Abstract
Reproducible data and results underpin the credibility and integrity of research findings across the sciences. However, experiments and measurements conducted across laboratories, or by different researchers, are often hindered by incomplete or inaccessible procedural data. Additionally, the time and resources needed to manually perform repeat experiments and analyses limit the scale at which experiments can be reproduced. Both improved methods for recording and sharing experimental procedures in machine-readable formats and efforts towards automation can be beneficial to circumvent these issues. Here we report the development of ExpFlow, a data collection, sharing, and reporting software currently customized for electrochemical experiments. The ExpFlow software allows researchers to systematically encode laboratory procedures through a graphical user interface that operates like a fill-in-the-blank laboratory notebook. Built-in calculators automatically derive properties such as diffusion coefficient and charge-transfer rate constant from uploaded data. Further, we deploy ExpFlow procedures with robotic hardware and software to perform cyclic voltammetry (CV) experiments in triplicate for eight well-known electroactive systems. The resulting oxidation potentials and diffusion coefficients are consistent with literature-reported values, validating our approach and demonstrating the utility of robotic experimentation in promoting reproducibility. Ultimately, these tools enable automated and (semi)autonomous cyclic voltammetry experiments and measurements that will facilitate high-throughput experimentation, reproducibility, and eventually data-driven electrochemical discovery.
Original language | English |
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Pages (from-to) | 163-172 |
Number of pages | 10 |
Journal | Digital Discovery |
Volume | 3 |
Issue number | 1 |
DOIs | |
State | Published - Dec 5 2023 |
Bibliographical note
Publisher Copyright:© 2024 RSC.
Funding
This work was generously supported by the National Science Foundation (NSF) under Cooperative Agreement Number 2019574. We thank Dr Andrew Horvath for testing ExpFlow and providing perspective on the software design, and we thank Dr Judy Jenkins for her expert advice regarding the robotic electrochemistry setup. Finally, we wholeheartedly thank the entire DTaLES ( https://d3tales.as.uky.edu/ ) team for their insights into the development of this software and robotic system. 3
Funders | Funder number |
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National Science Foundation Arctic Social Science Program | 2019574 |
National Science Foundation Arctic Social Science Program |
ASJC Scopus subject areas
- Chemistry (miscellaneous)