Dataset for "Exploring foundational machine learned potentials for treating the high temperature dynamics of metal-organic frameworks"

Supporting dataset for "Exploring foundational machine learned potentials for treating the high temperature dynamics of metal-organic frameworks", Connor W. Edwards and Jack D. Evans, 2025

Contains (in a zipped directory):    - code: script used for generating DFT simulations    - code: python scripts used for sampling DFT data randomly and using the flat histogram sampling methods    - code: python script to convert from an xyz file to sqlite database for finetuning foundational models    - code: scripts used to finetune foundational models    - code: python scripts used to calculate MAE values for models    - models: all finetuned models for ORB-d3-v2, MACE-MP-0 and SevenNet-0 using random, coordination number and bond length sampling    - data: xyz files for 15 ps DFT trajectories of ZIF-8 and CALF 20 at 300, 1000 and 2000 K    - data: xyz files for 15 ps DFT trajectories of MOF-5 and MOF-10 at 300 K    - dataL output files for DFT simulations including stress, forces and energy files