Research Data Supporting "Atomistic mechanisms of hard carbon formation from polyvinylidene chloride"

This repository accompanies the manuscript:

Litong Wu, Zitong Wu, Zakariya El-Machachi, and Volker L. Deringer, "Atomistic mechanisms of hard carbon formation from polyvinylidene chloride" (in preparation).

The repository is organized into two main directories:

• data/ stores the final machine-learned interatomic potential and the training and testing datasets.
• scripts/ contains the analysis and plotting scripts used to generate the manuscript figures.

data/

The data directory contains:

• The final trained potential:
  • pvdc_stagetwo.model
• The training and testing datasets used to fit and validate the MLIP model:
  • training-set.xyz
  • testing-set.xyz

A subset of the training and testing datasets were relabelled from the following open sources:

Amorphous carbon and graphitic configurations: Rowe, P.; Deringer, V. L.; Gasparotto, P.; Csányi, G.; Michaelides, A. J. Chem. Phys. 2020, 153, 034702.

Bulk CH configurations: Ibragimova, R.; Kuklin, M. S.; Zarrouk, T.; Caro, M. A. Chem. Mater. 2025, 37, 1094–1110.

Hydrocarbon molecules: Kim, S.; Chen, J.; Cheng, T.; Gindulyte, A.; He, J.; He, S.; Li, Q.; Shoemaker, B. A.;Thiessen, P. A.; Yu, B.; Zaslavsky, L.; Zhang, J.; Bolton, E. E. Nucleic Acids Res. 2025, 53, D1516–D1525.

QM9 molecules: Wichmann, C.; Ramakrishnan, R.; von Lilienfeld, O. A. Sci. Data 2025, 12, 9.

scripts/

The analysis scripts, processed data, and plotting scripts are organized by manuscript section:

• 1a/ — representative trajectory snapshots at multiple time points, including an OVITO session file for visualization
• 1b/ — simulation temperature profile
• 1c/ — mass over time
• 1d/ — density over time
• 2a/ — bond count over time
• 2d/ — pre-reactive encounter time
• 2e/ — event-based lifetime and frequency
• 2f/ — reaction type based on regioselectivity
• 3a/ — carbon coordination and cluster over time
• 3d/ — representative trajectory snapshots at multiple time points with six-membered rings highlighted, together with the corresponding ring-identification script

Each section directory typically contains:

• an analysis script (*_analysis.py),
• a plotting script (*_plot.py), and
• a generated CSV summary (*.csv).