Citation: Ying Liang, Yuheng Deng, Shilv Yu, Jiahao Cheng, Jiawei Song, Jun Yao, Yichen Yang, Wanlei Zhang, Wenjing Zhou, Xin Zhang, Wenjian Shen, Guijie Liang, Bin Li, Yong Peng, Run Hu, Wangnan Li. Machine learning-guided antireflection coatings architectures and interface modification for synergistically optimizing efficient and stable perovskite solar cells[J]. Acta Physico-Chimica Sinica, ;2025, 41(9): 100098. doi: 10.1016/j.actphy.2025.100098 shu

Machine learning-guided antireflection coatings architectures and interface modification for synergistically optimizing efficient and stable perovskite solar cells

  • Corresponding author: Wenjian Shen, shenwj@hbuas.edu.cn Run Hu, hurun@hust.edu.cn Wangnan Li, liwangnan@hbuas.edu.cn
  • These authors contribute equally to this work.
  • Received Date: 12 February 2025
    Revised Date: 3 April 2025
    Accepted Date: 28 April 2025

    Fund Project: the National Natural Science Foundation of China 22279031the National Natural Science Foundation of China 52422603the Key Research and Development Plan of Hubei Province 2023BAB109the Joint Foundation for Innovation and Development of Hubei Natural Science Foundation 2023AFD032the Joint Foundation for Innovation and Development of Hubei Natural Science Foundation 2025AFD026the Joint Foundation for Innovation and Development of Hubei Natural Science Foundation 2025AFD074the Natural Science Foundation of Hubei Province 2023AFB041the Natural Science Foundation of Hubei Province 2023AFA072the Graduate Quality Engineering Funding Project of Hubei University of Arts and Sciences YZ3202304the Independent Innovation Projects of the Hubei Longzhong Laboratory 2024KF-07the open research fund of Suzhou Laboratory SZLAB-1508-2024-TS016the Interdiciplinary Research Program of HUST 5003120094

  • In recent years, single-junction perovskite solar cells (PSCs) have experienced unprecedented development, approaching the Shockley-Queisser (S-Q) theoretical efficiency limit, due to versatile optimization strategies targeting functional layers to minimize energy loss. The antireflection coating (ARC), as part of the light-management strategy, plays a critical role in reducing optical loss to achieve higher efficiency. The development of multifunctional ARC that can simultaneously enhance visible light transmittance while suppressing ultraviolet (UV) light transmission, along with excellent adhesion and wear resistance on glass substrates, remains a significant challenge in current research. Herein, we propose ultra-thin ARC made of multilayer dioxides, SiO2-TiO2-SiO2 (STS) films, optimized using a machine learning approach with a Bayesian optimization algorithm. This process involved parameterized modeling of multilayer dioxide ARC, physical simulations using the Transfer Matrix Method (TMM), and evaluation of antireflective performance. The optimal configuration of STS ARC consists of 100 nm SiO2, 10 nm TiO2, and 10 nm SiO2, increasing the transmittance of FTO glass by 9.2% in the 400–800 nm wavelength range. The ARC effectively enhances external quantum efficiency, achieving 96.94%, thereby increasing the short-circuit current density (JSC) and power conversion efficiency (PCE) by 4%. PSCs with STS ARC retain 81.2% of their initial efficiency after continuous UV illumination for 300 h, while control devices degrade to approximately 69%, demonstrating effective UV filtration and improved operational stability. This ARC exhibit hardness exceeding 9H on the pencil hardness scale and achieve ISO class 0/ASTM class 5B in adhesion tests, meeting the outdoor durability requirements for PSCs. In addition to optical energy loss, the accumulation of defects on the surface of the perovskite layer induces non-radiative recombination energy loss and serves as initiation sites for lattice degradation. To address this, we use 3-amidinopyridinium iodide (3-PyADI) to passivate interface defects, further improving the PCE to 24.44%. The stability of the device remains at 93% of the initial PCE after 1000 h under atmospheric conditions. The proposed ARC and PSCs structure are expected to enhance optoelectronic performance and environmental stability, providing a promising and practical path for the development of PSCs.
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    1. [1]

      Best Research-Cell Efficiency Chart National Renewable Energy Laboratory (NREL), National Renewable Energy Laboratory (NREL), 2025. https://www.nrel.gov/pv/cell-efficiency.html (accessed: April 2025).

