Accurate machine learning in materials science facilitated by using diverse data sources

Multifidelity Information Fusion with Machine Learning: A Case Study of Dopant Formation Energies in Hafnia

(2019) Rohit Batra et al.   ACS Applied Materials & Interfaces

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

(2019) Chi Chen et al.   CHEMISTRY OF MATERIALS

Semi-supervised machine-learning classification of materials synthesis procedures

(2019) Haoyan Huo et al.   npj Computational Materials

Machine learning modeling of superconducting critical temperature

(2018) Valentin Stanev et al.   npj Computational Materials

Machine learning for molecular and materials science

(2018) Keith T. Butler et al.   NATURE

Machine Learning-Assisted Discovery of Solid Li-Ion Conducting Materials

(2018) Austin D. Sendek et al.   CHEMISTRY OF MATERIALS

Scoping the polymer genome: A roadmap for rational polymer dielectrics design and beyond

(2017) Arun Mannodi-Kanakkithodi et al.   Materials Today

Machine learning in materials informatics: recent applications and prospects

(2017) Rampi Ramprasad et al.   npj Computational Materials