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

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

CoPED ID
89e92046-e544-433b-8cb3-2f5a1539af49

Status
Active


Value
£8,282,260

Start Date
Jan. 1, 2023

End Date
Dec. 31, 2025

Description

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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 of
new 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 be
paired 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

Magdalena Titirici PI_PER
Aron Walsh COI_PER
Samuel Cooper COI_PER
Rebecca Greenaway COI_PER
Ifan Stephens COI_PER
Gregory Offer COI_PER
Mary Ryan COI_PER

Subjects by relevance
  1. Optimisation
  2. Fuel cells
  3. Accumulators
  4. Machine learning
  5. Batteries
  6. Testing
  7. Modelling (representation)

Extracted key phrases
  1. Throughput robotic platform
  2. Accelerated battery
  3. Battery material
  4. New battery chemistry
  5. Automated high
  6. Fuel discovery
  7. Platform C
  8. Fuel cell
  9. HT electrochemical testing
  10. HT synthesis
  11. Material characterisation
  12. Electrocatalyst discovery
  13. Material design space
  14. Material synthesis
  15. DIGIBAT

Related Pages

UKRI project entry

UK Project Locations