Materials Science · Cross-listed from physics.plasm-ph
Autonomous Sampling and SHAP Interpretation of Deposition-Rates in Bipolar HiPIMS
Alexander Wieczorek, Nathan Rodkey, Jan Sommerhäuser et al. (+2 more)
High-power impulse magnetron sputtering (HiPIMS) offers considerable control over ion energy and flux, making it invaluable for tailoring the microstructure and properties of advanced functional coatings. However, compared to conventional sputtering techniques, HiPIMS suffers from reduced deposition rates. Many groups have begun to evaluate complex pulsing schemes to improve upon this, leveraging multi-pulse schemes (e.g. pre-ionization or bipolar pulses). Unfortunately, the increased complexity of these pulsing schemes has led to high-dimensionality parameter spaces that are prohibitive to classic design of experi-ments. In this work we evaluate bipolar HiPIMS pulses for improving deposition rates of Al and Ti sputter tar-gets. Over 3000 process conditions were collected via autonomous
Bayesian sampling over a 6-dimensional parameter space. These process conditions were then interpreted using Shapley Additive Explanations (SHAP), to deconvolute complex process influences on deposition rates. This allows us to link observed var-iations in deposition rate to physical mechanisms such as back-attraction and
plasma ignition. Insights gained from this approach were then used to target specific processes where the positive pulse components were expected to have the highest impact on deposition rates. However, in practice, only minimal improve-ments in deposition rate were achieved. In most cases, the positive pulse appears to be detrimental when placed immediately after the neg. pulse which we hypothesize relates to quenching of the afterglow
plasma. The proposed workflow combining autonomous experimentation and interpretable machine learning is broad-ly applicable to the discovery and optimization of complex
plasma processes, paving the way for physics-informed, data-driven advancements in coating technologies.
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All authors Alexander Wieczorek, Nathan Rodkey, Jan Sommerhäuser, Jason Hattrick-Simpers, Sebastian Siol
Materials Science · Cross-listed from physics.optics
Processing-Dependent Near-Field Radiative Heat Transfer at Au/SiC Interfaces
A. Márquez and R. Esquivel-Sirvent
Thermal annealing is a widely used thin-film processing technique for modifying interfacial optical losses and electronic scattering in plasmonic materials. Here, we investigate how thermal annealing of gold thin films deposited on silicon carbide substrates influences interfacial near-field radiative heat transfer across nanoscale
vacuum gaps. Using experimentally measured dielectric functions for annealed and unannealed Au films, we evaluate the spectral and total radiative heat flux between Au/SiC interfaces within a fluctuational electrodynamics framework. We show that annealing-induced changes in the low-frequency dielectric losses of Au significantly alter evanescent electromagnetic coupling at the interface, leading to enhancements of up to ~40% in the total near-field radiative heat transfer at separations of tens of nanometers. Mode-resolved analysis reveals that this enhancement originates from strengthened coupling of overdamped plasmonic surface modes, which are highly sensitive to thin-film processing and interfacial microstructure. These results demonstrate that standard thermal annealing provides a practical route for tuning interfacial radiative heat transfer in metallic thin-film systems without modifying material composition or geometry, offering guidance for the design and interpretation of nanoscale thermal and plasmonic interfaces.
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Materials Science
SpectraFormer: an Attention-Based Raman Unmixing Tool for Accessing the Graphene Buffer-Layer Signature on SiC
Dmitriy Poteryayev, Pietro Novelli, Annalisa Coriolano et al. (+7 more)
Raman spectroscopy is a key tool for
graphene characterization, yet its application to
graphene grown on silicon carbide (SiC) is strongly limited by the intense and variable second-order Raman response of the substrate. This limitation is critical for buffer layer
graphene, a semiconducting interfacial phase, whose vibrational signatures are overlapped with the SiC background and challenging to be reliably accessed using conventional reference-based subtraction, due to strong spatial and experimental variability of the substrate signal. Here we present SpectraFormer, a
transformer-based deep learning model that reconstructs the SiC Raman substrate contribution directly from post-growth partially masked spectroscopic data without relying on explicit reference measurements. By learning global correlations across the entire Raman shift range, the model captures the statistical structure of the SiC background and enables accurate reconstruction of its contribution in mixed spectra. Subtraction of the reconstructed substrate signal reveals weak vibrational features associated with ZLG that are inaccessible through conventional analysis methods. The extracted spectra are validated by ab initio vibrational calculations, allowing assignment of the resolved features to specific modes and confirming their physical consistency. By leveraging a state-of-the-art
attention-based deep learning architecture, this approach establishes a robust, reference-free framework for Raman analysis of
graphene on SiC and provides a foundation, compatible with real-time data acquisition, to its integration into automated, closed-loop AI-assisted growth optimization.
