ORCID Profile
0000-0002-1572-6782
Current Organisation
University of Oxford
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Publisher: Wiley
Date: 11-10-2018
Publisher: Wiley
Date: 31-10-2019
Publisher: The Open Journal
Date: 13-03-2020
DOI: 10.21105/JOSS.01848
Publisher: Wiley
Date: 14-06-2021
Abstract: Use of carefully designed computer supported parameterisation methods in voltammetric studies can provide highly robust and accurate methods for simultaneously quantifying the large number of parameters present in complex electrochemical reactions. In this study, a computer program has been developed to parameterise large litude AC voltammetric data using mathematical optimisation in combination with Bayesian inference algorithms for calculating posterior distributions of parameters and hence uncertainties in parameter values. The computer program has been applied to objective functions, relevant to total AC current, frequency domain data in the form of the power spectrum derived from Fourier transformation and multivariate based methods using the resolved harmonic data. The robustness of the objective functions have been confirmed and Bayesian inference methods have been validated using “noisy” synthetic and experimental data for the [Fe(CN) 6 ] 3−/4− reduction process in aqueous 3.0 M KCl electrolyte at a gold electrode. It was found that the harmonic based Bayesian inference methods outperformed other methods in parameterisation of the thermodynamics and electrode kinetics of the close to reversible [Fe(CN) 6 ] 3−/4− process due to their ability to compensate for non‐ideality in the modelling and the superior parameter sensitivities available in the higher harmonics. The computer supported and heuristic methods were compared. Their advantages and limitations are discussed.
Publisher: Cold Spring Harbor Laboratory
Date: 30-07-2019
DOI: 10.1101/719666
Abstract: Neural crest migration requires cells to move through an environment filled with dense extracellular matrix and mesoderm to reach targets throughout the vertebrate embryo. Here, we use high-resolution microscopy, computational modeling, and in vitro and in vivo cell invasion assays to investigate the function of Aquaporin-1 (AQP-1) signaling. We find that migrating lead cranial neural crest cells express AQP-1 mRNA and protein, implicating a biological role for water channel protein function during invasion. Differential AQP-1 levels affect neural crest cell speed, direction, and the length and stability of cell filopodia. Further, AQP-1 enhances matrix metalloprotease (MMP) activity and colocalizes with phosphorylated focal adhesion kinases (pFAK). Co-localization of AQP-1 expression with EphB guidance receptors in the same migrating neural crest cells raises novel implications for the concept of guided bulldozing by lead cells during migration.
Publisher: American Chemical Society (ACS)
Date: 19-12-2019
DOI: 10.1021/ACS.ANALCHEM.8B04238
Abstract: Recently, we introduced the use of techniques drawn from Bayesian statistics to recover kinetic and thermodynamic parameters from voltammetric data and were able to show that the technique of large litude ac voltammetry yielded significantly more accurate parameter values than the equivalent dc approach. In this paper, we build on this work to show that this approach allows us, for the first time, to separate the effects of random experimental noise and inherent system variability in voltammetric experiments. We analyze ten repeated experimental data sets for the [Fe(CN)
Publisher: American Chemical Society (ACS)
Date: 10-2018
DOI: 10.26434/CHEMRXIV.7149281.V1
Abstract: Recently, we have introduced the use of techniques drawn from Bayesian statistics to recover kinetic and thermodynamic parameters from voltammetric data, and were able to show that the technique of large litude ac voltammetry yielded significantly more accurate parameter values than the equivalent dc approach. In this paper we build on this work to show that this approach allows us, for the first time, to separate the effects of random experimental noise and inherent system variability in voltammetricexperiments. We analyse ten repeated experimental data sets for the [Fe(CN) 6 ] 3−/4− process, again using large- litude ac cyclic voltammetry. In each of the ten caseswe are able to obtain an extremely good fit to the experimental data and obtain very narrow distributions of the recovered parameters governing both the faradaic (the reversible formal faradaic potential, E_0, the standard heterogeneous charge transfer rate constant k_0, and the charge transfer coefficient α) and non-faradaic terms (uncompensated resistance, R_u , and double layer capacitance, C_dl). We then employ hierarchicalBayesian methods to recover the underlying “hyperdistribution” of the faradaic and non-faradaic parameters, showing that in general the variation between the experimental data sets is significantly greater than suggested by in idual experiments, except for α where the inter-experiment variation was relatively minor. Correlations between pairs of parameters are provided, and for ex le, reveal a weak link between k_0 and C_dl (surface activity of a glassy carbon electrode surface). Finally, we discuss theimplications of our findings for voltammetric experiments more generally.
Publisher: American Chemical Society (ACS)
Date: 08-01-2021
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Martin Robinson.