High-density natural active sites for efficient nitrogen reduction on Kagome surfaces promoted by flat bands.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01663-w
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- Article
Works matching IS 20573960 AND DT 2025 AND VI 11 AND IP 1
Results: 156
1
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Human–AI collaboration for modeling heat conduction in nanostructures.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01657-8
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- Article
3
Layered multiple scattering approach to Hard X-ray photoelectron diffraction: theory and application.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01653-y
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- Article
4
Scalable training of neural network potentials for complex interfaces through data augmentation.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01651-0
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- Article
5
Theory of the divacancy in 4H-SiC: impact of Jahn-Teller effect on optical properties.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01609-2
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- Article
6
Simulating the dynamics of NV<sup>−</sup> formation in diamond in the presence of carbon self-interstitials.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01605-6
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- Article
7
Orbital-free density functionals based on real and reciprocal space separation.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01643-0
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- Article
8
Probabilistic phase labeling and lattice refinement for autonomous materials research.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01627-0
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9
Scalable machine learning approach to light induced order disorder phase transitions with ab initio accuracy.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01614-5
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- Article
10
Materials-discovery workflow guided by symbolic regression for identifying acid-stable oxides for electrocatalysis.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01596-4
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- Article
11
Inverse design of catalytic active sites via interpretable topology-based deep generative models.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01649-8
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- Article
12
Unified multimodal multidomain polymer representation for property prediction.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01652-z
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- Article
13
TiSe<sub>2</sub> is a band insulator created by lattice fluctuations, not an excitonic insulator.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01631-4
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14
Scaling Law of Sim2Real transfer learning in expanding computational materials databases for real-world predictions.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01606-5
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- Article
15
Publisher Correction: Atomistic simulations of out-of-equilibrium quantum nuclear dynamics.
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- 2025
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- Correction Notice
16
Electronic properties of stacking faults in Bernal graphite.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01641-2
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17
Unlocking the black box beyond Bayesian global optimization for materials design using reinforcement learning.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01639-w
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- Article
18
Unexpected density functional dependence of the antipolar Pbcn phase in HfO<sub>2</sub>.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01647-w
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19
Electro-chemo-mechanical modelling of structural battery composite full cells.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01646-x
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- Article
20
Computational discovery of metallic MBenes for two-dimensional semiconductor contacts approaching the quantum limit.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01640-3
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- Article
21
Interpretable machine learning for atomic scale magnetic anisotropy in quantum materials.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01637-y
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- Article
22
Crystal-like thermal transport in amorphous carbon.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01625-2
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- Article
23
Predicting practical reduction potential of electrolyte solvents via computational hydrogen electrode and interpretable machine-learning models.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01582-w
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- Article
24
Experimentally validated inverse design of FeNiCrCoCu MPEAs and unlocking key insights with explainable AI.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01600-x
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25
Ferroelectric control of diverse hyperbolic polaritons in the visible spectrum.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01644-z
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- Article
26
Charting electronic-state manifolds across molecules with multi-state learning and gap-driven dynamics via efficient and robust active learning.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01636-z
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- Article
27
Benchmarking machine learning models for predicting lithium ion migration.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01571-z
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- Article
28
Simulating magnetic transition states via string method in first principle calculation.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01603-8
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- Article
29
JAX-BTE: a GPU-accelerated differentiable solver for phonon Boltzmann transport equations.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01635-0
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- Article
30
Cartesian atomic moment machine learning interatomic potentials.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01623-4
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31
Multidimensional coherent spectroscopy of correlated lattice systems.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01619-0
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32
Polarization switching of HfO<sub>2</sub> ferroelectric in bulk and electrode/ferroelectric/electrode heterostructure.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01633-2
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- Article
33
Machine learned potential for high-throughput phonon calculations of metal—organic frameworks.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01611-8
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34
Dzyaloshinskii–Moriya interaction manipulation in multiferroic Janus monolayers.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01585-7
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35
Exhaustive screening of high-fold degenerate topological semimetal with chiral structure.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01624-3
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36
Unraveling charge effects on interface reactions and dendrite growth in lithium metal anode.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01615-4
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37
Ab initio mechanisms and design principles for photodesorption from TiO<sub>2</sub>.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01612-7
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38
Transferable machine learning model for multi-target nanoscale simulations in hydrogen-carbon system from crystal to amorphous.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01629-y
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39
An extensible open-source solution for research digitalisation in materials science.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01618-1
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40
Modeling extensive defects in metals through classical potential-guided sampling and automated configuration reconstruction.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01599-1
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41
Verification and validation of zero-point electron-phonon renormalization of the bandgap, mass enhancement, and spectral functions.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01587-5
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- Article
42
High throughput computational screening and interpretable machine learning for iodine capture of metal-organic frameworks.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01617-2
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43
Electron-mediated anharmonicity and its role in the Raman spectrum of graphene.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01610-9
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44
Strain and ligand effects in the 1-D limit: reactivity of steps.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01616-3
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45
Photoinduced ferroelectric phase transition triggering photocatalytic water splitting.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01601-w
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46
Advancing organic photovoltaic materials by machine learning-driven design with polymer-unit fingerprints.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01608-3
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47
A machine learning model with minimize feature parameters for multi-type hydrogen evolution catalyst prediction.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01607-4
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48
ELEQTRONeX: A GPU-accelerated exascale framework for non-equilibrium quantum transport in nanomaterials.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01604-7
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49
Uncertainty quantification for neural network potential foundation models.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01572-y
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50
Hierarchy-boosted funnel learning for identifying semiconductors with ultralow lattice thermal conductivity.
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- NPJ Computational Materials, 2025, v. 11, n. 1, p. 1, doi. 10.1038/s41524-025-01583-9
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- Article