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All authors Dmitriy Poteryayev, Pietro Novelli, Annalisa Coriolano, Riccardo Dettori, Valentina Tozzini, Fabio Beltram, Massimiliano Pontil, Antonio Rossi, Stiven Forti, Camilla Coletti
Materials Science
Oxygen in diamond: thermal stability of ST1 spin centres and creation of oxygen-pair complexes
Paul Neugebauer, Xinxi Huang, Chloe Newsom et al. (+11 more)
Little is known about oxygen-related defects in diamond. Recently, the promising room-temperature
spin centre named ST1 was identified as an oxygen centre, but of still unknown atomic structure and thermal stability. In this work, we report on the optically active oxygen-related centres and the conditions for their formation, using ion implantation of oxygen in various conditions of depth and fluence. More specifically, we establish the temperature formation/stability range of the ST1 centre, which has a maximum at about 1100{\deg}C and is narrower than for NV centres. In these conditions, optically detected
magnetic resonance (ODMR) on small ST1 ensembles was measured with a
spin readout contrast of > 20% at 300K. In cathodoluminescence, the 535 nm ST1 peak is not observed. Besides, a broad peak centred at 460 nm is measured for implantation of O$_2$ molecular ions. For an annealing temperature of 1500{\deg}C, a different centre is formed (with ZPL at 584.5 nm) with an intensity increasing with a power law 1.5 < p < 1.9 dependence from the implantation fluence. This suggests that this centre contains two oxygen atoms. Besides, a new spectral feature associated to an intrinsic defect was also observed, with four prominent lines (especially at 594nm). Finally, the thermal formation and stability of oxygen centres in diamond presented here are important for the identification of the atomic structure of defects such as the ST1 and possible O$_2$V$_x$ complex by means of ab initio calculations. Indeed, the formation energies and charge states of defect centres are easier to compute than the full energy level scheme, which to date still remains unsuccessful regarding the ST1 centre.
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All authors Paul Neugebauer, Xinxi Huang, Chloe Newsom, Christophe Arnold, Hjørdis Martelock, Séverine Diziain, Edoardo Monnetti, Jocelyn Achard, Tobias Lühmann, Paolo Olivero, Jan Meijer, Julien Barjon, Alexandre Tallaire, Sébastien Pezzagna
Materials Science
Interactive Analysis of Static, Dynamic, and Crystalline SDTrimSP Simulations: Application to Nitrogen Ion Implantation into Vanadium
Miroslav Lebeda, Jan Drahokoupil, Vojtěch Smola et al. (+1 more)
SDTrimSP is a widely used Monte Carlo simulation code based on the Binary Collision Approximation (BCA) for modeling ion implantation and ion-solid interaction processes. While an established graphical user interface (GUI) exists for simulation setup and execution, efficient post-processing, comparison of multiple simulations, and preparation of specific input file parameters remain limited. In this work, we present a web-based interface (sdtrimsp.streamlit.app) that complements existing SDTrimSP tools by focusing on interactive visualization and analysis of depth distribution profiles. The platform enables direct upload and comparison of static and fluence-dependent dynamic profiles, supports unit conversion, and provides an integrated calculator for determining the adjustable atomic density parameter of implanted ions required in dynamic simulations. In addition, the interface offers automated conversion of standard crystallographic file formats into the SDTrimSP-specific
crystal structure input format for simulations into crystalline targets. The capabilities of the interface are demonstrated for nitrogen ion implantation into vanadium, including amorphous static and dynamic simulations and static crystalline simulations for different surface orientations. The results illustrate fluence-dependent saturation effects as well as orientation-dependent ion channeling behavior. Overall, the presented web-based tool provides a convenient and flexible extension to existing SDTrimSP workflows.
