Programme Thesis
The Chemical Process Systems (CPS) program funds fundamental engineering research on chemical and biochemical processes to improve efficiency, sustainability, and resilience for manufacturing, energy, critical minerals, and biotechnology. It exists to advance U.S. competitiveness and security by supporting innovations from molecular-scale phenomena to process- and plant-scale design, including catalysis, separations, and AI-driven process optimization.
Selection Criteria
- Intellectual Merit: Potential to advance knowledge in chemical process engineering, including reaction engineering, catalysis, separations, or process design.
- Broader Impacts: Benefits to U.S. society, economy, or security, such as sustainable manufacturing, energy efficiency, or critical mineral recovery.
- Feasibility and Methodology: Soundness of research plan, including use of AI/ML, quantum science, or uncertainty quantification where relevant.
- Investigator Qualifications: Expertise in chemical engineering or closely related fields; track record in process systems research.
- Institutional Fit: Resources and environment to support the proposed work (e.g., lab facilities, HPC, collaborations).
Past Winners / Cohort Profiles
Past awardees are typically faculty or senior researchers at U.S. universities or research institutions with strong backgrounds in chemical engineering, catalysis, or process systems engineering. Named examples are not provided on the page, but typical winners include PIs from top engineering departments (e.g., MIT, UC Berkeley, Georgia Tech) working on reactor design, membrane separations, or electrochemical systems.
Ideal Candidate Fingerprint
A tenured or tenure-track professor in chemical engineering at a U.S. university, with a proven record of publications in AIChE Journal, Chemical Engineering Science, or similar, proposing fundamental research on catalytic reactors, separations, or process optimization with clear industrial relevance. The ideal applicant has access to advanced lab equipment and HPC resources, and a history of NSF funding.
Recommended Framing
Eniola, this program is not a fit for your CCT addiction model or computational neuroscience work. However, you could pivot to your computational chemistry and TDA skills (e.g., TOPOLOGIX for drug-protein interaction, hERG cardiotoxicity) by framing a project on AI-driven design of safer chemical catalysts or separations for pharmaceutical manufacturing, leveraging your Python/TDA/AlphaFold expertise. Emphasize the Nigeria/LMIC angle only if you can partner with a U.S. institution, as CPS requires U.S. affiliation.
Watch Out
Applicant is an independent researcher in Nigeria, not affiliated with a U.S. institution (NSF typically requires U.S. academic or nonprofit eligibility). No chemical engineering background or process systems research experience. Proposed work on addiction neuroscience is outside the program's scope. Age and pre-PhD status are not disqualifying but weaken competitiveness against established faculty.