To build an initial surrogate in each optimization, we simulate an initial set of 𝑁 parameter vectors, one of which is always the parameter vector corresponding to OpenFF 1.0.0. We select these vectors from an initial parameter space, described in Table . The size of this space is measured in percentage of the parameter values from OpenFF 1.0.0, and is determined from the results of our previous optimization study, based on how much each parameter was adjusted in that study. From this space, we select the remaining 𝑁 -1 parameter vectors using Latin Hypercube Sampling (LHS), as implemented with the Surrogate Modeling Toolbox (smt) Python, library version 1.1.0.