    2. [2]

      Z. Xiao, Y. Yan, Adv. Energy Mater. 7 (2017) 1701136, https://doi.org/10.1002/aenm.201701136.  doi: 10.1002/aenm.201701136

    3. [3]

      J. Huang, Y. Yuan, Y. Shao, Y. Yan, Nat. Rev. Mater. 2 (2017) 17042, https://doi.org/10.1038/natrevmats.2017.42.  doi: 10.1038/natrevmats.2017.42

    4. [4]

      R. Li, H. Liu, Y. Jiao, S. Qin, J. Meng, J. Song, R. Yan, H. Su, H. Chen, Z. Shang, J. Zhao, Acta Phys. -Chim. Sin. 40 (2024) 2311011, https://doi.org/10.3866/PKU.WHXB202311011.  doi: 10.3866/PKU.WHXB202311011

    5. [5]

      M. De Bastiani, V. Larini, R. Montecucco, G. Grancini, Energy Environ. Sci. 16 (2023) 421, https://doi.org/10.1039/D2EE03136A.  doi: 10.1039/D2EE03136A

    6. [6]

      C. Chen, S. Zheng, H. Song, Chem. Soc. Rev. 50 (2021) 7250, https://doi.org/10.1039/D0CS01488E.  doi: 10.1039/D0CS01488E

    7. [7]

      Y. Da, Y. Xuan, Q. Li, Sol. Energy Mater. Sol. Cells 174 (2018) 206, https://doi.org/10.1016/j.solmat.2017.09.002.  doi: 10.1016/j.solmat.2017.09.002

    8. [8]

      Y. Zhang, X. Jia, S. Liu, B. Zhang, K. Lin, J. Zhang, G. Conibeer, Sol. Energy Mater. Sol. Cells 225 (2021) 111073, https://doi.org/10.1016/j.solmat.2021.111073.  doi: 10.1016/j.solmat.2021.111073

    9. [9]

      Y. Ahmed, X. Feng, Y. Gao, Y. Ding, C. Long, M. Haider, H. Li, Z. Li, S. Huang, M.I. Saidaminov, J. Yang, Acta Phys. -Chim. Sin. 40 (2024) 2303057, https://doi.org/10.3866/PKU.WHXB202303057.  doi: 10.3866/PKU.WHXB202303057

    10. [10]

      Y. Wang, Z. Zhang, Y. Lan, Q. Song, M. Li, Y. Song, Adv. Energy Mater. 10 (2020) 1902579, https://doi.org/10.1002/aenm.201902579.  doi: 10.1002/aenm.201902579

    11. [11]

      C. Liu, Y. Yang, H. Chen, I. Spanopoulos, A.S.R. Bati, I.W. Gilley, J. Chen, A. Maxwell, B. Vishal, R.P. Reynolds, T.E. Wiggins, Z. Wang, C. Huang, J. Fletcher, Y. Liu, L.X. Chen, S. De Wolf, B. Chen, D. Zheng, T.J. Marks, A. Facchetti, E.H. Sargent, M.G. Kanatzidis, Nature 633 (2024) 359, https://doi.org/10.1038/s41586-024-07764-8.  doi: 10.1038/s41586-024-07764-8

    12. [12]

      W.E.I. Sha, H. Zhang, Z.S. Wang, H.L. Zhu, X. Ren, F. Lin, A.K. -Y. Jen, W.C.H. Choy, Adv. Energy Mater. 8 (2018) 1701586, https://doi.org/10.1002/aenm.201701586.  doi: 10.1002/aenm.201701586

    13. [13]

      Y. Liang, C. Jiao, P. Zhou, W. Li, Y. Zang, Y. Liu, G. Yang, L. Liu, J. Cheng, G. Liang, J. Wang, Z. Zhong, W. Yan, Bull. Chem. Soc. Jpn. 96 (2023) 148, https://doi.org/10.1246/bcsj.20220307.  doi: 10.1246/bcsj.20220307

    14. [14]

      E. Cho, J.G. Son, C.B. Park, I. Kim, D. Yuk, J. Park, J.Y. Kim, S. Lee, Adv. Funct. Mater. 33 (2023) 2301033, https://doi.org/10.1002/adfm.202301033.  doi: 10.1002/adfm.202301033

    15. [15]

      M.M. Tavakoli, K. -H. Tsui, Q. Zhang, J. He, Y. Yao, D. Li, Z. Fan, ACS Nano 9 (2015) 10287, https://doi.org/10.1021/acsnano.5b04284.  doi: 10.1021/acsnano.5b04284

    16. [16]

      Z. Gao, G. Lin, Y. Chen, Y. Zheng, N. Sang, Y. Li, L. Chen, M. Li, Sol. Energy 205 (2020) 275, https://doi.org/10.1016/j.solener.2020.05.065.  doi: 10.1016/j.solener.2020.05.065

