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The UK Car-Parrinello HEC Consortium

Lead Research Organisation: University of Southampton
Department Name: Sch of Chemistry

Abstract

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Publications

10 25 50
 
Description The availability of the HEC UKCP, and the developments on the ONETEP large-scale DFT code we have done as a result, have allowed us to do simulations in cutting edge technological areas such as processes of degradation of battery materials during operational conditions and mitigation strategies. Another area of active research where we have contributed with our developments is in catalysis where we have simulated and identified palladium carbide nanoparticles for selective hydrogenation of alkynes and also platinum nanoparticle catalysts for proton exchange membrane hydrogen fuel cells.
Exploitation Route Our findings are of direct industrial relevance. For example the hydrogen fuel cell catalyst simulations are done in collaboration with Johnson Matthey. The battery materials simulations are done within the Faraday Institution Multiscale Modelling project where we are in contact with experimental manufacturing and testing of batteries.
Sectors Aerospace

Defence and Marine

Chemicals

Energy

URL http://onetep.org
 
Description Our findings are of direct industrial relevance. For example the hydrogen fuel cell catalyst simulations are done in collaboration with Johnson Matthey. The battery materials simulations are done within the Faraday Institution Multiscale Modelling project where we are in contact with experimental manufacturing and testing of batteries.
First Year Of Impact 2025
Sector Chemicals,Energy,Manufacturing, including Industrial Biotechology
Impact Types Economic

 
Title Digital SEI model 
Description We are developing a computational model of the Solid-Electrolyte Interphase (SEI) which is a very complex and not well understood component, essential for the operation of the Li-ion batteries and also involved in degradation processes over time. For this we are combining experimental input from the Faraday Institution Degradation project and large-scale DFT and DFTB simulations from the ONETEP linear-scaling program. This will be a valuable asset to all researchers working on batteries that will lead to improved materials for batteries. 
Type Of Material Computer model/algorithm 
Year Produced 2024 
Provided To Others? Yes  
Impact Model is under development so it has not been used yet for predictions 
 
Title Multiscale coupling of atomistic simulations with higher scale models for batteries 
Description We are developing appropriate parametrisations and workflows to link large length and time-scale atomistic DFTB simulations with the ONETEP program to DFN simulation models for batteries such as in the PyBAMM program. 
Type Of Material Computer model/algorithm 
Year Produced 2024 
Provided To Others? Yes  
Impact The model is currently under development and we are focusing on predicting diffusion coefficients from atomistic simulations to be used in PyBAMM simulations. A unique strength of this approach is that it can be applied to virtually any material overcoming the lack of experimentally available parameters. 
 
Description ONETEP calculations on metallic nanoparticles: applications in catalysis 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact This was an invited seminar by BIOVIA / Dassault Systemes to showcase to industrial researchers cutting edge simulations in catalysis with the ONETEP linear-scaling DFT code we develop. There was much interest in questions after the talk the feedback was very positive.
Year(s) Of Engagement Activity 2023