The Woodruff School

SUMMARY

The transition from rigid to flexible electronic devices in the recent years has significantly expanded the electronic device applications into stretchable electronics and wearable electronics, such as smart socks, smart shirt, and smart chest-strip. Stretchable and wearable electronics undergo stretching, flexing, bending, and twisting during the process of being put on and while being worn. In addition, wearable textile electronics also need to survive under repeated washing and drying cycles. During such end-use wearing and washing conditions, it is necessary to ensure that the stretchable and wearable electronics remain reliable. The overall goal of this research is to model and characterize serpentine interconnects that are used in stretchable and wearable electronics, and to use topology optimization in combination with machine learning and innovative strain-relief approaches to enhance the reliability of serpentine interconnects in end-use conditions. The first objective of this work is to study the strain distributions in serpentine structures under uniaxial stretching. Analytical formulations and numerical models of stand-alone serpentine structures will be developed and validated against two-dimensional digital image correlation (2D-DIC) measurements. In addition, substrate-supported serpentine structures will be studied examining the substrate-to-interconnect stiffness ratio. The second objective of this work is to optimize the strain distributions in the serpentine structures by topology optimization and material selection to improve the stretchability of the serpentine structures. A random forest machine learning model will be employed for the optimization. An innovative strain relief mechanism will also be proposed. The third objective of this work is to examine the strain distribution in wearable electronics when a typical wearable smart garment is being put on. A commercially available wearable garment will be used to demonstrate the effectiveness of the proposed mechanical strain characterization procedure. The washing reliability of the smart garment will be accessed.

SUBJECT:	Ph.D. Dissertation Defense

BY:	Chong Ye

TIME:	Thursday, April 8, 2021, 3:00 p.m.

PLACE:	https://bluejeans.com/720849719, NA

TITLE:	Mechanical Characterization and Use-Condition Reliability Assessment of Wearable Textile Electronics

COMMITTEE:	Dr. Suresh Sitaraman, Chair (ME) Dr. Yuhang Hu (ME) Dr. Sundaresan Jayaraman (MSE) Dr. Yan Wang (ME) Dr. Chuck Zhang (ISYE)

SUMMARY The transition from rigid to flexible electronic devices in the recent years has significantly expanded the electronic device applications into stretchable electronics and wearable electronics, such as smart socks, smart shirt, and smart chest-strip. Stretchable and wearable electronics undergo stretching, flexing, bending, and twisting during the process of being put on and while being worn. In addition, wearable textile electronics also need to survive under repeated washing and drying cycles. During such end-use wearing and washing conditions, it is necessary to ensure that the stretchable and wearable electronics remain reliable. The overall goal of this research is to model and characterize serpentine interconnects that are used in stretchable and wearable electronics, and to use topology optimization in combination with machine learning and innovative strain-relief approaches to enhance the reliability of serpentine interconnects in end-use conditions. The first objective of this work is to study the strain distributions in serpentine structures under uniaxial stretching. Analytical formulations and numerical models of stand-alone serpentine structures will be developed and validated against two-dimensional digital image correlation (2D-DIC) measurements. In addition, substrate-supported serpentine structures will be studied examining the substrate-to-interconnect stiffness ratio. The second objective of this work is to optimize the strain distributions in the serpentine structures by topology optimization and material selection to improve the stretchability of the serpentine structures. A random forest machine learning model will be employed for the optimization. An innovative strain relief mechanism will also be proposed. The third objective of this work is to examine the strain distribution in wearable electronics when a typical wearable smart garment is being put on. A commercially available wearable garment will be used to demonstrate the effectiveness of the proposed mechanical strain characterization procedure. The washing reliability of the smart garment will be accessed.