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All authors Miroslav Lebeda, Jan Drahokoupil, Vojtěch Smola, Petr Vlčák
Materials Science
A Comprehensive Computational Framework for Materials Design, Ab Initio Modeling, and Molecular Docking
Md Rakibul Karim Akanda and Michael P. Richard
To facilitate rational molecular and materials design, this research proposes an integrated computational framework that combines
stochastic simulation, ab initio
quantum chemistry, and molecular docking. The suggested workflow allows systematic investigation of structural stability, binding affinity, and electronic properties across biological and materials science domains by utilizing complementary tools like Avogadro for molecular construction and visualization, AutoDock for docking and interaction analysis, and ORCA for high-level electronic structure computations. Uncertainty, configurational sampling, and optimization in high-dimensional chemical spaces are addressed by combining Monte Carlo-based and annealing-inspired techniques. The work shows how materials science ideas such as
polymer design, thin films, crystalline
lattices, and bioelectronic systems can be applied to drug development. On-device, open-source computational methods are viable, scalable, and economical, as demonstrated by comparative platform analysis. All things considered, the findings highlight the need of an integrated, repeatable computational pipeline for speeding up de novo molecule assembly and materials architecture while lowering experimental risk and expense.
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Materials Science · Cross-listed from quant-ph
Surface Optimization of Superconducting Aluminum Resonators for Robust Quantum Device Fabrication
Simon J. K. Lang, Ignaz Eisele, Alwin Maiwald et al. (+8 more)
Aluminum (Al) remains the central material for superconducting
qubits, and considerable effort has been devoted to optimizing its deposition and patterning for
quantum devices. However, post-processing strategies focused on
oxide removal of niobium (Nb) and tantalum (Ta) -based resonators using buffered
oxide etch (BOE), which can not be used for Al. This challenge becomes particularly relevant for industry-scale fabrication with multi-chip bonding, where delays between sample preparation and cooldown require surface treatments that preserve low dielectric loss during extended exposure to ambient conditions. In this work, we investigate surface modification approaches for Al resonators subjected to a 24-hour delay prior to cryogenic measurement. Passivation using self-limiting oxygen and fluorine chemistries was evaluated utilizing different
plasma processes. Remote oxygen
plasma treatment reduced dielectric losses, in contrast to direct oxygen
plasma. A fluorine-based
plasma process was developed that passivated the Al surface for subsequent BOE treatment. However, the fluorine content in the surface resulted in higher loss, identifying fluorine as an unsuitable passivation material for Al resonators. Above all, selective
oxide removal using HF (hydrogen fluoride) vapor and phosphoric acid yielded median dielectric losses as low as $\tilde{\delta}_\mathrm{LP} = 5.7 \times 10^{-7}$ ($Q_\mathrm{LP} \approx 1.7\,\mathrm{M}$) with $\tilde{\delta}_\mathrm{TLS} = 3.6 \times 10^{-7}$ ($Q_\mathrm{TLS} \approx 2.8\,\mathrm{M}$) in the single
photon regime. Selective
oxide removal provides a promising pathway for robust Al-based
qubit fabrication, as it preserves low dielectric losses for a 24-hour delay before cooldown.
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All authors Simon J. K. Lang, Ignaz Eisele, Alwin Maiwald, Emir Music, Luis Schwarzenbach, Carla Moran-Guizan, Johannes Weber, Daniela Zahn, Thomas Mayer, Rui N. Pereira, Christoph Kutter
Materials Science
Magnetoluminescence of ZnMnSe/BeMnTe heterostructures with type-II band alignment at millikelvin temperatures
Dennis Kudlacik, Linda Kersting, Nataliia E. Kopteva et al. (+3 more)
The magneto-optical properties of a Zn$_{0.99}$Mn$_{0.01}$Se/Be$_{0.93}$Mn$_{0.07} $Te diluted
magnetic semiconductor heterostructure with type-II band
alignment are investigated at cryogenic temperatures down to 16 mK. The temperature of the Mn
spin system, which at the lowest possible
laser power reaches 270 mK, is evaluated from the
giant Zeeman splitting of the direct
exciton in the Zn$_{0.99}$Mn$_{0.01}$Se layers subject to an external
magnetic field. The degree of circular polarization of the direct and indirect optical transitions, induced by the
magnetic field, is a sensitive indicator for the
laser heating of the Mn
spin system. Evidence of
spin glass formation in the Mn
spin system of the Be$_{0.93}$Mn$_{0.07}$Te layers with the critical temperature of $T_{SG}=400$ mK is found.
