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Details of Grant 

EPSRC Reference: EP/V036440/1
Title: University of Bristol Core Equipment Award 2020
Principal Investigator: Taylor, Professor PC
Other Investigators:
Butts, Professor CP Lepora, Professor NF Cotterell, Dr MI
Azarpeyvand, Professor M Fey, Dr N
Researcher Co-Investigators:
Project Partners:
Department: Research and Enterprise Development
Organisation: University of Bristol
Scheme: Standard Research - NR1
Starts: 01 November 2020 Ends: 30 April 2022 Value (£): 773,320
EPSRC Research Topic Classifications:
Aerodynamics Building Ops & Management
Chemical Synthetic Methodology Robotics & Autonomy
EPSRC Industrial Sector Classifications:
Aerospace, Defence and Marine Healthcare
Related Grants:
Panel History:
Panel DatePanel NameOutcome
29 Sep 2020 Core Equipment Award 2020 - Panel 1 Announced
Summary on Grant Application Form
The University of Bristol (UoB) has chosen to support investments in equipment which supports research across EPSRC's remit in the Engineering and Science Faculties. It will underpin programs incorporating >250 researchers, >£50M of EPSRC investment and addressing key strategic priorities in University research programs. Investments are as follows:

A 3D Precision Displacement Tracker and High-frequency data acquisition system enabling high-quality flow and structure displacement measurement and thus significantly enhancing the research capabilities of UoB's Lowson Wind Tunnel Facility.

A state-of-the-art 3D printer that will vastly extend rapid prototyping provision at Bristol Robotics Laboratory (BRL) enabling a range of current and future research targets, including smart human-interactive research, adaptive swarms, biomedical soft robotics, morphing UAVs and dexterous robot hands.

A Multi-user platform for Digital Chemistry integrated into the University's cutting-edge Blue Pebble high-performance computing Facilities that will support research challenges across the spectrum of chemical and mathematical science, including machine learning, mathematical tools, materials design, biochemical simulation, and data science.

A scanning Aerodynamic Aerosol Classifier (s-AAC), enabling the elucidation of mechanisms behind accelerated reactions in aerosol systems to provide routes to green chemical synthesis; transforming indoor and outdoor air quality models for aerosol transport and evolution; and providing pioneering insights into the role of aerosols in disease transmission, including Covid-19.

All of these equipment address three of the core objectives of this call: underpinning multi-user equipment, supporting ECRs and supporting critical mass doctoral training.

Key Findings
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Potential use in non-academic contexts
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Date Materialised
Sectors submitted by the Researcher
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Project URL:  
Further Information:  
Organisation Website: http://www.bris.ac.uk