Projects: Projects for Investigator |
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Reference Number | EP/T033231/1 | |
Title | Design rules for defect-tolerant photovoltaics | |
Status | Completed | |
Energy Categories | Renewable Energy Sources(Solar Energy, Photovoltaics) 100%; | |
Research Types | Basic and strategic applied research 100% | |
Science and Technology Fields | PHYSICAL SCIENCES AND MATHEMATICS (Metallurgy and Materials) 50%; PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 50%; |
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UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
Principal Investigator |
Dr A M Ganose Private Address Private Address |
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Award Type | Standard | |
Funding Source | EPSRC | |
Start Date | 07 June 2021 | |
End Date | 06 June 2024 | |
Duration | 36 months | |
Total Grant Value | £378,578 | |
Industrial Sectors | Energy | |
Region | London | |
Programme | Energy : Energy | |
Investigators | Principal Investigator | Dr A M Ganose , Private Address, Private Address (100.000%) |
Industrial Collaborator | Project Contact , University of Cambridge (0.000%) |
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Web Site | ||
Objectives | ||
Abstract | There is increasing demand for renewable energy, as highlighted by the UK government's aim of reducing carbon emissions by 80% before 2050. Solar power is the most promising renewable technology due to the enormous amount of energy the sun can provide. Most commercially available solar panels - based on crystalline silicon - are relatively efficient but expensive to manufacture. Accordingly, there is significant interest in alternative photovoltaic absorbers that are just as efficient but have lower materials and processing costs.One route to finding novel solar absorbers is using quantum-mechanical computations. Indeed, many of the properties that determine photovoltaic performance - such as the strength of visible light absorption - can be calculated relatively easily. Many studies have taken advantage of this by searching for new solar absorbers based solely on electronic and optical properties. Unfortunately, this approach generally gives rise to many false positives where materials are predicted as efficient but perform poorly in practice. These shortcomings often result when the behaviour of crystal imperfections is not considered. These imperfections, called point-defects, play a crucial role in photovoltaic devices by limiting the maximum obtainable voltage and current. However, predicting the effects of defects on photovoltaic performance has so far proved tricky and has only been achieved for a select few systems.By gaining an understanding of the fundamental factors that control defect formation we can design new materials that are resistant to their effects. Materials in which defects do not significantly affect photovoltaic performance are called "defect tolerant". Due to the difficulty of calculating the impact of defects, the structural and chemical properties that give rise to defect tolerance are not well understood. However, recent advances in computational workflow software means it is now possible to automate the calculation of complex properties. This project will develop an automatic computational workflow to determine whether a material is defect tolerant. By applying the workflow to many hundreds of materials and analysing the trends, we can extract the structure-property relationships that give rise to defect tolerance. We can also use this information to develop machine learning models for predicting the impact of defects without needing to perform any calculations. As many other applications also rely on the formation of point-defects - such as thermoelectrics and quantum computers - our calculated data will be of broad interest to the scientific community. We will therefore make the results available as an online database of computed defect properties. An advanced understanding of the factors that govern defect tolerance will enable the rational design of the next generation of photovoltaic materials. Photovoltaics with reduced cost will facilitate the adoption of solar power and pave the way for a revolution in clean energy | |
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Added to Database | 15/10/21 |