Materials Science · Cross-listed from cs.LG
Machine learning model for predicting surface wettability in laser-textured metal alloys
Mohammad Mohammadzadeh Sanandaji, Danial Ebrahimzadeh, Mohammad Ikram Haider et al. (+3 more)
Surface wettability, governed by both topography and chemistry, plays a critical role in applications such as heat transfer, lubrication, microfluidics, and surface coatings. In this study, we present a machine learning (ML) framework capable of accurately predicting the wettability of
laser-textured metal
alloys using experimentally derived morphological and chemical features. Superhydrophilic and superhydrophobic surfaces were fabricated on AA6061 and AISI 4130
alloys via nanosecond
laser texturing followed by chemical immersion treatments. Surface morphology was quantified using the Laws texture energy method and profilometry, while surface chemistry was characterized through X-ray photoelectron spectroscopy (XPS), extracting features such as functional group polarity, molecular volume, and peak area fraction. These features were used to train an ensemble neural network model incorporating residual connections, batch normalization, and dropout regularization. The model achieved high predictive accuracy (R2 = 0.942, RMSE = 13.896), outperforming previous approaches. Feature importance analysis revealed that surface chemistry had the strongest influence on contact angle prediction, with topographical features also contributing significantly. This work demonstrates the potential of artificial intelligence to model and predict wetting behavior by capturing the complex interplay of surface characteristics, offering a data-driven pathway for designing tailored functional surfaces.
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All authors Mohammad Mohammadzadeh Sanandaji, Danial Ebrahimzadeh, Mohammad Ikram Haider, Yaser Mike Banad, Aleksandar Poleksic, Hongtao Ding
Materials Science · Cross-listed from cond-mat.mes-hall
Combining laser ablation and Sol-Gel techniques for the synthesis of nanostructured organic-inorganic matrices
E. Haro-Poniatowski, C. A. Guarín, L. G. Mendoza-Luna et al. (+11 more)
In this work we report a new and simple method that combines the pulsed
laser ablation in
liquids (PLAL) and the Sol-Gel techniques to obtain nanocomposite glasses and gelatins. Gold nanoparticles (Au-NPs) are generated by PLAL using the corresponding target. The target is submerged in a transparent
liquid solution made previously with tetraetylorthosilicate (TEOS) adding diluted hydrochloric acid as catalyzer. In the case of gelatins commercial gelatin and tap water are used. The
laser source is a Nd:YAG
laser emitting at 1064 nm, with an energy of 100 mJ and 8 ns pulse duration at 10 Hz repetition rate focused on the target in a 2 mm diameter
laser spot. The ablation time is 10 min for the glasses and gelatins. The Au-NPs are uniformly dispersed in the solution. After the ablation process the gels are sealed and stored at room temperature for several days. The samples are characterized by UV-Vis spectroscopy, HRTEM, ellipsometry and AFM microscopy, these measurements reveal optical transparency and a refractive index near 1.45 for the pure glass, whereas a colorful aspect, a refractive index of 1.42, and a small surface roughness of 1.92 nm for the glass containing Au-NPs. In the case of gelatins self-sustained flexible films are obtained.
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All authors E. Haro-Poniatowski, C. A. Guarín, L. G. Mendoza-Luna, L. Escobar-Alarcón, J. L. Hernández-Pozos, L. I. Vera-Robles, P. Castillo, F. Cabello, J. Toudert, F. Chacón-Sánchez, M. García-Pardo, R. Serna, J. Gonzalo, J. Solís
Materials Science · Cross-listed from physics.app-ph
Supercritical Snapping and Controlled Launching via Dual Latch Gels
Xiaona M. Xu, Nolan A. Miller, Gregory M. Grason et al. (+1 more)
Natural organisms have evolved integrated Latch-Mediated Spring Actuation systems (LaMSA) that consist of multiple latches and springs to enhance power output and adapt to diverse environmental conditions. Similar designs are appealing yet largely unexplored in engineered materials due to the complexity of integrating multiple components into a single material platform. Here, we report a dual-latched magneto-elastic shell device capable of selectively activating the latches to regulate snapping pathways and energy output based on specific actuation requirements. Differential deswelling across the thickness acts as the motor to load the elastic energy into the shell, which is then released via the snap-through instability once the loading reaches the critical threshold, constituting an intrinsic mechanical latch. Activation of the external
magnetic latch delays snapping onset beyond the threshold of the intrinsic latch, leading to a power-amplified supercritical snap-through instability as well as a bifurcation instability. The combined function of both latches allows for flexible control over energy storage and release. Additionally, this integrated LaMSA system possesses an untethered anchoring mechanism, enabling the device to launch in arbitrary directions from the substrate, driven by the energy released during snapping. We envision that the design principles of dual-latched LaMSA systems will create opportunities for power-dense actuation in engineered materials and robotic devices.
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All authors Xiaona M. Xu, Nolan A. Miller, Gregory M. Grason, Alfred J. Crosby
Materials Science · Cross-listed from physics.ins-det
Charge-Carrier Mobility in Diamond: Review, Data Compilation, and Modelling for Detector Simulations
Faiz Rahman Ishaqzai, Muhammed Deniz, Kevin Kröninger et al. (+1 more)
Reported electron and hole mobilities and saturation velocities in diamond vary widely across the literature. We provide a consolidated review of first-principles predicted and experimentally measured mobility and saturation-velocity values in diamond, alongside a focused assessment of the semi-empirical mobility models used to extract low-field mobilities and high-field saturation velocities. We attribute the dispersion primarily to (i) the electric-field window probed in TCT measurements, (ii) the choice of mobility model, and (iii) the excitation source ($\alpha$,
laser, or electron). Using an aggregated literature
dataset, we
benchmark the Trofimenkoff and Caughey–Thomas parameterizations together with a new piecewise model for both conduction- and valence-band transport. For electrons, the piecewise model provides the best global description over a broad electric-field range. It can be interpreted as the room-temperature limit of a more general superposition framework that explicitly incorporates intervalley repopulation in the conduction band. For holes, the Caughey–Thomas model remains the statistically preferred description, consistent with the absence of a repopulation signature in the accessible data. Furthermore, we demonstrate a systematic source dependence ($\alpha$ versus
laser) and quantify its impact on fitted mobility and saturation-velocity values. We provide temperature scalings over narrow intervals around room temperature to support Jacoboni–Canali-type parameterization for diamond. Together, these results reconcile much of the apparent inconsistency in the literature and offer guidance for model selection, experimental design, and device-level simulation of charge transport in intrinsic diamond.
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All authors Faiz Rahman Ishaqzai, Muhammed Deniz, Kevin Kröninger, Jens Weingarten
Materials Science · Cross-listed from cond-mat.mes-hall
Lambert W Function Framework for Graphene Nanoribbon Quantum Sensing: Theory, Verification, and Multi-Modal Applications
F. A. Chishtie, K. Roberts, N. Jisrawi et al. (+3 more)
We establish a rigorous mathematical framework connecting
graphene nanoribbon
quantum sensing to the Lambert W function through the finite square well (FSW) analogy. The Lambert W function, defined as the inverse of $f(W)=We^W$, provides exact analytical solutions to transcendental equations governing
quantum confinement. Operating near the branch point singularity at $z=-1/e$ yields sensitivity enhancement factors scaling as $(z-z_c)^{-1/2}$, achieving 35-fold enhancement when the operating point lies within $\delta=0.001$ of the branch point. Comprehensive numerical verification confirms: (i) all seven bound states for strength parameter $R=10$ satisfy the constraint $u^2+v^2=R^2$ to machine precision; (ii) the theoretical band gap formula $E_g=2\pi\hbar v_F/(3W)$ is analytically equivalent to the independently determined empirical relation $E_g=1.38/W$~eV$\cdot$nm, establishing the validity of the FSW-GNR analogy; (iii) a universal sensitivity factorization $S_X = \mathcal{G}_k \cdot \eta_{\rm enh} \cdot \mathcal{P}_X$ applies across biomedical (SARS-CoV-2, inflammatory markers, cancer biomarkers), environmental (CO$_2$, CH$_4$, NO$_2$, N$_2$O, H$_2$O), and physical (strain,
magnetic field, temperature) sensing modalities. This unified framework provides analytically predictable design principles for next-generation
graphene quantum sensors. The framework is analytic and predictive rather than microscopic or experimental: band-structure and adsorption parameters are taken as inputs from tight-binding, first-principles, and experimental sources, and the framework returns closed-form sensitivity and design relations built upon them. Reported detection limits are labelled throughout as either literature-demonstrated device values or values predicted by the present framework.
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All authors F. A. Chishtie, K. Roberts, N. Jisrawi, S. R. Valluri, A. Soni, P. C. Deshmukh
Materials Science · Cross-listed from cond-mat.mes-hall
Emergent electric field induced by dissipative sliding dynamics of domain walls in a Weyl magnet
Rinsuke Yamada, Daichi Kurebayashi, Yukako Fujishiro et al. (+10 more)
The dynamic motion of topological defects in magnets induces an emergent electric field, as exemplified by the continuous flow of skyrmion
vortices. However, the electrodynamics underlying this emergent field remains poorly understood. In this context,
magnetic domain walls - one dimensional topological defects with two collective modes, sliding and
spin tilt - offer a promising platform for exploration. Here, we demonstrate that the dissipative motion of domain walls under oscillatory current excitation generates an emergent electric field. We image domain patterns and quantify domain wall length under applied
magnetic fields in mesoscopic devices based on the
magnetic Weyl semimetal NdAlSi. These devices exhibit exceptionally strong domain wall scattering and a pronounced emergent electric field, observed in the imaginary component of the complex impedance.
