To read the json.bz2 files you can use the following code in python: ------------------------------------ #!/usr/bin/env python import json, bz2 from pymatgen.entries.computed_entries import ComputedStructureEntry with bz2.open("step_1.json.bz2") as fh: data = json.loads(fh.read().decode('utf-8')) entries = [ComputedStructureEntry.from_dict(i) for i in data["entries"]] print("Found " + str(len(entries)) + " entries") print("\nEntry:\n", entries[0]) print("\nStructure:\n", entries[0].structure) ------------------------------------ Each file includes the calculations for a single substition step. In the article we present the results for three steps. We ended by performing also a forth step, and a part of the fifth. These calculations are also included here. All results are using the PBE approximation. The number of entries per file is step_1.json.bz2 61848 step_2.json.bz2 52800 step_3.json.bz2 79205 step_4.json.bz2 40328 step_5.json.bz2 23308 total 257489 In the summary.txt file, the meaning of the columns is 1. chemical composition of the material 2. number of sites in the primitive unit cell 3. volume of the primitive unit cell in Angstroem^3 4. total energy in eV 5. energy of formation in eV 6. distance to the convex hull in eV 7. indirect band gap in eV Note that the distance to the hull (and to a much lesser extent the energy of formation) depend on the reservoir compounds used to calculate the convex hull. In this case, we used the materials in the Materials Project database together with our own internal database. Note that the distances to the hull may be negative, as we exclude the composition from the hull during the calculation.