This $296,000 Project Grant awarded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041) aims to develop a comprehensive understanding of the dynamic drying process of particle-laden slurries and integrate these insights into a predictive machine learning model. The research tasks include:
(i) Establishing the correlation between drying conditions and multi-scale structural ordering;
(ii) Imaging and predicting the spatiotemporal evolution of the microstructure; and
(iii) Model-guided optimization of the mechanical and electrical properties of particulate composites.
The project is a collaboration between the University of Texas at Austin and the University of Wisconsin-Madison, with the latter serving as the prime awardee. The work is expected to provide new insights into particle self-assembly dynamics and guide the design of drying processes to control the microstructure and properties of various composite materials. No sub-awards are planned under this grant, which has an award date of August 15, 2024 and a completion date of July 31, 2027.
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