Spin dynamics simulations reveal that domain wall sliding dominates over
spin tilting, where the phase delay of the domain wall motion with respect to the driving force impacts the emergent electric field. Our findings establish domain-wall dynamics as a platform for studying emergent electromagnetic fields and motivate further investigations on the coupled motion of
magnetic solitons and conduction electrons.
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All authors Rinsuke Yamada, Daichi Kurebayashi, Yukako Fujishiro, Shun Okumura, Daisuke Nakamura, Fehmi S. Yasin, Taro Nakajima, Tomoyuki Yokouchi, Akiko Kikkawa, Yasujiro Taguchi, Yoshinori Tokura, Oleg A. Tretiakov, Max Hirschberger
Materials Science · Cross-listed from quant-ph
Quantum solver for single-impurity Anderson models with particle-hole symmetry
Mariia Karabin, Tanvir Sohail, Dmytro Bykov et al. (+8 more)
Quantum embedding methods, such as dynamical mean-field theory (DMFT), provide a powerful framework for investigating strongly correlated materials. A central computational bottleneck in DMFT is in solving the Anderson
impurity model (AIM), whose exact solution is classically intractable for large bath sizes. In this work, we develop and
benchmark a
quantum-classical hybrid solver tailored for DMFT applications, using the variational
quantum eigensolver (VQE) to prepare the ground state of the AIM with shallow
quantum circuits. The solver uses a unified ansatz framework to prepare the particle and hole excitations of the ground-state from parameter-shifted
circuits, enabling the reconstruction of the
impurity Green's function through a continued-fraction expansion. We evaluate the performance of this approach across a few bath sizes and interaction strengths under noisy, shot-limited conditions. We compare three optimization routines (COBYLA, Adam, and L-BFGS-B) in terms of convergence and fidelity, assess the benefits of estimating a
quantum-computed moment (QCM) correction to the variational energies, and
benchmark the approach by comparing the reconstructed density of states (DOS) against that obtained using a classical pipeline. Our results demonstrate the feasibility of Green's function reconstruction on near-term devices and establish practical
benchmarks for
quantum impurity solvers embedded within self-consistent DMFT loops.
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All authors Mariia Karabin, Tanvir Sohail, Dmytro Bykov, Eduardo Antonio Coello Pérez, Swarnava Ghosh, Murali Gopalakrishnan Meena, Seongmin Kim, Amir Shehata, In-Saeng Suh, Hanna Terletska, Markus Eisenbach
Materials Science
Emergence of unconventional magnetic order in strain-engineered RuO2/TiO2 superlattices
Seung Gyo Jeong, Seungjun Lee, Jin Young Oh et al. (+8 more)
The
spin ordering in RuO2 remains a highly debated topic, owing to its elusive nature, with reports ranging from a nonmagnetic ground state to signatures of unconventional
magnetic order. Here we provide the first unambiguous, and direct evidence of unconventional magnetism in epitaxial, fully strained RuO2/TiO2 superlattices on TiO2 (110) substrate grown by hybrid molecular beam epitaxy. Polarized
neutron reflectometry reveals a finite
magnetic moment localized within the compressively strained RuO2 layers, consistent with predictions obtained from first-principles calculations. Complementary density functional theory and X-ray photoemission spectroscopy show that epitaxial strain drives the Ru 4d states toward the
Fermi level, triggering a Stoner-type instability that stabilizes non-compensated
magnetic order. These unique results reveal that RuO2 exhibits unconventional
magnetic states under epitaxial strain, which are not accessible in bulk and establish strain engineering as a powerful route to uncover and control
magnetic phases in RuO2 and related
oxides.
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All authors Seung Gyo Jeong, Seungjun Lee, Jin Young Oh, Bonnie Y.X. Lin, Anand Santhosh, James M. LeBeau, Alexander J. Grutter, Woo Seok Choi, Tony Low, Valeria Lauter, Bharat Jalan
Materials Science
Incipient modulated phase in Sr$_{1-x}$Ca$_{x}$TiO$_3$
Benoît Fauqué, Daniel A. Chaney, Philippe Bourges et al. (+8 more)
Nanometer-scale modulations can spontaneously emerge in complex materials when multiple degrees of freedom interact. Here we demonstrate that ferroelectric Sr$_{1-x}$Ca$_x$TiO$_3$ lies in close proximity to an incipient structurally modulated phase. Using inelastic
neutron and X-ray scattering, we show that upon cooling, dipolar fluctuations strongly couple to and soften the $c_{44}$ transverse acoustic mode. We identify the wavevector at which this softening is maximal, thereby defining the characteristic length scale of the modulation. Calcium substitution enhances both the amplitude and the wavevector of the softening by strengthening the ferroelectric and antiferrodistortive instabilities. Our results demonstrate that nonlinear flexoelectric
phonon coupling tends to stabilize a modulated state that cooperates with, rather than competes against, the other
lattice instabilities in SrTiO$_3$.
