scholarly journals Effect of Surface Roughness on Electrochemical Adsorption/Desorption of Dopamine by Carbonaceous Electrodes

Author(s):  
Alexander G. Zestos ◽  
Hanning Chen

Electrochemical adsorption/desorption of dopamine by carbonaceous electrodes upon voltage variation is the key process of neurotransmitter detection through fast scan cyclic voltammetry. In the present study, <i>ab initio</i> molecular dynamics simulation empowered by image-charge method was applied to calculate the adsorption/desorption free energy profile of dopamine and dopamine o-quinone at fixed electrode potentials using our newly developed open-source CP2K simulation package. It was found that the activation barriers for both adsorption and desorption were substantially reduced with increasing surface roughness of the carbonaceous electrodes. For example, on the flat graphene electrode, the activation barrier for dopamine adsorption at V<sub>0</sub>=−0.4V is 1.34 kcal/mol, while its counterpart on the curved nanotube electrode drops to 0.82 kcal/mol. Moreover, the diffusion coefficient of dopamine decreases by approximately 60% when it is moving close to the graphene electrode, while its diffusion is accelerated by up to 100% when the nanotube electrode is adopted. The faster diffusion alongside the reduced activation barrier greatly facilitates the electrochemically driven adsorption/desorption of dopamine by nanotube electrodes, in consistent with experimental findings that a rougher carbonaceous surface is critical for fast scan cyclic voltammetry.

2021 ◽  
Author(s):  
Alexander G. Zestos ◽  
Hanning Chen

Electrochemical adsorption/desorption of dopamine by carbonaceous electrodes upon voltage variation is the key process of neurotransmitter detection through fast scan cyclic voltammetry. In the present study, <i>ab initio</i> molecular dynamics simulation empowered by image-charge method was applied to calculate the adsorption/desorption free energy profile of dopamine and dopamine o-quinone at fixed electrode potentials using our newly developed open-source CP2K simulation package. It was found that the activation barriers for both adsorption and desorption were substantially reduced with increasing surface roughness of the carbonaceous electrodes. For example, on the flat graphene electrode, the activation barrier for dopamine adsorption at V<sub>0</sub>=−0.4V is 1.34 kcal/mol, while its counterpart on the curved nanotube electrode drops to 0.82 kcal/mol. Moreover, the diffusion coefficient of dopamine decreases by approximately 60% when it is moving close to the graphene electrode, while its diffusion is accelerated by up to 100% when the nanotube electrode is adopted. The faster diffusion alongside the reduced activation barrier greatly facilitates the electrochemically driven adsorption/desorption of dopamine by nanotube electrodes, in consistent with experimental findings that a rougher carbonaceous surface is critical for fast scan cyclic voltammetry.


2018 ◽  
Vol 10 (24) ◽  
pp. 2834-2843 ◽  
Author(s):  
Do Hyoung Kim ◽  
Yoonbae Oh ◽  
Hojin Shin ◽  
Cheonho Park ◽  
Charles D. Blaha ◽  
...  

A novel multi-waveform FSCV (M-FSCV) developed for characterizing adsorption/desorption kinetics of neurotransmitters.


2021 ◽  
Vol MA2021-02 (55) ◽  
pp. 1606-1606
Author(s):  
Alexander George Zestos ◽  
Favian Alberto Liu ◽  
Thomas Asrat ◽  
Harmain Rafi

2006 ◽  
Vol 3 (4) ◽  
pp. 384-388 ◽  
Author(s):  
Damiano Di Penta ◽  
Karim Bencherif ◽  
Michel Sorine ◽  
Qinghua Zhang

This paper proposes a reduced fuel cell stack model for control and fault diagnosis which was validated with experimental data. Firstly, the electro-chemical phenomena are modeled based on a mechanism of gas adsorption/desorption on catalysts at the anode and at the cathode of the stack, including activation, diffusion, and carbon monoxide poisoning. The electrical voltage of a stack cell is then modeled by the difference between the two electrode potentials. A simplified thermal model of the fuel cell stack is also developed in order to take into account heat generation from reactions, heat transfers, and evaporation/condensation of water. Finally, the efficiency ratio is computed as a model output. It is used to evaluate the efficiency changes of the entire system, providing an important indicator for fault detection.


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