Assistant Professor Xian Du of the Mechanical and Industrial Engineering Department is the principal investigator (PI) on a five-year, $571,655 grant from the National Science Foundation’s (NSF) prestigious Faculty Early Career Development (CAREER) Program. Du’s research, as he explains, “enriches the knowledge base for soft lithography modeling, real-time sensing, deep learning, and design and control of the roll-to-roll print process and contributes to advancements in intelligent manufacturing” for such products as flexible electronics and wearables.
According to Du, his CAREER research focuses on improvements in roll-to-roll soft lithography by establishing a learning-based modeling method that guides the design and control of continuous microcontact printing processes and investigates continuous pattern formation mechanisms.
Du explains that microcontact soft lithography is an attractive and cost-effective method of patterning meter square areas of micro- and nano-scale features via selective mechanical contact on flexible substrates using stamps. Adapting microcontact printing to continuous, roll-to-roll platforms facilitates applications such as flexible electronics and wearables.
Du also observes that the fidelity of the transferred pattern in soft lithography is dependent on successful mechanical contact and control of material transfer at the stamp-substrate interface. However, the underlying microfeature evolution in commonly fabricated structures in roll-to-roll microcontact printing is not yet fully understood to guide the successful design and control of the printing process.
“This CAREER project addresses that critical issue,” says Du, “by studying a novel modeling approach for microcontact print pattern formation with real-time learning from the patterning processes while linking the pattern-formation mechanisms with print-process variations and defects for quality control.”
Du adds that “The goal of this research is to understand the fundamental mechanics of microcontact printing through deep learning and establishing a scientific basis for roll-to-roll soft lithography.”
Towards this goal, Du says his NSF research objectives are: to investigate a physical mechanics model of contact regions for the design and control of roll-to-roll microcontact printing; to establish an in-line, vision-force-deformation, sensing network for assessing print geometry; and to model real-time, stamp-microfeature, pattern-pressure-deformation behavior through deep learning.
“The overarching focus,” says Du, “is to achieve a deep understanding of the deformation behavior of the microcontact stamp and the formation mechanisms of print geometry.”
Du also says that his research is complemented by the development of a multi-disciplinary curriculum combined with research in roll-to-roll printing and the creation of self-contained, hands-on educational kits to encourage young students at various educational levels to pursue careers in manufacturing.
Du is the PI in the Intelligent Sensing Lab, in which the research focuses on the scale-up of flexible electronics printing processes from lab to industry using high-precision, in-line inspection and pattern-recognition technologies for large-surface quality control. He also works on automatic, high-resolution, accurate, and robust imaging tools for medical devices for noninvasive detection and description of biomarkers. (March 2020)