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All authors Benoît Fauqué, Daniel A. Chaney, Philippe Bourges, Stéphane Raymond, Arno Hiess, Paul Steffens, Benoît Baptiste, Luigi Paolasini, Alexeï Bosak, Kamran Behnia, Yasuhide Tomioka
Materials Science
Comprehensive parameter and electrochemical dataset for a 1 Ah graphite/LNMO battery cell for physical modelling as a blueprint for data reporting in battery research
Christina Schmitt, August Johansson, Xavier Raynaud et al. (+9 more)
While current technology has enabled their widespread use, further improvements are needed for stationary, portable, and mobile applications, for example by the development of novel cathode materials. Digitalization of battery development, combining both experimental and modelling efforts is extremely valuable in this development. This is addressed in the present paper, where the authors present a comprehensive
dataset for a graphite/LNMO 1 Ah pouch
cell, including material, design, and electrochemical data. The
dataset, validated through the BattMo modelling framework, supports physical modelling and aims to benefit the battery modelling community by offering a comprehensive resource for future studies. Both the
dataset and the accompanying software for numerical validation is openly available and processed in such a way that it can serve as blueprint for reporting of comparable research data.
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All authors Christina Schmitt, August Johansson, Xavier Raynaud, Eibar Joel Flores Cedeño, John Mugisa, Dane Sotta, Agathe Martin, Nicolas Schaeffer, Cédric Debruyne, Yvan Reynier, Simon Clark, Dennis Kopljar
Materials Science
Growth and Morphology of InN Nanowires on Si<111> and Si<100> at Back-End-Of-Line Compatible Temperatures
Andrea Orlando-cunnac, Arthur Arnaud, Martien Den Hertog et al. (+4 more)
InN nanowires were grown on Si<111> and Si<100> substrates by
plasma-assisted molecular beam epitaxy using a thin AlN buffer layer at temperatures compatible with the thermal budget limitation imposed by Back-End-Of-Line processing. Reflection high-energy electron diffraction reveals different nucleation behaviors on the two substrate orientations, with higher structural disorder in the case of Si<100>. However, vertically aligned nanowires with hexagonal cross section and N polarity are obtained on both substrates. A statistical analysis of nanowire morphology as a function of growth temperature indicates similar trends in diameter, density, and length on Si<111> and Si<100>, which are explained by adatom kinetics during growth. Nanowires on Si<100> exhibit improved uniformity and reduced tapering, attributed to the different nanowire nucleation due to microstructural properties of the AlN buffer layer. The results demonstrate the feasibility of growing high-quality InN nanowires on Si<100>, supporting their potential for monolithic integration of nanowire-based photodetectors on silicon.
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All authors Andrea Orlando-cunnac, Arthur Arnaud, Martien Den Hertog, Ettore Coccato, Vincent Calvo, Jonathan Steckel, Eva Monroy
Materials Science · Cross-listed from cond-mat.mes-hall
Plasmon dynamics in graphene
Suheng Xu, Birui Yang, Nishchhal Verma et al. (+15 more)
Plasmon are collective oscillations of mobile electrons with dynamics controlled by their charge stiffness("Drude weight"). Using terahertz spacetime metrology, we probe Plasmon dynamics of mono- and bi-layer
graphene. In both systems, the experimentally measured Drude weight systematically exceeds the prediction based on non-interacting electronic system. The relative enhancement increases as the carrier density decreases. We attribute the observed deviation to the interplay of interactions and wave function structure of the Dirac
fermions in multi-layer
graphene. Our results establish that pseudospin structure of the single-particle electronic wave function can directly influence collective excitations, with implications that extend beyond
graphene to a broad class of
quantum materials.
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All authors Suheng Xu, Birui Yang, Nishchhal Verma, Rocco A. Vitalone, Brian Vermilyea, Miguel Sánchez Sánchez, Julian Ingham, Ran Jing, Yinming Shao, Tobias Stauber, Angel Rubio, Milan Delor, Mengkun Liu, Michael M. Fogler, Cory R. Dean, Andrew Millis, Raquel Queiroz, D. N. Basov
Materials Science · Cross-listed from cond-mat.mes-hall
Quantum Theory and Unusual Dielectric Functions of Graphene
V. M. Mostepanenko and G. L. Klimchitskaya
We address the spatially nonlocal dielectric functions of
graphene at any frequency derived starting fromthe first principles of thermal
quantum field theory using the formalism of the polarization tensor. After a brief review of this formalism, the longitudinal and transverse dielectric functions are considered at any relationship between the frequency and the wave vector. The analytic properties of their real and imaginary parts are investigated at low and high frequencies. Emphasis is given to the double pole at zero frequency which arises in the transverse dielectric function. The role of this unusual property for solving the problem of disagreement between experiment and theory in the Casimir effect is discussed. We guess that a more complete dielectric response of ordinary metals should also be spatially nonlocal and its transverse part may possess the double pole in the region of evanescent waves.
