MOFA
Generative MOF design and screening at leadership-class scale.
MOFA is a workflow for generating and screening metal–organic frameworks at scale on HPC systems. It couples generative models for proposing new MOF structures with high-throughput property evaluation, orchestrated across many nodes so that generation, assembly, and simulation run as a continuous discovery pipeline.
My role is as a contributor to this collaboration, supporting multi-agent orchestration for high-throughput materials screening on leadership-class systems and large campaigns across hundreds of compute nodes.
- Role: Contributor.
- Stack: Python, Parsl, generative ML, HPC (ALCF).
- Code: github.com/globus-labs/mof-generation-at-scale