The value of negative results in data-driven catalysis research
Joint press release (in Japanese) by Japan Advanced Institute of Science and Technology (JAIST) and Hokkaido University
Abstract
Data science and machine learning have the potential to accelerate the discovery of effective catalysts; however, these approaches are currently held back by the issue of negative results. This Comment highlights the value of negative data by assessing the bottlenecks in data-driven catalysis research and presents a vision for a way forwards.
Read more on Nature Catalysis (Springer Nature)
Article information:
Taniike, T., Takahashi, K. The value of negative results in data-driven catalysis research. Nat Catal 6, 108–111 (2023).
DOI: 10.1038/s41929-023-00920-9