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
)研究背景简介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显著的光伏性能。基于原型化合物甲基碘化铵铅(MAPI3),这些材料的电力转换效率在10年内从3%提高到25%以上。摆脱了有毒的铅,锡基钙钛矿太阳能电池(PSCs)是第一个被研究的,并在光伏应用中成为有前途的竞争者。与铅基钙钛矿相比,锡基钙钛矿具有与最佳带隙相似的光学带隙和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,其潜在的机理还没有完全被了解。B)目的和目的要提高锡基钙钛矿太阳能电池的性能,对材料性能、稳定性和功率损耗的深入了解是至关重要的。这个项目将通过使用由赛弗·伊斯拉姆(SI)教授领导的材料模拟方法来解决关键问题,主要目标如下:(I)比较和对比锡和混合的锡/铅钙钛矿FA(铅,锡)I3的带隙和氧化性能,以评估稳定性和降解性的趋势。(Ii)研究体系中离子迁移能量学和扩散速率随铅/锡比例的变化,以便能够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缓离子迁移和锡(II)氧化,并为高稳定性成分制定材料设计规则,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模拟和预测光伏材料的性能方面发挥着至关重要的作用。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(例如VASP、LAMMPS程序)的能力,(Ii)高性能超级计算机(例如Archer-2)的有效开发,以及(Iii)与牛津物理实验工作的密切协同关系。此外,还将新颖地使用新兴的人工智能(AI)和机器学习技术,这些技术为研究新的光伏材料提供了创新能力,有望实现量子力学的准确性和预测能力,同时比传统方法快许多个数量级。对于这类材料建模工作,牛津大学拥有出色的内部计算设施,SI通过HPC材料化学联盟(SI是Co-I)广泛使用国家Archer-2超级计算机。d)与EPSRC的战略和研究领域保持一致本项目属于EPSRC“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的战略目标保持了良好的一致性,表明“新材料的利用”和“支持材料科学在太阳能技术方面的重大进步”。E)任何参与该项目的公司或合作者都将链接到Henry Snaith FRS教授和Laura Herz教授(两人都在牛津物理学院附近)团队中关于钙钛矿型太阳能电池的互补实验研究。此外,还将与牛津光伏公司进行行业互动。牛津光伏公司成立于2010年,是牛津大学的分支机构,旨在将混合光伏发电商业化。该公司已开发出钙钛矿型硅电池的串联效率高达29%,超过了硅的创纪录表现。
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: