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Micromachined Electrical Field-flow Fractionation Systems with On-column Electrical and Resonance Light Scattering Detection Modalities

The objective of this research was to develop efficient, non-invasive separation systems for various biological and non-biological substances. One of the major technological pushes in modern bioanalysis instrumentation development is the realization of efficient, miniaturized bioanalysis systems. In this work, three sizes of micromachined electrical field-flow fractionation (m-ElFFF) systems, with complementary on-column electrical and optical detection modalities were fabricated to achieve this objective. Field-flow fractionation (FFF) technology is capable of fractionating (or separating) a wide variety of materials and is capable of hundreds of consecutive analysis runs using a single system. A highly promising sub-technique, particularly for the analysis of biological / biochemical materials, is electrical field-flow fractionation (ElFFF). In this work, microfabrication technologies were used to fabricate m-ElFFF systems that have smaller system volumes, require smaller sample volumes and have shorter run times than their macro-scale counterparts. Direct, on-column detection within the miniaturized separation device improved the resolution, decreased the band broadening, lowered the plate height, and shortened the overall analysis time. Also, the information obtained from these detection systems can be used to elucidate information on the electrical and physical characteristics of a sample. Therefore, complimentary on-column detection systems, were designed, fabricated and characterized. Additionally, the data from the two detection systems was compared and a quantitative correlation was performed, enabling the independent use of each detection system.

Identiferoai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/10426
Date23 December 2005
CreatorsGraff, Mason R.
PublisherGeorgia Institute of Technology
Source SetsGeorgia Tech Electronic Thesis and Dissertation Archive
Languageen_US
Detected LanguageEnglish
TypeDissertation
Format3901609 bytes, application/pdf

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