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All authors Dennis Kudlacik, Linda Kersting, Nataliia E. Kopteva, Mladen Kotur, Dmitri R. Yakovlev, Manfred Bayer
Materials Science
Robust chirality memory in carbon nanotubes growing under modulated and evolving environments
K. Otsuka, R. Fujiwara and S. Maruyama
Controlling the chirality and yield of carbon nanotubes is essential for their diverse applications from macroscopic composites to nanoelectronics. Floating-catalyst chemical vapor deposition is widely employed as a scalable synthesis route, where catalysts inevitably traverse spatially varying environments. However, prevailing interpretations of nanotube growth largely rely on ensemble monitoring or static, post-growth snapshots. Here, we combine digital isotope labeling with programmed temperature modulation to reconstruct the dynamic growth histories of supported individual nanotubes. Growth rates exhibit hysteresis and extraordinary sensitivity to temperature changes, indicating irreversible catalyst coarsening; nevertheless, the nanotube chirality remains robustly preserved across lengths exceeding 300 um. This sharp contrast between kinetic adaptability and structural
memory in nanotube growth indicates that chirality control can be established at the nucleation stage, while allowing independent optimization of subsequent elongation. Our findings further call for a re-examination of static interpretations of diameter-determination mechanisms derived from post-growth snapshots.
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Materials Science
Material exploration through active learning – METAL
Joakim Brorsson, Henrik Klein Moberg, Joel Hildingsson et al. (+3 more)
The discovery and design of new materials are paramount in the development of green technologies. High
entropy oxides represent one such group that has only been tentatively explored, mainly due to the inherent problem of navigating vast compositional spaces. Thanks to the emergence of machine learning, however, suitable tools are now readily available. Here, the task of finding oxygen carriers for chemical looping processes has been tackled by leveraging active learning-based strategies combined with first-principles calculations. High efficiency and efficacy have, moreover, been achieved by exploiting the power of recently developed machine learning interatomic potentials. Firstly, the proposed approaches were validated based on an established computational framework for identifying high
entropy perovskites that can be used in chemical looping air separation and dry reforming. Chief among the insights thus gained was the identification of the best performing strategies, in the form of greedy or Thompson-based sampling based on uncertainty estimates obtained from Gaussian processes. Building on this newfound knowledge, the concept was applied to a more complex problem, namely the discovery of high
entropy oxygen carriers for chemical looping oxygen uncoupling. This resulted in both qualitative as well as quantitative outcomes, including lists of specific materials with high oxygen transfer capacities and configurational
entropies. Specifically, the best candidates were based on the known oxygen carrier CaMnO3 but also contained a variety of additional species, of which some, e.g., Ti; Co; Cu; and Ti, were expected while others were not, e.g., Y and Sm. The results suggest that adopting active learning approaches is critical in materials discovery, given that these methods are already shifting research practice and soon will be the norm.
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All authors Joakim Brorsson, Henrik Klein Moberg, Joel Hildingsson, Jonatan Gastaldi, Tobias Mattisson, Anders Hellman
Materials Science
Cleavage toughness of single crystals
Faming Gao
Griffith thermodynamic energy balance is employed to analyze cleavage phenomenon from atomic level. Results show that the cleavage toughness, the strain energy release rate, and the surface energy can be defined by the bond strength (the appropriate elastic modulus ) and the bond density. Such simple definition of fracture parameters is different from Irwin ones. This appropriate elastic modulus of single
crystals is obtained using the complex variable function method. The calculated results of cleavage toughness and surface energy of typical ionic and covalent
crystals by the present formulae are in excellent agreement with the experimental values. It demonstrates that our method offers a concise tool for predicting the cleavage toughness, the energy release rate and the surface energy of
crystal cleavage planes.
