The biological memory effect in microbial fuel cell biosensors

Jianwei Zhang, Hao Ren, Suren Jayasuriya, Xiao Jun Tian, Junseok Chae

Research output: Contribution to journalArticlepeer-review

Abstract

Microbial fuel cells (MFCs) are electrochemical fuel cells that directly convert the chemical energy of organic compounds in biomass into electrical energy. Due to their self-sustainability, direct current output and fast response, MFC biosensors have the potential for long-term environmental monitoring applications. For the first time, we report a biological memory effect (BME) in MFC biosensors during repeated toxin injections. The toxin response of the biosensors generally weakens over repeated toxin stimuli injection at low concentrations. Experimental results demonstrate that the current drop of the second and third toxin injection is only 48.88% and 28.13% of the first toxin injection on average. To investigate this biological memory effect, an ordinary differential equation (ODE) model is established. By fitting ODE model parameters to the experimental results, the model successfully simulates the experiments and the BME. This ODE model has good potential to compensate for the BME with its predictive ability, and it may potentially correct inaccuracies that accrue during long-term environmental monitoring for MFC biosensors. The current research paves the way for implementing MFC biosensors for long-term environmental toxic chemical detection.

Original languageEnglish (US)
Pages (from-to)1
Number of pages1
JournalIEEE Sensors Journal
DOIs
StateAccepted/In press - 2022

Keywords

  • Anodes
  • Biological memory effect (BME)
  • Biology
  • Biosensor
  • Biosensors
  • Fuel cells
  • Long-term monitoring
  • Mathematical models
  • Microbial fuel cell (MFC)
  • Microorganisms
  • Sensors
  • Toxin detection

ASJC Scopus subject areas

  • Instrumentation
  • Electrical and Electronic Engineering

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