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Prediction of room-temperature half-metallicity in layered halide double perovskites.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0252-6
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Phase-field lattice Boltzmann model for dendrites growing and moving in melt flow.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0250-8
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- Article
Publisher Correction: npj Computational Materials, volume 5.
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- 2019
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- Correction Notice
Non-glide effects and dislocation core fields in BCC metals.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0247-3
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Ab initio investigation of the cyclodehydrogenation process for polyanthrylene transformation to graphene nanoribbons.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0228-6
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Photorealistic modelling of metals from first principles.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. 1, doi. 10.1038/s41524-019-0266-0
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Machine learning guided appraisal and exploration of phase design for high entropy alloys.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. 1, doi. 10.1038/s41524-019-0265-1
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Attribute driven inverse materials design using deep learning Bayesian framework.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. 1, doi. 10.1038/s41524-019-0263-3
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- Article
Tailored morphology and highly enhanced phonon transport in polymer fibers: a multiscale computational framework.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. 1, doi. 10.1038/s41524-019-0264-2
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- Article
Coarse-graining auto-encoders for molecular dynamics.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. 1, doi. 10.1038/s41524-019-0261-5
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Deep-learning-based quality filtering of mechanically exfoliated 2D crystals.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. 1, doi. 10.1038/s41524-019-0262-4
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- Article
Parametrically constrained geometry relaxations for high-throughput materials science.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. 1, doi. 10.1038/s41524-019-0254-4
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Dodecagonal bilayer graphene quasicrystal and its approximants.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. 1, doi. 10.1038/s41524-019-0258-0
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Topological electronic states in HfRuP family superconductors.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. 1, doi. 10.1038/s41524-019-0260-6
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- Article
Multi-cell Monte Carlo method for phase prediction.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. 1, doi. 10.1038/s41524-019-0259-z
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- Article
Ferroelectric nonlinear anomalous Hall effect in few-layer WTe<sub>2</sub>.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0257-1
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- Article
A mechanism of defect-enhanced phase transformation kinetics in lithium iron phosphate olivine.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0255-3
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- Article
Continuous strengthening in nanotwinned diamond.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0256-2
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- Article
Ultralow lattice thermal conductivity of chalcogenide perovskite CaZrSe<sub>3</sub> contributes to high thermoelectric figure of merit.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0253-5
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- Article
Systematic beyond-DFT study of binary transition metal oxides.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0251-7
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- Article
Crowd-sourcing materials-science challenges with the NOMAD 2018 Kaggle competition.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0239-3
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- Article
Fast, accurate, and transferable many-body interatomic potentials by symbolic regression.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0249-1
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Reliable and explainable machine-learning methods for accelerated material discovery.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0248-2
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Recent advances and applications of machine learning in solid-state materials science.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0221-0
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Predicting superhard materials via a machine learning informed evolutionary structure search.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0226-8
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- Article
Smart machine learning or discovering meaningful physical and chemical contributions through dimensional stacking.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0222-z
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A comparative study using state-of-the-art electronic structure theories on solid hydrogen phases under high pressures.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0243-7
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- Article
Higher-order topological solitonic insulators.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0246-4
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- Article
Beyond the RPA and GW methods with adiabatic xc-kernels for accurate ground state and quasiparticle energies.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0242-8
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- Article
Topological phases in pyrochlore thallium niobate Tl<sub>2</sub>Nb<sub>2</sub>O<sub>6+x</sub>.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0245-5
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Ternary superconducting cophosphorus hydrides stabilized via lithium.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0244-6
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Identification of advanced spin-driven thermoelectric materials via interpretable machine learning.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0241-9
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Identification of stable adsorption sites and diffusion paths on nanocluster surfaces: an automated scanning algorithm.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0240-x
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- Article
Author Correction: Strain engineering of electro-optic constants in ferroelectric materials.
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- 2019
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- Publication type:
- Correction Notice
Absolute band alignment at semiconductor-water interfaces using explicit and implicit descriptions for liquid water.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0238-4
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De novo exploration and self-guided learning of potential-energy surfaces.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0236-6
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- Article
Body-centered-cubic structure and weak anharmonic phonon scattering in tungsten.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0235-7
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- Publication type:
- Article
The study of magnetic topological semimetals by first principles calculations.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0237-5
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- Article
Strong phonon localization in PbTe with dislocations and large deviation to Matthiessen's rule.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0232-x
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- Article
Tensorial stress−strain fields and large elastoplasticity as well as friction in diamond anvil cell up to 400 GPa.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0234-8
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- Article
Interpretable deep learning for guided microstructure-property explorations in photovoltaics.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0231-y
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- Article
High-performance bifunctional polarization switch chiral metamaterials by inverse design method.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0230-z
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- Article
Creating multiferroic and conductive domain walls in common ferroelastic compounds.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0229-5
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- Article
Charge disproportionation and site-selective local magnetic moments in the post-perovskite-type Fe<sub>2</sub>O<sub>3</sub> under ultra-high pressures.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0225-9
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Tracking materials science data lineage to manage millions of materials experiments and analyses.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0216-x
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Theoretical analysis of spectral lineshapes from molecular dynamics.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0220-1
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- Article
A property-oriented design strategy for high performance copper alloys via machine learning.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0227-7
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- Publication type:
- Article
Quantum topology identification with deep neural networks and quantum walks.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0224-x
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- Article
3D non-isothermal phase-field simulation of microstructure evolution during selective laser sintering.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0219-7
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- Article
Ab initio vibrational free energies including anharmonicity for multicomponent alloys.
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- NPJ Computational Materials, 2019, v. 5, n. 1, p. N.PAG, doi. 10.1038/s41524-019-0218-8
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- Article