SevenNet-Polar for MultiTask Prediction of Energy, Forces, Stress, and Born Effective Charges: Development and Application to ZrO2, Li3PO4, and PerovskitesAccurate prediction of the Born effective charge (BEC) tensor is crucial for modeling materials under electric fields but remains computationally expensive. To bridge this gap, we present…Anh Khoa Augustin Lu, Shungo Arai, Yutack Park et al.·Jul 21, 2026SaveLearn
A Magnon-Based Electric Field Controlled Magnetoelectric Device for Energy-Efficient Logic-in-MemoryWe demonstrate a non-volatile magnetoelectric magnonic memory (MEMM) that enables fully electrical write/read via direct magnon-driven sensing in an insulating antiferromagnet. A fabricated…Rongqing Cong, Sajid Husain, Yumin Su et al.·Jul 21, 2026SaveLearn
Dynamics of Long-lived Carriers in Molybdenum Carbide NanosheetsMolybdenum carbide (MoC) is a promising candidate for substituting expensive platinum-group metals in many applications owing to its low cost and excellent properties, therefore a comprehensive…Xiangyu Zhu, Zhong Wang, Tao Li et al.·Jul 21, 2026SaveLearn
Trans-scale spin Seebeck effect in nanostructured bulk composites based on magnetic insulatorThe spin Seebeck effect (SSE) enables thermoelectric conversion through thermally generated spin currents in magnetic materials, offering a promising transverse geometry for scalable devices.…Sang J. Park, Keisuke Hirata, Hossein Sepehri-Amin et al.·Jul 21, 2026SaveLearn
Bayesian inference of composition-dependent phase diagramsPhase diagrams serve as a highly informative tool for materials design, encapsulating information about the phases that a material can manifest under specific conditions. In this work, we develop a…Timofei Miryashkin, Olga Klimanova, Vladimir Ladygin et al.·Jul 21, 2026SaveLearn
Effect of independent parameters on nanoparticle sizes in magnetron-sputtering inert-gas condensationMagnetron-sputtering inert-gas condensation (MS-IGC) provides a scalable, environmentally friendly vapour-phase synthesis approach for preparing customised nanoparticles (NPs) with bespoke properties…Yizhou Wang, Evropi Toulkeridouc, Abisegapriyan K. S et al.·Jul 20, 2026SaveLearn
GQD-AdsNet: Graph Neural Networks Unlock Rapid Exploration of Transition Metal Adsorption on Graphene Quantum DotsIn recent years, interest in single-atom catalysts supported on carbon-based structures has grown considerably due to their high catalytic activity and efficient uses of metal atoms. However, the…Lara Goncebat, Rodrigo Echeveste, Matías Gerard et al.·Jul 20, 2026SaveLearn
Battery Material Comparisons Should Refocus on Diffusivity with Best PracticesThe continuous demand for improved batteries motivates the discovery and advancement of materials with improved transport. Ionic diffusivity is the relevant material property where its measurement…CJ Sturgill, Roya Rajabi, Md Abdullah Al Muhit et al.·Jul 20, 2026SaveLearn
Data-Efficient Training of Linear ACE Potentials through Leverage-Guided Subset Selection of ASSYST Structure PoolsThe construction of machine-learned interatomic potentials (MLIPs) is often limited by the cost of generating large density-functional-theory (DFT) training datasets. For systematically generated…Aynour Khosravi, Marvin Poul, Jörg Neugebauer et al.·Jul 20, 2026SaveLearn
Vacancy Diffusion Across FeCrAl Alloy Composition Space for Accident-Tolerant Fuel CladdingIron-chromium-aluminium (FeCrAl) alloys are leading candidates for accident-tolerant fuel cladding in light-water reactors, where their superior high-temperature oxidation resistance promises to…Mihai Pitigoi, Peter Hatton·Jul 20, 2026SaveLearn
Electron escape probability in high-efficiency photocathodes measured by reverse-injection photovoltageThe characterization of electron transfer through the emitting surface is of crucial importance for optimizing existing and developing new photocathodes. Here we propose and develop a method for the…S. A. Rozhkov, D. A. Kustov, V. V. Bakin et al.·Jul 20, 2026SaveLearn
Towards a universal model for spin-orbit coupled Wannier HamiltoniansWhile machine learning interatomic potentials (MLiPs) have matured to revolutionize material science, deep learning models for electronic structure are just beginning to emerge and restricted, almost…Alexander C. Tyner·Jul 20, 2026SaveLearn
