Files in this item



application/pdfLu_Chi.pdf (1MB)
(no description provided)PDF


Title:Highly sensitive strain gauge based entirely on elastomers via molding process
Author(s):Lu, Chi
Advisor(s):Rogers, John A.
Department / Program:Materials Science & Engineerng
Discipline:Materials Science & Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Strain Gauges
Hignly Sensitive
Molding Process
Abstract:This thesis is mainly about the research on highly sensitive strain gauges based entirely on elastomers and partially about the molding process which is used to fabricate the strain gauge and pattern poly-dimethylsiloxane (PDMS). In this thesis, I demonstrate the design, fabrication and characterization of high gauge factor (GF), all-elastomer strain gauge systems, with Young’s modulus of 224 kPa, which lies within the range of the human epidermis. The devices combine carbon black doped-PDMS resistors, carbon nanotube doped-PDMS conductors and an insulating PDMS matrix/substrate to yield, in mechanically optimized geometrical layouts, desired characteristics. Measurement of strains in human skin using sensor sheets of this type, physically laminated onto the wrist, illustrates a representative implementation. Strains measured in this mode on the wrist are between 11.2% and 22.6%. Such sheets can be readily laminated on and form conformal contact to the human skin, with only modest mechanical constraints on natural motions. Moreover, the devices remain attached even under full-range bending of the joint, with minimal effects of mechanical constraint or mass loading. The approach I used to pattern the conductive PDMS is molding and scrapping. Molding process can not only be used to pattern conductive PDMS but also regular PDMS. For example, skin-like PDMS sheet with an array of hollows will be discussed later in the thesis.
Issue Date:2012-06-27
Rights Information:Copy Right 2012 Chi Lu
Date Available in IDEALS:2014-06-28
Date Deposited:2012-05

This item appears in the following Collection(s)

Item Statistics