Modelling ac voltammetry with MECSim: facilitating simulation–experiment comparisons

Kennedy, Gareth; Bond, Alan M.; Simonov, Alexandr N.

doi:10.1016/j.coelec.2016.12.001

Cited by 46 publications

(67 citation statements)

References 31 publications

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“…Simulations of total current AC voltammograms used in initial heuristic forms of data analysis were carried out with MECSim (Monash Electrochemistry Simulator) software. [9] In the automated data optimisation studies, modelling was undertaken using the PINTS (Probabilistic Inference on Noisy Time Series) software [52] and code specifically written for use with this method. Details of the model and parametrization employed with this approach are provided in the Results and Discussion section.…”

Section: Simulations and Data Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The forward process of predicting the theory using a proposed model, once also highly demanding when computer coding of all steps was required in each study, can now be achieved routinely with user friendly, commercially available software packages such as DigiSim, DigiElch, KISSA or by using freeware that can be downloaded from the web such as MECSim. [9] Now it is the inverse problem of deciding which model and combination of parameters best describes the experimental data and how good is the fit that usually presents the daunting challenge. Typically, the experimentalist who collected the data may elect to "guess" the model that is applicable and rely on experience to fit the data by essentially trial and error procedures in what almost invariably becomes an extensive series of very tedious theory-experiment comparisons.…”

Section: Introductionmentioning

confidence: 99%

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Integration of Heuristic and Automated Parametrization of Three Unresolved Two‐Electron Surface‐Confined Polyoxometalate Reduction Processes by AC Voltammetry

et al. 2018

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The thermodynamic and electrode kinetic parameters that describe each of the three unresolved proton‐coupled two‐electron transfer processes of surface‐confined Keggin‐type phosphomolybdate, [PMo12O40]3− adsorbed onto glassy carbon electrode in 1.0 M H2SO4 have been elucidated by comparison of experimental and simulated AC voltammmetric data. Modelling of this problem requires the introduction of over 30 parameters, although this may be reduced to about half this number when intelligent forms of data analysis are introduced. Heuristic (i. e., an experimenter based trial and error method) and automated data optimization approaches are integrated in this very extensive parameter estimation exercise. However, obtaining a unique solution remains challenging for reasons that are outlined. In the final analysis and using the automated strategy, estimates of six reversible potentials, lower limits of the six electron transfer rate constants, the double layer capacitance, uncompensated resistance and surface coverage are reported, with others (such as the charge transfer co‐efficient) present in the model being unobtainable for reasons that are provided. The fit to experimental data using parameters obtained by automated data optimisation is excellent and slightly superior to that obtained by heuristic analysis. The parameters obtained by either method account for differences in shapes and current magnitudes of each of the overall two electron processes.

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Section: Simulations and Data Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Integration of Heuristic and Automated Parametrization of Three Unresolved Two‐Electron Surface‐Confined Polyoxometalate Reduction Processes by AC Voltammetry

et al. 2018

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“…While simulation of the forward multi‐step problem relevant to this study is inherently complex, it can be readily achieved nowadays with the aid of commercially available DigiElch or KISSA or web downloadable software packages such as MECSim. Alternatively, in‐house coding of the algorithms needed to generate the model can be undertaken as in our recent work on the reduction of

{[{PMo}_{12} O_{40}]}^{3 -}

at a GC electrode in 1 M H 2 SO 4 .…”

Section: Introductionmentioning

confidence: 99%

Models and Their Limitations in the Voltammmetric Parameterization of the Six‐Electron Surface‐Confined Reduction of [PMo₁₂O₄₀]³⁻ at Glassy Carbon and Boron‐Doped Diamond Electrodes

