Supplementary Data for "Self-consistent biased fine-tuning for highly accurate reaction-specific machine-learning interatomic potentials"

This repository contains all relevant data for the manuscript "Self-consistent biased fine-tuning for highly accurate reaction-specific machine-learning interatomic potentials". The fine-tuned MACE MLIPs used for rate constant calculations are stored in the folder: MACE_fine_tuned There, the MLIPs optimized from structures directly sampled by the analytical PESs are called "analytic", while those optimized by self-consistent biased fine-tuning are called "self". The folder "input_analytic" contains input files for MACE fine-tunings from direct samplings with the analytical PES. Here the malonaldehyde cheap-h example has been taken. The training set is generated in the folders "sampling_PES" (along reaction path) and sampling recross (recrossing trajectories), here at 150 K, respectively. The fine-tuning is done in the folder "tuning" (with a training set for all temperatures). A rate calculation at 150 K is done in the folder "rate_calculation". The energy deviations are calculated in the folder "benchmark" (here only for 150 K). The folder "input_self_consistent" contains input files for the self-consistent biased fine-tuning. Here the CH4+OH normal-e example has been taken (cycle 3). The training set is generated in the folder "sampling_PES", here at 150 K (no recrossing training needed). The fine-tuning is done in the folder "tuning" (with the full training set). A rate calculation at 500 K is done in the folder "rate_calculation". The energy deviations are calculated in the folder "benchmark" (here only for 300 K).