IDEA: Inverse Design of Electrochemical Interfaces with Explainable AI
Lead Research Organisation:
University of Surrey
Department Name: Chemical Engineering
Abstract
The IDEA Fellowship is a 5-year programme to pave the way for the UK's industrial decarbonisation and digitalisation, via emerging AI, digital transformations applied to fundamental electrochemical engineering research.
Electrochemical engineering is at the heart of many key energy technologies for the 21st century such as H2 production, CO2 reduction, energy storage, etc. Further developments in all these areas require a better understanding of the electrode-electrolyte interfaces in the electrochemical systems because almost all critical phenomena occur at such interface, which eventually determine the kinetics, thermodynamics and long-term performance of the systems. Designing the next generation of electrochemical interfaces to fulfil future requirements is a common challenge for all types of electrochemical applications.
Designing an electrochemical interface traditionally relies on high throughput screening experiments or simulations. Given the complex nature of the design space, it comes with no surprise that this brute-force approach is highly iterative with low success rates, which has become a common challenge faced by the electrochemical research community.
The vision of the fellowship is to make a paradigm-shift in how future electrochemical interfaces can be designed, optimised and self-evolved throughout their entire life cycle via novel Explainable AI (XAI) and digital solutions. It will create an inverse design framework, where we use a set of desired performance indicators as input for the XAI models to generate electrochemical interface designs that satisfy the requirements, in a physically-meaningful way interpretable by us. The methodology, once developed, will tackle exemplar challenges of central importance to the net zero roadmap, which include improving current systems such as H2 production/fuel cell and CO2 reduction, but also developing new electrochemical systems which do not yet exist today at industrial scale such as N2 reduction and multi-ion energy storage.
Electrochemical engineering is at the heart of many key energy technologies for the 21st century such as H2 production, CO2 reduction, energy storage, etc. Further developments in all these areas require a better understanding of the electrode-electrolyte interfaces in the electrochemical systems because almost all critical phenomena occur at such interface, which eventually determine the kinetics, thermodynamics and long-term performance of the systems. Designing the next generation of electrochemical interfaces to fulfil future requirements is a common challenge for all types of electrochemical applications.
Designing an electrochemical interface traditionally relies on high throughput screening experiments or simulations. Given the complex nature of the design space, it comes with no surprise that this brute-force approach is highly iterative with low success rates, which has become a common challenge faced by the electrochemical research community.
The vision of the fellowship is to make a paradigm-shift in how future electrochemical interfaces can be designed, optimised and self-evolved throughout their entire life cycle via novel Explainable AI (XAI) and digital solutions. It will create an inverse design framework, where we use a set of desired performance indicators as input for the XAI models to generate electrochemical interface designs that satisfy the requirements, in a physically-meaningful way interpretable by us. The methodology, once developed, will tackle exemplar challenges of central importance to the net zero roadmap, which include improving current systems such as H2 production/fuel cell and CO2 reduction, but also developing new electrochemical systems which do not yet exist today at industrial scale such as N2 reduction and multi-ion energy storage.
Organisations
- University of Surrey (Lead Research Organisation)
- Fraunhofer ISE (Project Partner)
- Princeton University (Project Partner)
- Imperial College London (Project Partner)
- Johnson Matthey (United Kingdom) (Project Partner)
- Siemens Process Systems Engineering Ltd (Project Partner)
- Intelligent Energy (Project Partner)
Publications
Daniel T
(2024)
Potential of Progressive and Disruptive Innovation-Driven Cost Reductions of Green Hydrogen Production.
in Energy & fuels : an American Chemical Society journal
| Description | Electrochem 2024 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Industry/Business |
| Results and Impact | At Electrochem 2024 on 11-13 September 2024 at Manchester Metropolitan University, Centre Director Prof Jin Xuan was invited as Keynote speaker and Centre researcher Mohammad Danish Khan also presented his research on 'Microbial Fuel Cells and Microbial Electrosynthesis: Transforming Glycerol-rich Wastewater and CO2 into Valuable Products with Future Integration Potential'. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.rsc.org/events/detail/79233/electrochem2024 |
| Description | IChemE Digitalisation Committee Member |
| Form Of Engagement Activity | A formal working group, expert panel or dialogue |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Serving as a member of the IChemE Digitalisation Committee |
| Year(s) Of Engagement Activity | 2024,2025 |
| Description | Policy Roundtable: AI and Machine Learning in Plant Operation and Control |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Policymakers/politicians |
| Results and Impact | Policy Roundtable: AI and Machine Learning in Plant Operation and Control, Organised by IChemE, London, UK |
| Year(s) Of Engagement Activity | 2024 |
