Dataset for ADAPT: Lightweight, Long-Range Machine Learning Force Fields Without Graphs

This is the data used in the *ADAPT: Lightweight, Long-Range Machine Learning Force Fields Without Graphs* paper found at: https://arxiv.org/abs/2509.24115. It is a set of DFT calculations for point defects in silicon. The majority of the set is complex defects featuring two defect atoms, although vacancy and simple substitional defects are also present. Supplementary materials Section A in the original paper gives a description of how the data was generated and further details. Further details about this research can be found at: https://evandramko.github.io/ADAPT_webpage/ We release all the raw pickle data files. We also release the data combined into xyz files for convenience. We suggest using all files except 11.pickle as training, and using 11.pickle as the testing file. We also release a selection of 100 frames that were used to make the diagrams in the associated ADAPT paper. Following updates to the ADAPT library at https://github.com/EvanDramko/ADAPT_Released we have updated the representation of atoms from a (n,12) setup (using all available atomic descriptors in the raw data) to a more standard (n,4) representation of (x, y, z, Z) per atom. The original (n,12) data can still be extracted from the pickle files if you would prefer to use that.