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Carolyn Bayer
Graduate Student
The University of Texas at Austin
1 University Station, MC C0400
Chemical Engineering Dept.
Austin, TX 78712
carolynbayer@mail.utexas.edu

   

Background

Carolyn Bayer (maiden name Lester) received a B.S. degree in Electrical Engineering from Case Western Reserve University in May 1998. After graduation, she worked for Motorola in Phoenix, AZ for four years. While at Motorola, she participated in the development of DNA microarrays within the Life Sciences Division (now part of GE Medical). Her experience at Motorola led to a position as a senior engineer at Neogenesis (now part of Schering-Plough) in Cambridge, MA. She was employed there for three years, developing processes for their high throughput drug screening lines. She returned to school in the fall of 2005 to pursue a PhD in Biomedical Engineering, working with Dr. Peppas at the University of Texas at Austin.

Research Summary

My PhD research seeks to develop novel sensing and recognition nanodevices that are entirely synthetic and tailored to have various biomedical and perhaps even diagnostic or recognitive properties. We investigate nanosystems based on intelligent diagnostic polymer layers such as ionic and biomimetic networks.

These network films are desirable alternatives to biological entities because they can be designed to mimic biological recognition pathways and at the same time exhibit properties that are more favorable for nanosensing applications. Procedures will be developed to facilitate integration of intelligent polymer networks and silicon substrates at the nanoscale. Mask aligned systems will be utilized to precisely micropattern ultra-thin polymers films into silicon. Biomolecules will be micropatterned onto silicon substrates via UV free-radical polymerization. Due to the inherent dissimilarities of organic polymer networks and inorganic silicon devices, either an organosilane coupling agent will be utilized to gain covalent adhesion between the polymer network and the silicon surface or an Iniferter-based method will be applied. These general procedures will be applied to multiple intelligent polymer networks.

Biomimetic recognitive networks specific for a target substrates and characterized by single and competitive fluorescent and confocal microscopy studies, SEM, and profilometry. Specifically, we micropattern biomimetic recognitive hydrogel networks that selectively recognizes various biomolecules among similar molecules via non-covalent complexation.

Publications

 

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