Works matching IS 20573960 AND DT 2024 AND VI 10 AND IP 1
Results: 297
Accurate formation enthalpies of solids using reaction networks.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01404-5
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- Article
Unsupervised deep denoising for four-dimensional scanning transmission electron microscopy.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01428-x
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Phonon-limited mobility for electrons and holes in highly-strained silicon.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01425-0
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Fast prediction of anharmonic vibrational spectra for complex organic molecules.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01400-9
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- Article
Simple arithmetic operation in latent space can generate a novel three-dimensional graph metamaterials.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01430-3
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- Article
Tunable Schottky barriers and magnetoelectric coupling driven by ferroelectric polarization reversal of MnI<sub>3</sub>/In<sub>2</sub>Se<sub>3</sub> multiferroic heterostructures.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01429-w
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Quantum-accurate machine learning potentials for metal-organic frameworks using temperature driven active learning.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01427-y
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Light-harvesting properties of photocatalyst supports—no photon left behind.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01409-0
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Publisher Correction: Machine learning-aided first-principles calculations of redox potentials.
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- 2024
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- Correction Notice
Machine learning assisted screening of two dimensional chalcogenide ferromagnetic materials with Dzyaloshinskii Moriya interaction.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01419-y
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- Article
Ultrafast antiferromagnetic switching of Mn<sub>2</sub>Au with laser-induced optical torques.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01416-1
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Implementing numerical algorithms to optimize the parameters in Kampmann–Wagner Numerical (KWN) precipitation models.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01415-2
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Setting standards for data driven materials science.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01411-6
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- Article
Integrated modeling to control vaporization-induced composition change during additive manufacturing of nickel-based superalloys.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01418-z
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- Article
High-throughput screening of 2D materials identifies p-type monolayer WS<sub>2</sub> as potential ultra-high mobility semiconductor.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01417-0
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- Article
Mapping structure-property relationships in fullerene systems: a computational study from C<sub>20</sub> to C<sub>60</sub>.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01410-7
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- Article
Machine-learned coarse-grained potentials for particles with anisotropic shapes and interactions.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01405-4
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- Article
Computational screening of sodium solid electrolytes through unsupervised learning.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01392-6
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Data-driven discovery of dynamics from time-resolved coherent scattering.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01365-9
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MEPO-ML: a robust graph attention network model for rapid generation of partial atomic charges in metal-organic frameworks.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01413-4
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Unsupervised machine learning and cepstral analysis with 4D-STEM for characterizing complex microstructures of metallic alloys.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01414-3
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Theoretical approaches for the description of plasmon generated hot carriers phenomena.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01412-5
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Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01408-1
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Quantum embedding method with transformer neural network quantum states for strongly correlated materials.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01406-3
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- Article
Data-driven modeling of dislocation mobility from atomistics using physics-informed machine learning.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01394-4
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- Article
Emergence and transformation of polar skyrmion lattices via flexoelectricity.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01398-0
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Chemical-motif characterization of short-range order with E(3)-equivariant graph neural networks.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01393-5
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- Article
A unified moment tensor potential for silicon, oxygen, and silica.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01390-8
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- Article
Hidden magnetism and split off flat bands in the insulator metal transition in VO<sub>2</sub>.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01382-8
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Accelerating multiscale electronic stopping power predictions with time-dependent density functional theory and machine learning.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01374-8
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Construction frontier molecular orbital prediction model with transfer learning for organic materials.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01403-6
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Machine learning driven performance for hole transport layer free carbon-based perovskite solar cells.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01383-7
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- Article
Deep learning for symmetry classification using sparse 3D electron density data for inorganic compounds.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01402-7
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Bayesian optimization acquisition functions for accelerated search of cluster expansion convex hull of multi-component alloys.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01391-7
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Graph neural network coarse-grain force field for the molecular crystal RDX.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01407-2
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- Article
Towards end-to-end structure determination from x-ray diffraction data using deep learning.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01401-8
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- Article
Efficient simulations of charge density waves in the transition metal Dichalcogenide TiSe<sub>2</sub>.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01396-2
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Impact of heteroatoms and chemical functionalisation on crystal structure and carrier mobility of organic semiconductors.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01397-1
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- Article
Co-training machine learning enables interpretable discovery of near-infrared phosphors with high performance.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01395-3
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Accelerated discovery of eutectic compositionally complex alloys by generative machine learning.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01385-5
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- Article
High temperature ferrimagnetic semiconductors by spin-dependent doping in high temperature antiferromagnets.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01362-y
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- Article
Enhanced high harmonic efficiency through phonon-assisted photodoping effect.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01399-z
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- Article
Obtaining parallax-free X-ray powder diffraction computed tomography data with a self-supervised neural network.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01389-1
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- Article
Unraveling the electronic properties in SiO<sub>2</sub> under ultrafast laser irradiation.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01350-2
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- Article
A deep generative modeling architecture for designing lattice-constrained perovskite materials.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01381-9
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Machine learning surrogate for 3D phase-field modeling of ferroelectric tip-induced electrical switching.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01375-7
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- Article
Competing nucleation pathways in nanocrystal formation.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01371-x
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- Article
Distinct amorphization resistance in high-entropy MAX-phases (Ti, M)<sub>2</sub>AlC (M=Nb, Ta, V, Zr) under in situ irradiation.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01370-y
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CELL: a Python package for cluster expansion with a focus on complex alloys.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01363-x
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- Article
Developing new electrocatalysts for oxygen evolution reaction via high throughput experiments and artificial intelligence.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01386-4
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- Article