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Materials Science
Ultrafast laser-driven topological phase patterning
Jianyu Wu, Arthur Niedermayr, Gaolong Cao et al. (+2 more)
Microscopic and dynamic control over
quantum states is essential for bridging fundamental studies of material properties to device function. Realizing such control at combined high spatial resolution and ultrafast temporal precision remains a major challenge. Here, we demonstrate femtosecond
laser-driven patterning of topological
quantum states in the Weyl semimetal WTe2. By engineering the excitation field into a transient optical grating, we spatially selectively and reversibly drive phase transitions between the topological Td and topologically trivial 1T* phases. Using ultrafast transmission electron microscopy, we directly visualize the formation of a periodic Td/1T*
heterostructure, observe the propagation of a phase front, and analyze nanoscale confinement of coherently excited optical
phonon modes. Our findings establish a platform for all-optical, spatially programmable, and reconfigurable control of
quantum states, paving the way for optically addressable topological devices.
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All authors Jianyu Wu, Arthur Niedermayr, Gaolong Cao, Oscar Grånäs, Jonas Weissenrieder
Materials Science
High-pressure synthesis of quantum magnet M-YbTaO4 with a stretched diamond lattice
Nicola D. Kelly, Xuan Liang, Siân E. Dutton et al. (+2 more)
We report bulk
magnetic properties of ytterbium tantalate in its monoclinic fergusonite modification, M-YbTaO4. The
spin-1/2 Yb3+ ions in this phase are arranged on a geometrically frustrated "stretched diamond"
lattice. M-YbTaO4 cannot be prepared at ambient pressure and was instead prepared in a belt-type apparatus at 6 GPa and 1800 C. Susceptibility and specific heat data show no long-range ordering down to 1.8 K and are consistent with a Jeff = 1/2 Kramers doublet which splits in an applied field. Furthermore, under high-pressure synthesis the entire solid solution YbNbxTa1-xO4 (0 < x < 1) can be stabilised in the M phase, in contrast to ambient-pressure synthesis which favours the competing M' phase for Ta-rich compositions. Subsequent annealing of the Nb-Ta mixed samples resulted in colour changes, suggesting oxygen deficiency in some of the as-prepared high pressure samples. There was little variation in the bulk
magnetic properties upon varying either the Nb/Ta ratio or the annealing conditions.
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All authors Nicola D. Kelly, Xuan Liang, Siân E. Dutton, Kazunari Yamaura, Yoshihiro Tsujimoto
Materials Science
Physically Consistent Machine Learning for Melting Temperature Prediction of Refractory High-Entropy Alloys
Mohd Hasnain
Predicting the melting temperature (Tm) of multi-component and high-
entropy alloys (HEAs) is critical for high-temperature applications but computationally expensive using traditional CALPHAD or DFT methods. In this work, we develop a gradient-boosted decision tree (XGBoost) model to predict Tm for complex
alloys based on elemental properties. To ensure physical consistency, we address the issue of data leakage by excluding temperature-dependent thermodynamic descriptors (such as Gibbs free energy of mixing) and instead rely on physically motivated elemental features. The optimized model achieves a coefficient of determination (R2) of 0.948 and a Mean Squared Error (MSE) of 9928 which is about 5% relative error for HEAs on a validation set of approximately 1300 compositions. Crucially, we validate the model using the Valence Electron Concentration (VEC) rule. Without explicit constraints during training, the model successfully captures the known stability transition between BCC and FCC phases at a VEC of approximately 6.87. These results demonstrate that data-driven models, when properly feature-engineered, can capture fundamental metallurgical principles for rapid
alloy screening.
