours delineating spatially contiguous regions. This approach produces cluster-averaged diffraction patterns that improve signal quality while reducing data volume by orders of magnitude, enabling rapid and accurate orientation, phase, and strain mapping. We demonstrate the applicability of this approach to in situ liquid-cell 4D-STEM data of gold nanoparticle growth. Our method provides a scalable and generalizable route for spatially coherent segmentation, data compression, and quantitative structure-strain mapping across diverse 4D-STEM modalities. The full analysis code and example workflows are publicly available to support reproducibility and reuse.
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All authors Serin Lee, Stephanie M. Ribet, Arthur R. C. McCray, Andrew Barnum, Jennifer A. Dionne, Colin Ophus

Materials Science

Assessment of the synthetic feasibility of hypothetical zeolite-like materials based on ZeoNet

Yachan Liu, Elaine Wu, Ping Yang et al. (+4 more)

A suite of classifiers was developed to distinguish experimentally synthesized zeolites from computationally predicted zeolite-like structures. Using convolutional neural networks applied to 3D volumetric grids, these classifiers achieve accuracies more than an order of magnitude higher than previous approaches based on geometric filters or other machine learning methods. The best-performing model differentiates among hypothetical zeolites and those that can be synthesized as silicates, as aluminophosphates, or as both. This four-class classifier attains a false negative rate of 3.4% and a false positive rate of 0.4%, misidentifying only 1,207 of over 330,000 hypothetical structures–even though the hypothetical structures exhibit similar formation energies as real zeolites and chemically reasonable bond lengths and angles. We hypothesize that the ZeoNet representation captures essential structural features correlated with synthetic feasibility. In the absence of comprehensive physics-based criteria for synthesizability, the small subset of misclassified hypothetical structures likely represents promising candidates for future experimental synthesis.
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All authors Yachan Liu, Elaine Wu, Ping Yang, Aaron Sun, Subhransu Maji, Wei Fan, Peng Bai