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Numerical Resolving of Net Faradaic Current in Fast-Scan Cyclic Voltammetry Considering Induced Charging Currents
Gabriel Wosiak1,2, Dyovani Coelho2, Evaldo B Carneiro-Neto2
1Universidade Estadual do Centro-Oeste, Campus CEDETEG, Al. Élio Antonio Dalla Vechia, 838, Guarapuava 85.040-167, PR, Brazil.
Induced charging currents affect fast-scan cyclic voltammetry by coupling faradaic and capacitive currents. A new method accurately separates these currents, improving analysis where conventional background subtraction fails.
Area of Science:
- Electrochemistry
- Analytical Chemistry
Background:
- Fast-scan cyclic voltammetry (FSCV) is sensitive to current contributions.
- Induced charging currents arise from coupled faradaic and capacitive currents with uncompensated resistance.
- These currents alter the capacitive contribution compared to measurements without electroactive species.
Purpose of the Study:
- To theoretically and experimentally investigate induced charging currents in FSCV.
- To address the inaccuracy of conventional background subtraction methods in specific conditions.
- To develop and validate a novel method for separating faradaic and capacitive currents.
Main Methods:
- Theoretical modeling of induced charging currents.
- Experimental validation using potassium ferrocyanide/ferricyanide redox couple.
- Utilizing platinum disk electrodes and varying NaClO4 concentrations for different cell time constants.
Main Results:
- Induced charging currents significantly impact FSCV, especially when capacitive current is close to the total current.
- Conventional background subtraction methods can be inaccurate under these conditions.
- The developed method successfully separates faradaic and capacitive currents, even with potential-dependent capacitance.
Conclusions:
- The proposed method accurately quantifies capacitive currents in FSCV, overcoming limitations of traditional approaches.
- This advancement is crucial for precise electrochemical analysis in systems with significant capacitive contributions.
- The study provides a more reliable approach for interpreting FSCV data.
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