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Physics Condensed Matter Materials Science

cond-mat.mtrl-sci Watch Materials Science

Tuesday 5 May

Materials Science · Cross-listed from cs.LG

Capabilities of Auto-encoders and Principal Component Analysis of the Reduction of Microstructural Images; Application on the Acceleration of Phase-Field Simulations

Seifallah Fetni, Thinh Quy Duc Pham, Truong Vinh Hoang et al. (+4 more)

In this work, a data-driven framework based on Phase-Field simulations data is proposed to highlight the capabilities of neural networks to ensure accurate low dimensionality reduction of simulated microstructural images and to provide time-series analysis. The dataset was indeed constructed from high-fidelity Phase-Field simulations. Analyses demonstrated that the association of auto-encoder neural networks and principal component analyses leads to ensure efficient and significant dimensionality reduction: 1/196 of reduction ratio with more than 80% of accuracy. These findings give insight to apply analyses on data from the latent dimension. Application of Long Short Term Memory (LSTM) neural networks showed the possibility of making next frame predictions; that makes possible the acceleration of Phase-Field simulation without the need of high computing resources. We discussed the application of such a framework on various areas of research. Different methods are proposed from the conducted analyses, in order to ensure dimensionality reduction, including auto-encoders, principal component analysis and Artificial Neural Networks, and time-series analysis, including LSTM and Gated Recurrent Unit (GRU).
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All authors Seifallah Fetni, Thinh Quy Duc Pham, Truong Vinh Hoang, Hoang Son Tran, Laurent Duchêne, Xuan-Van Tran, Anne Marie Habraken

Materials Science

Magneto Transport and Spin Reorientation in Pt Co78Ho22 Heterostructures Near the Sublattice Compensation Temperature

Rajeev Nepal, Jose Flores, Aurain Seaton et al. (+3 more)

Metallic amorphous ferrimagnets of 3d transition metals (TM) and rare earths (RE) with 4f electrons exhibit rich magneto transport behavior due to the interplay between the 3d and 4f magnetic sublattices and their interaction with mobile charges. Tuning the TM and RE concentrations in the alloy can effectively modulate the compensation temperature, where the moments of the two sublattices point in opposite direction leading to a net zero magnetization. Despite extensive magnetotransport studies in Gd and Tb based 3d 4f systems, Ho based alloys remain comparatively underexplored, even though Ho possesses the largest orbital angular momentum (OAM) among the lanthanides. This unquenched OAM can strongly impact magnetic anisotropy and magnetotransport in ferrimagnetic heterostructures. Here, we have investigated the anomalous Hall resistivity , dc magnetization, and spin Hall magnetoresistance (SHMR) of Co78Ho22.Al film and a Pt.Co78Ho22.Al heterostructure deposited using multitarget magnetron sputtering. The Hall resistivity of both systems shows a distinct sign reversal and prominent wing-shaped hysteresis loops in the vicinity of the compensation temperature (Tcomp), which is accompanied by the minimum saturation magnetization near Tcomp. Furthermore, the SHMR in Pt.Co78Ho22.Al film is enhanced due to the Pt layer. These HM interface-induced prominent features of magneto-transport are addressed in the light of the existing theories of spin flop transitions, spin orbit torque, and microscopic phase separation, which may lead to the formation of 3d and 4f magnetic clusters in the film.
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All authors Rajeev Nepal, Jose Flores, Aurain Seaton, Michael Newburger, John Derek Demaree, Ramesh C Budhani

Materials Science

Initial Development of MBE-Grown InAs Diodes for Thermoradiative Energy Harvesting

I. Artacho, I. Ramiro and A. Martí

We describe the development of 1x1 mm2 InAs thermoradiative diodes grown by molecular beam epitaxy with emphasis on their reverse saturation current and break-down voltage. P-i-n diode structures grown at 450 C, with As2 flux around 3 times stoichiometry and an In effusion cell tip temperature 150 C higher than the base temperature, exhibit the best results with breakdown voltages above 0.3 V and reverse saturation current densities 200 times the radiative limit.
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Materials Science · Cross-listed from physics.optics

Neural-network reconstruction of THz transmission spectra using electrically tunable AlGaN/GaN plasmonic-crystal analyzer

A. Witkowska, M. Dub, P. Sai et al. (+4 more)

We demonstrate machine learning (ML) based reconstruction of terahertz transmission spectra using an electrically tunable grating-gate AlGaN/GaN plasmonic-crystal analyzer. The analyzer encodes the transmission spectrum into a voltage-dependent intensity, which is then inverted by an ML algorithm. A feedforward neural network trained on a synthetic dataset is validated experimentally on four samples in standard Fourier Transform Infrared (FTIR) mode and in direct (fixed-mirror) acquisition mode. The network achieves a mean square error (MSE) of the reconstruction of 0.015 in FTIR mode and 0.038 in direct mode, correctly identifying six out of seven ground-truth resonances in each mode. Against a first-difference Tikhonov regularization baseline, the mean reconstruction error is reduced 3.6 times in FTIR mode and 1.55 times in direct mode, with fewer spurious peaks and lower peak-position errors. Voltage-tunable plasmonic filtering combined with neural-network inversion establishes an interferometer-free architecture for THz spectral reconstruction.
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All authors A. Witkowska, M. Dub, P. Sai, P. Tiwari, M. Sakowicz, J. A. Majewski, W. Knap

Materials Science

The high K anomaly in ScAlN explained

Ilan Shalish

The integration of scandium aluminum nitride (ScAlN) into functional heterostructures has pushed semiconductor device physics into an extreme piezoelectric regime. Accurately determining the fundamental clamped dielectric permittivity (\epsilon_33^S) of these alloys remains a major challenge, as standard density functional theory systematically overestimates this specific parameter due to well-known bandgap-underestimation limits. Furthermore, electrical capacitance-voltage (C-V) measurements of real-world devices do not yield this clamped baseline; instead, they capture an effective permittivity inflated by linear electromechanical coupling. Because epitaxial thin films are unconstrained in the out-of-plane direction, small-signal electrical measurements dynamically induce macroscopic lattice strain via the inverse piezoelectric effect. By applying these specific mechanical boundary conditions to the coupled equations of state, we utilize the analytical relation for operational permittivity: \epsilon_eff=\epsilon_33^S+e_33^2/C_33. Leveraging highly accurate first-principles predictions for the structural and piezoelectric tensors, we invert this model to extract the true, uninflated clamped dielectric baseline directly from experimental thin-film data. This approach circumvents the conventional limitations of pure first-principles dielectric calculations, flawlessly resolving the theoretical-experimental discrepancy and providing a critical framework for accurate device simulation in highly polar nitrides.
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Materials Science

