Self-Driving Laboratories for Chemistry and Materials Science
Abstrak
Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through the automation of experimental workflows, along with autonomous experimental planning, SDLs hold the potential to greatly accelerate research in chemistry and materials discovery. This review provides an in-depth analysis of the state-of-the-art in SDL technology, its applications across various scientific disciplines, and the potential implications for research and industry. This review additionally provides an overview of the enabling technologies for SDLs, including their hardware, software, and integration with laboratory infrastructure. Most importantly, this review explores the diverse range of scientific domains where SDLs have made significant contributions, from drug discovery and materials science to genomics and chemistry. We provide a comprehensive review of existing real-world examples of SDLs, their different levels of automation, and the challenges and limitations associated with each domain.
Topik & Kata Kunci
Penulis (16)
Gary Tom
Stefan P Schmid
Sterling G. Baird
Yang Cao
K. Darvish
Han Hao
Stanley Lo
Sergio Pablo-García
Ella M Rajaonson
Marta Skreta
Naruki Yoshikawa
Samantha Corapi
G. Akkoc
Felix Strieth-Kalthoff
Martin Seifrid
Alán Aspuru-Guzik
Akses Cepat
- Tahun Terbit
- 2024
- Bahasa
- en
- Total Sitasi
- 362×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1021/acs.chemrev.4c00055
- Akses
- Open Access ✓