Works in NPJ Computational Materials, 2024, Vol 10, Issue 1
Results: 297
Highly sensitive 2D X-ray absorption spectroscopy via physics informed machine learning.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01313-7
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Author Correction: Emergent topological states via digital (001) oxide superlattices.
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- 2024
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- Correction Notice
Author Correction: Optimizing and extending ion dielectric polarizability database for microwave frequencies using machine learning methods.
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- 2024
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- Correction Notice
Computational morphogenesis for liquid crystal elastomer metamaterial.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01300-y
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Uncertainty-aware particle segmentation for electron microscopy at varied length scales.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01302-w
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Dynamic mode decomposition of nonequilibrium electron-phonon dynamics: accelerating the first-principles real-time Boltzmann equation.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01308-4
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Realization of 2D multiferroic with strong magnetoelectric coupling by intercalation: a first-principles high-throughput prediction.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01301-x
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Machine-learning structural reconstructions for accelerated point defect calculations.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01303-9
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Probabilistic physics-integrated neural differentiable modeling for isothermal chemical vapor infiltration process.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01307-5
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Predicting polymerization reactions via transfer learning using chemical language models.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01304-8
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Tailoring the quantum anomalous layer Hall effect in multiferroic bilayers through sliding.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01306-6
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The cage effect of electron beam irradiation damage in cryo-electron microscopy.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01299-2
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Elasto-plastic residual stress analysis of selective laser sintered porous materials based on 3D-multilayer thermo-structural phase-field simulations.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01296-5
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Active learning of ternary alloy structures and energies.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01256-z
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Data-driven optimization and machine learning analysis of compatible molecules for halide perovskite material.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01297-4
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An autonomous design algorithm to experimentally realize three-dimensionally isotropic auxetic network structures without compromising density.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01281-y
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NSGAN: a non-dominant sorting optimisation-based generative adversarial design framework for alloy discovery.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01294-7
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AI-enabled Lorentz microscopy for quantitative imaging of nanoscale magnetic spin textures.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01285-8
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Enhancing deep learning predictive models with HAPPY (Hierarchically Abstracted rePeat unit of PolYmers) representation.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01293-8
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Charge density wave ordering in NdNiO<sub>2</sub>: effects of multiorbital nonlocal correlations.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01298-3
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Na in diamond: high spin defects revealed by the ADAQ high-throughput computational database.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01292-9
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Machine learning-aided first-principles calculations of redox potentials.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01295-6
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Imaging and structure analysis of ferroelectric domains, domain walls, and vortices by scanning electron diffraction.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01265-y
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Deep learning with plasma plume image sequences for anomaly detection and prediction of growth kinetics during pulsed laser deposition.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01275-w
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Author Correction: The rule of four: anomalous distributions in the stoichiometries of inorganic compounds.
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- 2024
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- Correction Notice
Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01274-x
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Growing strings in a chemical reaction space for searching retrosynthesis pathways.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01290-x
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Strain engineering the spin-valley coupling of the R-stacking sliding ferroelectric bilayer 2H-VX<sub>2</sub> (X = S, Se, Te).
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01288-5
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Attention towards chemistry agnostic and explainable battery lifetime prediction.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01286-7
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Coexistence of superconductivity and topological phase in kagome metals ANb<sub>3</sub>Bi<sub>5</sub> (A = K, Rb, Cs).
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01291-w
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Multi-plane denoising diffusion-based dimensionality expansion for 2D-to-3D reconstruction of microstructures with harmonized sampling.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01280-z
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Machine learning-enabled chemical space exploration of all-inorganic perovskites for photovoltaics.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01270-1
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The Bell-Evans-Polanyi relation for hydrogen evolution reaction from first-principles.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01244-3
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Imaging and ferroelectric orientation mapping of photostriction in a single Bismuth Ferrite nanocrystal.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01287-6
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Towards accurate prediction of configurational disorder properties in materials using graph neural networks.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01283-w
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Compositional design and phase formation capability of high-entropy rare-earth disilicates from machine learning and decision fusion.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01282-x
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Pretraining of attention-based deep learning potential model for molecular simulation.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01278-7
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Complexity of many-body interactions in transition metals via machine-learned force fields from the TM23 data set.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01264-z
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JARVIS-Leaderboard: a large scale benchmark of materials design methods.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01259-w
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Machine learning-based prediction of polaron-vacancy patterns on the TiO<sub>2</sub>(110) surface.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01289-4
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Composition and state prediction of lithium-ion cathode via convolutional neural network trained on scanning electron microscopy images.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01279-6
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Active learning graph neural networks for partial charge prediction of metal-organic frameworks via dropout Monte Carlo.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01277-8
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Surface-dominated conductance scaling in Weyl semimetal NbAs.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01263-0
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Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01254-1
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Group IV topological quantum alloy and the role of short-range order: the case of Ge-rich Ge<sub>1–x</sub>Pb<sub>x</sub>.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01271-0
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Giant piezoelectricity driven by Thouless pump in conjugated polymers.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01269-8
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Towards atom-level understanding of metal oxide catalysts for the oxygen evolution reaction with machine learning.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01273-y
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High-throughput approach to explore cold metals for electronic and thermoelectric devices.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01267-w
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Giant and controllable nonlinear magneto-optical effects in two-dimensional magnets.
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- NPJ Computational Materials, 2024, v. 10, n. 1, p. 1, doi. 10.1038/s41524-024-01266-x
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Author Correction: Machine-learning potentials for nanoscale simulations of tensile deformation and fracture in ceramics.
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- 2024
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- Correction Notice