Advanced dynamic electrochemistry with Bayesian inference

  • Zhang, Jie (Primary Chief Investigator (PCI))
  • Bond, Alan (Chief Investigator (CI))
  • Gavaghan, David (Partner Investigator (PI))
  • Parkin, Alison (Partner Investigator (PI))

Project: Research

Project Details

Project Description

Experiments designed to understand the complex phenomena that commonly govern the operation of electrochemical devices such as batteries and biosensors are often based on dynamic voltammetric principles. Now, in-house advanced alternating current voltammetric instrumentation and software packages that model the relevant physical chemistry will be integrated with data analysis tools derived from Bayesian inference to provide a roadmap needed to provide new insights into important problems in hydrogenase and ionic liquid electrochemistry. Collaboration with UK computational and bioinorganic experts in this multi-disciplinary project will set a new standard for reporting and commercially exploiting statistically understood electrode kinetics.
Effective start/end date1/01/1731/12/20


  • Australian Research Council (ARC): AUD509,500.00
  • Australian Research Council (ARC)
  • Monash University: AUD268,694.00
  • University of Oxford: AUD393,900.00
  • University of York: AUD112,200.00