Materials Science
Discovery of novel magnetic Y-Mn-B compounds via advanced machine learning guided framework
Weiyi Xia, Wei Shen Tee, Maxim Moraru et al. (+2 more)
Rare-earth transition-metal borides offer critical structural motifs for permanent-magnet design; however, the manganese-rich regions within these compositional phase spaces remain largely unexplored. In this work, we develop an advanced machine-learning-assisted discovery framework to explore Y-Mn-B ternary system. Starting from over one million hypothetical structures generated from known structures in databases, we filtered promising candidates by first applying graph neural networks to predict material stability, then using machine-learning-interatomic-potential to relax their structures, and finally validating the results with first-principles calculations. We identify 5 stable and near-stable Y-Mn-B phases along with 61 metastable compounds with the formation energy within 100 meV/atom with respect to the ternary convex hull. Among them, Y2Mn7B7 and YMn4B4 are structurally analogous to the previously synthesized $R_{1+\epsilon}Fe_4B_4$ 1D incommensurate composite chain compounds. In striking contrast to the strongly suppressed Fe moments reported, our first-principles calculations reveal that the predicted Mn-chain phases preserve sizable local Mn moments (approximately 1.1 $\mu_B$) and favored ferromagnetic ordering. Electronic structure analyses elucidate the microscopic origin of moment recovery via an enhanced exchange splitting driven by a Stoner-like instability. We also perform systematic Mn-Fe substitution to confirm the thermodynamic continuity and a monotonic enhancement of the macroscopic magnetization, from Fe to Mn. These findings indicate that targeted transition-metal substitution within a one-dimensional boride family can recover transition-metal magnetism, offering a physically interpretable route for designing new
magnetic rare-earth transition-metal borides.
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All authors Weiyi Xia, Wei Shen Tee, Maxim Moraru, Ying Wai Li, Cai-Zhuang Wang
Materials Science
Temperature-Induced Reorganization of Supported Zn$_3$ Clusters on Cu(111): From Minimum-Energy Structures to Finite-Temperature Ensembles
Jiayan Xu, Zheng Yu, Abhirup Patra et al. (+4 more)
Understanding the nature of catalytic active sites under reaction conditions remains a central challenge in heterogeneous catalysis. In industrial copper/zinc oxide/alumina catalysts for methanol synthesis, small Zn-based species at the Cu interface have long been proposed as active-site candidates, yet their atomic-scale structure and stability remain controversial. Computational studies typically identify such species from optimized 0 K structures, assuming that minimum-energy configurations remain representative under reaction conditions. Here, we combine machine-learning-interatomic-potential-accelerated global optimization, molecular dynamics, and enhanced-sampling free-energy calculations to investigate supported Zn$_3$(OH)$_3$ and Zn$_3$(OH)$_2$CHOO clusters on Cu(111)-based surfaces from 0 to 450 K. While compact triangular configurations are generally favored among minimum-energy structures at 0 K, finite-temperature free-energy calculations reveal a pronounced shift toward extended linear configurations with increasing temperature. This transition is driven primarily by entropic stabilization and cannot be inferred from potential energies alone. Molecular dynamics further shows substantial cluster mobility on pristine Cu(111), indicating that long-term persistence depends not only on configurational stability but also on surface mobility. Surface Zn alloying strongly suppresses
diffusion, thereby stabilizing isolated interfacial Zn species. Together, these results show that thermodynamically relevant structures of supported Zn-based clusters can differ fundamentally from static 0 K predictions because of competing enthalpic and entropic effects. Our findings highlight the limitations of identifying catalytic active sites solely from 0 K structures and underscore the importance of explicit finite-temperature sampling in catalyst modeling.
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All authors Jiayan Xu, Zheng Yu, Abhirup Patra, Amar Deep Pathak, Sharan Shetty, Detlef Hohl, Roberto Car
Materials Science
Over what length scale does an inorganic substrate perturb the structure of a glassy organic semiconductor?
Kushal Bagchi, Chuting Deng, Camille Bishop et al. (+6 more)
While the bulk structure of vapor-deposited glasses has been extensively studied, structure at buried interfaces has received little
attention, despite being important for organic electronic applications. To learn about glass structure at buried interfaces, we study the structure of vapor-deposited glasses of the organic
semiconductor DSA-Ph (1,4-di-[4-(N,N-diphenyl)amino]styryl-benzene) as a function of film thickness; structure is probed with grazing incidence X-ray scattering. We deposit on silicon and gold substrates and span a film thickness range of 10-600 nm. Our experiments demonstrate that interfacial molecular packing in vapor-deposited glasses of DSA-Ph is more disordered compared to the bulk. At a deposition temperature near room temperature, we estimate ~ 8 nm near the substrate can have modified molecular packing. Molecular dynamics simulations of a coarse-grained representation of DSA-Ph reveal a similar length scale. In both the simulations and the experiments, deposition temperature controls glass structure beyond this interfacial layer of a few nanometers.