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Materials Science · Cross-listed from physics.optics
DNA-Origami-Assembled Rhodium Nanoantennas for Deep-UV Label-Free Single-Protein Detection
Nicco Corduri, Malavika Kayyil Veedu, Yifan Yu et al. (+6 more)
Nanoparticles of plasmonic metals have significantly to the development of spectroscopic techniques, enabling strong confinement of electromagnetic fields at the nanoscale and corresponding signal amplification. However, to date, plasmonic applications have been limited mainly to the visible and near-infrared range, as materials supporting ultraviolet resonances typically exhibit poor chemical stability and lack robust surface functionalisation methods. In this work, we address these limitations by introducing a fully programmable approach to UV plasmonics based on rhodium nanocube dimers assembled using DNA origami templates. We have developed a reliable ligand exchange strategy that allows the functionalisation of rhodium nanocubes with DNA while maintaining their colloidal stability. These DNA-modified nanocubes act as modular building blocks that can be assembled into dimers with 69% efficiency and an average gap size of 10 nm. The DNA origami design also allows for the deterministic placement of a single streptavidin
protein in the plasmonic gap, unlike previous methods based on
stochastic diffusion. Experiments with single-molecule autofluorescence in UV, supported by numerical simulations, show an increase in brightness of up to 22, a reduction in fluorescence lifetime, and a more than tenfold increase in the total number of detected
photons. By creating a robust and versatile platform for the production of UV-resonant plasmonic nanoantennas, this work extends the functionality of plasmonics to the deep UV spectrum and opens up new possibilities for labelling-free single-
protein spectroscopy.
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All authors Nicco Corduri, Malavika Kayyil Veedu, Yifan Yu, Yanqiu Zou, Jie Liu, Denis Garoli, Guillermo P. Acuna, Jérôme Wenger, Karol Kołątaj
Materials Science · Cross-listed from cond-mat.mes-hall
Electric-current control of anomalous Hall effect
Jianping Guo, Gusthavo M. S. Brizolla, Peng Rao et al. (+10 more)
We demonstrate robust and reversible electric-current control of the anomalous
Hall effect (AHE) in a two-dimensional WTe2/Fe3GeTe2 (FGT) stack. Applying a current through Td-WTe2 leads to a
giant modulation of the AHE of the adjacent FGT layer, with the relative change of the AHE conductivity exceeding 180%. Control experiments show that i) the observed effect is absent in pure FGT, ii) the modulation weakens in thicker FGT films, confirming its interfacial origin, and iii) the modulation peaks for
bilayer WTe2, indicating that the Berry-
curvature dipole (BCD) plays the dominant role in the modulation. We propose that the charge current I generates an out-of-plane magnetization Mz via BCD in WTe2 and Mz modifies the exchange splitting of FGT via the inverse
magnetic proximity effect, thereby altering its Berry
curvature and nontrivially influencing the AHE. The demonstrated method of AHE control offers new possibilities for magnetism control, i.e., for the study of AHE-transistors as well as electric-current control of
quantum magnets, especially
magnetic insulators.
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All authors Jianping Guo, Gusthavo M. S. Brizolla, Peng Rao, Jian Shao, X. H. Huang, Thomas N. G. Meier, Tailai Xu, Peirui Ji, Jonathan Finley, Jaroslav Fabian, Johannes Knolle, Christian Back, Lin Chen
Materials Science
Impact of MAPbI3 Phase Transitions on Solar Cell Performance
Ph Baranek, J P Connolly, A Gissler et al. (+3 more)
This paper presents a first step toward a pragmatic phenomenological multiscale approach to evaluate perovskite
solar cell performance which determines material properties at the atomistic scale with first-principles calculations, and applies them in macro-scale device models. This work focuses on the MAPbI3 (MA = CH3NH3) perovskite and how its phase transitions impact on its optical, electronic, and structural properties which are investigated at the first-principles level. The obtained data are coupled to a numerical drift-
diffusion device model enabling evaluation of the performance of corresponding single junction devices. The first-principles simulation applies a hybrid exchange-correlation functional adapted to the studied family of compounds. Validation by available experimental data is presented from materials properties to device performance, justifying the use of the approach for predictive evaluation of existing and novel perovskites. The coupling between atomistic and device models is described in terms of a framework for exchange of optical and electronic parameters between the two scales. The obtained results are systematically discussed in terms of first-principles levels of approximation performances.
