Dear Materials Project team,
Thank you for providing this invaluable platform for materials research discussions.
I am currently working on modeling a high-entropy oxide system and am interested in employing genetic algorithms to predict the most stable or optimal atomic configurations for my material. Given the complexity and configurational space of these systems, I would appreciate your advice on:
-
Which genetic algorithm frameworks or tools are best suited for exploring the configurational space of multi-component oxides?
-
Are there any recommended packages (possibly compatible with Python or existing materials informatics libraries) that integrate well with DFT or atomistic modeling workflows?
-
Do you have any guidance on best practices or resources for setting up such calculations for disordered or high-entropy materials?
Any suggestions or references you can provide would be greatly appreciated.
Thank you for your time and support.
Best regards,
Lindokuhle