Spontaneous Topological Locking and Symmetry Restoration of Meron Lattices in Synthetic Antiferromagnets

Gülşen Doğan and Ümit Ak{\i}nc{\i}

Synthetic antiferromagnets offer a robust platform for stabilizing fractional topological textures, effectively circumventing the limitations of ferromagnetic systems. In this study, we utilize large-scale Monte Carlo simulations to investigate the spontaneous topological locking and structural symmetry restoration of meron-antimeron crystals within SAF bilayers subjected to easy-plane magnetic anisotropy. In the uncoupled monolayer limit, increasing anisotropy induces an extreme core-shrinking effect that physically expands the inter-core distance and triggers a $C_4 \rightarrow C_2$ symmetry breaking. However, the introduction of an ultra-weak interlayer antiferromagnetic exchange acts as an active structural scaffold. For rigid crystals, this coupling strictly enforces vertical synchronization, forming robust antiferromagnetic bimeron dipoles and fully restoring the macroscopic $C_4$ rotational symmetry. Furthermore, in highly expanded, pre-collapse crystals, we observe an anomalous interlayer-induced lattice compression that actively maximizes the exchange energy. At extreme anisotropy limits where macroscopic crystalline order irrecoverably collapses, the bilayer coupling continues to enforce a strict local topological locking of surviving isolated defects. These findings reveal a fundamental decoupling between local vertical synchronization and global structural order, providing a comprehensive theoretical roadmap for stabilizing and manipulating fractional topological textures in beyond-skyrmion spintronic architectures.
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Materials Science

Defect-Engineered Beryllium Dinitride (BeN2) Monolayer with Light-Metal Decoration for Reversible High-Capacity Hydrogen Storage

Wael Othman, Ibrahim Alghoul, K-F. Aguey-Zinsou et al. (+2 more)

Hydrogen (H2) possesses the highest gravimetric energy density of any chemical fuel and is the most abundant element in the universe. However, its extremely low volumetric energy density at standard conditions imposes a fundamental materials challenge for safe, efficient, and reversible storage. Here, we report a defect-engineered 2D beryllium dinitride (BeN2) monolayer that enables stable light-metal functionalization for high-capacity H2 storage. A 2 x 2 supercell containing two intrinsic beryllium vacancies accommodates four Li, Na, and K atoms without clustering, exhibiting strong average metal-vacancy binding energies of -3.80, -2.94, and -3.18 eV, respectively. Ab initio molecular dynamics simulations at 400 K confirm the thermal stability of the metal-decorated frameworks and the suppression of metal aggregation. The vacancy-stabilized alkali-metal centers generate localized charge polarization that facilitates the adsorption of up to 20 H2 molecules per supercell, with average adsorption energies of -0.182 eV (Li), -0.191 eV (Na), and -0.171 eV (K), making the adsorption reversible under near-ambient conditions. The corresponding gravimetric H2 storage capacities reach 11.64, 9.82, and 8.49 wt percent, respectively, significantly exceeding the US Department of Energy (DOE) ultimate target of 6.50 wt percent. Moreover, thermodynamic analysis further confirms favorable adsorption-desorption behavior within practical operating windows. These results establish vacancy-defected light-metal decorated BeN2 as a viable design strategy for high-density, reversible H2 storage, providing a scalable framework for engineering polar lightweight materials for energy storage applications.
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All authors Wael Othman, Ibrahim Alghoul, K-F. Aguey-Zinsou, Nacir Tit, Tanveer Hussain

Materials Science

A Correction Method for Crack Area Overestimation in Phase-Field Fracture

M. Castillón, J. Segurado and I. Romero

Phase-field fracture models are known to overestimate the crack area, a discrepancy that compromises the accuracy of fracture predictions. This issue stems from the diffuse crack representation and numerical artifacts, such as strain localization, where the phase-field variable artificially saturates across finite elements. Existing correction strategies, including mesh-dependent factors and skeletonization algorithms, have significant limitations. Mesh-based corrections are often unreliable for unstructured meshes, while skeletonization can be complex and inaccurate for intricate crack topologies, especially in three dimensions. This paper introduces a novel and robust framework to correct this overestimation. Our approach is founded on the principle of energy equipartition, where the energy contributions from the phase-field and its gradient are equal as the length-scale parameter approaches zero. Since numerical artifacts primarily affect the phase-field term while leaving the gradient term largely unperturbed, we propose that the crack area can be accurately approximated as twice the gradient-dependent energy. This method is inherently mesh-independent and readily applicable to the entire domain, including 3D simulations. The proposed methodology is validated against benchmarks with analytical solutions and compared with established methods like skeletonization to demonstrate its accuracy. It is then applied to complex geometries with curvilinear crack paths and evaluated in a three-dimensional simulation.
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Materials Science

Beyond lead halide perovskites: visible light photovoltaics with phase engineered bismuth-based oxide double-perovskites, Bi2MCrO6 (M = Fe, Mn)

N P Vikas, Ranjit K Pradhan, Somdutta Mukherjee et al. (+4 more)

Lead poisoning and notorious ambient instability in lead-based halide perovskites pave the way for the exploration of alternative materials for affordable and efficient solar cell fabrication. An important prerequisite to this end is the optoelectronic evaluation of the proposed material. Here we report, optoelectronic characterization of Bi2FeCrO6 (BFCO) and Bi2MnCrO6 (BMCO) thin films vis-à-vis performance of photovoltaic cells. Solution-deposited thin films (350-450 nm) of the above compositions demonstrate a double-perovskite structure with monoclinic P21/c symmetry, albeit with mixed cation valences and deep-level defects. A thorough optoelectronic evaluation exhibits large optical absorption in the visible range ({\alpha} ~ 104 -105 cm-1), and high carrier density, ~1017-20 cm-3. Ultraviolet photoelectron spectroscopy measurement allowed determination of the positions of the band-edges (valence band maximum and conduction band minimum), required for the selection of carrier transport layers. In its first, BMCO-based FTO/SnO2/BMCO/Spiro-OMeTAD/Ag solar cell produced a maximum 3.56% conversion efficiency. Using numerical simulation, we predict that with suitable defect control, the above conversion efficiency can increase significantly.
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All authors N P Vikas, Ranjit K Pradhan, Somdutta Mukherjee, Udai P Singh, Biplab K Patra, Ravi P Srivastava, Amritendu Roy

Materials Science

Deterministic positioning of circular Bragg gratings using atomic force lithography for high-performance quantum dot light sources

Sai Abhishikth Dhurjati, Moritz Langer, Yared G. Zena et al. (+6 more)

Semiconductor quantum dots (QDs) grown by molecular beam epitaxy are excellent quantum emitters, but their random spatial distribution hinders deterministic coupling to optical microcavities. We demonstrate a room-temperature atomic force microscopy (AFM)-assisted nano-oxidation lithography technique enabling QD positioning with a radial displacement of $51(28)$ nm. Free-standing asymmetric circular Bragg gratings incorporating AFM-positioned GaAs QDs exhibit a $245$-fold photoluminescence enhancement and fine-structure splitting (FSS) comparable to bulk QDs. Polarization-resolved spectroscopy and finite-difference time-domain simulations show robust emission for displacements up to $50$ nm (Stokes parameter $\lvert S \rvert < 0.05$ ). The devices display stable FSS and polarization imbalance below $5 \, \%$ , confirming precise, reproducible alignment and potential for high fidelity devices. This scalable approach enables deterministic integration of high-performance QDs with photonic cavities, advancing practical quantum light sources for quantum information technologies.
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All authors Sai Abhishikth Dhurjati, Moritz Langer, Yared G. Zena, Ahmad Rahimi, Liesa Raith, Martin Bauer, Frank H. P. Fitzek, Riccardo Bassoli, Caspar Hopfmann

Materials Science

Enhanced Valley Polarization via Nonlinear Cascaded Quantum-Geometric Selection Rules

Quentin Courtade, Sotirios Fragkos, Dominique Descamps et al. (+4 more)

The quantum geometric properties of Bloch electrons fundamentally govern light-matter interactions and optical selection rules in solids. In semiconducting transition-metal dichalcogenides, circularly polarized excitation near the band edge enables valley-selective interband transitions, providing the basis for valleytronics. While nonlinear optical protocols are being developed to manipulate and probe valley selection rules, they largely rely on band-edge transitions that proceed via virtual intermediate states. Here, we demonstrate a doubly resonant cascaded nonlinear pathway from the valence band to high-lying states, mediated by a real intermediate state whose participation substantially reshapes the valley optical selection rules. Using time- and angle-resolved extreme-ultraviolet photoemission spectroscopy in combination with a time-dependent Lindblad master-equation formalism, we show that this cascaded nonlinear photoexcitation produces a substantially enhanced high-lying valley polarization compared to the conventional linear optical response near the band edge. The extension of the quantum-geometry-based selection rules to the nonlinear regime and high-lying bands offers new perspectives for ultrafast valleytronics and should play a determinant role in strong-field-driven phenomena in quantum materials.
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All authors Quentin Courtade, Sotirios Fragkos, Dominique Descamps, Stéphane Petit, Yann Mairesse, Michael Schüler, Samuel Beaulieu

Materials Science

Pressure induced Electronic and Structural Transition in Ba$_2$NiTeO$_6$

Bidisha Mukherjee, Supratik Mukherjee, Mrinmay Sahu et al. (+5 more)

This study explores the pressure evolution of the double perovskite Ba$_2$NiTeO$_6$ by employing experimental and computational techniques. For the study of structural and vibrational properties, synchrotron X-ray diffraction (XRD) and micro-Raman spectroscopic experiments at high-pressures were carried out. As a complementary study, DFT simulations of the structural properties as a function of pressure were performed to support and explain the experimental findings. Furthermore, the electronic and magnetic properties as a function of pressure were investigated using DFT. Our study reveals a structural phase transition from a rhombohedral $R\bar{3}m$ to a monoclinic $C2/m$ phase at high pressure, accompanied by a significant increase in bulk modulus. Certain anomalies were observed in Raman mode frequencies at lower pressures of about 1 GPa, indicating changes in the electronic structure with a modification from direct to indirect bandgap in the sample. A minimum in the Raman mode full-width-half-maximum (FWHM) at about 11 GPa, coincides with an increase in ordering in the sample, indicated by a drop in the distortion index of Ni-O$_6$ octahedra as well as a discontinuity in the $c/a$ ratio.
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All authors Bidisha Mukherjee, Supratik Mukherjee, Mrinmay Sahu, Bhagyashri Giri, A C Gracia Castro, G Vaitheeswaran, Konstantin Glazyrin, Goutam Dev Mukherjee

Materials Science

Gauge-Field-Mediated Symmetry Breaking of Matters Under Electromagnetic Fields and Its Impact on Spin Dynamics

Uiseok Jeong, Esmaeil Taghizadeh Sisakht, Angel Rubio et al. (+3 more)

When a condensed-matter system is subjected to external electromagnetic fields, the gauge-invariant formulation of physical operators must explicitly incorporate the gauge-field contribution. However, in the context of spin-orbit coupling (SOC), this gauge-field term is often regarded as negligible or merely additive compared to the canonical SOC, which is typically localized near atomic cores. Here, we demonstrate that the symmetry breaking and consequent spin dynamics are governed by the gauge-field term, without which the spins remain symmetry-constrained. We perform real-time time-dependent density functional theory calculations to investigate spin-orbit dynamics, focusing on representative cases with mirror, glide, and screw-rotational symmetry. We demonstrate that when the gauge-field term in the time-dependent Hamiltonian perturbs the symmetry of the canonical term, a dynamical spin state gradually develops during the time evolution, beyond the symmetry-frozen states. We suggest that, for nonequilibrium spin-orbit dynamics, the gauge-invariant formulation of SOC is not only formally required but also quantitatively essential, even for a weak external field.
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All authors Uiseok Jeong, Esmaeil Taghizadeh Sisakht, Angel Rubio, Carsten A. Ullrich, Kyoung-Whan Kim, Noejung Park

Materials Science

Adjacent Sink Strengths Used in Multiscale Kinetic Rate Equation Simulations of Defects and Impurities in Solids

Tommy Ahlgren

Kinetic Rate Equation (kRE) modeling is widely used to simulate defect and impurity evolution in solids over experimentally relevant time and length scales. However, conventional kRE formulations include only random-position sink strengths, which adequately describe trapping of defects created at random lattice sites but fail to capture the enhanced retrapping of defects released directly adjacent to traps during detrapping or dissociation events. This omission leads to systematic errors, including underestimated thermal desorption (TDS) peak temperatures and incorrect kinetic parameters when fitting to experimental data. In this work, we derive for the first time analytical expressions for the adjacent sink strength, including correction for finite impurity diffusion jump length. We provide a practical implementation strategy for integrating these expressions into kRE simulations. Comparisons with kinetic Monte Carlo (kMC) benchmarks demonstrate that adjacent sink strengths dominate the retrapping probability and are essential for reproducing the correct temperature dependence of TDS release peaks. Simulations that employ only random sink strengths can still be tuned to match TDS spectra; however, the resulting fitted trapping energies, detrapping frequencies, and diffusion parameters are often physically inconsistent. The adjacent sink strength formulation introduced here significantly improves the predictive capability of kRE modeling, enabling accurate multiscale simulations of defect and impurity behavior in materials. This framework also establishes a foundation for future extensions, including adjacent sink strengths associated with extended defects such as dislocations and grain boundaries, offering new opportunities to resolve persistent discrepancies between experimental and simulated trapping energetics.
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Materials Science · Cross-listed from cond-mat.str-el

Influence of ligand field and correlation on the electronic structure of NiO and CoO from DFT+DMFT calculations

Daniel Mutter, Frank Lechermann, Daniel F. Urban et al. (+1 more)

The intriguing physics and rich application potential of strongly correlated first-row transition metal oxide compounds result from the complex interplay of several factors that influence the electronic structure. To shed light on the effect of composition, structure, and correlation strength, we apply a well-established charge self-consistent combination of density functional theory and dynamical mean field theory, which has proven to give electron binding energies in good agreement to experimentally derived excitation spectra. For paramagnetic NiO and CoO, we analyze the effect of rock-salt and zincblende structures and their different ligand fields on the spectral functions. By varying the value of the interaction parameter U, different correlation strengths among the transition-metal 3d electrons are considered, as well as the effect of additionally accounting for correlations in the oxygen 2p orbitals by a self-interaction-correction pseudopotential scheme. It is shown that this combined DFT+sicDMFT approach leads to spectral functions and band gaps close to experimental data, thereby offering a time-efficient alternative to using a fully correlated model which would treat both, metal and oxygen ligand electrons within DFT+DMFT.
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All authors Daniel Mutter, Frank Lechermann, Daniel F. Urban, Christian Elsässer

Materials Science

Scale-Dependent Input Representation and Confidence Estimation for LLMs in Materials Property Prediction

Shuichiro Ozawa, Izumi Takahara and Teruyasu Mizoguchi

Large language models (LLMs) are increasingly applied to materials science. However, the relationship between prediction accuracy, input representation, and model scale remains unclear, and reliable methods for assessing prediction confidence have not yet been established. In this study, we fine-tune two Llama models of different scales (1B and 8B) using low-rank adaptation (LoRA) on an inorganic crystal structure dataset. We systematically evaluate five input representations, namely chemical composition, crystal summary, local environment description, full text description, and crystallographic information files (CIF), for formation energy and bandgap prediction. Our results show that the optimal input representation depends on model scale. The 1B model performs better with compact representations, whereas the 8B model maintains high accuracy even with longer natural-language descriptions and CIF inputs. Across both model scales, crystal summaries that include space-group information consistently outperform composition-only inputs, indicating that symmetry information serves as a robust and informative feature. We further analyze the relationship between prediction error and the mean negative log-likelihood (mean NLL) of tokens corresponding to predicted numerical values. While no clear correlation is observed in base models, fine-tuned models exhibit a consistent trend in which lower mean NLL corresponds to smaller prediction errors. This result suggests that mean NLL can serve as a practical confidence indicator without requiring additional training. These findings demonstrate that both input representation and model scale play critical roles in LLM-based materials property prediction, and that mean NLL provides an effective and computationally efficient measure of prediction confidence.
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Materials Science · Cross-listed from cond-mat.mes-hall

First-principles prediction of chiral-phonon-induced orbital accumulation

A. Pezo, A. Manchon, Y. Nii et al. (+2 more)

Chiral phonons offer a route to transfer angular momentum without relying on magnetic order, but their electronic response in metals remains poorly understood from perspectives beyond spin-based scenarios. Using first-principles calculations, we show that coherent chiral lattice motion generates orbital accumulation and, through spin-orbit coupling, a smaller accompanying spin accumulation. Our approach evaluates orbital and spin expectation values directly from strain perturbed ab initio Hamiltonians in the long-wavelength limit, where the phonon perturbation is represented by symmetry adapted circular lattice distortions. We show that the response is controlled mainly by orbital character, near-degeneracies, and electron-phonon coupling, rather than by spin-orbit coupling alone. These results identify light transition metals as promising platforms for chiral-phonon-driven orbitronics.
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All authors A. Pezo, A. Manchon, Y. Nii, K. Ando, T. Kato

Materials Science

Influence of twist angle on ultrafast charge separation in WS2-graphene heterostructures

Niklas Hofmann, Leonard Weigl, Johannes Gradl et al. (+4 more)

Van der Waals (vdW) heterostructures, formed by stacking two-dimensional materials, offer highly tunable electronic and optical properties, with the twist angle between layers acting as a critical tuning parameter. While its impact on moiré patterns, band structure, and correlated states is well-established, the influence of twist angle on ultrafast charge transfer remains controversial. Here, we employ time- and angle-resolved photoemission spectroscopy (trARPES) to directly probe ultrafast charge transfer in epitaxially grown WS\textsubscript{2}-graphene heterostructures with twist angles of 0$^{\circ}$ and 30$^{\circ}$. Upon photoexcitation at $\hbar\omega = 3.1\,\mathrm{eV}$, we observe efficient charge separation at 0$^{\circ}$, while at 30$^{\circ}$, electron and hole transfer occur at similar rates. Our results highlight the crucial role of the twist angle in controlling charge separation efficiency, offering valuable insights for designing vdW heterostructures for applications in photovoltaics and optoelectronics.
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All authors Niklas Hofmann, Leonard Weigl, Johannes Gradl, Stiven Forti, Domenica Convertino, Camilla Coletti, Isabella Gierz

Materials Science

Energy dissipation at the atomic scale explains how fracture energy depends on crack velocity in silica glass

Marthe Grønlie Guren, Sigbjørn Løland Bore, François Renard et al. (+1 more)

The fracture energy of brittle materials rises with crack velocity, and this effect is typically attributed to surface roughening from path instabilities. Here we show, using molecular dynamics simulations of silica glass with a first-principles machine learned interatomic potential, that the structural fracture energy rises by up to 33 % already below the branching threshold, showing that fracture energy is not a constant material property. This rise in fracture energy is roughly equally partitioned between an increase in the intrinsic surface energy density and nanoscale roughening that increases the real fracture surface area. Results demonstrate that dynamic fracture in silica glass increases the fracture energy not merely by creating more apparent surface, but also by creating a fundamentally different surface at the nanoscale.
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All authors Marthe Grønlie Guren, Sigbjørn Løland Bore, François Renard, Henrik Andersen Sveinsson

Materials Science · Cross-listed from cond-mat.str-el

Nature of magnetism in bilayer nickelate La3Ni2O7 single crystals

Lixing Chen, Enkang Zhang, Yiqing Hao et al. (+10 more)

The recent discovery of high-temperature superconductivity in pressurized and thin film nickelates has generated intense interest, yet the nature of magnetism in their ambient-pressure parent phases remains poorly understood, despite its potentially crucial role in pairing. Here we use neutron scattering to resolve the spin order and dynamics of single-crystalline La3Ni2O7, an ambient-pressure parent of this class. Well defined spin excitations are observed at Q = (0, 0.5, 2.5), featuring a~5 meV spin gap and anisotropic in-plane dispersions, with zone-boundary softening along the transverse direction indicative of competing exchange interactions. The excitations exhibit pronounced out-of-plane modulations with bilayer periodicity, providing direct evidence for antiferromagnetic interlayer coupling. Their dispersion is well described by a bilayer Heisenberg Hamiltonian with strong interlayer exchange and competing in-plane couplings within a stripe-type magnetic order. Normalization of the spectra to absolute units reveals that, although the spin-wave bandwidth is only about 25% of that in cuprates, the local dynamic susceptibility at comparable energies is significantly enhanced, yielding a total fluctuating moment of comparable magnitude. These results highlight intense mid-energy spin excitations rooted in substantial electronic correlations as a defining feature of this family, establishing a magnetic framework distinct from cuprates and directly relevant to understanding superconductivity in this system.
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All authors Lixing Chen, Enkang Zhang, Yiqing Hao, Yinghao Zhu, Bingkun Cui, Douglas L. Abernathy, Travis J. Williams, Yoichi Ikeda, Hao Zhang, Feiyang Liu, Wenbin Wang, Qisi Wang, Jun Zhao

Materials Science

Coupled phase transitions in crystalline solids with extreme chemical disorder

Subha Dey, Rukma Nevgi, Suresh Chandra Joshi et al. (+13 more)

Structural phase transitions often couple to magnetic and electronic degrees of freedom, enabling emergent phenomena in solids. In high-entropy oxides (HEOs), which typically stabilize in highly symmetric cubic phases, such transitions are considered rare due to the extreme chemical disorder-analogous to the behavior observed in high-entropy alloys. This raises a fundamental question: can the rich physics of coupled phase transitions persist in such disordered systems? Here, we show that targeted design of compositionally complex oxides (CCOs) can trigger symmetry-lowering transitions, with spinel-type materials serving as a representative case. For instance, [Mn$_{0.2}$Co$_{0.2}$Ni$_{0.2}$Cu$_{0.2}$Zn$_{0.2}$]Cr$_2$O$_4$, having two Jahn-Teller (J-T) active ions, undergoes two successive coupled structural transitions upon cooling: an orbital-driven transition at 100 K and a magnetism-driven transition at 40 K. Systematic substitution of $A$-site cations reveals that both Ni and Cu are essential for these transitions. Element specific local structure investigations uncover distinct and opposing local distortions around Ni and Cu, while Mn, Co, and Zn remain largely undistorted. These results establish that CCOs can host coupled phase transitions through `cooperation via competition' among local distortions in a chemically disordered lattice. This discovery expands the design principles for complex oxides, introducing a new paradigm for tuning structural and functional properties in high-entropy systems beyond conventional symmetry constraints.
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All authors Subha Dey, Rukma Nevgi, Suresh Chandra Joshi, Sourav Chowdhury, Nandana Bhattacharya, Kashish Kapoor, Tinku Dan, Subhadip Chowdhury, Sabyasachi Karmakar, S. D. Kaushik, Shibabrata Nandi, Christoph Klewe, Manuel Valvidares, Moritz Hoesch, George E. Sterbinsky, Srimanta Middey

Monday 4 May

Materials Science · Cross-listed from physics.ins-det

Particulate analysis of post-thermal runaway soot of Li-ion battery using X-ray computed tomography

Avtar Singh and Donal P. Finegan

The microstructural characteristics of soot generated during thermal runaway events in lithium-ion batteries have been examined, with a focus on the associated health risks. X-ray computed tomography (Nano-CT) offers advanced 3D imaging for accurate analysis of particle shape, size, and distribution. Its primary benefit is the detection of core-shell structures that contain thin shell of carcinogenic materials. In contrast, traditional techniques like X-ray diffraction can only quantify the mass fraction of these hazardous phases, which is often minimal. Nevertheless, even a small mass fraction of carcinogenic materials on carbonaceous surfaces poses significant health risks when inhaled, potentially compromising internal organ function. This research underscores the need for a deeper understanding of particulate composition to inform safety regulations and respiratory protection measures.
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Materials Science · Cross-listed from cond-mat.soft

Quantifying the effects of particle clustering in random thermoelastic composites – numerical and mean-field analyses

Pawel Holobut, Michal Majewski and Katarzyna Kowalczyk-Gajewska

The effect of space distribution of randomly-placed particles in a representative composite volume on the thermoelastic effective properties and local stress and strain distribution is analyzed. Quantitative assessment is performed using both the full-field finite element analyses and the mean-field interaction model, known also as a ”cluster” model. The latter model is developed in the multi-family setting enabling one to study the mean stress and strain separately for each inclusion of the representative unit cell. The particles are assumed to be spherical and of equal size, while considered examples differ by the volume fraction of inclusions and mean nearest-neighbour distances.
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Materials Science · Cross-listed from cond-mat.mes-hall

Nonlinear Coherent Transport in 2D Thermal Metamaterials: From Solitons and Topological Defects to Quantum Computing

R. A. C. Correa, K. N. M. Sharma, P. Lolur et al. (+1 more)

Understanding heat transport in low-dimensional and nano-architectured materials remains a central challenge in nonequilibrium statistical physics due to persistent deviations from Fourier's law. These deviations are driven by anharmonicity, reduced dimensionality, and the emergence of long-lived coherent excitations. In this work, we develop a unified theoretical framework for two-dimensional thermal metamaterials that combines nonlinear lattice dynamics, soliton-based effective field theories, and geometrically organized defect networks as guiding structures for energy flow. We introduce minimal discrete and continuum-inspired models suitable for controlled benchmarking of thermal transport in patterned two-dimensional architectures and identify a two-channel transport mechanism in which coherent nonlinear excitations coexist with incoherent hydrodynamic modes. The interplay between these channels is shown to be highly sensitive to geometry, nonlinearity, and temperature, offering new avenues for thermal management. We establish rigorous connections between microscopic nonlinearity, geometry-driven channeling of heat in two dimensions, and quantum-enabled exploration of both high-occupation classical regimes and genuinely quantum regimes beyond the reach of standard simulation strategies. The theoretical predictions are corroborated by recent experimental and computational results in Stone-Wales-defected PdSSe monolayers and silicon phononic crystal nanostructures, which exhibit ultra-low thermal conductivity coexisting with high carrier mobility and strong anisotropy – direct manifestations of the two-channel mechanism. This synthesis provides actionable guidance for the design of engineered heat-spreading architectures and positions quantum simulation as a transformative tool for advancing the theory of nonlinear heat transport.
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All authors R. A. C. Correa, K. N. M. Sharma, P. Lolur, J. van Velzen

Materials Science

From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Aritra Roy, Kevin Shen, Andrew MacBride et al. (+350 more)

Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowledge. This paper analyzes a broad set of community-developed LLM applications in an effort to identify emerging patterns in how these systems can be used across the scientific research lifecycle. We organize the projects into two complementary categories: Knowledge Infrastructure, systems that structure, retrieve, synthesize, and validate scientific information; and Action Systems, systems that execute, coordinate, or automate scientific work across computational and experimental environments. The submissions reveal a shift from single-purpose LLM tools toward integrated, multi-agent workflows that combine retrieval, reasoning, tool use, and domain-specific validation. Prominent themes include retrieval-augmented generation as grounding infrastructure, persistent structured knowledge representations, multimodal and multilingual scientific inputs, and early progress toward laboratory-integrated closed-loop systems. Together, these results suggest that LLMs are evolving from general-purpose assistants into composable infrastructure for scientific reasoning and action. This work provides a community snapshot of that transition and a practical taxonomy for understanding emerging LLM-enabled workflows in materials science and chemistry.
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All authors Aritra Roy, Kevin Shen, Andrew MacBride, Awwal Oladipupo, Mudassra Taskeen, Wojtek Treyde, Ruaa A. E. A. Abakar, Ahmad D. Abbas, Elsayed Abdelfatah, Abbas A. Abdullahi, Seham S. Abyah, Chahd Rahyl Adjmi, Fariha Agbere, Savyasanchi Aggarwal, Muhammad Ahmed, Tasnim Ahmed, Motasem Ajlouni, Mattias Akke, Hussein AlAdwan, Anwaar S. Alazani, Zahra A. Alharbi, Wajd A. Aljulyhi, Mohammed A. AlKubaish, Fatima A. Almahri, Sayed A. Almohri, David Obeh Alobo, Mohammed Alouni, Azizah S. Alqahtani, Omar Alsaigh, Husain Althagafi, Md. Aqib Aman, Lena Ara, Arifin, Ignacio Arretche, Abdulaziz Ashy, Syeda A. Asim, Amro Aswad, Adeel Atta, Sören Auer, Abdullah al Azmi, Toheeb Balogun, Suvo Banik, Viktoriia Baibakova, Shakira A. Baksh, Neus G. Bastús, Christina J. Bayard, Adib Bazgir, Louis Beal, Lejla Biberić, Wahid Billah, Ankita Biswas, Joshua Bocarsly, Montassar T. Bouzidi, Esma B. Boydas, Youssef Briki, Cailin Buchanan, Mauricio Cafiero, Damien Caliste, Yi Cao, Rafael E. Castañeda, Sruthy K. Chandy, Benjamin Charmes, Shayantan Chaudhuri, Yiming Chen, Alexander Chen, Jieneng Chen, Min-Hsueh Chiu, Defne Circi, Cinthya H. Contreras, Yoann Cure, Nathan Daelman, Roshini Dantuluri, Thomas Davy, William Dawson, Leonid Didukh, Rui Ding, Aminu R. Doguwa, Claudia Draxl, Sathya Edamadaka, Oulaya Elargab, Christina Ertural, Matthew L. Evans, Edvin Fako, Hossam Farag, Nur A. Fathurrahman, Merve Fedai, Rodrigo P. Ferreira, Giuseppe Fisicaro, Thomas Frank, Sasi K. Gaddipati, Abhijeet Gangan, Jennifer Garland, James Garrick, Luigi Genovese, Maryam Ghadrdran, Sandip Giri, Maxime Goulet, Jeremy Goumaz, Sara U. Gracia, Jacob Graham, Gabriel Graves, Kevin P. Greenman, Tim Greitemeier, Cameron Gruich, Sophie Gu, Salomé Guilbert, Hans Gundlach, Muriel F. Gusta, Mourad El Haddaoui, Alexander J. Haibel, Anubhab Haldar, Vehaan Handa, Hassan Harb, Nathan D. Harms, Abdullah Al Hasan, Abir Hassan, Qiyao He, Andrés Henao-Aristizábal, Bram Hoex, Sungil Hong, Alexander J. Horvath, Md. Shaib Hossain, Yanqi Huang, Yuqing Huang, Kostiantyn Hubaiev, Donald Intal, Katherine Inzani, Kevin Ishimwe, Tugba Isik, Gopal R. Iyer, Katharina Jager, Jan Janssen, Hyewon Jeong, Michael Jirasek, Tyler R. Josephson, Nisarg Joshi, Yassir Ben Kacem, Remya A. M. Kalapurakal, Rakesh R. Kamath, Sugan Kanagasenthinathan, Dohun Kang, Jason Kantorow, Kübra Kaygisiz, Murat Keceli, Farhana Keya, Muhammad U. Khan, Sartaaj Takrim Khan, Hyungjun Kim, Alexander Kister, Sascha Klawohn, Collin Kovacs, Pranav Krishnan, Maurycy Kryzanowski, Ritesh Kumar, Suman Kumari, Gourav Kumbhojkar, Ryo Kuroki, Shashank Kushwaha, Magdalena Lederbauer, Jaejun Lee, Seunghan Lee, Jeonghwan Lee, Bingcan Li, Calvin Li, Zhanzhao Li, Shi Li, Shicheng Li, Chengyan Liu, Hao Liu, Tung Yan Liu, Yutong Liu, Lucia Vina-Lopez, Chayaphol Lortaraparsert, Andre K.Y. Low, Saffron Luxford, Carlos Madariaga, Rishikesh Magar, Piyush R. Maharana, Rahul Mallela, Shoaib Mahmud, Natesan Mani, Umair Mansoor, Omar B. Mansour, Cassandra Masschelein, Kinga O. Mastej, Ankit Mathanker, Jeffrey Meng, Omran Mezghani, Yidong Ming, Rishav Mitra, Michail Mitsakis, Matthew Miyagishima, Ravikumar Mohan, Naveen R. Mohanraj, Trupti Mohanty, Bernadette Mohr, Francisco A. Molina-Bakhos, Jeremy Monat, Seyed Mohamad Moosavi, Shayan Mousavi, Arman Moussavi, Rubel Mozumber, Muhammad J. Mufti, Diyana Muhammed, Ram Munde, Mrigi Munjal, José A. Márquez, Shankha Nag, Giacomo Nagaro, Juno Nam, Jose M. Napoles-Duarte, Ry Nduma, Xuan-Vu Nguyen, Ebrahim Norouzi, Oluwatosin Ohiro, Ryotaro Okabe, Viejay Ordillo, Shuichiro Ozawa, Sebastian Pagel, Daniel Palmer, Angela Pan, Akash Pandey, Vivek Pandit, Prakul Pandit, Chiku Parida, Jaehee Park, Hyunsoo Park, Hemangi Patel, Shakul Pathak, Taradutt Pattnaik, Elena Patyukova, Noah Paulson, Deepak S. Pendyala, Erick S. Pepek, Martin H. Petersen, Thang D. Pham, Aniket Phutane, Sabila K. Pinky, Étienne Polack, Alison Polasik, Maria Politi, Tim Pongratz, Akhila Ponugoti, Fabio Priante, Thomas Michael Pruyn, Sai S. Puppala, Mohammad A. Qazi, Heike Quosdorf, Gollam Rabby, Mohammad J. Raei, Md. Habibur Rahman, A.B.M. Ashikur Rahman, Subhashree Rajasekaran, Tawfiqur Rakib, Hemanth N. Ramesh, Vrushali Ranadive, Karnamohit Ranka, Bojana Rankovic, Adwaith Ravichandran, Ilija Rašović, Sergei Rigin, Tatem Rios, Varun Rishi, Victor Naden Robinson, Lucas S. Rodrigues, Oswaldo Rodriguez, Mahule Roy, Diptendu Roy, Subhas Roy, Arokia Anto Royan M, Joseph F. Rudzinski, Muhammad Sabih, Subramanyam Sahoo, Srusti Bheem Sain, Thahira Saliya, Vignesh Sampath, Jesus Diaz Sanchez, Arthur S. S. Santos, Muliady Satria, Hasan M. Sayeed, Jörg Schaarschmidt, Philippe Schwaller, Nofit Segal, Abhishec Senthilvel, Sherjeel Shabih, Devanshu Shah, Faezeh Shahmoradi, Samiha Sharlin, Killian Sheriff, Qiuyu Shi, Abubakar D. Shuaibu, Ayesha Siddiqua, M.A. Shadab Siddiqui, Darian Smalley, Benjamin Smith, Taylor D. Sparks, Daniel T. Speckhard, Elena Stojanovska, Akshay Subramanian, Jiwon Sun, Yunkai Sun, Abdul W. Syed, Souvik Ta, Izumi Takahara, Kelly Tallau, Guannan Tang, Ans B. Tariq, Sui X. Tay, Nurlybek Temirbay, Surya P. Tiwari, Febin Tom, Tajah Trapier, Kasidet J. Trerayapiwat, Samanvya Tripathi, Hawra H. Tuhaifa, Mustafa Unal, Mohammad Uzair, Vallabh Vasudevan, Estefania Vazquez, Victor Venturi, Rahul Verma, Ashwini Verma, Alvaro Vazquez-Mayagoitia, Nicholas Wagner, Araki Wakiuchi, Hao Wan, Liaoyaqi Wang, Wolfgang Wenzel, Alexander Wieczorek, Sze H. Wong, Yue Wu, Tong Xie, Andrew Yi, Ziqi Yin, Jodie A. Yuwono, Nahed A. Zaid, Mohd Zaki, Shehtab Zaman, Maimuna U. Zarewa, Mahtab Zehtab, Baosen Zhang, Wenyu Zhang, Melody Zhang, Yangfan Zhang, Yuwen Zhang, Runze Zhang, Zongmin Zhang, Huanhuan Zhao, Yuanlong Bill Zheng, Ramzi Zidani, Xue Zong, Ian Foster, Ben Blaiszik

Materials Science · Cross-listed from cond-mat.supr-con

Quantum Geometric Quadrupole of Cooper Pairs

Wenqin Chen, Kaijie Yang, Ting Cao et al. (+3 more)

The size of Cooper pairs defines a fundamental length scale of superconductivity, conventionally set by band dispersion and the superconducting gap. This picture breaks down in flat bands, where quenched dispersion makes quantum geometry essential. Here we develop a general framework based on the Cooper pair quadrupole moment, whose trace gives the pair size. The framework holds for both dispersive and flat-band cases, and provides a unified description of the geometric origin of this length scale. In particular, when time-reversal symmetry is broken, Berry curvature enters through the phase structure of the pair wavefunction and gives an essential contribution absent from previous quantum-metric theories. Together, Berry curvature and quantum metric impose a geometric lower bound on the pair size. Applying this framework to rhombohedral graphene, we find that the Berry-curvature-induced contribution can dominate and yields pair sizes comparable to experimentally inferred coherence lengths. These results identify Berry curvature as a central geometric ingredient controlling the microscopic length scale of superconductivity.
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All authors Wenqin Chen, Kaijie Yang, Ting Cao, Shi-Zeng Lin, Jiabin Yu, Di Xiao

