The case for data science in experimental chemistry: examples and recommendations

The physical sciences community is increasingly taking advantage of the possibilities offered by modern data science to solve problems in experimental chemistry and potentially to change the way we design, conduct and understand results from experiments. Successfully exploiting these opportunities i...

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Veröffentlicht in:Nature reviews. Chemistry Jg. 6; H. 5; S. 357 - 370
Hauptverfasser: Yano, Junko, Gaffney, Kelly J., Gregoire, John, Hung, Linda, Ourmazd, Abbas, Schrier, Joshua, Sethian, James A., Toma, Francesca M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 01.05.2022
Nature Publishing Group
Springer Nature
Schlagworte:
639/638/440
639/638/675
639/638/77
Algorithms
Analytical Chemistry
Biochemistry
Catalysis
Chemistry
Chemistry and Materials Science
Chemistry/Food Science
Chemists
Co-design
Data science
Energy
Experiments
Expert Recommendation
Inorganic Chemistry
INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
Organic Chemistry
Physical Chemistry
Physical sciences
ISSN:2397-3358, 2397-3358
Online-Zugang:Volltext
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Zusammenfassung:The physical sciences community is increasingly taking advantage of the possibilities offered by modern data science to solve problems in experimental chemistry and potentially to change the way we design, conduct and understand results from experiments. Successfully exploiting these opportunities involves considerable challenges. In this Expert Recommendation, we focus on experimental co-design and its importance to experimental chemistry. We provide examples of how data science is changing the way we conduct experiments, and we outline opportunities for further integration of data science and experimental chemistry to advance these fields. Our recommendations include establishing stronger links between chemists and data scientists; developing chemistry-specific data science methods; integrating algorithms, software and hardware to ‘co-design’ chemistry experiments from inception; and combining diverse and disparate data sources into a data network for chemistry research. Modern data science can help to address challenges in experimental chemistry. This Expert Recommendation describes examples of how data science is changing the way we conduct experiments and outlines opportunities for further integration of data science and experimental chemistry to advance these fields.
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USDOE Office of Science (SC), Basic Energy Sciences (BES)
AC02-76SF00515; SC0002164
ISSN:2397-3358
2397-3358
DOI:10.1038/s41570-022-00382-w