Description
From: Schrier, J.; Norquist, A.; Buonassisi, T.; Brgoch, J. In Pursuit of the Exceptional: Research Directions for Machine Learning in Chemical and Materials Science. ChemRxiv May 19, 2023. https://doi.org/10.26434/chemrxiv-2023-x23s9.
Nevertheless, recent demonstrations of autonomous materials research include metallic thin films,79 wear-resistant metallic glasses,80 organic laser materials,81 acid generators for photoresists relevant to semiconductor device fabrication,2 multi-modal materials characterization,82 and reversible addition–fragmentation chain transfer (RAFT) polymerization.83
For comprehensive recent reviews on autonomous systems for materials, see Refs. 52,84–86, and for a recent perspective on the current state of the art15 of these systems for exceptional materials see Ref. 15 while organic synthesis is discussed in Refs. 61 & 87.)
A self-driving laboratory varied different reaction conditions for combustion synthesis (fuel source, fuel-to-oxidizer ratio, precursor solution concentration, and annealing temperature) to simultaneously maximize the film’s conductivity and minimize the combustion temperature, by using a differential expected hypervolume improvement (qEHVI) algorithm.94