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All authors Kushal Bagchi, Chuting Deng, Camille Bishop, Yuhui Li, Nicholas E Jackson, Lian Yu, M.F. Toney, J.J. de Pablo, M.D. Ediger
Materials Science · Cross-listed from cond-mat.soft
Rejuvenation versus overaging: The effect of cyclic loading/unloading on the segmental dynamics of PMMA glasses
Trevor Bennin, Enran Xing, Josh Ricci et al. (+1 more)
The acceleration of structural relaxation or physical aging by deformation, known as overaging, has been reported in experiments and simulations of
polymer and colloid glasses, and correctly accounting for overaging is important for the prediction of the long-term behavior of
polymer glasses in engineering applications. Here the effects of cyclic loading/unloading on the segmental dynamics and mechanical properties of PMMA glasses are investigated using a probe reorientation technique and time-aging time superposition of the mechanical response, respectively. Sets of 5000 tensile loading/unloading cycles were performed at temperatures between Tg - 10 K and Tg - 25 K with cycle extension strains ranging from 0.003 to 0.007. After cycling, the segmental dynamics measured with the probe reorientation technique either remained unchanged or were faster relative to an undeformed sample. The relaxation times of cycled glasses recovered with a common time scale on the order of their aging time, indicating that they retain a
memory of their original age, as opposed to a full erasure of their thermal and mechanical history. Surprisingly, changes as a result of cycling were more obvious in probe reorientation measurements than in the mechanical properties, suggesting that the probe reorientation technique can sensitively detect nonlinear effects of deformation. No evidence of overaging was observed in the optical or mechanical measurements as a result of these cyclic loading/unloading experiments.
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All authors Trevor Bennin, Enran Xing, Josh Ricci, M.D. Ediger
Materials Science · Cross-listed from cond-mat.soft
Controlling Structure and Properties of Vapor-Deposited Glasses of Organic Semiconductors: Recent Advances and Challenges
Kushal Bagchi and MD Ediger
The last decade has seen great progress in manipulating the structure of vapor-deposited glasses of organic
semiconductors. By varying the substrate temperature during deposition, glasses with a wide range of density and molecular orientation can be prepared from a given molecule. We review recent studies that show the structure of vapor-deposited glasses can be tuned to significantly improve the external
quantum efficiency and lifetime of OLEDs (organic light emitting diodes). We highlight the ability of molecular simulations to reproduce experimentally observed structures, setting the stage for in-silico design of vapor-deposited glasses in the coming decade. Finally, we identify research opportunities for improving the properties of organic
semiconductors by controlling the structure of vapor-deposited glasses.
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Materials Science · Cross-listed from cond-mat.mes-hall
Emissivity by Design: Geometric Mesh Inductance Governs Thermal Radiation in Metallic Nanowire Networks
Amaury Baret and Ngoc Duy Nguyen
The thermal infrared emissivity of metallic nanowire networks - the property that makes them candidate low-emissivity transparent electrodes - follows regularities that have resisted physical explanation: a strong wire-diameter dependence with no wire-length dependence, a correlation with sheet resistance that breaks down above ~15 ohm/sq, and an angular signature that turns from dielectric-like to metallic as the network densifies. We show that all of them follow from one local
geometric length, the average inter-wire gap g, acting through the
geometric inductance of a mesh finer than the thermal wavelength: $X_L = Z_0 (g/\lambda) \ln(2g/\pi D)$, a parameter-free reactance that exceeds the ohmic loss and, unlike the DC sheet resistance, stays finite instead of diverging at the percolation threshold. Since the gap is fixed by areal density and wire diameter alone, the optics is length-independent and decoupled from percolative transport; what has been read as a second, optical percolation is instead a smooth impedance crossing. With a single fitted parameter the theory reproduces 56 silver-nanowire samples across four diameters to a mean absolute error of 0.04, collapses them onto one universal curve, and - unchanged - predicts the emissivity-transmittance data of five independent groups and the measured spectral emissivity, including the silica
phonon band. Because this reactance contains no material constant, the inter-wire gap emerges as the master design variable for the radiative properties of metallic nanowire transparent conductors.