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All authors Ph Baranek, J P Connolly, A Gissler, Ph Schulz, M Rérat, R Dovesi
Materials Science · Cross-listed from astro-ph.EP
Protonic thermoelectric effect of Superionic H$_2$O and magnetic field generation in Uranus and Neptune
Daohong Liu, Wei Zhang, Yu He et al. (+3 more)
The origin of the anomalous
magnetic fields of Uranus and Neptune, with significant tilts and multi-dipole configurations, is central to understanding the internal structure and
evolution of the ice
giants. Recent investigations confirmed that superionic H$_2$O ice is thermodynamically stable and constitutes the dominant H$_2$O phase within their icy mantles. Here, we use deep learning and ab initio molecular dynamics to investigate the thermal and protonic transport properties of superionic H$_2$O ice. We demonstrate that superionic H$_2$O ice exhibits a pronounced protonic thermoelectric effect, with a maximum Seebeck coefficient that can reach $\sim 620$ $\mu$V K$^{-1}$ within the interior of Uranus, whereas Neptune's is lower, within the range of 570-585 $\mu$V K$^{-1}$. Consequently, the temperature gradients in the icy mantles can induce
proton migration, thereby driving
magnetic field generation. Based on this mechanism, and within a dipolar approximation that captures the mean field, the disparities in mean dipolar
magnetic field strength between Uranus and Neptune can be explained exclusively by their differing internal temperature gradients, and the predicted mean field strengths are comparable to those observed by Voyager 2.
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All authors Daohong Liu, Wei Zhang, Yu He, Xinzhuan Guo, Chuanyu Zhang, Yang Sun
Materials Science · Cross-listed from cond-mat.mes-hall
Comments on the formula to extract current-induced torques from the harmonic Hall voltage measurements
Yong-Chang Lau, Yukihiro Marui, Zhendong Chi et al. (+2 more)
We examine the formulas commonly used to estimate current-induced
spin-orbit torques from harmonic
Hall voltage measurements. In particular, we focus on the factor of two discrepancy among expressions employed to fit harmonic
Hall signals measured under an in-plane rotating
magnetic field. By explicitly deriving the relevant relations, we clarify the origin of this discrepancy and present the correct form of the fitting formula. We further discuss the determination of the sign of the field-like torque from harmonic
Hall voltage measurements, which depends on the assumed form of the current-induced torques.
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All authors Yong-Chang Lau, Yukihiro Marui, Zhendong Chi, Masashi Kawaguchi, Masamitsu Hayashi
Materials Science · Cross-listed from cond-mat.mes-hall
Unitary Transformation of Two-Dimensional Spin-Orbit Coupled Models
Manish Kumar Mohanta
The Rashba, Dresselhaus, and Weyl
Hamiltonians form a foundational framework for modeling
spin-orbit interactions across condensed matter systems. Although they describe distinct material classes and produce seemingly different
spin textures, they are conventionally treated as separate, unrelated theoretical frameworks. Here, this work demonstrates that the linear 2D Rashba and Weyl models are connected by a specific
unitary transformation that maps one
Hamiltonian exactly onto the other. The same
unitary can be applied to map the linear Dresselhaus-1 model onto the Dresselhaus-2 models and vice versa. Such hidden correspondence establishes a unified theoretical foundation for
spin-orbit interactions, deepening our conceptual understanding of
spin-orbit coupling and opening new avenues for exploring complex
spin textures. To illustrate the application, this work introduces a unique, improved, and more realistic model
Hamiltonian H_MKM combining all known foundational spintronic models, where the stringent condition of equal
spin-orbit coupling strength of Rashba and Dresselhaus may not be required to observe persistent
spin texture under MKM transformation.
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Materials Science
Structural heterogeneity-induced enhancement of transverse magneto-thermoelectric conversion revealed by thermoelectric imaging in functionally graded materials
Sang J. Park, Ravi Gautam, Takashi Yagi et al. (+3 more)
Functionally graded materials (FGMs) exhibit continuous property variations that enable unique functionalities and provide efficient platforms for systematic property optimization. Here, we report the fabrication of FGMs with graded structural heterogeneity by annealing an amorphous metal under a one-dimensional temperature gradient. Using lock-in thermography (LIT), we spatially mapped transverse thermoelectric conversion with high spatial and temperature resolution. A pronounced non-monotonic response was observed, with the maximum anomalous Ettingshausen effect, transverse charge-to-heat conversion in
magnetic materials, appearing in the atomic-heterogeneity regime well before crystallization. This enhancement was not captured by conventional structural or longitudinal transport measurements, highlighting the exceptional sensitivity of transverse thermoelectric phenomena to subtle structural heterogeneity. Structural analyses using scanning transmission electron microscopy and atom probe
tomography revealed Fe-based crystalline
alloys and Cu nanoclusters embedded in the amorphous
matrix, whose heterogeneity accounts for the enhanced response. These findings establish temperature-gradient-annealed FGMs, combined with LIT, as a powerful methodology for probing structural-heterogeneity-driven transverse electron transport and designing high-performance flexible materials.
