An automated high-throughput robotic platform for accelerated battery and fuels discovery - DIGIBAT

Started

Other Power and Storage Technologies(Energy storage)
Hydrogen and Fuel Cells(Fuel Cells, Other applications)

Basic and strategic applied research

PHYSICAL SCIENCES AND MATHEMATICS (Chemistry)
PHYSICAL SCIENCES AND MATHEMATICS (Metallurgy and Materials)
PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics)
ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering)

Not Cross-cutting

Professor M Titirici
Engineering and Materials Science
Queen Mary University of London

Standard

EPSRC

01 January 2023

31 July 2026

43 months

£1,656,452

Energy

London

Energy : Energy

Professor M Titirici, Engineering and Materials Science, Queen Mary University of London

Dr SJ Cooper, Design Engineering (Dyson School, Imperial College London
Dr R Greenaway, Chemistry, Imperial College London
Dr GJ Offer, Earth Science and Engineering, Imperial College London
Dr M Ryan, Materials, Imperial College London
Dr I E L Stephens, Materials, Imperial College London
Dr A Walsh, Chemistry, University of Bath

Project Contact, University of Toronto, Canada
Project Contact, Imperial College London
Project Contact, Johnson Matthey Plc
Project Contact, Toyota Motor Europe, Belgium
Project Contact, Ruhr-University Bochum (RUB), Germany
Project Contact, Sheffield Forgemasters Engineering Ltd (SFEL)
Project Contact, BP International Ltd
Project Contact, DiGiFab
Project Contact, Enserv Group
Project Contact, University Centre Somerset
Project Contact, Federal University of Toulouse Midi-Pyrénées
Project Contact, Faradion Limited
Project Contact, Deregallera Ltd

Batteries and electrocatalytic devices (i.e electrolysers, fuel cells) have multiple components spanning different length scales. The materials design space in these research fields is too large to be explored empirically. While experimental work can be directed by computational modelling to make this challenge more tenable, this is time consuming, and the number of tests/syntheses is still be too large on the experimental scale.DIGIBAT will combine computational tools (e.g. atomistic and molecular modelling, process modelling, computer-aided design, machine learning algorithms, data science) and automated HT synthesis, characterisation and testing from atoms to devices to accelerate the discovery and optimisation ofnew batteries and electrofuels.Specifically, DIGIBAT will comprise three HT stations: Platform A dedicated to materials synthesis and characterisation, Platform B dedicated to HT electrodes manufacturing all the way to device manufacturing and Platform C dedicated to HT electrochemical testing for both batteries and electrocatalysts. DIGIBAT will bepaired with materials characterisation also applied in HT, including in operando characterisation. By executing data-rich experiments, DIGIBAT will increase the pace of innovation, while enhancing reproducibility by eliminating human errors.The research enabled by ATLAS will target challenges related to: (1) the discovery and optimisation of new battery chemistries, (2) synthesising, optimising, and testing recycled battery materials; (3) Discovering precious metal free electrocatalysts for green H2 production and fuel cells; (4) Efficient N2 to ammonia and CO2 reduction to fuels and chemicals for electrocatalysts discovery

25/01/23