Works matching IS 20573960 AND DT 2023 AND VI 9 AND IP 1
Results: 236
An interpretable machine learning strategy for pursuing high piezoelectric coefficients in (K<sub>0.5</sub>Na<sub>0.5</sub>)NbO<sub>3</sub>-based ceramics.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01187-1
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- Article
Finite-temperature screw dislocation core structures and dynamics in α-titanium.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01181-7
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- Article
Finite-temperature screw dislocation core structures and dynamics in α-titanium.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01181-7
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- Article
Machine learning for automated experimentation in scanning transmission electron microscopy.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01142-0
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- Article
The innate interfacial elastic strain field of a transformable B2 precipitate embedded in an amorphous matrix.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01182-6
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Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01180-8
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- Article
Exploitable magnetic anisotropy and half-metallicity controls in multiferroic van der Waals heterostructure.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01178-2
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Many-body potential for simulating the self-assembly of polymer-grafted nanoparticles in a polymer matrix.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01166-6
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- Article
Atomistic fracture in bcc iron revealed by active learning of Gaussian approximation potential.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01174-6
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A rule-free workflow for the automated generation of databases from scientific literature.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01171-9
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Dual activation and C-C coupling on single atom catalyst for CO<sub>2</sub> photoreduction.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01177-3
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Mechanical-electrical-chemical coupling study on the stabilization of a hafnia-based ferroelectric phase.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01176-4
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- Article
Tunable ferroelectricity in oxygen-deficient perovskites with Grenier structure.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01175-5
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- Article
A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01173-7
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- Article
Coherent and semicoherent α/β interfaces in titanium: structure, thermodynamics, migration.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01170-w
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Towards understanding structure–property relations in materials with interpretable deep learning.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01163-9
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Automated classification of big X-ray diffraction data using deep learning models.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01164-8
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Full-scale ab initio simulations of laser-driven atomistic dynamics.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01168-4
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Physics-informed neural networks for solving time-dependent mode-resolved phonon Boltzmann transport equation.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01165-7
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Structure and properties of graphullerene: a semiconducting two-dimensional C<sub>60</sub> crystal.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01167-5
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Author Correction: A machine learning enabled hybrid optimization framework for efficient coarse-graining of a model polymer.
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- 2023
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- Correction Notice
Exciton fine structure in twisted transition metal dichalcogenide heterostructures.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01145-x
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Topological superconductor candidates PdBi<sub>2</sub>Te<sub>4</sub> and PdBi<sub>2</sub>Te<sub>5</sub> from a generic ab initio strategy.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01144-y
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Parametric simulation of electron backscatter diffraction patterns through generative models.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01143-z
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The best thermoelectrics revisited in the quantum limit.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01141-1
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Infrared-active phonons in one-dimensional materials and their spectroscopic signatures.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01140-2
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Realizing unipolar and bipolar intrinsic skyrmions in MXenes from high-fidelity first-principles calculations.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01129-x
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A Continuous Action Space Tree search for INverse desiGn (CASTING) framework for materials discovery.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01128-y
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Circumventing the phonon bottleneck by multiphonon-mediated hot exciton cooling at the nanoscale.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01102-8
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Machine learning force fields for molecular liquids: Ethylene Carbonate/Ethyl Methyl Carbonate binary solvent.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01100-w
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Ultra-fast interpretable machine-learning potentials.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01092-7
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The γ/γ′ microstructure in CoNiAlCr-based superalloys using triple-objective optimization.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01090-9
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Enhancing the Faradaic efficiency of solid oxide electrolysis cells: progress and perspective.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01044-1
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Development of a radical polymerization algorithm for molecular dynamics simulations of antifreezing hydrogels with double-network structures.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01161-x
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Publisher Correction: Crystal structure prediction at finite temperatures.
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- 2023
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- Correction Notice
Projectability disentanglement for accurate and automated electronic-structure Hamiltonians.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01146-w
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Automated mixing of maximally localized Wannier functions into target manifolds.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01147-9
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Trajectory sampling and finite-size effects in first-principles stopping power calculations.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01157-7
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Prediction of Van Hove singularity systems in ternary borides.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01156-8
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- Article
Rational design of large anomalous Nernst effect in Dirac semimetals.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01159-5
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Controlling the magnetic state of the proximate quantum spin liquid α-RuCl<sub>3</sub> with an optical cavity.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01158-6
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Efficient screening framework for organic solar cells with deep learning and ensemble learning.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01155-9
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Divide and conquer: Machine learning accelerated design of lead-free solder alloys with high strength and high ductility.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01150-0
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- Article
Parametric simulation of electron backscatter diffraction patterns through generative models.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01143-z
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- Publication type:
- Article
Symmetry-driven half-integer conductance quantization in Cobalt–fulvalene sandwich nanowire.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01151-z
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- Article
Crystal structure prediction at finite temperatures.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01120-6
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Lanthanide molecular nanomagnets as probabilistic bits.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01149-7
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- Article
A machine learning method to quantitatively predict alpha phase morphology in additively manufactured Ti-6Al-4V.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01152-y
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- Publication type:
- Article
Infrared-active phonons in one-dimensional materials and their spectroscopic signatures.
- Published in:
- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01140-2
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- Publication type:
- Article
Primitive to conventional geometry projection for efficient phonon transport calculations.
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- NPJ Computational Materials, 2023, v. 9, n. 1, p. 1, doi. 10.1038/s41524-023-01148-8
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