Representations of materials for machine learning

J Damewood, J Karaguesian, JR Lunger… - Annual Review of …, 2023‏ - annualreviews.org
High-throughput data generation methods and machine learning (ML) algorithms have
given rise to a new era of computational materials science by learning the relations between …

QSAR without borders

EN Muratov, J Bajorath, RP Sheridan… - Chemical Society …, 2020‏ - pubs.rsc.org
Prediction of chemical bioactivity and physical properties has been one of the most
important applications of statistical and more recently, machine learning and artificial …

Recent advances and applications of machine learning in solid-state materials science

J Schmidt, MRG Marques, S Botti… - npj computational …, 2019‏ - nature.com
One of the most exciting tools that have entered the material science toolbox in recent years
is machine learning. This collection of statistical methods has already proved to be capable …

From DFT to machine learning: recent approaches to materials science–a review

GR Schleder, ACM Padilha, CM Acosta… - Journal of Physics …, 2019‏ - iopscience.iop.org
Recent advances in experimental and computational methods are increasing the quantity
and complexity of generated data. This massive amount of raw data needs to be stored and …

Machine learning for catalysis informatics: recent applications and prospects

T Toyao, Z Maeno, S Takakusagi, T Kamachi… - Acs …, 2019‏ - ACS Publications
The discovery and development of catalysts and catalytic processes are essential
components to maintaining an ecological balance in the future. Recent revolutions made in …

Data‐driven materials innovation and applications

Z Wang, Z Sun, H Yin, X Liu, J Wang, H Zhao… - Advanced …, 2022‏ - Wiley Online Library
Owing to the rapid developments to improve the accuracy and efficiency of both
experimental and computational investigative methodologies, the massive amounts of data …

Machine learning in materials science: From explainable predictions to autonomous design

G Pilania - Computational Materials Science, 2021‏ - Elsevier
The advent of big data and algorithmic developments in the field of machine learning (and
artificial intelligence, in general) have greatly impacted the entire spectrum of physical …

Emerging materials intelligence ecosystems propelled by machine learning

R Batra, L Song, R Ramprasad - Nature Reviews Materials, 2021‏ - nature.com
The age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its
successes and promises, several AI ecosystems are blossoming, many of them within the …

A strategy to apply machine learning to small datasets in materials science

Y Zhang, C Ling - Npj Computational Materials, 2018‏ - nature.com
There is growing interest in applying machine learning techniques in the research of
materials science. However, although it is recognized that materials datasets are typically …

Machine learning in materials informatics: recent applications and prospects

R Ramprasad, R Batra, G Pilania… - npj Computational …, 2017‏ - nature.com
Propelled partly by the Materials Genome Initiative, and partly by the algorithmic
developments and the resounding successes of data-driven efforts in other domains …