Project Details
Description
The provision of clean sustainable energy is among the most urgent challenges to society and to the global economy, and poses fundamental, exciting scientific questions. Materials performance lies at the heart of the development and optimisation of green energy technologies, and computational methods now play a vital role in modelling and predicting the structures, properties and reactivity of complex materials. UK science has an enviable position in the international field, and many key techniques and applications were pioneered here.
Particular strengths of the UK community have been the ability to harness the full range of techniques from force-field to electronic structure methods, the effective exploitation of high performance computing facilities, the extensive range of applications and the synergistic relationship with experiment. All these aspects will feed into our collaborative project and, indeed, our team has leading programmes involving both technique development and applications, which exploit the latest development in computational hardware and software.
The performance of energy storage and conversion devices is controlled by the atomistic and electronic processes within bulk materials, nano-structures, and across interfacial boundaries. These processes remain, however, poorly understood. The vision of this project is therefore to develop and apply predictive techniques for modelling the atomic level operation of energy materials, thereby enabling both academic and industrial communities to develop new materials for the next generations of energy devices with a step change in performance; and thereby addressing specifically the following critical technological objectives, which will push the RCUK energy agenda forward: (i) increasing the efficiency and stability of solar cells; (ii) enhancing the energy density and charge rate of lithium-ion batteries; (iii) improving the performance and lifetime of solid oxide fuel cells, and (iv) increasing the power from thermoelectric devices.
To address these ambitious and exciting challenges, we require a concerted and systematic programme combining a range of state-of-the-art simulation methods with new techniques to work on the following major Themes: (a) exploration of materials; (b) nanostructures and interfaces; (c) ionic and electronic transport; and (d) new technique development. Hence, we have brought together a consortium team from the University of Bath, UCL and Daresbury, with wide and complementary experience in the field. There is no equivalent concerted programme inter-linking different expertise being undertaken elsewhere, and hence will be world-leading in this domain. Indeed, the project will ensure that the UK community remains ahead of the international competition in the field.
Particular strengths of the UK community have been the ability to harness the full range of techniques from force-field to electronic structure methods, the effective exploitation of high performance computing facilities, the extensive range of applications and the synergistic relationship with experiment. All these aspects will feed into our collaborative project and, indeed, our team has leading programmes involving both technique development and applications, which exploit the latest development in computational hardware and software.
The performance of energy storage and conversion devices is controlled by the atomistic and electronic processes within bulk materials, nano-structures, and across interfacial boundaries. These processes remain, however, poorly understood. The vision of this project is therefore to develop and apply predictive techniques for modelling the atomic level operation of energy materials, thereby enabling both academic and industrial communities to develop new materials for the next generations of energy devices with a step change in performance; and thereby addressing specifically the following critical technological objectives, which will push the RCUK energy agenda forward: (i) increasing the efficiency and stability of solar cells; (ii) enhancing the energy density and charge rate of lithium-ion batteries; (iii) improving the performance and lifetime of solid oxide fuel cells, and (iv) increasing the power from thermoelectric devices.
To address these ambitious and exciting challenges, we require a concerted and systematic programme combining a range of state-of-the-art simulation methods with new techniques to work on the following major Themes: (a) exploration of materials; (b) nanostructures and interfaces; (c) ionic and electronic transport; and (d) new technique development. Hence, we have brought together a consortium team from the University of Bath, UCL and Daresbury, with wide and complementary experience in the field. There is no equivalent concerted programme inter-linking different expertise being undertaken elsewhere, and hence will be world-leading in this domain. Indeed, the project will ensure that the UK community remains ahead of the international competition in the field.
Status | Finished |
---|---|
Effective start/end date | 20/05/13 → 19/11/18 |
Collaborative partners
- University of Bath (lead)
- Johnson Matthey plc
- Sharp Laboratories of Europe Ltd.
Funding
- Engineering and Physical Sciences Research Council
RCUK Research Areas
- Materials sciences
- Materials Characterisation
- Materials Synthesis and Growth
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Datasets
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Dataset for "Partial Cation Substitution Reduces Iodide Ion Transport in Lead Iodide Perovskite Solar Cells"
Cameron, P. (Creator), Pering, S. (Data Collector), Ferdani, D. (Data Collector), Ghosh, D. (Researcher), Islam, M. (Supervisor) & Walker, A. (Supervisor), University of Bath, 8 Nov 2019
DOI: 10.15125/BATH-00528, http://www.rsc.org/suppdata/c9/ee/c9ee00476a/c9ee00476a1.pdf
Dataset
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Dataset for "Prospects for engineering thermoelectric properties in La1/3NbO3 ceramics revealed via atomic-level characterization and modelling"
Azough, F. (Creator), Ekren, D. (Creator), Srivastava, D. (Creator), Parker, S. (Creator), Freer, R. (Creator), Kepaptsoglou, D. (Project Member), Baran, J. (Project Member), Molinari, M. (Researcher) & Ramasse, Q. M. (Project Member), University of Bath, 19 Dec 2017
DOI: 10.15125/BATH-00463
Dataset