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Title: A 𝘬-means analysis of the voltage response of a soil-based microbial fuel cell to an injected military-relevant compound (urea)
Authors: Jones, Robert M.
Musty, Michael
Reynolds, Randall W.
Slone, Scott Michael L.
Barbato, Robyn A.
Creagar, Molly
Keywords: Biosensors
Contaminant detection
Pattern recognition
Soil microbial fuel cells
Soil pollution--Detection
Soil sensors
Voltage patterns
Publisher: Engineer Research and Development Center (U.S.)
Series/Report no.: Technical Report (Engineer Research and Development Center (U.S.)) ; no. ERDC/CRREL TR-22-24
Abstract: Biotechnology offers new ways to use biological processes as environmental sensors. For example, in soil microbial fuel cells (MFCs), soil electro-genic microorganisms are recruited to electrodes embedded in soil and produce electricity (measured by voltage) through the breakdown of substrate. Because the voltage produced by the electrogenic microbes is a function of their environment, we hypothesize that the voltage may change in a characteristic manner given environmental disturbances, such as the contamination by exogenous material, in a way that can be modelled and serve as a diagnostic. In this study, we aimed to statistically analyze voltage from soil MFCs injected with urea as a proxy for gross contamination. Specifically, we used 𝘬-means clustering to discern between voltage output before and after the injection of urea. Our results showed that the 𝘬-means algorithm recognized 4–6 distinctive voltage regions, defining unique periods of the MFC voltage that clearly identify pre- and postinjection and other phases of the MFC lifecycle. This demonstrates that 𝘬-means can identify voltage patterns temporally, which could be further improve the sensing capabilities of MFCs by identifying specific regions of dissimilarity in voltage, indicating changes in the environment.
Description: Technical Report
Gov't Doc #: ERDC/CRREL TR-22-24
Rights: Approved for Public Release; Distribution is Unlimited
Appears in Collections:Technical Report

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