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近几年, 钙钛矿/硅异质结叠层太阳电池发展迅速, 效率已经从13.7%提升到29.1%. 由于叠层电池器件的制作工艺复杂, 而叠层太阳电池中的光学损失对转换效率的影响很大, 所以通过光学模拟进而获得高效电池至关重要. 本文首先从商业软件和自建模型两方面概述了光学模拟的方法, 接着从反射损失和寄生吸收两方面针对光学模拟研究进展进行了总结和分析, 最后指出了叠层电池光学模拟过程中需要注意的问题. 钙钛矿/硅异质结叠层太阳电池的转换效率极限最高可达40%, 具备很大的提升空间, 结合模拟工作的研究, 叠层电池的发展将会取得更大的进步.Perovskite/silicon heterojunction tandem solar cells have developed rapidly in recent years, and their efficiency is enhanced from 13.7% to 29.1%. As is well known, the optical loss has a great influence on the efficiency. Due to the complex fabrication process of tandem solar cells, it is important to obtain high-performance tandems through optical simulation. In this paper, optical simulation methods are mainly summarized from two aspects: commercial software and self-built model. Then, the progress of optical simulation is analyzed in terms of reflection loss and parasitic absorption. Finally, what should be paid more attention to in the optical simulation of tandem solar cells is pointed out. The efficiency limit of perovskite/silicon heterojunction tandem solar cells can reach up to 40%, but there remains much room for improvement. The research on optical simulation will lay the foundation of developing the tandem solar cells.
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Keywords:
- perovskite/silicon tandem solar cells /
- optical simulation /
- reflection losses /
- parasitic absorption
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图 3 (a) 光学导纳法自建模型的光线分析过程[19]; CH3NH3PbI3为吸收层的太阳电池的(b)结构和(c)光学损耗分析[19]; (d) 钙钛矿/硅异质结叠层太阳电池隧穿结优化的光损耗分析[59]
Fig. 3. (a) Light analysis process of optical admittance method[19]; (b) structure and (c) optical loss analysis of solar cells with CH3NH3PbI3 as absorber[19]; (d) tunnel junction optical loss analysis of perovskite / silicon tandem solar cells[59].
图 4 (a) PDMS作减反层的电池结构[69]; (b) 有、无PDMS减反层的器件EQE对比[69]; (c) LM箔作减反层的电池结构[67]; (d), (e) LM箔作减反层的优化结果[67]
Fig. 4. (a) Solar cell structure using PDMS as anti-reflection coating[69]; (b) EQE comparison with and without PDMS[69]; (c) solar cell structure using LM foil as anti-reflection coating[67]; (d) (e) optimized result using LM foil as anti-reflection coating[67].
图 5 (a) 使用LiF作减反层的电池结构[71]; (b) LiF作减反层的电池优化结果[71]; (c) 使用MgF2作减反层的电池结构和优化结果[72]
Fig. 5. (a) Solar cell structure with LiF as anti-reflection coating[71]; (b) optimized result with LiF as anti-reflection coating[71]; (c) solar cell structure and optimization result with MgF2 as anti-reflection coating[72].
图 6 (a) 具有平面硅底电池的叠层电池、背面制绒但正面平坦的结构以及增加了中间层的叠层电池结构、具有双面制绒的硅底电池和掩埋层的叠层电池以及增加了减反层的叠层电池、顶和底电池均是双面制绒的叠层器件[75]; (b) 平面的硅、单面制绒的硅以及双面制绒的硅作为底电池的钙钛矿/硅异质结叠层器件结构[76]; (c) 具有单面制绒、双面制绒的器件的光损耗对比图[23]
Fig. 6. (a) Perovskite/silicon tandem solar cell structure with flat silicon, single-side textured silicon with/without interface layer, tandem solar cell with double-side textured silicon and burial layer, solar cell with anti-reflection layer and double-sided textured structure[75]; (b) perovskite/silicon tandem solar cell structure with flat silicon、one-side textured silicon and double-side textured silicon as bottom cell[76]; (c) comparison of optical loss of devices with one-side texture, double-side texture devices[23].
图 7 (a) 具有六角形正弦纳米结构的基底原子力显微图(AFM)[22]; (b)生长在这种基底上的钙钛矿的原子力显微图(AFM)[22]; (c)平面钙钛矿的原子力显微图(AFM)[22]; (d)未使用陷光结构的电池EQE图[22]; (e)使用陷光结构后的电池EQE图[22]; (f)和(g)蛾眼纹理钙钛矿的结构图[77]; (h)使用蛾眼纹理钙钛矿的叠层器件EQE图[77]
Fig. 7. (a) Atom force microscopy (AFM) of substrate with hexagonal sinusoidal nanostructure[22]; (b) AFM image of perovskite growing on this substrate[22]; (c) AFM image of flat perovskite[22]; (d) EQE curve of solar cell without dimple structure[22]; (e) EQE curve of solar cell with dimple structure[22]; (f) and (g) structure image of perovskite with moth eye texture[77]; (h) EQE curve of device with moth eye textured perovskite[77].
