Force fields used in molecular simulations contain numerical parameters, such as Lennard–Jones (LJ) parameters, which are assigned to the atoms in a molecule based on a classification of their chemical environments. The number of classes, or types, should be no more than needed to maximize agreement with experiment, as parsimony avoids overfitting and simplifies parameter optimization. However, types have historically been crafted based largely on chemical intuition, so current force fields may contain more types than needed. In this study, we seek the minimum number of LJ parameter types needed to represent the key properties of organic liquids. We find that highly competitive force field accuracy is obtained with minimalist sets of LJ types; e.g., two H types and one type apiece for C, O, and N atoms. We also find that the fitness surface has multiple minima, which can lead to local trapping of the optimizer.

分子模拟中使用的力场包含数值参数，例如 Lennard-Jones (LJ) 参数，这些参数根据化学环境的分类分配给分子中的原子。类或类型的数量不应超过与实验最大程度一致所需的数量，因为简约可以避免过度拟合并简化参数优化。然而，历史上类型主要是基于化学直觉而设计的，因此当前的力场可能包含比所需更多的类型。在本研究中，我们寻求表示有机液体关键特性所需的 LJ 参数类型的最少数量。我们发现使用极简的 LJ 类型集可以获得极具竞争力的力场精度；例如，两种 H 类型和一种 C、O 和 N 原子类型。我们还发现适应度表面有多个最小值，这可能导致优化器的局部捕获。