Computer modelling of novel perovskite halides for next-generation solar cells

a) Brief description of the context of the research

Metal halide perovskites are generating enormous excitement for their use in low-cost, high-performance and scalable photovoltaic (PV) devices. These materials have the general ABX3 structure, where A is a mono-cation (methylammonium, MA; formamidinium, FA; and/or cesium, Cs), B is a di-cation (typically Pb), and X is an anion (typically I or an I/Br mixture). In contrast to crystalline silicon, perovskites offer low-temperature processability and band gap tunability through modifications of the chemical composition. Within 10 years, there has been an unprecedented rise in the power conversion efficiency (PCE) of perovskite solar cells from 3% to over 25%. However, there are significant stability issues and a full understanding of the underpinning defect, ion transport and interfacial properties is incomplete. Hence, we have yet to unlock the full performance potential of these materials.

b) Aims and objectives

This project will address critical challenges of this extraordinary class of material through a multi-faceted computational approach led by Prof Saiful Islam (SI) with the following key objectives:
(i) To elucidate the activation energies and diffusion coefficients for ion migration across multiple compositions (partial A-cation substitution vs mixed I/Br) with comparison to the best-in-class perovskite (FA,Cs)PbI3 as an appropriate reference system.
(ii) To compare and contrast how ion accumulation at the interfaces influence current transport and device stability.
(iii) To elucidate how A-site cation doping and 2D structures can mitigate ion migration and surface reactions, and to formulate design guidelines for optimum compositions, enabling industrial relevance.

c) Novelty of the research methodology

Particular strengths of this project will be (i) the ability to harness a range of density functional theory (DFT) and molecular dynamics (MD) 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 involved

This 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.