| EPSRC Reference: |
EP/W03722X/1 |
| Title: |
IDEA: Inverse Design of Electrochemical Interfaces with Explainable AI |
| Principal Investigator: |
Xuan, Professor J |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Department: |
Chemical Engineering |
| Organisation: |
University of Surrey |
| Scheme: |
EPSRC Fellowship |
| Starts: |
01 October 2023 |
Ends: |
30 September 2028 |
Value (£): |
2,177,756
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| EPSRC Research Topic Classifications: |
| Carbon Capture & Storage |
Electrochemical Science & Eng. |
| Fuel Cell Technologies |
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Summary on Grant Application Form |
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.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.surrey.ac.uk |