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All authors Sang J. Park, Ravi Gautam, Takashi Yagi, Rajkumar Modak, Hossein Sepehri-Amin, Ken-ichi Uchida
Materials Science · Cross-listed from physics.ins-det
muT2-NMR: Micro-Scale Correlation Relaxometry for in-situ High-Pressure Nuclear Magnetic Resonance
Thomas Meier, Meng Yang, Yishan Zhou et al. (+6 more)
Over the last decade, frequency-domain in-situ high-pressure
nuclear magnetic resonance (NMR) spectroscopy in diamond anvil
cells (DACs) has been employed as a structural and electronic probe of condensed matter systems at pressures well into the megabar range. However, extensive
spin interactions and sample heterogeneities under pressure often lead to significant spectral overlap, inhibiting independent observation of chemically similar
spin sub-species in the same sample. In this work, we introduce a time-domain relaxometry framework specifically suited for DAC experiments, named muT2-NMR. Experimental flexibility and operational robustness are benchmarked on three hydrogen-rich molecular solids at pressures up to 72 GPa. We demonstrate that muT2-NMR can resolve individual molecular subunits in relaxation space, paving the way for novel high-pressure, high-resolution NMR applications in molecular solids.
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All authors Thomas Meier, Meng Yang, Yishan Zhou, Yunhua Fu, Rui Zhang, Ziliang Wang, Tianyao Zheng, Rajesh Jana, Takeshi Nakagawa
Materials Science
Ir3Ge20: A 3n-Connected Cloverleaf-Shaped Supercluster
Xue Wu, Wen-Shuai Dai, Lulu Li et al. (+4 more)
Group 14 Zintl clusters are promising molecular building blocks for nanoscale architecture. Endohedral variants, which encapsulate d/f-block metals within p-block semimetal cages, provide insights into intermetallic bonding and compound formation. In this study, experimental photoelectron spectroscopy and first-principles calculations were used to investigate the Ir-doped germanium cluster species. A new C2v symmetric building block, IrGe12, was identified, serving as the basis for designing the supercluster Ir3Ge20 with a cloverleaf-shaped, D3h symmetric architecture. This structure consists of three interconnected aromatic IrGe12 units linked by Ge-Ge sigma bonds, forming shielding cones. Ir3Ge20 follows the 5n rule with 100 valence electrons, featuring a core-Ir3 unit with a d10 closed-shell configuration sharing electrons with the Ge20 skeleton. The stability, chemical bonding, and aromaticity of Ir3Ge20 were confirmed, demonstrating a novel approach to precise atom manipulation in cluster-based materials and devices.
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All authors Xue Wu, Wen-Shuai Dai, Lulu Li, Fangying Hao, Hong-Guang Xu, Wei-Jun Zheng, Jijun Zhao
Materials Science · Cross-listed from cond-mat.mes-hall
Wigner solid or Anderson solid – 2D electrons in strong disorder
Aryaman Babbar, Zi-Jian Li and Sankar Das Sarma
Critically analyzing recent STM and transport experiments [Z. Ge, et al, arXiv:2510.12009] on 2D electron systems in the presence of random quenched
impurities, we argue that the resulting low-density putative "solid" phase reported experimentally is better described as an Anderson solid with the carriers randomly spatially localized by
impurities than as a Wigner solid where the carriers form a
crystal due to an interaction-induced spontaneous breaking of the translational
symmetry. In strongly disordered systems, the resulting solid is amorphous, which is adiabatically connected to the infinite disorder Anderson fixed point rather than the zero disorder Wigner
crystal fixed point.
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