Materials discovery systems that predict real-world manufacturability for low-income communities
open
Global, Global
WS05333
AI and laboratory automation can identify promising compounds that fail during scale-up, processing, or deployment. The open problem is connecting discovery models to cost, supply, safety, and lifecycle constraints. The solution must work with limited capital, intermittent services, and local maintenance capacity. The research opportunity is to define measurable success criteria, test the approach in realistic settings, identify failure modes, and create a pathway from prototype to accountable deployment.