Abstract
Enzymatic electrochemistry harnesses the selectivity of enzymes to enable electrochemical applications spanning sensing, synthesis, and energy conversion. However, the sequential nature of electroanalytical experiments limits throughput, restricting the scale at which enzyme-electrode systems can be screened. Here we demonstrate the capabilities of an automated electrochemistry platform, eLab, to increase the throughput of enzymatic electrochemistry investigations. We used the eLab to collect over 10,000 cyclic voltammograms across a large parameter space consisting of two enzyme variants (promiscuous and wild-type glucose oxidase), 20 saccharide substrates, 21 concentrations, and four scan rates, with measurements being made all in triplicate. The expansive dataset enabled rapid identification of apparent outlier behavior of wild-type glucose oxidase toward glucose, which was confirmed to arise from oxygen sensitivity through targeted manual experiments. The promiscuous variant showed negligible oxygen sensitivity, a critical advantage for applications, such as enzymatic sensors, bioelectrosynthesis, and biofuel cells. Overall, this work demonstrates how automation can be applied to accelerate discovery in bioelectrochemistry.
Recommended Citation
M. A. Pence et al., "An Automated Electrochemistry Platform for Accelerating the Characterization of Enzymatic Electrochemistry," ACS Electrochemistry, vol. 2, no. 7, pp. 1519 - 1526, American Chemical Society, Jul 2026.
The definitive version is available at https://doi.org/10.1021/acselectrochem.6c00095
Department(s)
Chemistry
Publication Status
Open Access
Keywords and Phrases
automation; cyclic voltammetry; enzyme electrochemistry; glucose oxidase; high-throughput
International Standard Serial Number (ISSN)
2997-0571
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2026 American Chemical Society, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
02 Jul 2026