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Materials Science
PowderLine: a programmatic powder diffraction analysis application
Adam A. Corrao, Jennifer A. Perez, John D. Langhout et al. (+3 more)
Whole-pattern fitting methods, such as Rietveld refinement, excel at extracting detailed structural, chemical, and microstructural information from powder diffraction data. Obtaining reliable results requires both considerable expertise and software-specific knowledge, and applying these methods at scale typically relies on custom scripts written for each application. High-throughput experiments and autonomous self-driving laboratories increasingly utilize powder diffraction analysis to proceed programmatically and to return structured, machine-readable results. Here, we introduce PowderLine, a Python application that encapsulates a complete refinement into a single declarative recipe, validates that recipe against a versioned schema, and executes it through refinement software to return structured results. The refinement recipe is an all-inclusive, machine-readable and -writable description of either Rietveld or single peak analysis that users, scripts, and automated
agents can specify and run in the same way. As a result of PowderLine's composability, it naturally fits into interactive, scripted, and autonomous workflows alike.
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All authors Adam A. Corrao, Jennifer A. Perez, John D. Langhout, Megan M. Butala, Thomas A. Caswell, Daniel Olds
Materials Science
Automated Burgers Vector Identification for Individual Dislocations in Bulk Crystals
Abderrahmane Benhadjira, Carsten Detlefs, Vincent Favre-Nicolin et al. (+4 more)
Weak-beam imaging in dark-field X-ray microscopy (DFXM) can resolve individual dislocations in bulk
crystals, but assigning Burgers vectors from the resulting contrast typically requires manual comparison with forward simulations. Here, we train a physics-informed convolutional neural network (CNN) on geometrical optics simulations of isolated dislocations in face-centred cubic (FCC) aluminium, incorporating crystallographic constraints into the learning pro- cess. The model identifies Burgers vectors from weak-beam integrated rocking-curve images. On synthetic test data, the model achieves an accuracy of approximately 93%. In an experimental cross-slip case, the constrained model as- signs 72.7% of the layer-wise predictions to the reference Burgers vector. These results show that simulation-trained, physics-informed CNNs represent a step toward automated dislocation identification in DFXM.
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All authors Abderrahmane Benhadjira, Carsten Detlefs, Vincent Favre-Nicolin, Henning Friis Poulsen, Grethe Winther, Can Yildirim, Sina Borgi
Materials Science · Cross-listed from cond-mat.mes-hall
Reduced vortex descriptors linking polycrystallinity in magnetic nanoparticles with polarized magnetic small-angle neutron scattering
M.P. Adams, J. Leliaert, A. Michels et al. (+1 more)
Analytical
vortex models reduce polarized
magnetic small-angle
neutron scattering (SANS) from nanoparticle ensembles to a small set of texture descriptors. In this work, we apply this reduction to micromagnetic simulations of polycrystalline iron oxide nanoflowers at a fixed particle size and examine how a controlled parametrization of multigrain disorder is reflected in the remanent descriptors. The particles are represented by explicit Voronoi microstructures, and intraparticle disorder is varied through the intergrain exchange coupling and anisotropy-axis coherence. Fitting each remanent magnetization state to a
hyperbolic vortex model reveals a predominantly two-channel organization: the intergrain exchange coupling is associated mainly with the radial
vortex profile, whereas the anisotropy-axis coherence is associated mainly with the orientational moment of the
vortex-axis distribution. The normalized
spin-flip SANS cross sections are accurately represented by independent fits of the analytical linear-
vortex SANS expression obtained from the first-order expansion of the
hyperbolic profile. The fitted orientational descriptor agrees closely with its independent real-space estimate, whereas the corresponding radial descriptors exhibit a strong global nonlinear relation. This separation identifies which information from the micromagnetic
vortex textures is robustly retained by the reduced analytical representation.
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All authors M.P. Adams, J. Leliaert, A. Michels, E.M. Jefremovas
Materials Science
A nuclear-quantum-corrected machine-learning potential reveals quantum-enhanced hydrogen segregation at general grain boundaries in alpha-iron
Kazuma Ito
Atomistic descriptions of hydrogen
diffusion and trapping at defects are essential for understanding hydrogen embrittlement. As the lightest solute in metals, hydrogen exhibits nuclear
quantum effects that alter these processes even at room temperature. Explicit treatment of such effects is computationally demanding, limiting large-scale simulations of complex environments. Here, we use an Fe-H machine-learning interatomic potential (MLIP) based on the performant implementation of the atomic cluster expansion (PACE), covering diverse Fe-H environments, and relabel the training configurations underpinning its transferability with
quantum mean forces from centroid-constrained path-integral molecular dynamics at 300 K. This yields a nuclear-
quantum-corrected PACE (NQC-PACE) without additional density functional theory calculations. At parent PACE, NQC-PACE describes nuclear
quantum effects on hydrogen trapping at vacancies, dislocations, surfaces and general grain boundaries, H-H interactions, and
diffusion in alpha-Fe. Grand-canonical Monte Carlo/molecular dynamics simulations show nuclear
quantum effects markedly enhance hydrogen segregation at general grain boundaries and trapping behaviour in closer agreement with experimental trends. This enhancement arises from selective
quantum stabilisation of open, anisotropically soft local environments. Our framework uses finite-temperature
quantum mean forces to relabel the configurational space covered by an MLIP, enabling large-scale analysis of complex materials where light-element
quantum effects matter.
