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exaly
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Journals
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Npj Computational Materials
›
top-articles
Npj Computational Materials
9.6
(top 2%)
impact factor
1.0K
(top 20%)
papers
39.4K
(top 10%)
citations
84
(top 10%)
h
-index
9.6
(top 2%)
impact factor
1.3K
all documents
42.1K
doc citations
155
(top 5%)
g
-index
Top Articles
#
Title
Journal
Year
Citations
1
The ReaxFF reactive force-field: development, applications and future directions
Npj Computational Materials
2016
1,319
2
Recent advances and applications of machine learning in solid-state materials science
Npj Computational Materials
2019
1,289
3
The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies
Npj Computational Materials
2015
1,200
4
Machine learning in materials informatics: recent applications and prospects
Npj Computational Materials
2017
1,013
5
Review on modeling of the anode solid electrolyte interphase (SEI) for lithium-ion batteries
Npj Computational Materials
2018
961
6
A general-purpose machine learning framework for predicting properties of inorganic materials
Npj Computational Materials
2016
922
7
Understanding the physical metallurgy of the CoCrFeMnNi high-entropy alloy: an atomistic simulation study
Npj Computational Materials
2018
501
8
A review of oxygen reduction mechanisms for metal-free carbon-based electrocatalysts
Npj Computational Materials
2019
480
9
Computational understanding of Li-ion batteries
Npj Computational Materials
2016
411
10
A strategy to apply machine learning to small datasets in materials science
Npj Computational Materials
2018
404
11
On the tuning of electrical and thermal transport in thermoelectrics: an integrated theory–experiment perspective
Npj Computational Materials
2016
399
12
Precision and efficiency in solid-state pseudopotential calculations
Npj Computational Materials
2018
390
13
Plasmon-enhanced light–matter interactions and applications
Npj Computational Materials
2019
334
14
Active learning in materials science with emphasis on adaptive sampling using uncertainties for targeted design
Npj Computational Materials
2019
315
15
New frontiers for the materials genome initiative
Npj Computational Materials
2019
312
16
Machine learning enabled autonomous microstructural characterization in 3D samples
Npj Computational Materials
2020
308
17
Machine learning modeling of superconducting critical temperature
Npj Computational Materials
2018
274
18
Uncovering electron scattering mechanisms in NiFeCoCrMn derived concentrated solid solution and high entropy alloys
Npj Computational Materials
2019
251
19
Shift current bulk photovoltaic effect in polar materials—hybrid and oxide perovskites and beyond
Npj Computational Materials
2016
246
20
Statistical variances of diffusional properties from ab initio molecular dynamics simulations
Npj Computational Materials
2018
240
21
Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm
Npj Computational Materials
2019
234
22
Autonomy in materials research: a case study in carbon nanotube growth
Npj Computational Materials
2016
233
23
Interplay between Kitaev interaction and single ion anisotropy in ferromagnetic CrI3 and CrGeTe3 monolayers
Npj Computational Materials
2018
226
24
Recent advances and applications of deep learning methods in materials science
Npj Computational Materials
2022
207
25
On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events
Npj Computational Materials
2020
199
26
Computationally predicted energies and properties of defects in GaN
Npj Computational Materials
2017
196
27
Solving the electronic structure problem with machine learning
Npj Computational Materials
2019
191
28
Machine learning for perovskite materials design and discovery
Npj Computational Materials
2021
189
29
A universal strategy for the creation of machine learning-based atomistic force fields
Npj Computational Materials
2017
188
30
Discovery of new materials using combinatorial synthesis and high-throughput characterization of thin-film materials libraries combined with computational methods
Npj Computational Materials
2019
186
31
Theoretical prediction of high melting temperature for a Mo–Ru–Ta–W HCP multiprincipal element alloy
Npj Computational Materials
2021
186
32
The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design
Npj Computational Materials
2020
181
33
Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks
Npj Computational Materials
2019
177
34
Machine learning guided appraisal and exploration of phase design for high entropy alloys
Npj Computational Materials
2019
171
35
Atomistic Line Graph Neural Network for improved materials property predictions
Npj Computational Materials
2021
159
36
Efficient first-principles prediction of solid stability: Towards chemical accuracy
Npj Computational Materials
2018
157
37
Machine learning hydrogen adsorption on nanoclusters through structural descriptors
Npj Computational Materials
2018
156
38
Exchange-correlation functionals for band gaps of solids: benchmark, reparametrization and machine learning
Npj Computational Materials
2020
156
39
Inverse-designed spinodoid metamaterials
Npj Computational Materials
2020
151
40
Effective mass and Fermi surface complexity factor from ab initio band structure calculations
Npj Computational Materials
2017
145
41
Deep learning approach based on dimensionality reduction for designing electromagnetic nanostructures
Npj Computational Materials
2020
139
42
Genetic algorithms for computational materials discovery accelerated by machine learning
Npj Computational Materials
2019
136
43
Discovery of high-entropy ceramics via machine learning
Npj Computational Materials
2020
133
44
De novo exploration and self-guided learning of potential-energy surfaces
Npj Computational Materials
2019
132
45
Virtual screening of inorganic materials synthesis parameters with deep learning
Npj Computational Materials
2017
131
46
Identifying Pb-free perovskites for solar cells by machine learning
Npj Computational Materials
2019
129
47
Physics and applications of charged domain walls
Npj Computational Materials
2018
128
48
Coarse-graining auto-encoders for molecular dynamics
Npj Computational Materials
2019
122
49
Completing density functional theory by machine learning hidden messages from molecules
Npj Computational Materials
2020
121
50
Using machine learning and a data-driven approach to identify the small fatigue crack driving force in polycrystalline materials
Npj Computational Materials
2018
120
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