图 8 (a)带有亚微米级金字塔制绒的钙钛矿/硅叠层太阳电池结构[78]; (b)叠层器件I-V测试结果[78]; (c)与其他陷光结构的对比[78]; (d)使用四种陷光结构的叠层器件的反射损耗模拟结果对比图[78]
Fig. 8. (a) Structure of perovskite/silicon tandem solar cell with submicron pyramids textured structure[78]; (b) I-V results of devices[78]; (c) comparison with the other light trapping structures[78]; (d) comparison of reflection loss of the device using four kinds of structure[78].
图 9 (a)开槽和(b)棱镜SiO2结构减少钙钛矿太阳电池寄生吸收[79]; 叠层电池优化寄生吸收(c)前和(d)后的器件EQE对比图[73]; (e) 光学和电学综合考虑对ITO寄生吸收优化[71]; (f) 仅从光学角度优化ITO的寄生吸收[71]
Fig. 9. (a) Slotted and (b) prismatic structure of SiO2 to reduce parasitic absorption of perovskite solar cells[79]; EQE comparison of tandem solar cells (c) before and (d) after optimizing for parasitic absorption[73]; (e) optimization for parasitic absorption of ITO with both optical and electrical considerations[71]; (f) optimization for parasitic absorption of ITO only considerate optical aspect[71].
表 1 商用软件模拟包及其功能
Table 1. Simulation package of commercial software and its functions.
软件名称 功能 参考文献 JCMsuite 适用于复杂纳米光学系统的仿真 [22] FDTD 使用时域有限差分算法对太阳电池模拟 [26] AFORS-HET 用于异质结构太阳电池的数值模拟软件 [27] SunCalculator 用于计算所测量的综合太阳辐照度的角度和光谱分布 [33] Solar spectrum calculator 确定入射到器件的光谱辐照度的直接分量, 散射分量和全局分量 [34] TRACEY 用于确定模块在各种入射光谱下的效率以及相关光学损耗 [35] OPAL 模拟太阳电池前表面(主要是减反层) [36] OPTOS 基于矩阵的仿真算法, 能有效地计算任何表面陷光结构的反射率和透射率 [37,38] PC3 D 用于硅太阳电池的开源三维器件模拟器 [39,40] SETFOS 计算短路电流密度(Jsc), 开路电压(Voc)和填充因子(FF), 添加光散射层以增强吸收 [21,41] SCAPS 一维太阳电池仿真, 适用于晶硅、砷化镓、非晶硅和微晶硅太阳电池 [42] WXAMPS 一维太阳电池模拟 [43—46] 表 2 光学色散模型及其适用材料
Table 2. Optical dispersion model and its applicable materials.
表 3 使用减反层减少器件反射损耗
Table 3. Using anti-reflection coating to reduce reflection loss of device.
ARC Structure Jsc /(mA·cm2) Improved Jsc/(mA·cm2) Year Ref. LiF LiF/ITO/SnO2/PCBM/perovskite/NiO/ITO/silicon 21.3 1.6 2018 [22] LiF LiF/ITO/TiO2/perovskite/spiro/p-uc-SiOx:H/defective layer/silicon 16.7 1.4 2016 [65] LM foil LM/IZO/SnO2/C60/ perovskite/PTAA/ITO/nc-SiOx:H/a-Si:H/Si/a-Si:H/ZnO:Al/Ag 19.4 2.3 2018 [67] PDMS PDMS/ITO/na-Si:H/ia-Si:H/C-Si/ia-Si:H/pa-Si:H/ITO/Ag 37.5 3.0 2017 [69] LiF LiF/IZO/SnO2/C60/perovskite /PTAA/ITO/nc-SiOx:H(n)/silicon 19.2 1.4 2019 [71] LiF LiF/ITO/SnO2/PCBM/ perovskite /NiO/ITO/silicon 19.0 1.4 2017 [73] MgF2 MgF2/ITO/SnO2/C60/ perovskite /NiO/ITO/silicon 19.8 1.0 2018 [74] MgF2 MgF2/IZO/spiro/ perovskite /TiO2/ITO/Ag 19.55 1.5 2019 [72] -
[1] Yoshikawa K, Kawasaki H, Yoshida W, Irie T, Konishi K, Nakano K, Uto T, Adachi D, Kanematsu M, Uzu H 2017 Nat. Energy 2 17032Google Scholar
[2] Wolf S D, Descoeudres A, Holman Z C, Ballif C 2012 Green 2 7
[3] Kojima A, Teshima K, Shirai Y, Miyasaka T 2019 J. Am. Chem. Soc. 131 6050
[4] Bailie C D, Mcgehee M D 2015 MRS Bull. 40 681Google Scholar
[5] Etgar L, Gao P, Xue Z, Peng Q, Chandiran A K, Liu B, Nazeeruddin M K, Graetzel M 2012 J. Am. Chem. Soc. 134 17396Google Scholar
[6] Eperon G E, Stranks S D, Menelaou C, Johnston M B, Herz L M, Snaith H J 2014 Energy Environ. Sci. 7 982Google Scholar
[7] Dewi H A, Wang H, Li J, Thway M, Sridharan R, Stangl R, Lin F, Aberle A G, Mathews N, Bruno A, Mhaisalkar S 2019 ACS Appl. Mater. Interfaces 11 34178Google Scholar
[8] Qiu W, Paetzold U W, Aernouts T, Debucquoy M, Gehlhaar R, Poortmans J 2018 Energy Environ. Sci. 11 1489Google Scholar
