Structure prediction in Materials Science and Characterisation with EELS in the low-loss regime

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Title
Structure prediction in Materials Science and Characterisation with EELS in the low-loss regime

CoPED ID
8496db50-7d12-4dee-8171-2238bf2e5395

Status
Closed

Funders

Value
No funds listed.

Start Date
Sept. 30, 2017

End Date
Nov. 30, 2021

Description

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This project is to enable new developments to the CASTEP Density Functional Theory (DFT) code to provide accurate low loss EELS (Electron Energy Loss Spectra). This necessary to interpret high resolution measurements made possible with the latest generation of Scanning Transmission Electron Microscopes (STEM). This includes the EPSRC National Facility for Aberration-Corrected Scanning Transmission Electron Microscopy (SuperSTEM) located at Daresbury Laboratories. Together, the combination of quantum mechanical DFT calculations and STEM measurements present a powerful tool for materials characterisation. Work in the last decade has shown that it is now possible to use techniques based on quantum mechanics to predict the structure of hitherto unknown materials. To identify the existence of such materials in nature requires the use of experimental techniques such as EELS, which can be compared to the spectra predicted for the proposed structure from DFT simulations. By enhancing our ability to predict low-loss EELS this project will both expand the range of materials systems we can study, and the certainty and confidence with which we can make predictions. The project will enable simulations of a number of materials systems of importance to future materials and the energy sector; including zirconium oxides used in the nuclear industry, fuel cells, Li based batteries and catalysts.

The CASTEP code is developed by academics at the Universities of Cambridge, Oxford, York, Durham and Royal Holloway (London). It is freely available to UK academics and a supported commercial version is marketed by Dassault Systèmes / BIOVIA (with UK HQ in Cambridge). They provide support to industrial users across a wide variety of sectors including: pharmaceuticals, catalysis, energy.

This project delivers new capabilities to accelerate the development of novel materials, particularly for energy applications. However, note that the general nature of quantum-mechanical modelling means that the tools can be applied to a very wide range of materials. In the first instance the beneficiary is the UK company Johnson-Matthey who will supply experimental data on catalysts and fuel cell materials. Through this project they will enhance their understanding of the structure and composition of these materials. However, by working with a leading scientific software company (Dassault Systèmes / BIOVIA) we ensure that the tools developed will be made available across Materials sector - ensuring maximum impact.

The Themes are:

Energy
Physical sciences

University of Oxford LEAD_ORG
University of Oxford COLLAB_ORG
Johnson Matthey Plc STUDENT_PP_ORG
BIOVIA STUDENT_PP_ORG

Jonathan Yates SUPER_PER
Xinlei Liu STUDENT_PER

Subjects by relevance
  1. Energy
  2. Quantum mechanics
  3. Materials (matter)
  4. Anguilla anguilla
  5. Fuel cells
  6. Physics
  7. Eels

Extracted key phrases
  1. Structure prediction
  2. Accurate low loss eel
  3. Fuel cell material
  4. Material sector
  5. Material system
  6. Unknown material
  7. Material characterisation
  8. Future material
  9. Novel material
  10. Corrected Scanning Transmission Electron Microscopy
  11. Scanning Transmission Electron Microscopes
  12. Quantum mechanical dft calculation
  13. Electron Energy Loss Spectra
  14. Materials Science
  15. CASTEP Density Functional Theory

Related Pages

UKRI project entry

UK Project Locations