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Materials Science
Data-driven discovery and rapid, direct synthesis of MXenes
Ali Saffar Shamshirgar, Guilherme Ribeiro Portugal, Soheil Ershadrad et al. (+9 more)
MXenes, two-dimensional transition-metal carbides and nitrides, are typically obtained from MAX phases, yet historical reports suggest a broader, largely unexplored chemical space. Here we combine machine-learning-assisted database mining with experiments to uncover overlooked multilayer (ml) MXenes. Screening of repositories reveals a "Treasure Chest" of 38 previously synthesized but unrecognized ml-MXene candidates. Guided by these findings, we rediscover five MXenes using a rapid, scalable self-propagating high-temperature synthesis that requires no sustained external heating and completes within minutes. Inspired by the identified chemistries, we further realize 11 previously unexplored rare-earth-based M2CT2 MXenes (M= Pr, Nd, Sm, Gd, Tb, Ho, and Tm). Experiments and theory reveal semiconducting behavior and diverse
magnetic states across this family. Together, these results expand the MXene family and demonstrate a data-driven strategy for accelerating materials discovery through sustainable methods.
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All authors Ali Saffar Shamshirgar, Guilherme Ribeiro Portugal, Soheil Ershadrad, Roman Ivanov, Martin Dahlqvist, Florian Chabanais, Sanjay Chakraborty, Rainer Traksmaa, Irina Hussainova, Fredrik Heintz, Per O.Å. Persson, Johanna Rosen
Materials Science
Strain control of mid-IR spectroscopic nonlinear photocurrents in PtSe$_2$
M. Gerlei, G. J. de Coster, J. Papp et al. (+4 more)
Semi-metallic noble-metal dichalcogenides are promising materials for infrared optoelectronics, yet the origin and tunability of their nonlinear optical responses remain poorly understood. Here, we demonstrate in-situ mechanical control of
photon-drag photocurrents in polycrystalline PtSe$_2$ thin films grown on flexible polyimide substrates. Using polarization-resolved mid-infrared photocurrent spectroscopy under uniaxial tensile strain, we observe pronounced strain-dependent changes in resistivity, photoconductivity, and helicity-dependent nonlinear photocurrents. The spectral response is consistent with optical excitations across the
spin-orbit-coupling-induced (SOC) band gap near the K point. We develop a theoretical framework attributing the photocurrent primarily to
photon-drag induced by
photon-momentum
symmetry breaking. Strain modifies its magnitude and polarization dependence through deformation potentials that tune the SOC-induced band gap. These results establish mechanical strain as a route toward reconfigurable infrared polarization detection.
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All authors M. Gerlei, G. J. de Coster, J. Papp, S. Heiserer, S. Schlosser, G. S. Duesberg, P. Seifert
Materials Science
Machine Learning-Accelerated Band-Edge Engineering of Pnictogen Chalcohalide Solid Solutions for Solar Energy Technologies
Cibrán López, David Rovira, Edgardo Saucedo et al. (+1 more)
Pnictogen chalcohalide (MChX; M=Bi,Sb; Ch=S,Se; X=I,Br) solid solutions combine earth-abundant constituents, tunable band gaps ($1.2$-$2.1$ eV), and strong optical absorption, making them attractive for solar energy conversion. Yet their vast compositional space has so far prevented a systematic assessment of how band-edge positions vary with stoichiometry and surface termination. Here, we combine first-principles density functional theory with machine learning to predict the valence and conduction band-edge positions of $\mathrm{Bi}_x\mathrm{Sb}_{1-x}\mathrm{S}_y\mathrm{Se}_{1-y}\mathrm{I}_z\mathrm{Br}_{1-z}$ solid solutions across their full compositional range on the two most stable surfaces, (010) and (011). We find that the valence-band maximum and conduction-band minimum can be tuned by more than $1$ eV through composition alone, and shift by up to $0.6$ eV between the two surface terminations for a same composition despite their nearly degenerate formation energies, establishing facet selection as a design parameter on par with chemical substitution. Guided by these results, we identify specific compositions capable of driving hydrogen, ammonia, methane, hydrogen peroxide, and oxygen (photo)electrochemical half-reactions, and show that several electron- and hole-transport contact materials commonly used in photovoltaic devices align with MChX solid solutions only as hole-selective contacts.
