All projects must have: a materials component; computational component; interested industry partner with a clear, vested interest in commercialization of technologies; and a commitment to broadening participation and impact.
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Luis R. De Jesús Báez, PhD
Advance AI-driven discovery of molecular copper inks, building on prior data to optimize conductive ink formulations
Uttam Singisetti, PhD
Develop high-voltage semiconductor diodes to enable reliable, efficient power for EVs and AI infrastructure
Janet Morrow, PhD
Develop multinuclear Fe(III) complexes as sustainable MRI contrast agents to replace gadolinium-based products
James Chen, PhD and
Wei Chen, PhD
Develop CeramShield AI, a fine-tuned generative model to optimize ceramic matrix composites manufacturing incorporating LCVD-produced materials
Bibhudatta Sahoo, PhD
Develop compact, precision multi-channel current sources to bias RSFQ logic and superconducting qubits for scalable quantum computing
Krishna Rajan, ScD
Enhance materialsIN’s materials informatics platform to optimize processes and detect anomalies across diverse industrial applications
Paschalis Alexandridis, PhD
and Marina Tsianou, PhD
Commercialize eco-friendly drug disposal solutions that prevent pharmaceutical contamination in landfills and water systems
Y. Chris Li, PhD
Combining machine learning-driven catalyst discovery with experimental validation to develop efficient NOx-to-ammonia conversion technologies, advancing PlasmaChem’s prototype reactor development
