LEARNING MATTER

Shao-Horn, Yang

Year of Publication:
2023
Atom-by-atom design of metal oxide catalysts for the oxygen evolution reaction with machine learning

arXiv:2305.19930
,

2023
Year of Publication:
2021
Crystal graph convolutional neural networks for per-site property prediction

Fourth Workshop on Machine Learning and the Physical Sciences at NeurIPS
,

2021
Year of Publication:
2023
Lamellar ionenes with highly dissociative, anionic channels provide lower barriers for cation transport

J. Am. Chem. Soc.
,

2023
Year of Publication:
2023
Chemistry-Informed Machine Learning for Polymer Electrolyte Discovery

ACS Central Science
,

2023
Year of Publication:
2022
Human- and machine-centred designs of molecules and materials for sustainability and decarbonization

Nature Reviews Materials
,

2022
Year of Publication:
2022
Examining graph neural networks for crystal structures: limitation on capturing periodicity

arXiv:2208.05039
,

2022
Year of Publication:
2021
Accelerating the screening of amorphous polymer electrolytes by learning to reduce random and systematic errors in molecular dynamics simulations

arXiv:2101.05339
,

2021
Year of Publication:
2020
Quantitative Mapping of Molecular Substituents to Macroscopic Properties Enables Predictive Design of Oligoethyleneglycol-Based Lithium Electrolytes

ACS Central Science
,

2020
Year of Publication:
2019
The Materials Research Platform: Defining the Requirements from User Stories

Matter
,

vol.
1
,

pp.
1433 – 1438
,

2019