    17. [17]

      M. Shahiduzzaman, M.I. Hossain, S. Visal, T. Kaneko, W. Qarony, S. Umezu, K. Tomita, S. Iwamori, D. Knipp, Y.H. Tsang, M. Akhtaruzzaman, J. -M. Nunzi, T. Taima, M. Isomura, Nano-Micro Lett. 13 (2021) 36, https://doi.org/10.1007/s40820-020-00559-2.  doi: 10.1007/s40820-020-00559-2

    18. [18]

      J.S. Choi, Y. Jang, U. Kim, M. Choi, S.M. Kang, Adv. Energy Mater. 12 (2022) 2201520, https://doi.org/10.1002/aenm.202201520.  doi: 10.1002/aenm.202201520

    19. [19]

      H.K. Raut, A.S. Nair, S.S. Dinachali, V.A. Ganesh, T.M. Walsh, S. Ramakrishna, Sol. Energy Mater. Sol. Cells 111 (2013) 9, https://doi.org/10.1016/j.solmat.2012.12.023.  doi: 10.1016/j.solmat.2012.12.023

    20. [20]

      L. Ye, Y. Zhang, X. Zhang, T. Hu, R. Ji, B. Ding, B. Jiang, Energy Mater. Sol. Cells 111 (2013) 160, https://doi.org/10.1016/j.solmat.2012.12.037.  doi: 10.1016/j.solmat.2012.12.037

    21. [21]

      İ. Kavakil, K. Kantarli, Turk. J. Phys. 26 (2002) 349.

    22. [22]

      Y. Wang, H. Wang, M. Chen, P. Wang, Y. Mao, W. Han, T. Wang, D. Liu, Sci. China Mater. 64 (2020) 789, https://doi.org/10.1007/s40843-020-1478-5.  doi: 10.1007/s40843-020-1478-5

    23. [23]

      Y. Liu, X. Tan, J. Liang, H. Han, P. Xiang, W. Yan, Adv. Funct. Mater. 33 (2023) 2214271, https://doi.org/10.1002/adfm.202214271.  doi: 10.1002/adfm.202214271

    24. [24]

      Z. Liu, N. Rolston, A.C. Flick, T.W. Colburn, Z. Ren, R.H. Dauskardt, T. Buonassisi, Joule 6 (2022) 834, https://doi.org/10.1016/j.joule.2022.03.003.  doi: 10.1016/j.joule.2022.03.003

    25. [25]

      W. Yan, Y. Liu, Y. Zang, J. Cheng, Y. Wang, L. Chu, X. Tan, L. Liu, P. Zhou, W. Li, Nano Energy 99 (2022) 107394, https://doi.org/10.1016/j.nanoen.2022.107394.  doi: 10.1016/j.nanoen.2022.107394

    26. [26]

      E.D. Palik, Handbook of Optical Constants of Solids, first ed., Academic Press, Burlington, USA, 1998, pp. 795–798, 719-721.

    27. [27]

      T. Siefke, S. Kroker, K. Pfeiffer, O. Puffky, K. Dietrich, D. Franta, I. Ohlídal, A. Szeghalmi, E. Kley, A. Tünnermann, Adv. Opt. Mater. 4 (2016) 1780, https://doi.org/10.1002/adom.201600250.  doi: 10.1002/adom.201600250

    28. [28]

      R. Wasielewski, J. Domaradzki, D. Wojcieszak, D. Kaczmarek, A. Borkowska, E.L. Prociow, A. Ciszewski, Appl. Surf. Sci. 254 (2008) 4396, https://doi.org/10.1016/j.apsusc.2008.01.017.  doi: 10.1016/j.apsusc.2008.01.017

    29. [29]

      S.-H. Jeong, J.-K. Kim, B.-S. Kim, S.-H. Shim, B.-T. Lee, Vacuum 76 (2004) 507, https://doi.org/10.1016/j.vacuum.2004.06.003.  doi: 10.1016/j.vacuum.2004.06.003

    30. [30]

      H.-S. Wei, K.-T. Liu, Y.-C. Chang, C.-H. Chan, C.-C. Lee, C.-C. Kuo, Surf. Coat. Technol. 320 (2017) 377, https://doi.org/10.1016/j.surfcoat.2016.12.025.  doi: 10.1016/j.surfcoat.2016.12.025

    31. [31]