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Materials Science
The transformation mechanisms among cuboctahedra, Ino's decahedra and icosahedra structures of magic-size gold nanoclusters
Ehsan Rahmatizad Khajehpasha, Mohammad Ismaeil Safa, Nasrin Eyvazi et al. (+2 more)
Gold nanoclusters possess multiple competing structural motifs with small energy differences, enabling structural coexistence and interconversion. Using a high-accuracy machine learned potential trained on some 20'000 density functional theory reference data points, we investigate transformation pathways connecting both high-
symmetry and amorphous cuboctahedra, Ino's decahedra and icosahedra for Au55, Au147, Au309 and Au561 nanoclusters. Our saddle point searches reveal that high-
symmetry transformations from cuboctahedra and Ino's decahedra to icosahedra proceed through a single barrier and represent soft-mode-driven jitterbug-type and slip-dislocation motions. In addition, we identify lower-barrier asymmetric transformation pathways that drive the system into disordered, Jahn-Teller-stabilized amorphous icosahedra. Minima Hopping sampling further uncovers, in this context, many such low-
symmetry minima. Some of the newly identified global minima for Au309 and Au561 have energies that are up to 2.8 eV lower than the previously reported global minima. Hence, both the shapes and the transformation pathways studied in previous investigations are not the physically relevant ones. In contrast to the previously studied pathways, our transformation pathways give reasonable transformation times that are in rough agreement with experiments.
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All authors Ehsan Rahmatizad Khajehpasha, Mohammad Ismaeil Safa, Nasrin Eyvazi, Marco Krummenacher, Stefan Goedecker
Materials Science · Cross-listed from hep-ex
A comparison of simulation tools for Muon-Induced X-ray Emission (MIXE) in thin films: a study case with lithium batteries
Maxime Lamotte, Michael W. Heiss, Thomas Prokscha et al. (+1 more)
We present a comparative study of three Monte Carlo simulation frameworks -SRIM, GEANT4, and PHITS- for modeling the transport, stopping, and atomic cascade of negative
muons in micrometer-scale, multilayer systems relevant to
Muon-Induced X-ray Emission (MIXE) experiments at the Paul Scherrer Institute (PSI). Using a lithium-ion battery as a
benchmark target, simulated implantation profiles are compared with experimental data from the
GIANT spectrometer. All three codes reproduce the overall
muon depth distributions with good consistency, even across sharp density contrasts. SRIM provides reliable implantation estimates for compact geometries, whereas PHITS reproduces GEANT4 results with comparable accuracy and additionally generates muonic X-ray spectra. These spectra, however, exhibit a systematic energy offset in the K-line transitions of medium- and high-Z elements relative to theoretical and experimental values. Despite this bias, PHITS accurately captures relative intensities and spectral shapes, enabling element-specific line identification. The results demonstrate that SRIM and PHITS constitute practical tools for rapid estimation of
muon implantation and stopping profiles, and that PHITS holds strong potential for predictive MIXE spectroscopy once its transition-energy bias is corrected.
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All authors Maxime Lamotte, Michael W. Heiss, Thomas Prokscha, Alex Amato
Materials Science
Topology-Directed Silicide Formation: An Explanation for the Growth of C49-TiSi$_2$ on the Si(100) Surface
Lukas Hückmann, Jonathon Cottom, Jörg Meyer et al. (+1 more)
Designing metal-
semiconductor junctions is essential for optimizing the performance of modern nanoelectronic devices. A widely used material is TiSi$_2$, which combines low electronic resistivity with good endurance. However, its multitude of polymorphs continues to pose a challenge for device fabrication. In particular, the naturally occurring formation of the metastable C49-TiSi$_2$ modification remains poorly understood and is problematic due to its unfavorable electronic properties. Based on extensive DFT calculations, we present a comprehensive model of Ti adsorption on Si(100) that highlights the pivotal role of surface
topology for the initial stages of the interfacial TiSi$_2$ formation process. We show that the interplay between Si surface dimers, the
symmetry of the Si(100) surface, and the incorporation of Ti adsorbates below the surface drives an adsorption pattern that yields a nucleation template for the C49-TiSi$_2$ phase. Our atomistic model rationalizes experimental observations like the Stranski-Krastanov growth mode, the preferential formation of C49-TiSi$_2$ despite it being less favorable than the competing C54 phase, and why disruption of the surface structure restores thermodynamically driven growth of the latter. Ultimately, this novel perspective on the unique growth of TiSi$_2$ will help to pave the way for next-generation electronic devices.
