Mentor Areas
- Autonomous Experimentation
- Machine Learning and Artificial Intelligence
- Polymer Chemistry
- Materials Science
- Battery Technology and Energy Storage
Description:
This project integrates autonomous experimentation powered by AI to study process-structure-property relationships in polyelectrolyte-based polymer nanocomposites. Polymer-based alternatives to lithium-ion batteries can enhance safety and sustainability. By introducing polymer-grafted nanoparticles into a polymer matrix, the ion conductivity of the resulting composite can be tuned for applications like energy storage. Machine learning aids in navigating this complex material system through automated synthesis, characterization, and data analysis. Students will contribute to developing autonomous sample preparation methods and AI-based decision algorithms for experimental campaigns.
Preferred Qualifications
- Major in Materials Science and Engineering, Chemical Engineering, MEAM or Physics
- Familiarity with general laboratory procedures and interest in material preparation, characterization, and analysis
- Some background in programming (Python preferred)
Project Website
Learn more about the researcher and/or the project here. Learn more about the researcher and/or the project here.
Details:
Preferred Student Year
Second-Year, Junior
Academic Term
Fall
I prefer to have students start during the above term(s).Volunteer
No
Yes indicates that faculty are open to volunteers.Paid
No
Yes indicates that faculty are open to paying students they engage in their research, regardless of their work-study eligibility.Work Study
Yes
Yes indicates that faculty are open to hiring work-study-eligible students.