Excitonic effects in the photocarriers dynamics of two-dimensional materialsWe investigate the role of excitonic correlations in shaping the ultrafast dynamics of photoexcited carriers in semiconductors. Conventional approaches describe relaxation within single-particle…Carlos Betancur, Gianluca Stefanucci, Enrico Perfetto·Jul 20, 2026SaveLearn
Machine Learning Potential-Driven Molecular Dynamics Simulations of Dehydrogenation in Pristine and Doped MgH2Machine learning potential-driven molecular dynamics simulations (ML-MD) were employed to provide atomistic insights into the dehydrogenation kinetics of pristine and doped MgH2. Through systematic…Bo Han, Jianchuan Wang, Rui Zhang et al.·Jul 20, 2026SaveLearn
Phase-field modeling of TiO2 nanocarving via reaction with hydrogen-bearing gasTiO2 nanocrystals can be fabricated by carving the TiO2 bulk polycrystals using reductive H2-bearing gases, yielding single-crystal [001] nanowire arrays. However, the origin of the strongly…Alireza Seifi, Sheikh Akbar, Yanzhou Ji·Jul 20, 2026SaveLearn
Defect configuration, not nitrogen content, governs the mechanical integrity of nitrogen-doped graphene: a molecular dynamics studyThe mechanical reliability of nitrogen-doped graphene is often attributed to its nitrogen content, yet nitrogen occurs in chemically distinct configurations whose individual mechanical roles, and…Indranil Rudra, Jahid Emon, A. K. M. Monjur Morshed·Jul 20, 2026SaveLearn
Study of ordering in (MoCrTi)100-xAlx refractory high-entropy alloys using machine learning interatomic potentialRefractory high-entropy alloys are promising candidates for high-temperature applications, yet the effects of composition on their chemical-ordering pathways and mechanical properties remain…Jiyao Zhang, Klemens Lechner, Markus Maßwohl et al.·Jul 20, 2026SaveLearn
Correcting DFT formation energies towards experimental accuracy using foundational MLIPs and latent-feature delta-learningCrystal structure databases curated by high-throughput density functional theory calculations typically serve as the starting point for computational materials discovery efforts. Thermodynamic…Timo Reents, Marnik Bercx, Giovanni Pizzi·Jul 20, 2026SaveLearn
First-principles electronic transport properties of Ti and Ti-6Al-4V for modeling ultrashort-pulse laser ablationPredictive modeling of ultrashort-pulse laser ablation requires temperature-dependent material parameters derived from the electronic structure, namely the electronic thermal conductivity,…Korbinian Hobmaier, Guillaume E. Allemand, Alberto Marmodoro et al.·Jul 20, 2026SaveLearn
DFT+U+V is equivalent to DFT+U with density-dependent hybridized projectorsHubbard-corrected density-functional theory (DFT+U) is a popular tool for first-principles modeling of materials with localized d or f electrons, but its on-site corrections tend to…Edward Linscott, Alberto Carta, Nicola Marzari·Jul 20, 2026SaveLearn
Foundry CMOS platform for multimodal quantum materials characterizationQuantum materials experiments increasingly rely on microwave, electrical, thermal, optical, and structural probes, but these capabilities are typically assembled from custom hardware that limits…Sharad Kumar Yadav, Luca Nessi, Ondrej Dyck et al.·Jul 20, 2026SaveLearn
Spin-phonon interaction in a symmetry-enforced spin-polarized stateSymmetry-governed magnetic materials have emerged as a promising platform for spintronic functionalities without net magnetization or stray magnetic fields, motivating the exploration of how lattice…Suman Kalyan Pradhan, Dayal Das, Shubham Patel et al.·Jul 20, 2026SaveLearn
Informatics Modeling of High Tg Polymers: Assessing the Role of Processing versus ChemistryDespite the advances in structure-based modeling of polymer properties, accurately predicting glass transition temperature (Tg) is still challenging for polymers whose behavior is strongly influenced…Qinrui Liu, Scott R. Broderick·Jul 20, 2026SaveLearn
The Recurrent Structural Frameworks of Stable Inorganic MaterialsThe number of possible crystal structures vastly exceeds the number realized among thermodynamically stable inorganic materials, suggesting that experimentally accessible structure space is organized…Roee Asher, Nadav Moav, Lee A. Burton·Jul 20, 2026SaveLearn
Chemical filters for ultra-high-throughput materials screening and generationGenerative artificial intelligence is rapidly transforming materials design by enabling de novo exploration of immense chemical spaces. Yet a large proportion of AI-generated compositions remain…Kinga O. Mastej, Panyalak Detrattanawichai, Hyunsoo Park et al.·Jul 20, 2026SaveLearn