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Dr Tim Duignan

Adjunct Research Fellow

School of Chemical Engineering
Faculty of Engineering, Architecture and Information Technology
t.duignan@uq.edu.au

Overview

I completed my PhD at the Australian National University in 2015 working on modelling and simulation of ion specific effects working with Drew Parsons and Barry Ninham. I then completed postdoctoral research at the Pacific Northwest National Laboratory in Washington State working with Christopher Mundy and Gregory Schenter on quantum mechanical molecular dynamics simulation and modelling of electrolyte solution before coming to the University of Queensland to work on electrochemcial enery storage. I am currently working on my DECRA project on improving the prediction of electrolyte solution properties for improved electrochemical energy storage.

Research Interests

  • Prediction of electrolyte solution properties
    I am interested in using both first principles molecular simulation and continuum solvent models in order to predict the fundamental properties of electrolyte solutions such as their free energies or chemical potentials. Understanding and predicting these properties are crucial for understanding and controlling a vast range of important practical applications where electrolyte solutions play a central role. This is because they determine many important properties such as solubilities, chemical equilibria, reaction rates and more. Unfortunately, we still have to rely almost entirely on equations with parameters fitted to experiment to determine these properties for the many practical applications where they play a role. This limits the predictive capability of our theories to cases where there has already been extensive experimental measurements. This is a huge problem as this experimental data is unreliable in many cases and non existent in many others. I am working to demonstrate that it is possible to use the information from first principles molecular simulation to build improved computationally cheap but accurate models of electrolyte solutions that can be rapidly applied to predict their many important properties.
  • Electrochemical energy storage
    I am interested in using modelling to predict and understand and design potential strategies to improve the energy storage capability of various materials such as hard carbon, expanded graphite and activated carbon.
  • Electrolyte solutions and surfactants at interfaces
    I am interested in predicting the properties of electrolyte and surfactants at the interfaces particularly the air-water interface. There are many unusual and important properties of electrolyte solutions at the air water interface such as the negative zeta potential, the Jones-Ray effect and bubble-bubble coalescence inhibtion that can be explained by careful modelling of the distribution of ions and charged surfactants at the air-water interface.

Qualifications

  • Doctor of Philosophy, Australian National University
  • Bachelor of Science, Australian National University

Publications

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Grants

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Supervision

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Available Projects

  • Prediction of electrolyte solution properties for improved energy storage

    This project aims to predict the properties of electrolyte solutions in order to develop improved energy storage devices. Electrolyte solutions play a central and fundamental role in a huge range of important systems and applications. They carry the electrical currents that make life possible, they control the chemical properties of the ocean such as its acidity and ability to absorb carbon dioxide. They also carry the electrical current between the positive and negative terminals of a battery. Optimising the electrolyte is, therefore, crucial to improving the stability, charging rate and lifetime of batteries. To do this we need accurate predictive models of the properties of electrolyte solutions. Unfortunately, we still cannot predict even some of the most basic properties of electrolytes solutions.

    In this project, we will use state of the art computational techniques to directly simulate electrolyte solutions and calculate their properties. We will then use these simulations to improve approximate models that can rapidly predict the properties of many different electrolyte solutions. These models will then be used to identify suitable candidate electrolytes for use in real energy storage devices. By joining this project, the successful candidate will have an excellent opportunity to develop skills in programming, computational chemistry and energy storage technology.

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Publications

Book Chapter

Journal Article

Conference Publication

Grants (Administered at UQ)

PhD and MPhil Supervision

Current Supervision

  • Prediction of new electrolytes for improved electrical energy storage.

    Doctor Philosophy — Principal Advisor

    Other advisors:

Completed Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • Prediction of electrolyte solution properties for improved energy storage

    This project aims to predict the properties of electrolyte solutions in order to develop improved energy storage devices. Electrolyte solutions play a central and fundamental role in a huge range of important systems and applications. They carry the electrical currents that make life possible, they control the chemical properties of the ocean such as its acidity and ability to absorb carbon dioxide. They also carry the electrical current between the positive and negative terminals of a battery. Optimising the electrolyte is, therefore, crucial to improving the stability, charging rate and lifetime of batteries. To do this we need accurate predictive models of the properties of electrolyte solutions. Unfortunately, we still cannot predict even some of the most basic properties of electrolytes solutions.

    In this project, we will use state of the art computational techniques to directly simulate electrolyte solutions and calculate their properties. We will then use these simulations to improve approximate models that can rapidly predict the properties of many different electrolyte solutions. These models will then be used to identify suitable candidate electrolytes for use in real energy storage devices. By joining this project, the successful candidate will have an excellent opportunity to develop skills in programming, computational chemistry and energy storage technology.

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Links

ResearcherID: B-8938-2014

ORCID: 0000-0003-3772-8057

Scopus ID: 37561391000

Google Scholar ID: NcMzLmMAAAAJ

Personal Profile: Link

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