Atomistic Computer Modelling of New Solar Cell Materials
Atomistic Computer Modelling of New Solar Cell Materials
批准号:
2729550
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
太阳能电池技术在帮助减少碳排放和气候变化方面发挥着关键作用。新型无机-有机钙钛矿材料具有优异的光伏性能。基于原型化合物甲基碘化铅铵(MAPI3),这些材料的功率转换效率在10年内从3%提高到25%以上。远离有毒的铅,锡基钙钛矿太阳能电池(PSCs)是第一个被研究的,并且已经成为光伏应用中有前途的竞争者。锡基钙钛矿具有与最佳带隙相似的光学带隙,并且与铅基钙钛矿相比具有更高的载流子迁移率。然而,就像铅基钙钛矿一样,低稳定性也是阻碍锡基钙钛矿商业化的关键问题,其潜在机制尚不完全清楚。b)目的和目标为了提高锡基钙钛矿太阳能电池的性能,对材料特性、稳定性和功率损耗的深入了解至关重要。该项目将通过使用Saiful Islam教授(SI)领导的材料建模方法来解决关键问题,其主要目标如下:(i)比较和对比Sn与混合Sn/Pb钙钛矿FA(Pb,Sn)I3的带隙和氧化特性,以评估稳定性和降解趋势。(ii)研究离子迁移的能量和扩散速率作为系统中铅/锡比的函数,以便定量筛选可能抑制离子迁移的成分。(iii)阐明a位阳离子掺杂如何减轻离子迁移和Sn(II)氧化,并制定高稳定性成分的材料设计规则,从而实现技术影响。c)研究方法的新颖性最先进的计算方法在建模和预测PV材料的性质方面起着至关重要的作用。该项目的主要优势将是:(i)利用一系列密度泛函理论和分子动力学方法的能力(例如VASP, LAMMPS代码),(ii)有效利用高性能超级计算机(例如Archer-2),以及(iii)与牛津物理实验工作的密切协同关系。此外,新兴的人工智能(AI)和机器学习技术也将有新的应用,这些技术为研究新的光伏材料提供了创新的能力,有望实现量子力学精度和预测能力,同时比传统方法快许多个数量级。对于这样的材料建模工作,牛津大学拥有优秀的内部计算设施,SI可以通过HPC材料化学联合会(SI是Co-I)广泛访问国家Archer-2超级计算机。该项目属于EPSRC的“能源和脱碳”主题和研究领域:“太阳能技术”和“能源应用材料”。因此,该项目与EPSRC的战略目标非常一致,表明了“新材料的利用”和“太阳能技术的重大进步源于基础材料科学”。e)参与该项目的任何公司或合作者将与Henry Snaith FRS教授和Laura Herz教授(两人都在牛津物理学院附近)的钙钛矿太阳能电池小组的互补实验研究联系起来。牛津光伏公司成立于2010年,是牛津大学的一个分支机构,旨在将混合光伏商业化,并已开发出钙钛矿-硅串联效率为bbbb29 %,超过了硅的记录性能。
英文摘要
) 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.
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国内基金
海外基金
基于多重计算全息片(Computer-generated Hologram,CGH)的光学非球面干涉绝对检验方法研究
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批准号:62375132
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项目类别:面上项目
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资助金额:54.00万元
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批准年份:2023
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负责人:马骏
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依托单位:
Journal of Computer Science and Technology
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批准号:61224001
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项目类别:专项基金项目
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资助金额:20.0万元
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批准年份:2012
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负责人:万晓霰
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依托单位:
Journal of Computer Science and Technology
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批准号:61040017
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项目类别:专项基金项目
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资助金额:4.0万元
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批准年份:2010
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负责人:万晓霰
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依托单位: