Ab initio informed electronic stopping models for light ion propagation in metalsUnderstanding ion-matter interactions at the atomistic level is key to advancing materials for the semiconductor industry, space systems, and nuclear fusion technologies. However, most atomistic…Evgeniia Ponomareva, Artur Tamm, Andrea E. Sand·Jul 29, 2026SaveLearn
Long-Range Machine Learning of Electron Density for Twisted Bilayer Moiré MaterialsMoiré superlattices in two-dimensional (2D) materials exhibit rich quantum phenomena, but ab initio modelling of these systems remains computationally prohibitive. Existing machine learning methods…Zekun Lou, Alan M. Lewis, Mariana Rossi·Jul 29, 2026SaveLearn
Thermodynamics-Informed Machine Learning for Energy Materials DiscoveryMachine learning (ML) is transforming materials discovery by enabling rapid prediction of properties that previously required computationally expensive first-principles calculations. Yet most current…Pol Benítez, Cibrán López, Claudio Cazorla·Jul 28, 2026SaveLearn
Dynamic phase-field model for brittle fracture in grounded glaciersFracture and calving of glaciers are key contributors to ice-mass loss and sea-level rise, yet predictive modeling remains challenging. Fracture in grounded glaciers is driven by gravitational forces…Aarosh Dahal, Umar Khayaz, Ravindra Duddu et al.·Jul 28, 2026SaveLearn
Soft-mode nonlinearities away from ferroelectric phase transitionThe interplay between ionic and electronic subsystems dictates the behavior of structural phase transitions in polar dielectrics, a coupling mediated by soft optical phonon modes. In incipient…Payel Shee, Ipek Efe, Jingwen Li et al.·Jul 28, 2026SaveLearn
The interplay of crystal-field transitions and exchange spin dynamics in a ferrimagnetRare-earth iron garnets offer an ideal platform for exploring the interplay of low-energy excitations and the complex temperature-dependent magnetization dynamics. In these systems, exchange coupling…Arpita Dutta, Pratyay Mukherjee, Ritwik Mondal et al.·Jul 28, 2026SaveLearn
Facet-Dependent Electronic Properties and Interfacial Point Defect Interactions in WS2/ZnO HeterostructuresAiming at two-dimensional materials for high-efficiency optoelectronics, WS2/ZnO heterostructures are computationally screened for their facet-dependent electronic properties and interfacial defect…Dedi Sutarma, Peter Kratzer·Jul 28, 2026SaveLearn
Accurate Prediction of the α β Phase Transformation Temperature in Tin via Full Anharmonic TreatmentPredicting the α β (grey-to-white) transition temperature in tin presents a longstanding challenge for atomistic simulations, with existing theoretical approaches over- or underestimating the…Petr Šesták, Matous Mrovec, Martin Friák·Jul 28, 2026SaveLearn
Stacking Polarity-Controlled Interlayer Photocarrier Dynamics in MoSe2/MoS2 HeterostructuresControl of interlayer photocarrier dynamics is central to optoelectronic applications of van der Waals heterostructures, yet deterministic and spatially uniform tuning strategies remain limited. Here…Gbenga S. Agunbiade, Ting Zheng, Hui Zhao·Jul 28, 2026SaveLearn
Pressure-Induced Irreversible Disorder in β-Mn3(PO4)2: A High-Pressure X-ray Diffraction and Density-Functional Theory StudyThe high-pressure structural behavior of β-Mn3(PO4)2 was investigated using synchrotron X-ray diffraction up to 20 GPa combined with density-functional theory calculations. At…Ana Melissa P. Brito, Neha Bura, Pablo Botella et al.·Jul 28, 2026SaveLearn
Integrating moment tensor potentials with finite-element modeling for heat transfer prediction in FLiBe-based molten salt systemsMolten fluoride salts are promising heat-transfer media for advanced molten salt reactors (MSRs), where reliable thermophysical property determination is critical for component design and safety. We…Mikhail Polovinkin, Ksenia Abramova, Oksana Rahmanova et al.·Jul 28, 2026SaveLearn
Laser induced optical reconfiguration in GeSbTe Films with composition dependent responsePhase change GeSbTe (GST) materials exhibit pronounced optical contrast and tunability driven by structural transformations, enabling a diverse range of photonic and optoelectronic applications.…M. Zhezhu, A. Vasilev, M. Sukiasyan et al.·Jul 28, 2026SaveLearn
Transformer Atomic Cluster Expansion: TRACEDesigning machine-learning interatomic potentials involves achieving the precise representation of complex many-body interactions alongside the efficiency required for scalable molecular dynamics. We…Paramvir Ahlawat·Jul 28, 2026SaveLearn
Ferroelectricity and antiferroelectricity in the BaS-PbS system with the rocksalt structureThe ferroelectric instability in superstructures, superlattices, quantum wires, and disordered solid solutions in the BaS--PbS system with the NaCl structure has been discovered and investigated…Alexander I. Lebedev·Jul 28, 2026SaveLearn
Imaging the Néel Vector in Two-Dimensional Antiferromagnets using Antisymmetric Compton ScatteringWe demonstrate that antisymmetric Compton scattering can detect both the switching and the continuous rotation of the Néel vector in two-dimensional (2D) antiferromagnets. By probing magnetoelectric…Wuxuan Li, Zhuocheng Lu, Jingshan Qi et al.·Jul 28, 2026SaveLearn
A Catalogue of Topological Moiré Bands in Twisted SemiconductorsTwisted two-dimensional semiconductors provide a route to flat and topological moiré minibands, but systematic principles for organizing their material dependence have remained unclear. Here, we…Jiaheng Li, Yan Zhang, Jiaxuan Liu et al.·Jul 28, 2026SaveLearn
Universal temperature-dependent electrical resistivity in actinidesTemperature-dependent electrical resistivity ρ(T) is one of the most common types of experimental data analyzed in condensed matter physics. For one group of pure metals, the actinides,…E. F. Talantsev·Jul 28, 2026SaveLearn
Giant Flat Band Amplification via Inertial AnchorsIn electronic materials, flat bands are associated with compact electron localization, with implications for superconductivity, ferromagnetism and strongly correlated systems. The physical…Wentao Mao, Stefano Gonella·Jul 28, 2026SaveLearn
mCGCNN: A Dual-Stream Crystal Graph Convolutional Neural Network for the Efficient Prediction of Magnetic Properties of Crystalline MaterialsMagnetic order in crystals is governed by moment-carrying sublattices and ligand-mediated exchange pathways, yet standard crystal graph neural networks treat all atoms homogeneously and encode bonds…Sourav Mal, Satadeep Bhattacharjee·Jul 28, 2026SaveLearn
Molecular reference corrections for quantum Monte Carlo adsorption energiesAccurate surface thermochemistry requires balanced error cancellation between extended slabs and molecular reference states. This balance can fail whenever the electronic-structure error is not…Roman Fanta, Michal Bajdich·Jul 28, 2026SaveLearn
A systematic study of single molecule metallocenes with 4d and 3d transition metal atomsThe realization of spin-based devices remains one of the central goals of spintronics research. Single-molecule magnets (SMMs) constitute an important class of nanoscale magnetic systems with…Daniela Herrera-Molina, Kushantha P. K. Withanage, Jesus N. Pedroza-Montero et al.·Jul 28, 2026SaveLearn
Identifying Contact Barrier Types in Few-Layer MoS2 Devices Using Correlative IV, LBIC, and Bias-Dependent KPFMElectrical contacts between metals and two-dimensional (2D) semiconductors such as molybdenum disulfide (MoS2) critically govern device performance, yet their microscopic nature remains difficult to…Ariane Ufer, Zeinab Eftekhari, Benjamin Mayer et al.·Jul 27, 2026SaveLearn
First-Principles Origins of Charge Transport in Molecular SemiconductorsCharge transport governs organic transistors and photovoltaics, yet predicting it from atomic structure remains challenging. Electron--phonon interactions span disparate frequencies, strengths and…Tong Jiang, Joonho Lee·Jul 27, 2026SaveLearn
Machine-Learning Potentials for sodium-potassium chloride mixtures: Predicting thermophysical properties and phase behavior of multicomponent saltsPredicting the properties of multicomponent molten salts using density functional theory (DFT) remains challenging because the spatial and temporal scales required to evaluate transport properties…Karim Zongo, Hao Sun, Zijian Meng et al.·Jul 27, 2026SaveLearn
MANDALA: An E(3)-Equivariant Graph Neural Network Framework for Learning Electronic-Structure Operators with Observable GuidanceElectronic-structure calculations based on Kohn-Sham density functional theory remain indispensable in computational materials science and chemistry. Their computational cost, however, limits…Bartosz Brzoza, Wiktoria Szopa, Zakaria Elabid et al.·Jul 27, 2026SaveLearn