A 𝘬-means analysis of the voltage response of a soil-based microbial fuel cell to an injected military-relevant compound (urea)

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.

Key findings

• ▸The k-means algorithm recognized 4-6 distinctive voltage regions, identifying unique periods of the MFC lifecycle.
• ▸The study demonstrated that voltage patterns can be used to identify pre- and post-injection phases of the MFC lifecycle.
• ▸The results suggest that MFCs can be used as environmental sensors to detect contamination and other disturbances.

Keywords

Identifiers

DOI

10.21079/11681/45940

Journal

Unknown journal

Year

2022