Human versus Robots in the Discovery and Crystallization of Gigantic Polyoxometalates

The discovery of new gigantic molecules formed by self-assembly and crystal growth is challenging as it combines two contingent events; first is the formation of a new molecule, and second its crystallization. Herein, we construct a workflow that can be followed manually or by a robot to probe the envelope of both events and employ it for a new polyoxometalate cluster, Na-6[Mo120Ce6O366H12(H2O)(78)]center dot 200H(2)O (1) which has a trigonal-ring type architecture (yield 4.3% based on Mo). Its synthesis and crystallization was probed using an active machine-learning algorithm developed by us to explore the crystallization space, the algorithm results were compared with those obtained by human experimenters. The algorithm-based search is able to cover ca. 9 times more crystallization space than a random search and ca. 6 times more than humans and increases the crystallization prediction accuracy to 82.4 +/- 0.7% over 77.1 +/- 0.9% from human experimenters.