My name is Kenjiro, I’m a senior undergrad Chemistry student from the University of Puerto Rico. I’m currently working on an implementation of machine learning to a materials science project related to batteries (I’m not an expert in computer science but I know Python). I’ve coded a program that can calculate some abstract characteristics of the materials mostly based on the distances between particular atoms. The reason I’m asking here is that I need a 3x3x3 supercell to be able to calculate one of the characteristics, but I’m not sure how to obtain that from the Materials Project Database; I only get unit cell information.
I can create a program that obtains unit cell information and duplicates the cell in all dimensions, generating a kind of supercell, but that would cost a lot of time and resources with the idea I came up with (since I don’t know any other). Right now I’m only working with a few materials and I can do this manually for all of them, but if I want to implement this to say, for example, all Lithium containing materials, it would be physically impossible for me to do it. So I want to automate this, but I need a better way to generate or obtain supercell information. Is there a pymatgen tool, or really anything else I can use that can generate these supercells for me? I have seen some tools like VESTA, but I have to download the CIF file first, open it, and manually convert them to supercells, so this isn’t practical. It would be better to use the MAPI or something on the server side.