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All authors Cibrán López, David Rovira, Edgardo Saucedo, Claudio Cazorla
Materials Science · Cross-listed from physics.chem-ph
Through the Looking-Glass: Efficient Parity-Complete Learning via Local $O(2)$ Frames
Zemin Xu and Wenbo Xie
Making all
symmetry-allowed tensor representations computationally accessible remains a central challenge in equivariant atomistic learning. Clebsch–Gordan tensor products (CGTPs) are computationally demanding, whereas efficient $SO(2)$-based alternatives lack a unified treatment of natural- and unnatural-parity representations. We first introduce a generalized Wigner-$6j$ convolution that exactly recouples interactions involving additional node representations, replacing the first edge-level tensor-product intermediate with reusable node features. This reduces edge computation and storage but leaves the $\mathcal O(L^5)$ angular scaling of the sparse CGTPs unchanged. To address this remaining bottleneck, we develop a local $O(2)$ framework whose convolutions scale as $\mathcal O(L^3)$. The framework explicitly accounts for both rotations and reflections. Its linear maps, tensor products, and gated nonlinearities, combined with frame transformations, ensure global $O(3)$ equivariance for both spatial parities. Incorporating time-reversal labels extends this construction to $O(3)\times\mathbb Z_2^{\mathcal T}$. We apply the framework to
magnetic TACE (mTACE), using distinct interactions for systems with and without
spin–orbit coupling. On collinear CrN and noncollinear Fe
benchmarks, mTACE achieves substantial reductions in atomic- and
magnetic-force errors. We also provide EquivariantX, a library for global and local $O(2)$-equivariant computation.
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Materials Science · Cross-listed from quant-ph
Scientific applications of quantum computing: challenges and opportunities
Bruno Camino, C. Richard A. Catlow, John Buckeridge et al. (+13 more)
The predictive simulation of molecules and materials has had a broad and significant impact. It nevertheless remains constrained by the cost of accurately treating electronic correlation, excited states, and complex energy landscapes.
Quantum computing offers a fundamentally different computational paradigm in which
quantum states are encoded and manipulated directly rather than approximated on classical hardware. Here we discuss where this approach may provide a genuine scientific advantage in chemistry, materials science, and biochemistry. Promising directions include the high-accuracy treatment of correlated active spaces, improved excited-state simulations, and accelerated exploration of combinatorial structure spaces. The central challenge is therefore not
qubit scaling alone, but demonstrably chemically meaningful gains in predictive reliability. We argue that near-term value is most likely to come from disciplined workflow integration rather than wholesale replacement of classical methods. Noisy physical devices, error-mitigated utility experiments, early fault-tolerant devices, and fully fault-tolerant
quantum computers offer different scientific prospects, and claims of usefulness must be tied to the specific regime being discussed.
Quantum computing will become scientifically valuable when it demonstrably reduces uncertainty in computed energies, rates, spectra, or materials stability after the full costs of state preparation, measurement, error handling, and coupling to classical simulation are included.
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All authors Bruno Camino, C. Richard A. Catlow, John Buckeridge, Alin M. Elena, Vladimir V. Gusev, Sarah Harris, Thomas W. Keal, Glenn Jones, Vivien Kendon, Syma Khalid, Phalgun Lolur, Jamal A. Nasir, Matthew J. Rosseinsky, Chris-Kriton Skylaris, Paul A. Warburton, Scott M. Woodley
Materials Science
Enhancing Hydrogen Adsorption Ability of MOF-5 with Metal Node Exchange and Linker Functionalisation
Joshua Edzards, Holger-Dietrich Sassnick and Caterina Cocchi
In the search for promising material candidates for hydrogen storage, we investigate from first principles derivatives of metal organic framework 5 (MOF-5), including isoelectronic substitution of the metal centers (Zn $\rightarrow$ Mg, Cd) and linker functionalization with NH$_2$, OH, and NO$_2$ groups. Metal-node substitution consistently stabilises and ligand functionalization systematically enhances H$_2$ binding at the metal-oxo cluster sites. The combination of Cd centers and NO$_2$ groups proves to be most efficient, yielding an adsorption energy of -15.58 kJ mol$^{\text{-1}}$, which substantially outperforms the storage ability of pristine MOF-5. Detailed electronic structure analysis clarifies how the local framework environment coordinates the guest molecule, providing a robust design framework to guide the experimental development of advanced adsorbent materials.
