Atomistic Computer Modelling of New Solar Cell Materials

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) Brief description of the context of the researchSolar cell technologies play a critical role in helping to mitigate carbon emissions and climate change. Novel inorganic-organic perovskite materials have shown remarkable photovoltaic properties. Based on the prototype compound methylammonium lead iodide (known as MAPI3), the power conversion efficiencies of these materials have increased from 3% to more than 25% in 10 years. Moving away from toxic lead, tin-based perovskite solar cells (PSCs) were the first to be investigated and have emerged as promising contenders in photovoltaic applications. Tin-based perovskites have optical bandgaps similar to the optimum bandgap, and higher charge carrier mobility compared to their Pb counterparts. However, just like Pb-based perovskites, low stability is also the critical issue that impedes tin-based perovskites from commercialisation and the underlying mechanisms are not fully understood. b) Aims and objectivesTo improve the performance of tin-based perovskite solar cells, deeper understanding of materials properties, stability and power loss is crucial. This project will address key issues through the use of materials modelling methods led by Prof Saiful Islam (SI) with the following key objectives: (i) To compare and contrast band gap and oxidation properties of Sn versus mixed Sn/Pb perovskites FA(Pb,Sn)I3 to assess trends in stability and degradation.(ii) To investigate ion migration energetics and diffusion rates as a function of Pb/Sn ratios in systems to allow quantitative screening of compositions that may inhibit ion migration. (iii) To elucidate how A-site cation doping can mitigate ion migration and Sn(II) oxidation, and to formulate materials design rules for high stability compositions, enabling technological impact.c) Novelty of the research methodologyState-of-the-art computational methods play a vital role in modelling and predicting the properties of PV materials. Key strengths of this project will be (i) the ability to harness a range of density functional theory and molecular dynamics methods (e.g. VASP, LAMMPS codes), (ii) the effective exploitation of high-performance supercomputers (e.g. Archer-2), and (iii) the close synergistic relationship with experimental work in Oxford Physics. In addition, there will be the novel use of emerging artificial intelligence (AI) and machine learning techniques which offer innovative capabilities for studying new PV materials, promising quantum-mechanical accuracy and predictive power, whilst being many orders of magnitude faster than conventional methods. For such materials modelling work, Oxford has excellent in-house computational facilities and SI has extensive access to the national Archer-2 supercomputer through the HPC Materials Chemistry Consortium (SI is Co-I).d) Alignment to EPSRC's strategies and research areas This project falls within the EPSRC 'Energy and Decarbonation' theme and the research areas: 'Solar Technology' and 'Materials for Energy Applications'. Hence, this project aligns well with EPSRC strategic objectives indicating the 'utilisation of new materials' and that 'significant advances in solar technology have arisen from underpinning materials sciences'. e) Any companies or collaborators involvedThis project will have links to complementary experimental studies on perovskite solar cells in the groups of Prof Henry Snaith FRS and Prof Laura Herz (both nearby in Oxford Physics). There will also be industry interactions with Oxford-PV, which was founded in 2010 as a spinout from the University of Oxford to commercialise hybrid photovoltaics and have developed a perovskite-on-silicon tandem efficiency of > 29%, exceeding that of the record performance of silicon.