Non-destructive impedance monitoring of bacterial metabolic activity towards continuous lead biorecovery
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Date
Authors
Andrews, George
Neveling, Olga
De Beer, Dirk Johannes
Chirwa, Evans M.N.
Brink, Hendrik Gideon
Trudi-Heleen
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Abstract
The adverse health effects of the presence of lead in wastewater streams are well documented,
with conventional methods of lead recovery and removal suffering from disadvantages such
as high energy costs, the production of toxic sludge, and low lead selectivity. Klebsiella pneumoniae
and Paraclostridium bifermentans have been identified as potential lead-precipitating species for use
in a lead recovery bioreactor. Electrical impedance spectroscopy (EIS) on a low-cost device is used
to determine the potential for the probe-free and label-free monitoring of cell growth in a bioreactor
containing these bacteria. A complex polynomial is fit for several reactive equivalent circuit
components. A direct correlation is found between the extracted supercapacitance and the plated
colony-forming unit count during the exponential growth phase, and a qualitative correlation is
found between all elements of the measured reactance outside the exponential growth phase. Strong
evidence is found that Pb(II) ions act as an anaerobic respiration co-substrate for both cells observed,
with changes in plated count qualitatively mirrored in the Pb(II) concentration. Guidance is given on
the implementation of EIS devices for continuous impedance monitoring.
Description
DATA AVAILABILITY STATEMENT : The data used in this study are publicly available in Mendeley Data at https://DOI.org/10.17632/jfvzvwzggv.1.
Keywords
Nondestructive, Inline monitoring, Bacterial growth, Metabolic activity, Lead biorecovery, Impedance spectroscopy
Sustainable Development Goals
Citation
Andrews, G.; Neveling, O.;
De Beer, D.J.; Chirwa, E.M.N., Brink,
H.G.; Joubert, T.-H. Non-Destructive
Impedance Monitoring of Bacterial
Metabolic Activity towards
Continuous Lead Biorecovery.
Sensors 2022, 22, 7045. https://DOI.org/10.3390/s22187045.