Carnegie Mellon University
Smith_cmu_0041E_10601.pdf (2.73 MB)

Molecular Scale Engineering of Functional Conducting Polymer Thin Films

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posted on 2020-12-17, 21:07 authored by Phil SmithPhil Smith
In the ever-growing electronics industry, products are constantly being reimagined and tailored around novel materials and processing techniques. Since the discovery of conducting polymers, interest in organic electronics have shifted, as is evident by the rise in market presence of organic light-emitting diodes (OLEDs) which was long the focus of research in academic and industry labs. Lightweight, mechanically flexible, easy to process and low manufacturing costs are a few desirable qualities that conducting polymers have over its inorganic counterparts.
Oxidative chemical vapor deposition (oCVD) polymerization is a new technique that merges CVD thin film processing with the versatility of organic chemistry. This vapor phase polymerization technique offers a facile, solvent-free and low temperature route to simultaneously tune chemistry, morphology and functionality, allowing for creative ways to engineer multiscale (thicknesses from nano to micro) and multifunctional (semiconducting, conducting) polymer films on a variety of substrates including paper, plastic, and biological tissue.
This thesis will study conducting polymers deposited via oCVD from thin film process development, thermal characterization, and various applications in which conducting polymers play a unique role. The deposition parameters for the conducting polymer, poly(3,4-ethylenedioxythiophene) (PEDOT) and the semi conducting polymer, polythiophene (PT) are optimized to create uniform and conformal thin films. Furthermore, the thermal conductivity of oCVD PEDOT is reported for the first time and a relationship to electrical conductivity is determined. This thesis also explores unique applications for these conducting polymers. First, a conducting polymer-based biosensor was utilized for distinguishing between specific and non-specific binding events. Processing the output data using machine learning resulted in a 75 % accurate prediction of the targeted biomolecule, Biotin. Second, surface modification of a lithium ion battery (LiMn2O4) electrode with oCVD PEDOT has yielded an 83% increase in rate capacity and a 40 % increase in cycling life. Third, coatings of oCVD PEDOT on 3D graphene structures resulted in the selective and sensitive detection of dopamine among other electroactive species.




Degree Type

  • Dissertation


  • Mechanical Engineering

Degree Name

  • Doctor of Philosophy (PhD)


B. Reeja Jayan Sheng Shen

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