TY - JOUR
T1 - Hard Potato
T2 - A Python Library to Control Commercial Potentiostats and to Automate Electrochemical Experiments
AU - Rodríguez, Oliver
AU - Pence, Michael A.
AU - Rodríguez-López, Joaquín
N1 - Publisher Copyright:
© 2023 American Chemical Society.
PY - 2023/3/21
Y1 - 2023/3/21
N2 - Here, we develop and show the use of an open-source Python library to control commercial potentiostats. It standardizes the commands for different potentiostat models, opening the possibility to perform automated experiments independently of the instrument used. At the time of this writing, we have included potentiostats from CH Instruments (models 1205B, 1242B, 601E, and 760E) and PalmSens (model Emstat Pico), although the open-source nature of the library allows for more to be included in the future. To showcase the general workflow and implementation of a real experiment, we have automated the Randles-Ševčĺk methodology to determine the diffusion coefficient of a redox-active species in solution using cyclic voltammetry. This was accomplished by writing a Python script that includes data acquisition, data analysis, and simulation. The total run time was 1 min and 40 s, well below the time it would take even an experienced electrochemist to apply the methodology in a traditional manner. Our library has potential applications that expand beyond the automation of simple repetitive tasks; for example, it can interface with peripheral hardware and well-established third-party Python libraries as part of a more complex and intelligent setup that relies on laboratory automation, advanced optimization, and machine learning.
AB - Here, we develop and show the use of an open-source Python library to control commercial potentiostats. It standardizes the commands for different potentiostat models, opening the possibility to perform automated experiments independently of the instrument used. At the time of this writing, we have included potentiostats from CH Instruments (models 1205B, 1242B, 601E, and 760E) and PalmSens (model Emstat Pico), although the open-source nature of the library allows for more to be included in the future. To showcase the general workflow and implementation of a real experiment, we have automated the Randles-Ševčĺk methodology to determine the diffusion coefficient of a redox-active species in solution using cyclic voltammetry. This was accomplished by writing a Python script that includes data acquisition, data analysis, and simulation. The total run time was 1 min and 40 s, well below the time it would take even an experienced electrochemist to apply the methodology in a traditional manner. Our library has potential applications that expand beyond the automation of simple repetitive tasks; for example, it can interface with peripheral hardware and well-established third-party Python libraries as part of a more complex and intelligent setup that relies on laboratory automation, advanced optimization, and machine learning.
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U2 - 10.1021/acs.analchem.2c04862
DO - 10.1021/acs.analchem.2c04862
M3 - Article
C2 - 36888926
AN - SCOPUS:85149764981
SN - 0003-2700
VL - 95
SP - 4840
EP - 4845
JO - Analytical Chemistry
JF - Analytical Chemistry
IS - 11
ER -