et al. 2019

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In acidic media, three well-defined surface confined overall two electron transfer reactions derived from closely spaced oneelectron steps are observed in the DC and AC voltammetry of ½PMo 12 O 40 � 3À . In this study, parameterization of these processes by sinusoidal AC voltammetry at glassy carbon (GC) and boron doped diamond (BDD) electrodes has been undertaken in 1 M HClO 4 . The experiment-simulation comparison of even a simplified reaction scheme required estimation of 21 parameters, which is an exceptionally large number in voltammetry. The six reversible potentials were robustly recovered from data obtained at low (9.02 Hz) and higher (60.05 Hz) frequencies at both GC and BDD electrodes. Examination of the harmonic content by the Fourier transformed version of AC voltammetry enabled imperfections in the model associated with faradaic and non-faradaic aspects of the voltammetry to be readily detected. After consideration of these imperfections, all processes were considered to be reversible within experimental uncertainty. Subtle differences in reversible potentials observed at both electrodes account for electrode dependence in shapes of the overall two electron steps. Fits of experimental data were superior using BDD at both frequencies and for the higher frequency GC case. Non-compliance with an assumed potential independent model of the double layer capacitance was considered to be a significant contributor to discrepancies found with the GC electrode.[a] Dr.

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“…The capacitance-potential data are generated and fitted95 with a polynomial equation. Equation 3.7 describes the potential dependence of a non-linear capacitor140…”

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confidence: 99%

The electrochemical double layer in ionic liquids

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First of all, I have the utmost thanks for my wife, Molly, for her support and sacrifices while pursuing my degree. She has kept me sane during our time in Iowa, especially during the more demanding times in graduate school. Secondly, I owe many thanks to my advisor, Prof. Scott K. Shaw for his guidance and mentorship throughout my studies. He is the definition of a good boss and it has been a pleasure working under his supervision. With his direction I have learned a lot during my time at Iowa and he has helped me in countless research endeavors with no biology. Thirdly, I would like to thank my Shaw group co-workers and many others in the department. We literally helped build the laboratory and it's been a fun ride learning with everyone along the way. I would also like to thank my mentors and collaborators Professors Alan M. Bond and Jie Zhang from Monash University. They welcomed me in 2015 during my three-month research visit to Monash University and have helped me grow as a scientist. Furthermore, I would also like to thank my parents and brother, Gerald, Sherrie and Adam, in addition to countless mentors I met throughout my undergraduate studies who all helped encourage and support me in pursuing a PhD degree. Lastly, I wish to thank the University of Iowa, Department of Chemistry and the administrators/staff. They have always treated me with respect and provided a platform to embark on research and teaching. Included in this list are my faculty committee members who have guided me during my studies. I am very grateful for your support.

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Modelling ac voltammetry with MECSim: facilitating simulation–experiment comparisons

Cited by 46 publications

References 31 publications

Integration of Heuristic and Automated Parametrization of Three Unresolved Two‐Electron Surface‐Confined Polyoxometalate Reduction Processes by AC Voltammetry

Integration of Heuristic and Automated Parametrization of Three Unresolved Two‐Electron Surface‐Confined Polyoxometalate Reduction Processes by AC Voltammetry

Models and Their Limitations in the Voltammmetric Parameterization of the Six‐Electron Surface‐Confined Reduction of [PMo₁₂O₄₀]³⁻ at Glassy Carbon and Boron‐Doped Diamond Electrodes

The electrochemical double layer in ionic liquids

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Modelling ac voltammetry with MECSim: facilitating simulation–experiment comparisons

Cited by 46 publications

References 31 publications

Integration of Heuristic and Automated Parametrization of Three Unresolved Two‐Electron Surface‐Confined Polyoxometalate Reduction Processes by AC Voltammetry

Integration of Heuristic and Automated Parametrization of Three Unresolved Two‐Electron Surface‐Confined Polyoxometalate Reduction Processes by AC Voltammetry

Models and Their Limitations in the Voltammmetric Parameterization of the Six‐Electron Surface‐Confined Reduction of [PMo12O40]3− at Glassy Carbon and Boron‐Doped Diamond Electrodes

The electrochemical double layer in ionic liquids

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Models and Their Limitations in the Voltammmetric Parameterization of the Six‐Electron Surface‐Confined Reduction of [PMo₁₂O₄₀]³⁻ at Glassy Carbon and Boron‐Doped Diamond Electrodes