United States. Scientists at the University of Nebraska-Lincoln are using artificial intelligence to develop an advanced manufacturing platform for polymer coatings.
Mona Bavarian, an assistant professor of chemical and biomolecular engineering, received a $576,802 grant from the National Science Foundation's Faculty Early Professional Development Program for her research to meet these exacting standards.
Polymer coatings are essential components in the manufacture of many electronic devices, including those for communications, computing, healthcare, military systems, transportation, energy, and more.
Polymers, especially those used in semiconductor technology, have strict quality requirements, and increasing scale, purity, and production time present significant challenges to their manufacture.
Guided by artificial intelligence, Bavarian aims to replace traditional batch manufacturing with a more precise flow chemistry process. The change would allow better control of polymer properties and structures, reducing defects and improving overall quality.
In line with the topic of continuous polymerization of special polymers, the proposed research focuses on understanding the reaction mechanisms and structural-property behavior of microelectronic polymers synthesized in flow reactors.
Bavarian will combine first principles and machine learning models to gain this insight.
"With this approach, we can improve manufacturers' ability to produce synthetic materials while limiting defects and improving the quality of high-performance materials," Bavarian said.
"The 'continuous flow' process also offers an opportunity to monitor the process and control quality attributes through an advanced control strategy," he added.
"This approach would enable high-performance manufacturing of specialty polymers with unattainable qualities using traditional batch manufacturing," Bavarian continued.
