
This is the datasets and trained models for the work "Active learning accelerated exploration of the single atom local environments in multimetallic systems for oxygen electrocatalysis", by Hoje Chun, Jaclyn R. Lunger, Jeung Ku Kang, Rafael Gómez-Bombarelli, and Byungchan Han. Folder named Models contains the trained models of "m-PaiNN" and "per-site PaiNN". Folder named Dataset contains the torch dataset and Dataset_raw contains the raw Density Functional Theory (DFT) dataset parsed in format of pymatgen Structure. Some structures (868) in the search space are missing due to the lost track of the geometry optimization during the initial dataset curation.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
