Robust design and fabrication of highly stretchable sensor networks for the creation of intelligent materials

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Taking advantage of the state-of-the-art CMOS/MEMS technology, a cost-effective fabrication method was developed to integrate large arrays of micro/nano scale sensors, switches, and electronics into materials as a step to create a new class of next generation materials that are capable of self-sensing and self-diagnosing the state of a structure in real time. The method was built upon a highly stretchable sensor network that could be stretched to span more than 10,000% of its original area, and embedded into polymer materials during cure at elevated temperatures such as advanced aerospace composite materials. The method included three major efforts: 1). Design a sensor network fabricated at the micro/nano scale but expandable to more than 10,000% its original size to cover a large, macro, areas of materials without experiencing failures. 2). Develop a robust micro/nano manufacturing method to incorporate sensors and switches into the network. A high-resolution fabrication process based on spin-coated-on polyimide was developed to integrate large arrays of micro/nano scale sensors, switches and electrodes into the network. This enables multiple layers to be integrated together with high precision alignment (sub-micron). Designs were developed to integrate organic thin film diodes into the network as switching devices. 3). Confirm the survivability of the network through an elevated cure process for aerospace composite material applications. A stretched sensor network was embedded into carbon fiber composite materials and put through a composite curing process with elevated temperature (350°F) and pressure (27 psi). Tests were made to ensure good insulation between the stretchable sensor network and the conductive carbon fiber composite materials. Network sensitivity was tested with a composite panel with a built-in sensor network that was able to sense the temperature change and impact loads through a simple electronic readout. Finally, an off-the-shelf robotic arm was integrated with a sensor network to exhibit the sensing, decision-making and control concept for intelligent material systems through the robot.


Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2014
Issuance monographic
Language English


Associated with Guo, Zhiqiang
Associated with Stanford University, Department of Mechanical Engineering.
Primary advisor Chang, Fu-Kuo
Thesis advisor Chang, Fu-Kuo
Thesis advisor Howe, Roger Thomas
Thesis advisor Kenny, Thomas William
Thesis advisor Pavone, Marco, 1980-
Advisor Howe, Roger Thomas
Advisor Kenny, Thomas William
Advisor Pavone, Marco, 1980-


Genre Theses

Bibliographic information

Statement of responsibility Zhiqiang Guo.
Note Submitted to the Department of Mechanical Engineering.
Thesis Thesis (Ph.D.)--Stanford University, 2014.
Location electronic resource

Access conditions

© 2014 by Zhiqiang Guo
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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