Dynamic Data Driven Control of Nanoparticle Self-Assembly Processes
Abstract
The objective of this research is to develop a dynamic data-driven control loop to sense and controla nanorod self-assembly process in real time for the purpose of producing nanorods with desirabledimensions and reduced variation. To achieve this objective, one must precisely control the ratesof three key chemical kinetics in a self-assembly process: nucleation, growth and aggregation,which are sensitive to internal or external disturbances, such as variations in temperature,concentration and chemical impurities, or lack of precision in human intervention in the process.The variations cannot be sensed and controlled in the design stage of a self-assembly process, asthey only occur in the run time of the self-assembly process. We propose to measure the kineticrates while in process through a set of multi-resolution instruments and steer and control thesekinetic rates dynamically based on a data-driven, model predictive control strategy.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 09, 2018
- Source ID
- FA95501810144
Entities
People
- Chiwoo Park
Organizations
- Air Force Office of Scientific Research
- Florida State University
- United States Air Force