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Materials Science
Mechanical-microstructural correlation on SPS-fabricated NiTi alloy
Tadeáš Těhan, Jaromír Kopeček, Elizaveta Iaparova et al. (+2 more)
Mechanical properties and dynamical mechanical analysis were performed on compact Spark
Plasma Sinter samples. It has been observed that the sample with less porosity reflects the behavior of superelasticity response. Other samples show failure during first cycles that may be due to porosity. Compaction of metallic powder is one of the standard procedures in the field of powder metallurgy for the fabrication of bulk material. Consolidation of the sample as a function of sintering temperature plays a crucial role in the final compaction mechanism. However, the
evolution of compaction, microstructure, phase transformation and mechanical properties as a function of sintering temperature is hardly disclosed. In this work, a correlation has been established between mechanical and microstructural properties of compact samples. The maximum compactness and the corresponding microstructure, porosity, texture, phase transformation, grain size, hardness, mechanical properties of compact samples were discussed. The research establishes mechanical properties-structure correlations for compaction of NiTi
alloy in advanced engineering applications.
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All authors Tadeáš Těhan, Jaromír Kopeček, Elizaveta Iaparova, Eduardo Alarcón, Sneha Samal
Materials Science
Insights into the Structural and Orientational Ordering of 2D Metal Halide Perovskites
Mustafa Mahmoud Aboulsaad, German Alvarez Carrero, Trupthi Devaiah Chonamada et al. (+4 more)
Metal halide perovskite nanoplatelets combine
quantum confinement with structural anisotropy, yet how thickness and processing govern their internal
crystal lattice versus collective organization remains unresolved. In this study, we separate internal structure, superlattice organization, and film texture using 2-5 monolayer CsPbBr3 nanoplatelets and larger nanocrystals across
spin-coating and drop-casting routes. Grazing incidence X-ray diffraction analysis of the specimens indicates that orthorhombic-compatible signatures recur throughout the thickness and deposition series, with a preserved
lattice-morphology relationship in which 020/040 and 101/202
lattice planes are associated with the platelet thickness and lateral dimensions, respectively. Upon deposition on the substrate, we notice a thickness-dependent crossover: 2-monolayer nanoplatelets remain predominantly face-on across deposition routes, whereas thicker nanoplatelets show marked processing sensitivity and orientational disorder. Processing therefore can be used as a tool to direct the NPL packing, establishing thickness as a key determinant of processing sensitivity.
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All authors Mustafa Mahmoud Aboulsaad, German Alvarez Carrero, Trupthi Devaiah Chonamada, Germán Salazar Alvarez, Ute Cappel, Rafael B. Araujo, Tomas Edvinsson
Materials Science
Tuning electronic properties and Schottky contact in graphene-based van der Waals heterostructures by electric gating and interlayer coupling
Poonam Sharma, Archana Sharma and Alok Shukla
Van der Waals
heterostructures (vdW HTSs) incorporating
graphene (GE) have been an active area of research, both theoretical and experimental, due to their potential to yield devices with a wide variety of applications. In this paper, first-principles calculations are employed to investigate C$_{6}$N$_{6}$/GE, hg-C$_{3}$N$_{4}$/GE, and C$_{6}$N$_{6}$/hg-C$_{3}$N$_{4}$ 2D vdW HTSs. A systematic analysis of structural and thermodynamic stability, electronic, mechanical, and optical properties of
semiconductor/metal and
semiconductor/
semiconductor interfaces is performed. Both
semiconductor/metal HTSs form $n$-type Schottky contacts, which can be converted into $p$-type Schottky or Ohmic contacts by tuning the external perpendicular electric field and the interlayer coupling. In the
semiconductor/
semiconductor C$_{6}$N$_{6}$/hg-C$_{3}$N$_{4}$ HTS, the valence and conduction band edges originate from distinct layers, resulting in a type-II band
alignment that promotes efficient electron-hole (e-h) separation. Furthermore, the band
alignment can be effectively tuned between type-I and type-II by applying an external electric field and varying the interlayer distance. From the optical absorption spectra of the HTSs, we concluded that the C$_{6}$N$_{6}$/GE and hg-C$_{3}$N$_{4}$/GE exhibit an optical response across a wide frequency range, whereas the C$_{6}$N$_{6}$/hg-C$_{3}$N$_{4}$ HTS shows prominent activity primarily in the ultraviolet region. Using the $G_{0}W_{0}$+BSE approach, the
exciton binding energies are also calculated for the gapped systems, namely C$_{6}$N$_{6}$, hg-C$_{3}$N$_{4}$ monolayers, and their HTS (C$_{6}$N$_{6}$/hg-C$_{3}$N$_{4}$), yielding values of 1.01 eV, 1.14 eV, and 1.18 eV, respectively, highlighting strong e-h interactions. Moreover, the band-edge analysis of C$_{6}$N$_{6}$/hg-C$_{3}$N$_{4}$ HTS further favors pronounced interlayer e-h coupling.
