High-throughput screening of polycrystalline solar absorbers (Ext.)

这是对《金属氧化物薄膜中的非平衡电子-离子动力学》(EP/K003151/1)的延伸。开发低成本、高效的太阳能电池装置将使我们能够更多地利用阳光中可获得的大量自由和清洁的能源。在太阳能电池中吸收光线以产生高能电子的材料被称为太阳能吸收体。在目前的消费级太阳能电池中，太阳能吸收材料是结晶硅。硅基电池显示出高效率(~25%)，但生产成本相对较高。例如，目前一个典型的4千瓦家庭安装需要大约14年的运行才能实现收支平衡(例如，参见http://www.theecoexperts.co.uk/are-solar-pv-panels-good-investment).在降低成本的愿望的驱动下，人们一直专注于开发制造成本低于硅的新型高效太阳能吸收材料，以形成下一代太阳能电池技术的基础。材料开发的总趋势是从硅向更复杂的二元、三元和四元化合物半导体发展，其提供了更宽的成分和结构参数空间，在其中可以优化所需的性能。性能良好的例子包括CuInGaSe2，CdTe，Cu2ZnSn4(S，Se)4(CZTS)和卤化铅钙钛矿(如CH3NH3PbI3，MAPI)。与硅不同，这些新兴材料通常含有相当高浓度的点缺陷，因为它们几乎总是非化学计量比的。它们通常也是多晶的，晶界(连同相关的点缺陷)通过促进非辐射电子-空穴复合和降低开路电压(这两种效应都会降低效率)来影响材料性能。虽然预测计算材料筛选方法在帮助识别有前途的太阳能吸收材料方面被证明是非常有价值的，但目前还没有考虑晶界缺陷性质的筛选方法。这项建议旨在通过开发系统的方法，根据晶界的热力学和电子性质筛选材料，以填补材料建模工具箱中的这一关键空白。这些方法将被应用于确定用于CdTe、卤化铅钙钛矿和CZTS材料的最佳成分和掺杂剂，以帮助优化性能和加速创新。我们将与实验合作者和我们的工业合作伙伴(Dyesol)密切合作，验证理论模型和测试预测，以提高太阳能电池的性能。我们开发的计算筛选方法也将适用于更广泛的材料模拟社区，并将在晶界电子性质影响材料性能的许多其他领域(包括热电材料、电池、光电化学电池、压敏电阻、透明导电氧化物和介电材料等)得到应用。

This is an extension of the Fellowship: 'Non-equilibrium electron-ion dynamics in thin metal-oxide films' (EP/K003151/1).The development of low-cost high-efficiency solar cell devices would allow us to make more use of the vast amount of free and clean energy available in sunlight. Materials which absorb light to generate energetic electrons in solar cells are known as solar absorbers. In current consumer level solar cells the solar absorber is crystalline silicon. Silicon based cells exhibit high efficiencies (~25%) but are relatively expensive to produce. For example, it currently takes about 14 years of operation for a typical 4 kW domestic installation to break even (e.g. see http://www.theecoexperts.co.uk/are-solar-pv-panels-good-investment). Driven by the desire to reduce cost there has been a continued focus on the development of new high-efficiency solar absorber materials that are less expensive to manufacture than silicon to form the basis of next generation solar cell technologies.A general trend in materials development has been the progression from silicon towards more complex binary, ternary and quaternary compound semiconductors, which offer a wider compositional and structural parameter space within which desired properties can be optimised. Highly performing examples include CuInGaSe2, CdTe, Cu2ZnSn(S,Se)4 (CZTS) and lead-halide perovskites (e.g. CH3NH3PbI3, MAPI). Unlike silicon these emerging materials often contain relevantly high concentrations of point defects since they are almost always non-stoichiometric. They are also usually polycrystalline and grain boundaries (together with associated point defects) are known to affect material performance by contributing to non-radiative electron-hole recombination and reduction of open circuit voltage (both effects that reduce efficiency). While predictive computational materials screening approaches have proved invaluable in helping to identify promising solar absorber materials there are currently no screening approaches that consider the properties of grain boundary defects. This proposal aims to fill this critical gap in the materials modelling toolbox by developing systematic approaches to screen materials against the thermodynamic and electronic properties of grain boundaries. These approaches will be applied to identify optimal compositions and dopants for CdTe, lead-halide perovskites and CZTS materials to help optimise performance and accelerate innovation. We will work closely with experimental collaborators and our industrial partner (Dyesol) to validate theoretical models and test predictions in order to deliver improvement in solar cell performance. The computational screening approaches we develop will also be made available to the wider materials modelling community and will find application in many other areas where the electronic properties of grain boundaries impact on material performance (including thermoelectrics, batteries, photoelectrochemical cells, varistors, transparent conducting oxides and dielectrics to name a few).