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Npj Computational Materials
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Top Articles
Npj Computational Materials
Physics
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Chemistry
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Mechanics
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Mechanics of Materials
10.9
(top 1%)
Impact Factor
11.7
(top 1%)
extended IF
60
(top 7%)
H-Index
1.4K
authors
736
papers
19.6K
citations
1.1K
citing journals
15.8K
citing authors
Most Cited Articles of Npj Computational Materials
Title
Year
Citations
The ReaxFF reactive force-field: development, applications and future directions
2016
858
The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies
2015
670
Machine learning in materials informatics: recent applications and prospects
2017
635
Recent advances and applications of machine learning in solid-state materials science
2019
631
Review on modeling of the anode solid electrolyte interphase (SEI) for lithium-ion batteries
2018
589
A general-purpose machine learning framework for predicting properties of inorganic materials
2016
558
Computational understanding of Li-ion batteries
2016
299
On the tuning of electrical and thermal transport in thermoelectrics: an integrated theory–experiment perspective
2016
290
Understanding the physical metallurgy of the CoCrFeMnNi high-entropy alloy: an atomistic simulation study
2018
269
A review of oxygen reduction mechanisms for metal-free carbon-based electrocatalysts
2019
257
A strategy to apply machine learning to small datasets in materials science
2018
218
Precision and efficiency in solid-state pseudopotential calculations
2018
181
Plasmon-enhanced light–matter interactions and applications
2019
176
New frontiers for the materials genome initiative
2019
171
Machine learning modeling of superconducting critical temperature
2018
170
Active learning in materials science with emphasis on adaptive sampling using uncertainties for targeted design
2019
158
Uncovering electron scattering mechanisms in NiFeCoCrMn derived concentrated solid solution and high entropy alloys
2019
155
A universal strategy for the creation of machine learning-based atomistic force fields
2017
155
Autonomy in materials research: a case study in carbon nanotube growth
2016
146
Statistical variances of diffusional properties from ab initio molecular dynamics simulations
2018
143
Shift current bulk photovoltaic effect in polar materials—hybrid and oxide perovskites and beyond
2016
142
Computationally predicted energies and properties of defects in GaN
2017
141
Machine learning enabled autonomous microstructural characterization in 3D samples
2020
137
Interplay between Kitaev interaction and single ion anisotropy in ferromagnetic CrI3 and CrGeTe3 monolayers
2018
126
Solving the electronic structure problem with machine learning
2019
114
previous
2016
2017
2018
How are inpact factors calculated?
The impact factor (IF) is calculated by counting citations from peer-reviewed journals only.
extended IF
also counts citations from books and conference papers. However, no patent, abstract, working papers, online documents, etc., are covered.
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