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All authors Lukas Hückmann, Jonathon Cottom, Jörg Meyer, Emilia Olsson
Materials Science · Cross-listed from physics.chem-ph
Molecular electrostatic potentials from machine learning models for dipole and quadrupole predictions
Kadri Muuga, Lisanne Knijff and Chao Zhang
The molecular electrostatic potential (MEP) is a key quantity for describing and predicting intermolecular and ion-molecule interactions. Here, we assess the ability of machine-learning (ML) models to infer the MEP, based on the equivariant graph-convolutional neural network architecture PiNet2 and trained on dipole and quadrupole moments. For the established QM9
dataset, we find that including the quadrupole contribution in the ML models substantially improves their ability to recover the MEP compared to dipole-only models. This trend is confirmed on the SPICE
dataset, which spans a much broader region of organic chemical space. Together, this study underscores the central role of the quadrupole moment as a fitting target for ML models aiming at rapid access to the MEP.
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Materials Science
Physically Unclonable Functions Based on Single-Walled Carbon Nanotubes: A Scalable and Inexpensive Method toward Unique Identifiers
Enrique Burzurí, Daniel Granados and Emilio M. Pérez
A physically un-clonable function (PUF) is a physical system that cannot be reproduced or predicted and therefore is a good basis to build security and anti-counterfeiting applications. The unclonability of PUFs typically stems from the randmoness induced in a system during sophisticated fabrication methods. It is precisely this built-in complexity the bottleneck hindering scalability and increasing costs. Here, we produce in a simple manner PUFs based on arrays of carbon nanotubes junctions simultaneously assembled by dielectrophoresis. We demonstrate that the intrinsic inhomogeneity of carbon nanotubes at the nanoscale, combined with the unpredictability introduced by
liquid phase-based fabrication methods results in unique electronic profiles of easily scalable devices. This approach could be extrapolated to generate PUFs based on other nanoscale materials
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Materials Science
Comprehensive Molecular-level Understanding of MgO Hydration through Computational Chemistry
Taichi Inagaki and Miho Hatanaka
The hydration of magnesium
oxide (MgO) to magnesium hydroxide (Mg(OH)$_2$) is a fundamental solid-surface chemical reaction with significant implications for materials science. Yet its molecular-level mechanism from water adsorption to Mg(OH)$_2$ nucleation and growth remains elusive due to its complex and multi-step nature. Here, we elucidate the molecular process of MgO hydration based on structures of the MgO/water interface obtained by a combined computational chemistry approach of potential-scaling molecular dynamics simulations and first-principles calculations without any a priori assumptions about reaction pathways. The result shows that the Mg$^{2+}$ dissolution follows the dissociative water adsorption. We find that this initial dissolution can proceed exothermically even from the defect-free surface with an average activation barrier of $\sim$12 kcal/mol. This exothermicity depends crucially on the stabilization of the resulting surface vacancy, achieved by
proton adsorption onto neighboring surface oxygen atoms. Further Mg$^{2+}$ dissolution then occurs in correlation with
proton penetration into the solid. Moreover, we find that the Mg(OH)$_2$ nucleation and growth proceeds according to the dissolution-precipitation mechanism, rather than a solid-state reaction mechanism involving a direct topotactic transformation. In this process, Mg$^{2+}$ ions migrate away from the surface and form amorphous Mg-OH chains as precursors for Mg(OH)$_2$ nucleation. We also demonstrate that sufficient water facilitates the formation of more ordered crystalline
nuclei. This computational study provides a comprehensive molecular-level understanding of MgO hydration, representing a foundational step toward elucidating the mechanisms of this class of complex and multi-step solid-surface chemical reactions.
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Materials Science
Classification and design of two-dimensional altermagnets
Sike Zeng, Dong Liu, Hongjie Peng et al. (+3 more)
Altermagnets – newly identified collinear antiferromagnets – carry zero net moment with non-relativistic,
spin-polarized bands, distilling the best of ferromagnets and antiferromagnets into a single spintronic platform. Shrunking to the two-dimensional limit, they inherit the tunability of two-dimensional
crystals while adding
symmetry-protected
spin splitting, a combination now driving intense experimental interest. Here, we review the
symmetry classification of two-dimensional altermagnets based on
spin-group theory and survey the growing list of candidate materials, emphasizing those with large
spin splitting for experimental realization. We then examine strategies for engineering two-dimensional altermagnetism. This Review aims to consolidate theoretically proposed candidate materials and realization strategies for two-dimensional altermagnets, providing insights for future experimental efforts in this emerging field.
