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dc.contributor.advisorHunter, Ian W.
dc.contributor.authorAling, Michael
dc.date.accessioned2023-04-06T14:32:16Z
dc.date.available2023-04-06T14:32:16Z
dc.date.issued2022-09
dc.date.submitted2022-10-05T13:45:34.833Z
dc.identifier.urihttps://hdl.handle.net/1721.1/150433
dc.description.abstractBiologically active fluids dominate living systems, from human blood to global agriculture. Characterizing the growth of microorganisms within these biofluids is of key importance from scientific roles identifying pathogens and their biochemical behavior to industrial applications in food safety, healthcare, and pharmaceuticals. Compact, low-cost electrochemical sensors that monitor microorganism population and growth have attracted attention as replacements for days-long plate-counting -- potentially delivering results within hours or seconds by monitoring model parameters from diverse physical and chemical phenomena as they trace sigmoidal growth curves under microbial influence. Within the measurement framework of electrochemical impedance spectroscopy, this work proposes extracting additional information from biofluid systems by harnessing a nonlinear dynamic electrochemical model. A modular laboratory platform has been developed to perform parallel, temperature-controlled two-electrode electrochemical experiments from DC conditions to 10 MHz on compact hardware amenable to a low-cost sensor format for end users. An outline of a general-purpose, black-box technique to characterize fluids and predict their evolution over time is also presented, along with platform commissioning tests and preliminary data and analysis.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright MIT
dc.rights.urihttp://rightsstatements.org/page/InC-EDU/1.0/
dc.titleAn Electrochemical Sensor Development Platform: Applications of System Identification to Biological Sensing in Evolving Fluids
dc.typeThesis
dc.description.degreeS.M.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.identifier.orcidhttps://orcid.org/0000-0001-7622-4850
mit.thesis.degreeMaster
thesis.degree.nameMaster of Science in Mechanical Engineering


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