Mechanistic and data-driven modeling of carbon respiration with bio-electrochemical sensors.

Autor: Puri R; Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States., Emaminejad SA; Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States; Black & Veatch, 180 N Wacker Dr Suite 550, Chicago, IL 60606, United States., Cusick RD; Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States. Electronic address: rcusick@illinois.edu.
Jazyk: angličtina
Zdroj: Current opinion in biotechnology [Curr Opin Biotechnol] 2024 Aug; Vol. 88, pp. 103173. Date of Electronic Publication: 2024 Jul 20.
DOI: 10.1016/j.copbio.2024.103173
Abstrakt: Bioelectrochemical sensor (BES) technologies have been developed to measure soluble carbon concentrations in wastewater. However, architectures and analytical methods developed in controlled laboratory environments fail to predict BES behavior during field deployments at water resource recovery facilities (WRRFs). Here, we examine the possibilities and obstacles associated with integrating BESs into environmental sensing networks and machine learning algorithms to monitor the biodegradable carbon dynamics and microbial metabolism at WRRFs. This approach highlights the potential of BESs to provide real-time insights into full-scale biodegradable carbon consumption across WRRFs.
Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest related to the manuscript submission.
(Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
Databáze: MEDLINE
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