Materials Science

Building a physics-aware AI ecosystem for solid-state hydrogen storage materials

Seong-Hoon Jang, Yiwen Yao, Chuanyu Liu et al. (+66 more)

Hydrogen storage remains a central bottleneck for scalable hydrogen energy systems due to the multiscale and coupled nature of the thermodynamics, kinetics, and microstructural evolution of hydrogen storage materials (HSMs). Although artificial intelligence (AI) has accelerated materials discovery, current approaches remain constrained by fragmented data, limited physical consistency, and weak integration with experimental validation. Here, we propose a unified framework that integrates coherent data infrastructure, physics-grounded modeling, and AI-driven inverse design within a closed-loop discovery paradigm. By embedding physical constraints and experimental feedback, this approach enables adaptive, physically consistent optimization, thereby establishing a pathway toward autonomous, digital-twin-enabled discovery of HSMs.
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All authors Seong-Hoon Jang, Yiwen Yao, Chuanyu Liu, Linda Zhang, Di Zhang, Xue Jia, Hung Ba Tran, Eric Jianfeng Cheng, Ryuhei Sato, Yusuke Ohashi, Toyoto Sato, Yusuke Hashimoto, Mark Allendorf, Nongnuch Artrith, Marcello Baricco, Andreas Borgschulte, Darren P. Broom, Ang Cao, Benjamin W. J. Chen, Lixin Chen, Ping Chen, Eun Seon Cho, Stefano Deledda, Zhao Ding, Martin Dornheim, Michael Felderhoff, Yaroslav Filinchuk, George E. Froudakis, Mingxia Gao, Thomas Gennett, Zaiping Guo, Ikutaro Hamada, Jason Hattrick-Simpers, Bjørn C. Hauback, Michael Hirscher, Torben R. Jensen, Baohua Jia, Hyoung Seop Kim, Takahiro Kondo, Kentaro Kutsukake, Xiao-Yan Li, Tongliang Liu, Piao Ma, Jianfeng Mao, Rana Mohtadi, Hyunchul Oh, Mark Paskevicius, Chris J. Pickard, Astrid Pundt, Anibal Ramirez-Cuesta, Hiroyuki Saitoh, Kaihang Shi, Aloysius Soon, Chenghua Sun, Chris Wolverton, Hiroshi Yabu, Weijie Yang, Zhenpeng Yao, Xuebin Yu, Jianxin Zou, Shouyi Hu, Panpan Zhou, Xi Lin, Zhigang Hu, Zhenhao Zhou, Pengfei Ou, Jiayu Peng, Shin-ichi Orimo, Hao Li

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

Tunable Mixed Parity Spin Splittings in Altermagnets

Yue Yu

Momentum-dependent spin splitting and its relation to inversion ($P$) and time-reversal ($T$) symmetries are central to nonrelativistic spintronics. Representative examples include collinear altermagnets with $(P,T)=(+,-)$ and non-collinear odd-parity magnets with $(P,T)=(-,+)$. In this work, we develop a theoretical framework to induce odd-parity spin splittings in the more abundant collinear altermagnets through two mechanisms: driving by a two-color linearly polarized light field or coupling to a $P$-odd loop-current order. Properly phase-locked two-color driving induces a static $(P,T)=(-,-)$ order, symmetry-equivalent to a translationally invariant $P$-odd loop-current order. Coupling this order to an altermagnet produces a controllable mixed-parity spin texture, opening new avenues for the electrical and optical manipulation of spin-polarized currents in spintronics applications. The same mechanism applied to a collinear $PT$-symmetric magnet induces a distinct $(P,T)=(+,+)$ state with a nonrelativistic dissipationless anomalous spin Hall conductivity. We present group-theory and microscopic Floquet theory to highlight the emergent responses.
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Materials Science

Structural evolution of Ti/Cu multilayers as a function of period thickness

Sergei S. Sakhonenkov, Aidar U. Gaisin, Anita O. Petrova et al. (+2 more)

Ti/Cu multilayers with periods ranging from 4 to 52.5 nm were synthesized by magnetron sputtering to examine how the period thickness affects morphology, crystallization, texture development, and preservation of periodicity. The structural evolution was analyzed using complementary transmission electron microscopy techniques with X-ray diffraction and reflectometry. The results show that the period thickness governs the balance between interfacial transition-region formation, crystallization, and growth-induced morphological instabilities. At the smallest period of 4 nm, the structure has strongly reduced periodic contrast, which may be attributed to extended interfacial regions, partial Cu-Ti intermixing, and suppression of well-defined layer formation. At 10 nm, the multilayer structure is preserved but remains affected by accumulated roughness and layer waviness; local modification of the Cu lattice is suggested to be significant relative to the bilayer period, likely due to mixed Cu-Ti interfacial regions and/or coherent strain. With increasing period, the multilayers become more regular, and the layers show progressive crystallization and texture development during growth. Cu crystallizes predominantly in the fcc structure with a strong Cu(111) contribution, whereas Ti exhibits a more complex structural evolution, from an amorphous or weakly crystallized state near the substrate toward a more ordered and textured state closer to the surface.
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All authors Sergei S. Sakhonenkov, Aidar U. Gaisin, Anita O. Petrova, Vasilii A. Matveev, Elena O. Filatova

Materials Science

Unified Mapping of Multi-Site Electrocatalytic Activity Using a Single Descriptor

A. Dana, D. Terrones, S. Gelin et al. (+1 more)

We present a precise and general method to map the activity of electrocatalysts across multiple sites. Starting from a mean-field statistical mechanics model, we introduce an effective adsorption free energy descriptor that explicitly incorporates lateral adsorbate-adsorbate interactions, enabling the construction of coverage-consistent volcano relationships. Extending this approach, we show that adsorption energetics and interaction strength define a two-dimensional activity landscape that gives rise to a "volcano ridge" that captures the coupled influence of binding and interactions on catalytic performance. For multi-site systems, we demonstrate that the inherently nonlinear coupling between distinct adsorption environments leads to multi-peaked activity trends that cannot be represented by conventional single-site descriptors. To address this, we introduce a reduced descriptor mapping that projects the multidimensional activity landscape onto a single effective coordinate while preserving the underlying physics of site heterogeneity and lateral interactions. The resulting framework generalizes Sabatier-type analysis to complex alloy catalysts and provides a physically interpretable route for screening electrocatalytic materials of arbitrary compositional complexity.
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All authors A. Dana, D. Terrones, S. Gelin, I. Dabo