Experimental planners are the keystone of SDL prompting us to equip ChemOS 2.0 with Atlas, a package for Bayesian optimization (BO) designed explicitly for experimental sciences. Atlas is a general-purpose optimization framework for expensive-to-evaluate black-box problems, capable of mixedparameter and multi-objective optimization. Importantly, Atlas incorporates BO concepts particularly relevant to chemistry, such as a molecular kernel function, general experimental parameter optimization, robust optimization, and asynchronous experimental execution. For more information, see Note S12 and the Ref. , where we show an additional closed-loop electrochemical campaign orchestrated by ChemOS 2.0.