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Materials Science · Cross-listed from physics.plasm-ph
Assessing the Projector Augmented-Wave Method for Stopping Power Calculations
Bryn Lloyd, Dirk O. Gericke, Gilles Rodway-Gant et al. (+1 more)
The stopping power of charged particles is investigated using time-dependent density functional theory (TDDFT). Such simulations are made possible by recent advances in computational resources and numerical implementations of this first-principles method. In practice, DFT simulations widely employ the projector augmented-wave (PAW) method to approximate all-electron behaviour, but the implications of the PAW approximation for non-adiabatic stopping simulations remain insufficiently explored. Here, the suitability of the PAW method for stopping power simulations is evaluated. A workflow for generating and selecting PAW
datasets tailored to these simulations is developed, enabling systematic optimisation of augmentation radii and projector constructions. The approach is applied to
proton stopping in FCC aluminium, demonstrating how
dataset design influences stopping predictions, and enabling an investigation of
crystal channelling effects on charged-particle transport.
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All authors Bryn Lloyd, Dirk O. Gericke, Gilles Rodway-Gant, Gianluca Gregori
Materials Science
Javier Sivianes, Enrique Boquete-Someso, Daniel Hernangómez-Pérez et al. (+1 more)
The optical response of
magnetic materials is conventionally classified through
magnetic space groups (MSGs), where
spin and
lattice are locked by the relativistic
spin-orbit interaction. However, most optical observables are governed primarily by nonrelativistic physics, and thus a purely MSG-based description can overlook important insights. Here we systematically show that
spin-space groups (SSGs), which operate at the nonrelativistic level, provide a broader and more predictive framework for analyzing a variety of optical responses of magnets. Focusing on linear optical absorption, we derive the transformation rules imposed by SSGs and show that they generate effective real-space point groups, which can enforce relations among charge response coefficients that are absent from conventional MSG analysis. We illustrate the basic principle in a Lieb-
lattice altermagnet model with tunable
spin-orbit coupling, where SSG predictions on the linear dichroism remain remarkably accurate even when relativistic band splittings become sizable. We further establish the predictive power of this framework through first-principles calculations on two altermagnetic candidates: the actinide UCr2Si2C, where the optical absorption remains nearly isotropic despite its strong
spin-orbit coupling and the pronounced anisotropy apparent from
magnetic symmetries, and the transition-metal fluoride RbMnF4, where birefringence is confined to a single plane by
symmetries emerging exclusively from SSGs. Finally, we extend the concept to the
spin Hall response of the coplanar noncollinear antiferromagnet ScMnO3, where SSGs explain the hierarchy of calculated
spin Hall coefficients, demonstrating their direct relevance to spintronics as well.
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All authors Javier Sivianes, Enrique Boquete-Someso, Daniel Hernangómez-Pérez, Julen Ibañez-Azpiroz
Materials Science · Cross-listed from physics.chem-ph
Extracting a nitrile-centered, ether-assisted motif hierarchy for lithium-battery electrolyte design from billion-scale molecular space
Yifeng Xia, Guanghui Wang, Sining Wang et al. (+4 more)
Designing electrolyte molecules for lithium batteries requires balancing electronic stability with appropriate Li+ solvation, yet the structural basis remains unclear across chemically diverse molecules. High-throughput screening expands the searchable space, but ranked candidates alone do not reveal recurring motifs or their applicability limits. We searched nearly one billion GDB13 structures using electronic–solvation descriptors without explicit functional-group preferences or scaffold constraints. Across descriptor weights, high-ranking populations separated into a nitrile-dominant regime and a coexistence regime containing substantial fractions of both nitrile- and ether-containing molecules. These regimes together define a nitrile-centered, ether-assisted motif hierarchy: nitrile remains favored across broad weight ranges, whereas ether becomes prominent under stronger electrostatic and polarity constraints. Encoding this hierarchy in a generative model expands the candidate space beyond GDB13 and yields high-scoring fluorinated structures without an explicit fluorination reward. Explicit-solvent molecular dynamics simulations show weak, exchangeable coordination of representative candidates without displacing ethylene carbonate from the dominant first solvation shell around Li+; effects on ion association and transport depend on molecular structure and concentration. These results establish a quantitative, interpretable and physically bounded motif hierarchy that systematizes established nitrile and ether chemistry for lithium-battery electrolyte design.
