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Details of Grant 

EPSRC Reference: EP/V028537/1
Title: CCP5++: Integrating Computer Simulation of Condensed Phases with experiments and data science.
Principal Investigator: Carbone, Professor P
Other Investigators:
Elena, Dr A
Researcher Co-Investigators:
Project Partners:
AWE CCP NC CCP Quantum Computing
CCP-Biosim Collaborative Computational Project ccp9 Computational Science Centre for Researc
CSIR - South Africa Henry Royce Institute IBM UK Ltd
Johnson Matthey Materials Chemistry Consortium Molecular Sciences Software Institute
nVIDIA Royal Society of Chemistry Publishing STFC Laboratories (Grouped)
UCL
Department: Chem Eng and Analytical Science
Organisation: University of Manchester, The
Scheme: Network
Starts: 01 April 2021 Ends: 31 March 2024 Value (£): 366,829
EPSRC Research Topic Classifications:
Biophysics Chemical Synthetic Methodology
Condensed Matter Physics Materials Characterisation
Materials Synthesis & Growth
EPSRC Industrial Sector Classifications:
R&D
Related Grants:
Panel History:
Panel DatePanel NameOutcome
09 Dec 2020 EPSRC Physical Sciences - December 2020 Announced
Summary on Grant Application Form
Molecular modelling has established itself as a powerful predictive tool for a large range of materials and phenomena whose intrinsic multiscale nature requires modelling tools able to capture their chemical, morphological and structural complexity. In the UK, the molecular modelling community, supported by the software, training and networking activities coordinated by the CCP5, has become, over the past 40 years, international-leading in this field. Building upon these successes, the new CCP5++ network will revolutionise the field of materials molecular modelling creating a new integrated community of modellers, experimentalists and data scientists that together will identify the new frontiers of the field and will transform the way these disciplines work together.

To achieve its mission, the CCP5++ will coordinate and support an ambitious plan of meetings, sandpits, coding workshops, secondments and visitor schemes to cater for the large community of modellers, experimentalists and data scientists working on advanced materials. This support has proved to be vital to enable the UK condensed matter community to attain and maintain an international position at the forefront of such an intensely competitive field and will enable the UK researchers to identify and tackle major world challenges in-silico materials discovery.

From the start the network memberships include key representatives of the experimental and data science communities, international software and modelling institutes, industrial collaborators and national HPC consortia and CCPs, that working together will shape the future of materials molecular modelling.
Key Findings
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Potential use in non-academic contexts
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Summary
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Organisation Website: http://www.man.ac.uk