In Bayesian optimization, the acquisition function used for sampling is crucial, and we employed upper confidence bound (UCB). Through pre-simulation, we set the hyperparameter of UCB to be κ = 5 for the optimal balance between exploration and exploitation (Supplementary Figure ). We measured 10 points (five light conditions of two crystals) for initial data, with the maximum value among these being Fmax = 9.8 mN (Figure ). Here, Fmax is defined as the maximum blocking force minus the initial load. We then performed crystal sampling using Bayesian optimization and measured Fmax iteratively. The maximum Fmax increased progressively from 9.8 mN to 16.0 mN, then to 26.8 mN, 34.4 mN, and finally to 37.0 mN over the course of 100 experiments (Figure and Supplementary Table ). The decision to terminate the optimization process after 110 experiments was based on the convergence behavior of Fmax. The final three updates of Fmax showed progressively smaller [a] The average value of two independent molecules with slightly different conformation.