Federal Grant Award Summary

Fordham University received a $393,021 Project Grant award from the National Science Foundation's Division of Materials Research (Mathematical and Physical Sciences program, CFDA 47.049) effective February 15, 2026, through January 31, 2029. This collaborative research initiative focuses on accelerated discovery of lead-free metal halide perovskitoids through automation and artificial intelligence (AI). The primary deliverables include the development of machine learning models trained on published experimental data to identify gaps in chemical knowledge and guide exploratory synthesis efforts; novel robotic-compatible synthetic routes enabling iterative testing and refinement of these models; and AI-based research planning assistants to support complex multistep research planning. The project advances lead-free perovskite material development for applications including photovoltaic solar cells, lighting, lasers, photodetectors, X-ray detectors, and catalysis, thereby addressing the current limitation of toxic lead-containing materials in these technologies.

Beyond core research outputs, the award supports development of general-purpose AI tools to be shared with the broader materials chemistry community and creation of undergraduate-level teaching resources for distribution to other institutions. The project incorporates workforce development components, providing interdisciplinary training in data science and chemical experimentation to undergraduate, graduate, and postdoctoral researchers, while also developing age-appropriate educational games teaching materials design principles. These deliverables collectively address scientific workforce gaps and advance both fundamental knowledge and practical applications in materials chemistry.