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All authors Yifeng Xia, Guanghui Wang, Sining Wang, Wenting Chen, Zheng Cheng, Jinzhe Zeng, Qiangqiang Gu
Materials Science
Effect of Magnetic Vacancies on the Spontaneous Spin-Reorientation Transition in HoFe$_{1-x}$Al$_x$O$_3$ Single Crystals
S. A. Skorobogatov, V. A. Babkina, M. S. Pavlovskii et al. (+5 more)
In this work, we report the first growth of single
crystals of the substitution series HoFe$_{1-x}$Al$_x$O$_3$ with aluminium concentrations up to $x=0.2$ and investigate the
evolution of their spontaneous
spin-reorientation transition (SRT). Among rare-earth orthoferrites, HoFeO$_3$ exhibits a distinctive sequence of
magnetic phases ($\Gamma_4$-$\Gamma_{24}$-$\Gamma_{12}$-$\Gamma_2$). This complex sequence arises from the competition between the $K_{ac}$ and $K_{ab}$ anisotropies associated with the Ho$^{3+}$ ions and the effective
magnetic field produced by the weak ferromagnetic moment of the canted Fe$^{3+}$ sublattice. Introducing
magnetic vacancies perturbs the antiferromagnetic compensation of the Fe$^{3+}$ subsystem in the $ab$ plane and generates an additional effective
magnetic field acting on the Ho$^{3+}$ ions. This field alters the balance between the $K_{ac}$ and $K_{ab}$ anisotropies within the SRT temperature range and thereby broadens the stability range of the $\Gamma_{12}$ phase in the
magnetic phase diagram.
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All authors S. A. Skorobogatov, V. A. Babkina, M. S. Pavlovskii, M. I. Kolkov, S. V. Semenov, I. N. Khoroshiy, S. E. Nikitin, K. A. Shaykhutdinov
Materials Science
Dimensionality Mismatch Enables Decoupled Heat and Charge Transport
Luman Shang, Shuming Zeng, Chenhan Liu et al. (+1 more)
Decoupling heat and charge transport is a key challenge in thermoelectrics. Here, we identify a route to spatially separate
phonon and carrier transport in quasi-one-dimensional materials through high-throughput screening of the Materials Project database. Representative Sn$_2$S$_3$ and SbTeI exhibit a strong-intrachain–weak-interchain bonding hierarchy that favors
phonon propagation along the chains while suppressing transverse
lattice heat transport. In contrast, transverse valence-band states provide effective interchain electronic coupling and relatively light hole transport. This mismatch between
lattice and electronic transport dimensionalities produces an inverted thermal–electrical anisotropy. Across the screened candidates, interchain
lattice thermal conductivity is strongly suppressed, whereas hole transport remains weakly anisotropic or even favors the interchain direction. For SbTeI, this decoupling yields a maximum $zT$ of approximately 2.1 near 900~K. These results establish dimensionality mismatch as a general strategy for decoupling
phonon and carrier transport in thermoelectric materials.
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All authors Luman Shang, Shuming Zeng, Chenhan Liu, Yu Wu
Materials Science
Bond Disproportionation, Ligand Holes, and Persistent Spin Textures in Ag$_2$BiO$_3$
Atanu Paul, Subhadeep Bandyopadhay, Anupam Mondal et al. (+1 more)
The origin of the proposed bond disproportionated insulating state of the non-centrosymmetric ($Pnn2$) phase of Ag$_{2}$BiO$_{3}$ is explored using first principles electronic structure calculations. The novel insulating state is elucidated by first considering the initially proposed centosymmetric metallic ($Pnna$) phase of Ag$_{2}$BiO$_{3}$. Our calculations reveal that the valence skipping Bi$^{4+}$ ions in this phase are better described as Bi$^{3+}\underline{L}$ with completely filled Bi-(6$s$) states and a ligand hole. However,
phonon calculations indicate that the metallic ($Pnna$) state is dynamically unstable. Structural stability is achieved through breathing distortions of the oxygen octahedra, resulting in two inequivalent Bi sites and a reduction of
symmetry to the $Pnn2$ phase. Electronic structure calculations further reveal that the $Pnn2$ phase is a bond disproportionated
insulator where the nominal charge state of Bi is described by : 2[Bi$^{3+}\underline{L}$ (Bi$^{4+}$)] $\rightarrow$ Bi$^{3+}\underline{L}^{2-\delta}$ (Bi1$^{5+}$) + Bi$^{3+}\underline{L}^{\delta}$ (Bi2$^{3+}$), highlighting the crucial role of ligand holes in driving the insulating state. Next we have investigated the electronic structure of Ag$_{2}$BiO$_{3}$ in the insulating ($Pnn2$) phase including
spin-orbit coupling. Our density functional theory (DFT ) calculations complemented by ${\bf k.p}$ model
Hamiltonian analysis reveal persistent
spin-textures around the $X$ and $Y$ high
symmetry points of the orthorhombic Brillouin zone imposed by non-symmorphic
symmetry, positioning Ag$_{2}$BiO$_{3}$ as a promising candidate for spintronic applications.
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All authors Atanu Paul, Subhadeep Bandyopadhay, Anupam Mondal, Indra Dasgupta