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All authors Sike Zeng, Dong Liu, Hongjie Peng, Chang-Chun He, Xiao-Bao Yang, Yu-Jun Zhao
Materials Science
Effect of Number of Bilayers on the Anomalous Hall Effect in [Si/Fe]N Multilayers
Sudhansu Sekhar Das and M. Senthil Kumar
The influence of varying the number of
bilayers (N) on the anomalous
Hall effect (AHE) in sputtered Si/Fe multilayers has been investigated. Both the AHE and magnetisation data reveal the in-plane
magnetic anisotropy in the samples. Large enhancement of about 24 times in the saturation anomalous
Hall resistance (R_Ahs) and anomalous
Hall sensitivity (S) has been observed upon decreasing N from 20 to 1. When compared with the bulk Fe, the values of R_Ahs and anomalous
Hall coefficient, Rs obtained for N= 1 were enhanced by about 5 and 3 orders of magnitude, respectively. The Rs follows the longitudinal electrical resistivity Rho as Rs proportional to Rho^2.1, suggesting side jump as the dominant mechanism of the AHE. The S as high as 22 Ohm/T over a wide operational field range of -8 to +8 kOe has been obtained for N = 1.
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Materials Science
A Neuroevolution Potential for Gallium Oxide: Accurate and Efficient Modeling of Polymorphism and Swift Heavy-Ion Irradiation
Yaohui Gu, Binbo Li, Lingyang Jiang et al. (+6 more)
Gallium
oxide (Ga2O3) is a wide-bandgap
semiconductor with promising applications in high-power and high-frequency electronics. However, its complex polymorphic nature poses substantial challenges for fundamental studies, particularly in understanding phase-transformation behaviors under nonequilibrium conditions. Here, we develop a robust, accurate, and computationally efficient machine-learning interatomic potential (MLIP) for Ga2O3 based on the neuroevolution potential (NEP) framework combined with an energy-dependent weighting strategy. The resulting NEP potential demonstrates clear advantages over the state-of-the-art tabGAP potential with respect to both accuracy and computational efficiency. Furthermore, we introduce a physically process-oriented sampling strategy to systematically augment the training
dataset, thereby enhancing the MLIP performance for targeted physical phenomena. As a representative application, a dedicated NEP potential is constructed for swift heavy-ion (SHI) irradiation simulations of e̱ta}-Ga2O3. The simulated results are in quantitative agreement with experimental observations and provide a consistent physical explanation for the reported experimental discrepancies regarding phase transformations in the ion track of e̱ta}-Ga2O3.
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All authors Yaohui Gu, Binbo Li, Lingyang Jiang, Yuhui Hu, Wenqiang Liu, Lijun Xu, Pengfei Zhai, Jie Liu, Jinglai Duan
Materials Science · Cross-listed from cond-mat.supr-con
Microwave Kerr/Faraday Resonance in Two-dimensional Chiral Superconductors
Taiki Matsushita, Jun'ichi Ieda, Yasufumi Araki et al. (+3 more)
We investigate the polar Kerr and Faraday effects in two-dimensional multiband
chiral superconductors. We show that the clapping modes–the relative phase and amplitude oscillations between two
chiral components of the superconducting order parameter–lie well within the quasiparticle excitation gap in multiband systems and dominate these magneto-optical responses in the microwave regime. The Kerr and Faraday rotation angles exhibit the resonant enhancement with sign reversals in the microwave regime as a function of the light frequency, reaching peak values on the order of 100 nrad–10 $\mu$rad in thin films of candidate
chiral superconductors. These resonances are accessible in superconducting atomic layer materials and provide a generic probe of
chiral superconductivity in two-dimensional systems.
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All authors Taiki Matsushita, Jun'ichi Ieda, Yasufumi Araki, Takahiro Morimoto, Ilya Vekhter, Youichi Yanase
Materials Science
Density of States of Ru3 and Pt3 Clusters Supported on Sputter-Deposited TiO2
Liam Howard-Fabretto, Timothy J. Gorey, Guangjing Li et al. (+4 more)
In this work, 3-atom clusters, Ru3 and Pt3, were deposited onto
radio frequency RF-sputter deposited TiO2, treated with Ar+ ion sputtering. Ru3 was deposited by both solution submersion and chemical vapor deposition of Ru3(CO)12, while Pt3 was deposited under ultra-high
vacuum using a
laser vaporisation cluster source. The valence electronic density of states (DOS) of the deposited clusters were analysed after heat treatment using ultraviolet photoelectron spectroscopy (UPS) and metastable impact electron spectroscopy (MIES), where UPS measures the top several layers while MIES measures only the top atomic layer. XPS was used to determine the cluster surface coverages. The DOS were found to be very similar between Ru3 deposited by solution submersion and chemical vapor deposition. MIES results for Ru3 had contributions from titania O 2p sites due to encapsulation by a reduced titania overlayer. For Pt3 clusters the UPS and MIES results provided evidence that Pt was present on the topmost layer, and encapsulation did not occur. The proposed reason for the encapsulation of Ru3 but not of Pt3 is the higher surface energy of Ru over Pt. It is concluded that Pt clusters deposited onto TiO2 can modify the outermost layer by adding discrete energy levels on the surface, whereas the Ru clusters being encapsulated just below the surface generate a broad distribution of energy states close to the
Fermi level. The outcome of this work is that Pt3-cluster-modified surfaces could be used as catalysts for reactions where the Pt3 energy levels are suitable for the respective reaction. The implication of the DOS found for photocatalytic water splitting are discussed.
