Works matching IS 20573960 AND DT 2017 AND VI 3 AND IP 1
Results: 54
First-principles screening of structural properties of intermetallic compounds on martensitic transformation.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0053-8
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Virtual screening of inorganic materials synthesis parameters with deep learning.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0055-6
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Publisher Correction: First-principles calculation of intrinsic defect chemistry and self-doping in PbTe.
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- 2017
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- Correction Notice
Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0048-5
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Chemomechanical modeling of lithiation-induced failure in high-volume-change electrode materials for lithium ion batteries.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0009-z
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Niobium pentoxide: a promising surface-enhanced Raman scattering active semiconductor substrate.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0008-0
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Computational modeling sheds light on structural evolution in metallic glasses and supercooled liquids.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0007-1
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Comparison of dissimilarity measures for cluster analysis of X-ray diffraction data from combinatorial libraries.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0006-2
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Machine learning in materials informatics: recent applications and prospects.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0056-5
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Author Correction: Chemically intuited, large-scale screening of MOFs by machine learning techniques.
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- 2017
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- Correction Notice
Theory, simulations and the design of functionalized nanoparticles for biomedical applications: A Soft Matter Perspective.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0050-y
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- Article
First-principles prediction of high-entropy-alloy stability.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0049-4
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- Article
First-principles calculation of intrinsic defect chemistry and self-doping in PbTe.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0047-6
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- Article
Rethinking phonons: The issue of disorder.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0052-9
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- Article
An efficient and accurate framework for calculating lattice thermal conductivity of solids: AFLOW—AAPL Automatic Anharmonic Phonon Library.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0046-7
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- Article
Chemically intuited, large-scale screening of MOFs by machine learning techniques.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0045-8
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- Article
Chemically induced large-gap quantum anomalous Hall insulator states in III-Bi honeycombs.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0044-9
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Voltage-driven charge-mediated fast 180 degree magnetization switching in nanoheterostructure at room temperature.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0043-x
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A universal strategy for the creation of machine learning-based atomistic force fields.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0042-y
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Metallic and highly conducting two-dimensional atomic arrays of sulfur enabled by molybdenum disulfide nanotemplate.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0041-z
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The origin of uniaxial negative thermal expansion in layered perovskites.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0040-0
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Ferroic glasses.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0039-6
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Learning surface molecular structures via machine vision.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0038-7
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Phonon broadening in high entropy alloys.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0037-8
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Inhomogeneous strain-induced half-metallicity in bent zigzag graphene nanoribbons.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0036-9
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Revealing and exploiting hierarchical material structure through complex atomic networks.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0035-x
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Atomic-scale structural signature of dynamic heterogeneities in metallic liquids.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0034-y
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Dynamics of antipolar distortions.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0033-z
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Construction of ground-state preserving sparse lattice models for predictive materials simulations.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0032-0
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Hydrogen embrittlement of grain boundaries in nickel: an atomistic study.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0031-1
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- Article
Dislocations interaction induced structural instability in intermetallic Al<sub>2</sub>Cu.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0030-2
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Ultra-large-scale phase-field simulation study of ideal grain growth.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0029-8
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Data analytics using canonical correlation analysis and Monte Carlo simulation.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0028-9
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Discovering the building blocks of atomic systems using machine learning: application to grain boundaries.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0027-x
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Empirical interatomic potentials optimized for phonon properties.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0026-y
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In silico designing of power conversion efficient organic lead dyes for solar cells using todays innovative approaches to assure renewable energy for future.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0025-z
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Atomic and electronic basis for the serrations of refractory high-entropy alloys.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0024-0
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Continuum understanding of twin formation near grain boundaries of FCC metals with low stacking fault energy.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0023-1
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Effect of nonlinear and noncollinear transformation strain pathways in phase-field modeling of nucleation and growth during martensite transformation.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0022-2
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Thermodynamic potential and phase diagram for multiferroic bismuth ferrite (BiFeO<sub>3</sub>).
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0021-3
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Understanding and designing magnetoelectric heterostructures guided by computation: progresses, remaining questions, and perspectives.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0020-4
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Facile measurement of single-crystal elastic constants from polycrystalline samples.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0019-x
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A review: applications of the phase field method in predicting microstructure and property evolution of irradiated nuclear materials.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0018-y
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A high-throughput framework for determining adsorption energies on solid surfaces.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0017-z
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A three-dimensional polyhedral unit model for grain boundary structure in fcc metals.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0016-0
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A phase field model for snow crystal growth in three dimensions.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0015-1
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Computationally predicted energies and properties of defects in GaN.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0014-2
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Effective mass and Fermi surface complexity factor from ab initio band structure calculations.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0013-3
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Mechanical properties of Fe-rich Si alloy from Hamiltonian.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0012-4
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Wide-range ideal 2D Rashba electron gas with large spin splitting in Bi<sub>2</sub>Se<sub>3</sub>/MoTe<sub>2</sub> heterostructure.
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- NPJ Computational Materials, 2017, v. 3, n. 1, p. N.PAG, doi. 10.1038/s41524-017-0011-5
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