Electrode reactions are inherently complex as they involve interfacial charge transfer, mass transport, many species, different timescales, thermodynamics and kinetics, as well as chemical, material and electrical properties. Furthermore the electron transfer may be complicated by adsorption and desorption of reactants or products, by solid state processes such as the insertion and extraction of ions and by the presence of two or three phases. To account for this complexity modern electrochemistry and electrochemical engineering research increasingly relies on simulations to predict the evolution of key electrochemical parameters, typically current, charge, electrode potential, cell voltage and impedance, during the course of an electrochemical process.
This module will introduce the key principles and techniques used to model electrochemical processes and produce qualitative and quantitatively predictions of electrochemical parameters. The different computational and numerical methods will be considered through examples. Each case will start with the physical and chemical aspects of the model then move on to the computational or numerical approach appropriate for the problem. The module will consider dedicated electrochemistry modelling software such as DigiElch or DigiSim and general numerical modelling software such as Matlab and COMSOL Multiphyiscs.
The module will cover modelling across different length scales. The continuum length scale will be used to describe reactions involving mass transport, e.g. by numerically solving partial differential equations of the concentrations in space and time. Numerical methods such as finite difference, finite elements and boundary elements will be discussed. The atomistic scale will be used to compute the energetics of molecular and ionic interactions, predict the thermodynamics and kinetics of reactions on electrodes or describe the structure of the double layer. Molecular dynamics, Monte Carlo and density functional theory methods will be presented. A meso-scale technique such as the lattice Boltzmann method will be described to bridge the continuum with the atomistic world.
Aims and Objectives
Having successfully completed this module you will be able to:
- assess the limitations of these key methods
- select a computational or numerical technique appropriate for a given electrochemical process
- use electrochemical modelling terminology and concepts
- appraise the use of modelling in electrochemical research
- explain the principles of key computational and numerical modelling techniques used in electrochemical science
- explain the principles of modelling electrochemical systems
- use available electrochemical modelling software to simulate simple electrochemical processes
- simulate basic electrochemical processes
- mathematical models which mimic the physicochemical properties of the electrode process
- numerical techniques to solve partial differential equations relevant to electrochemical processes: finite difference, finite element, boundary elements
- atomistic algorithms to compute the molecular arrangement and energetics: Monte Carlo, molecular dynamics, empirical potentials, density functional theory
Learning and Teaching
Teaching and learning methods
Directed reading, BB online support
|Preparation for scheduled sessions||8|
|Completion of assessment task||16|
|Practical classes and workshops||4|
|Total study time||75|
This is how we’ll formally assess what you have learned in this module.
Repeat type: Internal & External