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All authors Liam Howard-Fabretto, Timothy J. Gorey, Guangjing Li, Siriluck Tesana, Gregory F. Metha, Scott L. Anderson, Gunther G. Andersson
Materials Science · Cross-listed from cs.CE
A Generalizable Framework for Building Executable Domain-Specific LLMs under Data Scarcity: Demonstration on Semiconductor TCAD Simulation
Di Wang, Zhenhua Wu, Yu Liu et al. (+2 more)
Scientific and engineering verticals often suffer from data scarcity and strict executability requirements: models must generate not only fluent text, but also syntactically valid, tool-compilable scripts. We present a schema-first
alignment framework for building compact, executable domain-specific LLMs in low-resource settings. The framework integrates three core components: (i) large-scale synthetic QA data generation from expert documentation to instill foundational domain knowledge; (ii) a code-centric IR->DPO workflow that converts verified tool decks into interpretable intermediate representations (IR), performs equivalence-preserving diversification, and constructs preference pairs to directly optimize instruction compliance and code executability; and (iii) a controlled evaluation of
Retrieval-Augmented Generation (RAG), showing that while RAG benefits general LLMs, it can marginally degrade the performance of already domain-aligned models. We demonstrate the framework by instantiating TcadGPT for
semiconductor Technology Computer-Aided Design (TCAD). Using 1.5M synthetic QA pairs and an IR-driven DPO
dataset, TcadGPT attains 85.6% semantic accuracy and an 80.0% syntax pass rate on SDE executability tests, substantially outperforming state-of-the-art general LLMs such as GPT-4o. To probe portability beyond TCAD, we apply the same recipe to the open-source FEM solver Elmer, observing consistent improvements in script-level success rates over general-purpose baselines. All
datasets,
benchmarks, and code (including P1, P2, and IR->DPO) are released for reproducibility. Together, these results suggest that the proposed framework provides a robust and reproducible path toward executable LLMs in specialized, data-scarce professional domains.
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All authors Di Wang, Zhenhua Wu, Yu Liu, Kai Chang, Shaohua Wu
Materials Science · Cross-listed from cond-mat.supr-con
Electronic structure theory of H$_{3}$S: Plane-wave-like valence states, density-of-states peak and its guaranteed proximity to the Fermi level
Ryosuke Akashi
Superconductivity in sulfur superhydride H$_{3}$S under extreme pressures has been explained theoretically, but it requires a peaked concentration of the electronic density of states (DOS), which has been found in first-principles calculations. The mechanism of this peak formation, though vital for its high transition temperature, has however remained obscure. We address this problem through detailed analysis of the first-principles electronic wave functions. The valence wave functions are shown to be significantly plane-wave-like. From the
Fourier-mode analysis of the self-consistent potential and atomic pseudopotentials, we extract the nearly uniform models that accurately reproduce the first-principles band structure with very few parameters. The DOS peak is shown to be the consequence of the hybridization of specific plane waves. Adjacency of Jones' large zone to the plane-wave spherical
Fermi surface is posited to be the root cause of the multiple plane-wave hybridization, the DOS peak formation and its proximity to the
Fermi level. The present theory resolves the minimal modeling problem of electronic states in H$_{3}$S, as well as establishes a mechanism that may help to boost the transition temperatures in pressure induced
superconductors.
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Materials Science
Performance of AI agents based on reasoning language models on ALD process optimization tasks
Angel Yanguas-Gil
In this work we explore the performance and behavior of
reasoning large
language models to autonomously optimize atomic layer deposition (ALD) processes. In the ALD process optimization task, an
agent built on top of a
reasoning LLM has to find optimal dose times for an ALD precursor and a coreactant without any prior knowledge on the process, including whether it is actually self-limited. The
agent is meant to interact iteratively with an ALD reactor in a fully unsupervised way. We evaluate this
agent using a simple model of an ALD tool that incorporates ALD processes with different self-limited surface reaction pathways as well as a non self-limited component. Our results show that
agents based on
reasoning models like OpenAI's o3 and GPT5 consistently succeeded at completing this optimization task. However, we observed significant run-to-run variability due to the non deterministic nature of the model's response. In order to understand the logic followed by the
reasoning model, the
agent uses a two step process in which the model first generates an open response detailing the
reasoning process. This response is then transformed into a structured output. An analysis of these
reasoning traces showed that the logic of the model was sound and that its
reasoning was based on the notions of self-limited process and saturation expected in the case of ALD. However, the
agent can sometimes be misled by its own prior choices when exploring the optimization space.
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