Fresh Quantitative Approaches for High-Throughput Characterization Using ChemFETs and Statistical Analysis

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dc.contributor.advisorBanning, Douglas
dc.contributor.authorBanning, Douglas
dc.date.accessioned2025-02-24T19:58:01Z
dc.date.issued2025-02-24
dc.description.abstractAnion receptors are an increasingly important area of focus in synthetic organic chemistry, especially in areas such as environmental pollution detection and remediation. Many organic anion receptors are hydrophobic, limiting their utility for direct evaluation of aqueous anion affinity. Electrochemical sensors such as chemically-sensitive field effect transistors (ChemFETs) can bridge this gap. Incorporation of anion receptors into the chemically sensitive membrane of a ChemFET can facilitate direct measurement of aqueous anion affinity of hydrophobic sensors. One key piece of information that this can elucidate is the relative affinities of anions with the host by direct comparison of detection limits for each anion. Relative ranking of anion detection limits can be compared to the Hofmeister series, especially useful for determining the placement of relatively unknown, reactive species into the Hofmeister series.Dodeca-n-butyl bambus[6]uril was used in the selective membrane of a ChemFET to produce the first reported placement of hydrosulfide in the Hofmeister series. The contribution of the binding pocket geometry on anion affinities was then explored by comparing anion detection limits of dodeca-n-butyl bambus[6]uril with dodecabenzyl bambus[6]uril. The utility of ChemFETs was then expanded to assess the anion affinity of metal organic frameworks (MOFs), to learn about the anion binding nature of a novel MOF. After studying the nature of host-guest interactions using electrochemical sensors, research efforts expanded to include a statistically-based analytical method for characterization of synthetic pathways. Design of experiments (DOE) is generally used to characterize processes, and quantify impacts of main and multi-factor interactions on desired outputs. In chemical applications, DOE can characterize syntheses, specifically the impacts of each factor (together or in isolation) on the resulting product. This information can then be used to provide optimization conditions to produce desired properties. Significantly, this evaluation technique can be applied to historical data in order to characterize reactions before running any new experiments. In this particular case, flat aluminum 13 (f-Al13) cluster was analyzed via DOE in an effort to optimize desired properties. This data was then used to provide optimization conditions for the factors of size (minimize) and polydispersity index (minimize). Two different sets of optimization conditions were used as a validation run to synthesize aluminum particles, demonstrating a drastic improvement in one of the two optimization conditions. Finally, other research efforts are examined and documented. These efforts include ChemFET characterization of anion receptors, synthetic challenges, and application of DOE to characterize and optimize reactions. Overall, this dissertation involves the coalescence of different areas of study in order to solve difficult problems.en_US
dc.description.embargo2025-10-30
dc.identifier.urihttps://hdl.handle.net/1794/30470
dc.language.isoen_US
dc.publisherUniversity of Oregon
dc.rightsAll Rights Reserved.
dc.subjectAnion Receptoren_US
dc.subjectChemFETen_US
dc.subjectDesign of Experimentsen_US
dc.subjectDOEen_US
dc.subjectHost Guest Chemistryen_US
dc.subjectPhysical Organic Chemistryen_US
dc.titleFresh Quantitative Approaches for High-Throughput Characterization Using ChemFETs and Statistical Analysis
dc.typeElectronic Thesis or Dissertation
thesis.degree.disciplineDepartment of Chemistry and Biochemistry
thesis.degree.grantorUniversity of Oregon
thesis.degree.leveldoctoral
thesis.degree.namePh.D.

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