      T. Chen, J. Xie, P. Gao, Adv. Energy Sustain. Res. 3 (2022) 2100218, https://doi.org/10.1002/aesr.202100218.  doi: 10.1002/aesr.202100218

    32. [32]

      T. Bu, J. Li, H. Li, C. Tian, J. Su, G. Tong, L.K. Ono, C. Wang, Z. Lin, N. Chai, X.-L. Zhang, J. Chang, J. Lu, J. Zhong, W. Huang, Y. Qi, Y.-B. Cheng, F. Huang, Science 372 (2021) 1327, https://doi.org/10.1126/science.abh1035.  doi: 10.1126/science.abh1035

    33. [33]

      Y. Gao, C. Liu, M. He, C. Zhang, L. Liu, Q. Luo, Y. Wu, H. Zhang, X. Zhong, R. Guo, Y. Xie, S. Wu, R.E.I. Schropp, Y. Mai, Adv. Mater. 36 (2024) 2309310, https://doi.org/10.1002/adma.202309310.  doi: 10.1002/adma.202309310

    34. [34]

      T. Kim, S. Park, V. Iyer, B. Shaheen, U. Choudhry, Q. Jiang, G. Eichman, R. Gnabasik, K. Kelley, B. Lawrie, K. Zhu, B. Liao, Nat. Commun. 14 (2023) 1846, https://doi.org/10.1038/s41467-023-37486-w.  doi: 10.1038/s41467-023-37486-w

    35. [35]

      S. Kim, K. Zhu, Adv. Energy Mater. 13 (2023) 2300603, https://doi.org/10.1002/aenm.202300603.  doi: 10.1002/aenm.202300603

    36. [36]

      S. Teale, M. Degani, B. Chen, E.H. Sargent, G. Grancini, Nat. Energy 9 (2024) 779, https://doi.org/10.1038/s41560-024-01529-3.  doi: 10.1038/s41560-024-01529-3

    37. [37]

      Y. Yang, H. Chen, C. Liu, J. Xu, C. Huang, C.D. Malliakas, H. Wan, A.S.R. Bati, Z. Wang, R.P. Reynolds, I.W. Gilley, S. Kitade, T.E. Wiggins, S. Zeiske, S. Suragtkhuu, M. Batmunkh, L.X. Chen, B. Chen, M.G. Kanatzidis, E.H. Sargent, Science 386 (2024) 898, https://doi.org/10.1126/science.adr2091.  doi: 10.1126/science.adr2091

    38. [38]

      B. Chen, P.N. Rudd, S. Yang, Y. Yuan, J. Huang, Chem. Soc. Rev. 48 (2019) 3842, https://doi.org/10.1039/C8CS00853A.  doi: 10.1039/C8CS00853A

    39. [39]

      L. Liu, W.-H. Fang, R. Long, O.V. Prezhdo, J. Phys. Chem. Lett. 9 (2018) 1164, https://doi.org/10.1021/acs.jpclett.8b00177.  doi: 10.1021/acs.jpclett.8b00177

    40. [40]

      G. Kim, H. Min, K.S. Lee, D.Y. Lee, S.M. Yoon, S.I. Seok, Science 370 (2020) 108, https://doi.org/10.1126/science.abc4417.  doi: 10.1126/science.abc4417

    41. [41]

      B. Yang, D. Bogachuk, J. Suo, L. Wagner, H. Kim, J. Lim, A. Hinsch, G. Boschloo, M.K. Nazeeruddin, A. Hagfeldt, Chem. Soc. Rev. 51 (2022) 7509, https://doi.org/10.1039/D2CS00278G.  doi: 10.1039/D2CS00278G

    42. [42]

      Y. Kong, W. Shen, H. Cai, W. Dong, C. Bai, J. Zhao, F. Huang, Y.-B. Cheng, J. Zhong, Adv. Funct. Mater. 33 (2023) 2300932, https://doi.org/10.1002/adfm.202300932.  doi: 10.1002/adfm.202300932

    43. [43]

      W. Shen, H. Cai, Y. Kong, W. Dong, C. Bai, G. Liang, W. Li, J. Zhao, F. Huang, Y. Cheng, J. Zhong, Small 19 (2023) 2302194, https://doi.org/10.1002/smll.202302194.  doi: 10.1002/smll.202302194

    44. [44]

      J. Zhou, M. Li, S. Wang, L. Tan, Y. Liu, C. Jiang, X. Zhao, L. Ding, C. Yi, Nano Energy 95 (2022) 107036, https://doi.org/10.1016/j.nanoen.2022.107036.  doi: 10.1016/j.nanoen.2022.107036

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