Works matching IS 20573960 AND DT 2021 AND VI 7 AND IP 1
Results: 218
Microstructural impacts on ionic conductivity of oxide solid electrolytes from a combined atomistic-mesoscale approach.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00681-8
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- Article
Dipolar spin relaxation of divacancy qubits in silicon carbide.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00673-8
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Transition metal on topological chiral semimetal PdGa with tailored hydrogen adsorption and reduction.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00684-5
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p-Block elements for catalysis.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00680-9
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Elasticity-based-exfoliability measure for high-throughput computational exfoliation of two-dimensional materials.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00677-4
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Importance of charge self-consistency in first-principles description of strongly correlated systems.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00676-5
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Common microscopic origin of the phase transitions in Ta<sub>2</sub>NiS<sub>5</sub> and the excitonic insulator candidate Ta<sub>2</sub>NiSe<sub>5</sub>.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00675-6
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Specialising neural network potentials for accurate properties and application to the mechanical response of titanium.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00661-y
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Author Correction: Inverse design of two-dimensional materials with invertible neural networks.
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- 2021
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- Correction Notice
Linear-superelastic Ti-Nb nanocomposite alloys with ultralow modulus via high-throughput phase-field design and machine learning.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00674-7
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Reversal of the magnetoelectric effect at a ferromagnetic metal/ferroelectric interface induced by metal oxidation.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00679-2
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Glide symmetry protected higher-order topological insulators from semimetals with butterfly-like nodal lines.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00672-9
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Understanding X-ray absorption spectra by means of descriptors and machine learning algorithms.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00664-9
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- Article
Generalized stacking fault energy surface mismatch and dislocation transformation.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00660-z
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Inverse design of two-dimensional materials with invertible neural networks.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00670-x
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Chemical hardness-driven interpretable machine learning approach for rapid search of photocatalysts.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00669-4
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COPEX: co-evolutionary crystal structure prediction algorithm for complex systems.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00668-5
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- Article
Valley-filling instability and critical magnetic field for interaction-enhanced Zeeman response in doped WSe<sub>2</sub> monolayers.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00665-8
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On the possibility that PbZrO<sub>3</sub> not be antiferroelectric.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00671-w
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- Article
Degenerate topological line surface phonons in quasi-1D double helix crystal SnIP.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00667-6
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Bayesian optimization with adaptive surrogate models for automated experimental design.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00662-x
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Predicting the inhibition efficiencies of magnesium dissolution modulators using sparse machine learning models.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00658-7
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Unraveling energy and charge transfer in type-II van der Waals heterostructures.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00663-w
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A machine vision tool for facilitating the optimization of large-area perovskite photovoltaics.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00657-8
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Author Correction: Different types of spin currents in the comprehensive materials database of nonmagnetic spin Hall effect.
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- 2021
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- Correction Notice
Excitonic effects in absorption spectra of carbon dioxide reduction photocatalysts.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00640-3
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Benchmarking the performance of Bayesian optimization across multiple experimental materials science domains.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00656-9
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Rapid and flexible segmentation of electron microscopy data using few-shot machine learning.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00652-z
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Low-dimensional non-metal catalysts: principles for regulating p-orbital-dominated reactivity.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00654-x
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Atomistic Line Graph Neural Network for improved materials property predictions.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00650-1
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Towards prediction of ordered phases in rechargeable battery chemistry via group–subgroup transformation.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00653-y
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A scheme for simulating multi-level phase change photonics materials.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00655-w
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Exploring DFT+U parameter space with a Bayesian calibration assisted by Markov chain Monte Carlo sampling.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00651-0
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Deep Bayesian local crystallography.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00621-6
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Defect detection in atomic-resolution images via unsupervised learning with translational invariance.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00642-1
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Electron–plasmon and electron–magnon scattering in ferromagnets from first principles by combining GW and GT self-energies.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00649-8
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Glass transition temperature prediction of disordered molecular solids.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00647-w
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Prediction of thermoelectric performance for layered IV-V-VI semiconductors by high-throughput ab initio calculations and machine learning.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00645-y
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Tunable vertical ferroelectricity and domain walls by interlayer sliding in β-ZrI<sub>2</sub>.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00648-9
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Three-dimensional coherent X-ray diffraction imaging via deep convolutional neural networks.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00644-z
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Tuning two-dimensional electron and hole gases at LaInO<sub>3</sub>/BaSnO<sub>3</sub> interfaces by polar distortions, termination, and thickness.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00646-x
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AtomSets as a hierarchical transfer learning framework for small and large materials datasets.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00639-w
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Intertwined ferroelectricity and topological state in two-dimensional multilayer.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00643-0
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Ultrafast reorientation of the Néel vector in antiferromagnetic Dirac semimetals.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00641-2
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Efficient Gaussian process regression for prediction of molecular crystals harmonic free energies.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00638-x
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High-dimensional neural network potentials for magnetic systems using spin-dependent atom-centered symmetry functions.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00636-z
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Systematic coarse-graining of epoxy resins with machine learning-informed energy renormalization.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00634-1
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Different types of spin currents in the comprehensive materials database of nonmagnetic spin Hall effect.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00635-0
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- Article
Symmetry-aware recursive image similarity exploration for materials microscopy.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00637-y
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Comparing crystal structures with symmetry and geometry.
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- NPJ Computational Materials, 2021, v. 7, n. 1, p. 1, doi. 10.1038/s41524-021-00627-0
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