npj Computational Materials

Titel Veröffentlichungsdatum Sprache Zitate
The ReaxFF reactive force-field: development, applications and future directions2016/03/04English1,259
Recent advances and applications of machine learning in solid-state materials science2019/08/08English1,219
The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies2015/12/11English1,189
Machine learning in materials informatics: recent applications and prospects2017/12/13English967
Review on modeling of the anode solid electrolyte interphase (SEI) for lithium-ion batteries2018/03/26English951
A general-purpose machine learning framework for predicting properties of inorganic materials2016/08/26English896
Understanding the physical metallurgy of the CoCrFeMnNi high-entropy alloy: an atomistic simulation study2018/01/10English484
A review of oxygen reduction mechanisms for metal-free carbon-based electrocatalysts2019/07/19English479
Computational understanding of Li-ion batteries2016/03/18English405
Precision and efficiency in solid-state pseudopotential calculations2018/12/06English397
On the tuning of electrical and thermal transport in thermoelectrics: an integrated theory–experiment perspective2016/02/26English390
A strategy to apply machine learning to small datasets in materials science2018/05/14English380
Plasmon-enhanced light–matter interactions and applications2019/04/11English322
Active learning in materials science with emphasis on adaptive sampling using uncertainties for targeted design2019/02/18English300
New frontiers for the materials genome initiative2019/04/05English298
Machine learning enabled autonomous microstructural characterization in 3D samples2020/01/06English276
Machine learning modeling of superconducting critical temperature2018/06/28English270
Statistical variances of diffusional properties from ab initio molecular dynamics simulations2018/04/03English248
Shift current bulk photovoltaic effect in polar materials—hybrid and oxide perovskites and beyond2016/08/26English237
Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm2019/06/21English231
Interplay between Kitaev interaction and single ion anisotropy in ferromagnetic CrI3 and CrGeTe3 monolayers2018/11/05English230
Autonomy in materials research: a case study in carbon nanotube growth2016/10/21English227
Uncovering electron scattering mechanisms in NiFeCoCrMn derived concentrated solid solution and high entropy alloys2019/01/04English224
On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events2020/03/18English210
Recent advances and applications of deep learning methods in materials science2022/04/05English204
Computationally predicted energies and properties of defects in GaN2017/03/24English195
Machine learning for perovskite materials design and discovery2021/01/29English193
Discovery of new materials using combinatorial synthesis and high-throughput characterization of thin-film materials libraries combined with computational methods2019/07/10English180
The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design2020/11/12English177
Solving the electronic structure problem with machine learning2019/02/18English176