Future work includes (1) inventing new (a) predictive, uncertainty-calibrated, and dataefficient multi-fidelity surrogate models and (b) exploration-, exploitation-, and cost-balancing multi-fidelity acquisition functions; (2) extending MFBO to (a) the batch setting, where experiments can be done in parallel and multiple materials are selected at each iteration and (b) the multi-objective setting, 107,108 where we seek the Pareto-optimal set of COFs.