Published May 12, 2026 | Version v1

Reweighting free energy profiles between universal machine learning interatomic potentials for fast consensus building

  • 1. ROR icon Massachusetts Institute of Technology
  • 2. ROR icon University of Vienna
  • 3. ROR icon Fraunhofer Institute for Algorithms and Scientific Computing
  • 4. Charles University, Faculty of Science

Description

# Dataset -- Reweighting Free Energies

## Folder Contents

### `zeolite_structure/`
CIF file of the studied system: Li⁺ ion in a water-solvated zeolite framework (1 Al, 1 Li, 55 H₂O, 601 atoms total).

### `umbrella_sampling_data/`
Output data from umbrella sampling (US) simulations used to construct the PMFs directly:
- MACE-MATPES US simulation log files (54 umbrella windows, z = −6.61 to 6.64 Å)
- Pre-computed PMF from MACE-MP0 umbrella sampling (`pmf_april9_umb_mace-mp0.npz`)

### `data_540000_frames/`
Processed frames used for free energy reweighting (10,000 downsampled frames × 54 windows = 540,000 frames total). Contains per-MLIP subdirectories with source and target potential energies, for 7 target MLIPs:
- MACE-MATPES, MACE-MP0-D3, MACE-MPA, MACE-finetuned, UMA, ORB, PET-MAD

### `data_parity_plots/`
DFT and MLIP energies and forces for 1,100 structures used in the parity plots (8 MLIPs vs DFT PBE+D3 reference). POSCAR files for the DFT calculations are provided in `dft_li.zip`.

### `MACE-finetuned/`
The finetuned MLIP developed in this work, along with the training data used.

### `MBAR_weights/`
The MACE-MP0 unbiased MBAR weights obtained for the 540,000 downsampled frames 

Files

data_540000_frames.zip

Files (918.4 MB)

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Additional details