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Details of Grant 

EPSRC Reference: EP/W03722X/1
Title: IDEA: Inverse Design of Electrochemical Interfaces with Explainable AI
Principal Investigator: Xuan, Professor J
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Fraunhofer ISE Imperial College London Intelligent Energy Ltd
Johnson Matthey Princeton University Siemens Healthineers
Department: Chemical Engineering
Organisation: University of Surrey
Scheme: EPSRC Fellowship
Starts: 01 October 2023 Ends: 30 September 2028 Value (£): 2,177,756
EPSRC Research Topic Classifications:
Carbon Capture & Storage Electrochemical Science & Eng.
Fuel Cell Technologies
EPSRC Industrial Sector Classifications:
Chemicals Energy
Related Grants:
Panel History:
Panel DatePanel NameOutcome
17 Oct 2022 ELEMENT Fellowship Interview Panel 18 19 and 20 October 2022 Announced
17 Aug 2022 Engineering Prioritisation Panel Meeting 17 and 18 August 2022 Announced
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.

Key Findings
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Date Materialised
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Organisation Website: http://www.surrey.ac.uk