[9] Jackson E 1995 Transactions of the Conference on the Use of Solar Energy Tucson, October 31–November 1, 1995 5 122
[10] Werner J, Niesen B, Ballif C 2018 Adv. Mater. Interfaces 17 00731
[11] Kohnen E 2020 European PV Solar Energy Conference and Exhibition (EUPVSEC) Lisbon, Portugal, Germany, September 7–11, 2020
[12] Filipic M, Loper P, Niesen B, de Wolf S, Krc J, Ballif C, Topic M 2015 Opt. Express 23 A263Google Scholar
[13] Loper P, Niesen B, Moon S J, Martin de Nicolas S, Holovsky J, Remes Z, Ledinsky M, Haug F J, Yum J H, De Wolf S, Ballif C 2014 IEEE J. Photovoltaics 4 1545Google Scholar
[14] Lal N N, White T P, Catchpole K R 2014 IEEE J. Photovoltaics 4 1380Google Scholar
[15] Shockley W, Queisser H J 1961 J. Appl. Phys. 32 510Google Scholar
[16] Brittman S, Garnett E C 2016 J. Phys. Chem. A 120 616
[17] Green M A 2015 Sol. Energy Mater. Sol. Cells 92 1305
[18] Hara T, Maekawa T, Minoura S, Sago Y, Niki S, Fujiwara H 2014 Phys. Rev. Appl. 2 034012Google Scholar
[19] Nakane A, Tampo H, Tamakoshi M, Fujimoto S, Kim K M, Kim S, Shibata H, Niki S, Fujiwara H 2016 J. Appl. Phys. 120 61
[20] Nakane A, Fujimoto S, Fujiwara H 2017 J. Appl. Phys. 122 20
[21] Altazin S, Stepanova L, Lapagna K, Losio P, Ruhstaller B 2018 Opt. Express 26 A579Google Scholar
[22] Chen D, Manley P, Tockhorn P, Eisenhauer D, Jäger K 2018 J. Photonics Energy 8 2
[23] Jacobs D A, Langenhorst M, Sahli F, Richards B S, Paetzold U W 2019 J. Phys. Chem. Lett. 10 3159Google Scholar
[24] Askari S A, Kumar M, Das M K 2018 Semicond. Sci. Technol. 33 115003Google Scholar
[25] Guang T Y, Pei Q G, Paul, Procel, Gianluca, Limodio, Arthur, Weeber 2018 Sol. Energy Mater. Sol. Cells 186 13
[26] Park H, Lee Y J, Shin M, Lee Y J, Lee J, Park C, Yi 2018 Curr. Photovoltaics Research 4 102
[27] Borah C K, Tyagi P K, Kumar S, Patel K 2018 Comput. Mater. Sci. 151 65Google Scholar
[28] Santbergen R, Uzu H, Yamamoto K, Zeman M 2019 IEEE J. Photovoltaics PP 1
[29] Macqueen R W, Martin L, Jens N, Mathias M, Clemens G, Sara J C, Klaus J G, Tayebjee M J Y, Schmidt T W, Bernd R 2018 Mater. Horiz. 5 1065Google Scholar
[30] Nico T, Oliver H H, Christoph G J, Benedikt B S 2018 Opt. Express 2 6
[31] Solar Energy Systems, Johannes E, Nico T, Habtamu G https://pvlighthouse.com.au/cms/simulation-programs/optos [2020-10-23]
[32] JCMsuite, Jservice http://www.jservice.com.cn/sciencenews/jcmsuite/ [2020-10-23]
[33] Ernst M, Holst H, Winter M, Altermatt P P 2016 Sol. Energy Mater. Sol. Cells 157 913Google Scholar
[34] Bird R E, Riordan C 1986 J. Climate Appl. Meteor. 25 87Google Scholar
[35] Mcintosh K R, Cotsell J N, Norris A W, Powell N E, Ketola B M 2010 Photovoltaic Specialists Conference Hawaii, June 20–25, 2010 p269
[36] Baker-Finch S C, Mcintosh K R 2010 Photovoltaic Specialists Conference (PVSC) December 17–19, 2010 p2184
[37] Eisenlohr J, Tucher N, Hn O, Hauser H, Peters M, Kiefel P, Goldschmidt J C, BläSi B 2015 Opt. Express 23 A502Google Scholar
[38] Tucher N, Eisenlohr J, Kiefel P, Höhn O, Bläsi B 2015 Opt. Express 23 A1720Google Scholar
[39] Basore P A 2020 IEEE J. Photovoltaics 10 905Google Scholar
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