請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/96103完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃慶怡 | zh_TW |
| dc.contributor.advisor | Ching-I Huang | en |
| dc.contributor.author | 張怡晨 | zh_TW |
| dc.contributor.author | Yi-Chen Chang | en |
| dc.date.accessioned | 2024-10-15T16:05:10Z | - |
| dc.date.available | 2024-10-16 | - |
| dc.date.copyright | 2024-10-15 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-10-08 | - |
| dc.identifier.citation | [1] M. C. Scharber and N. S. Sariciftci, "Efficiency of bulk-heterojunction organic solar cells," Progress in polymer science, vol. 38, no. 12, pp. 1929-1940, 2013.
[2] G. Li, R. Zhu, and Y. Yang, "Polymer solar cells," Nature photonics, vol. 6, no. 3, pp. 153-161, 2012. [3] H. S. Vogelbaum and G. Sauvé, "Recently developed high-efficiency organic photoactive materials for printable photovoltaic cells: a mini review," Synthetic metals, vol. 223, pp. 107-121, 2017. [4] F. C. Krebs, "Fabrication and processing of polymer solar cells: A review of printing and coating techniques," Solar energy materials and solar cells, vol. 93, no. 4, pp. 394-412, 2009. [5] Y. Li, J.-D. Lin, X. Che, Y. Qu, F. Liu, L.-S. Liao, and S. R. Forrest, "High efficiency near-infrared and semitransparent non-fullerene acceptor organic photovoltaic cells," Journal of the American Chemical Society, vol. 139, no. 47, pp. 17114-17119, 2017. [6] C. J. Emmott, J. A. Röhr, M. Campoy-Quiles, T. Kirchartz, A. Urbina, N. J. Ekins-Daukes, and J. Nelson, "Organic photovoltaic greenhouses: a unique application for semi-transparent PV?," Energy & environmental science, vol. 8, no. 4, pp. 1317-1328, 2015. [7] H. Zhou, L. Yang, and W. You, "Rational design of high performance conjugated polymers for organic solar cells," Macromolecules, vol. 45, no. 2, pp. 607-632, 2012. [8] C.-C. Chueh and A. K.-Y. Jen, "Recent advances in molecular design of functional conjugated polymers for high-performance polymer solar cells," Progress in Polymer Science, vol. 99, p. 101175, 2019. [9] H.-C. Liao, C.-C. Ho, C.-Y. Chang, M.-H. Jao, S. B. Darling, and W.-F. Su, "Additives for morphology control in high-efficiency organic solar cells," Materials today, vol. 16, no. 9, pp. 326-336, 2013. [10] F. Zhao, C. Wang, and X. Zhan, "Morphology control in organic solar cells," Advanced Energy Materials, vol. 8, no. 28, p. 1703147, 2018. [11] F. Zhang, X. Xu, W. Tang, J. Zhang, Z. Zhuo, J. Wang, J. Wang, Z. Xu, and Y. Wang, "Recent development of the inverted configuration organic solar cells," Solar Energy Materials and Solar Cells, vol. 95, no. 7, pp. 1785-1799, 2011. [12] T. Ameri, G. Dennler, C. Waldauf, H. Azimi, A. Seemann, K. Forberich, J. Hauch, M. Scharber, K. Hingerl, and C. J. Brabec, "Fabrication, optical modeling, and color characterization of semitransparent bulk‐heterojunction organic solar cells in an inverted structure," Advanced Functional Materials, vol. 20, no. 10, pp. 1592-1598, 2010. [13] J. Fu, P. W. Fong, H. Liu, C.-S. Huang, X. Lu, S. Lu, M. Abdelsamie, T. Kodalle, C. M. Sutter-Fella, and Y. Yang, "19.31% binary organic solar cell and low non-radiative recombination enabled by non-monotonic intermediate state transition," Nature communications, vol. 14, no. 1, p. 1760, 2023. [14] K. Liu, Y. Jiang, G. Ran, F. Liu, W. Zhang, and X. Zhu, "19.7% efficiency binary organic solar cells achieved by selective core fluorination of nonfullerene electron acceptors," Joule, vol. 8, no. 3, pp. 835-851, 2024. [15] H. Lu, W. Liu, G. Ran, Z. Liang, H. Li, N. Wei, H. Wu, Z. Ma, Y. Liu, and W. Zhang, "High‐pressure fabrication of binary organic solar cells with high molecular weight D18 yields record 19.65% efficiency," Angewandte Chemie, vol. 135, no. 50, p. e202314420, 2023. [16] Y. Zhou, M. Eck, and M. Krüger, "Bulk-heterojunction hybrid solar cells based on colloidal nanocrystals and conjugated polymers," Energy & Environmental Science, vol. 3, no. 12, pp. 1851-1864, 2010. [17] S. Banerjee and S. S. K. Iyer, "Short-circuit current density and spectral response modelling of bulk-heterojunction solar cells," Organic Electronics, vol. 11, no. 12, pp. 2032-2036, 2010. [18] P. Peumans, A. Yakimov, and S. R. Forrest, "Small molecular weight organic thin-film photodetectors and solar cells," Journal of Applied Physics, vol. 93, no. 7, pp. 3693-3723, 2003. [19] N. A. Ran, J. A. Love, C. J. Takacs, A. Sadhanala, J. K. Beavers, S. D. Collins, Y. Huang, M. Wang, R. H. Friend, and G. C. Bazan, "Harvesting the full potential of photons with organic solar cells," Advanced Materials (Deerfield Beach, Fla.), vol. 28, no. 7, pp. 1482-1488, 2015. [20] M. Pope, "Electronic Processes in Organic Crystals and Polymers," ed: Oxford University Press, 1999. [21] S. R. Forrest, "The path to ubiquitous and low-cost organic electronic appliances on plastic," nature, vol. 428, no. 6986, pp. 911-918, 2004. [22] P. Morvillo and E. Bobeico, "Tuning the LUMO level of the acceptor to increase the open-circuit voltage of polymer-fullerene solar cells: A quantum chemical study," Solar energy materials and solar cells, vol. 92, no. 10, pp. 1192-1198, 2008. [23] H.-Y. Chen, J. Hou, S. Zhang, Y. Liang, G. Yang, Y. Yang, L. Yu, Y. Wu, and G. Li, "Polymer solar cells with enhanced open-circuit voltage and efficiency," Nature photonics, vol. 3, no. 11, pp. 649-653, 2009. [24] B. Qi and J. Wang, "Fill factor in organic solar cells," Physical Chemistry Chemical Physics, vol. 15, no. 23, pp. 8972-8982, 2013. [25] M.-S. Kim, B.-G. Kim, and J. Kim, "Effective variables to control the fill factor of organic photovoltaic cells," ACS applied materials & interfaces, vol. 1, no. 6, pp. 1264-1269, 2009. [26] M.-H. Jao, H.-C. Liao, and W.-F. Su, "Achieving a high fill factor for organic solar cells," Journal of Materials Chemistry A, vol. 4, no. 16, pp. 5784-5801, 2016. [27] P. H. Wöbkenberg, D. D. Bradley, D. Kronholm, J. C. Hummelen, D. M. de Leeuw, M. Cölle, and T. D. Anthopoulos, "High mobility n-channel organic field-effect transistors based on soluble C60 and C70 fullerene derivatives," Synthetic Metals, vol. 158, no. 11, pp. 468-472, 2008. [28] J. Zhang, H. S. Tan, X. Guo, A. Facchetti, and H. Yan, "Material insights and challenges for non-fullerene organic solar cells based on small molecular acceptors," Nature Energy, vol. 3, no. 9, pp. 720-731, 2018. [29] M. Reyes-Reyes, K. Kim, and D. L. Carroll, "High-efficiency photovoltaic devices based on annealed poly (3-hexylthiophene) and 1-(3-methoxycarbonyl)-propyl-1-phenyl-(6, 6) C61 blends," Applied Physics Letters, vol. 87, no. 8, 2005. [30] W. Ma, C. Yang, X. Gong, K. Lee, and A. J. Heeger, "Thermally stable, efficient polymer solar cells with nanoscale control of the interpenetrating network morphology," Advanced functional materials, vol. 15, no. 10, pp. 1617-1622, 2005. [31] A. Ajayaghosh, "Donor–acceptor type low band gap polymers: polysquaraines and related systems," Chemical Society Reviews, vol. 32, no. 4, pp. 181-191, 2003. [32] H. Zhou, L. Yang, S. Stoneking, and W. You, "A weak donor− strong acceptor strategy to design ideal polymers for organic solar cells," ACS applied materials & interfaces, vol. 2, no. 5, pp. 1377-1383, 2010. [33] Y. Liang, Z. Xu, J. Xia, S.-T. Tsai, Y. Wu, G. Li, C. Ray, and L. Yu, "For the bright future-bulk heterojunction polymer solar cells with power conversion efficiency of 7.4%," Advanced materials, vol. 22, no. 20, p. E135, 2010. [34] Y. Liu, J. Zhao, Z. Li, C. Mu, W. Ma, H. Hu, K. Jiang, H. Lin, H. Ade, and H. Yan, "Aggregation and morphology control enables multiple cases of high-efficiency polymer solar cells," Nature communications, vol. 5, no. 1, p. 5293, 2014. [35] Y. Jin, Z. Chen, M. Xiao, J. Peng, B. Fan, L. Ying, G. Zhang, X. F. Jiang, Q. Yin, and Z. Liang, "Thick film polymer solar cells based on naphtho [1, 2‐c: 5, 6‐c] bis [1, 2, 5] thiadiazole conjugated polymers with efficiency over 11%," Advanced Energy Materials, vol. 7, no. 22, p. 1700944, 2017. [36] S. Rasool, Q. V. Hoang, D. Van Vu, T. T. T. Bui, S.-M. Jin, T. T. Ho, C. E. Song, H. K. Lee, S. K. Lee, and J.-C. Lee, "High-efficiency non-halogenated solvent processable polymer/PCBM solar cells via fluorination-enabled optimized nanoscale morphology," Journal of Materials Chemistry A, vol. 7, no. 43, pp. 24992-25002, 2019. [37] P. Cheng, G. Li, X. Zhan, and Y. Yang, "Next-generation organic photovoltaics based on non-fullerene acceptors," Nature Photonics, vol. 12, no. 3, pp. 131-142, 2018. [38] Y. Lin, J. Wang, Z. G. Zhang, H. Bai, Y. Li, D. Zhu, and X. Zhan, "An electron acceptor challenging fullerenes for efficient polymer solar cells," Advanced materials, vol. 27, no. 7, pp. 1170-1174, 2015. [39] W. Zhao, D. Qian, S. Zhang, S. Li, O. Inganäs, F. Gao, and J. Hou, "Fullerene-Free Polymer Solar Cells with over 11% Efficiency and Excellent Thermal Stability," Advanced Materials (Deerfield Beach, Fla.), vol. 28, no. 23, pp. 4734-4739, 2016. [40] M. Zhang, X. Guo, S. Zhang, and J. Hou, "Synergistic effect of fluorination on molecular energy level modulation in highly efficient photovoltaic polymers," Advanced Materials, vol. 26, no. 7, pp. 1118-1123, 2014. [41] K. Reichenbächer, H. I. Süss, and J. Hulliger, "Fluorine in crystal engineering—“the little atom that could”," Chemical Society Reviews, vol. 34, no. 1, pp. 22-30, 2005. [42] W. Zhao, S. Li, H. Yao, S. Zhang, Y. Zhang, B. Yang, and J. Hou, "Molecular optimization enables over 13% efficiency in organic solar cells," Journal of the American Chemical Society, vol. 139, no. 21, pp. 7148-7151, 2017. [43] J. Yuan, Y. Zhang, L. Zhou, G. Zhang, H.-L. Yip, T.-K. Lau, X. Lu, C. Zhu, H. Peng, and P. A. Johnson, "Single-junction organic solar cell with over 15% efficiency using fused-ring acceptor with electron-deficient core," Joule, vol. 3, no. 4, pp. 1140-1151, 2019. [44] Y. Cui, H. Yao, J. Zhang, K. Xian, T. Zhang, L. Hong, Y. Wang, Y. Xu, K. Ma, and C. An, "Single‐junction organic photovoltaic cells with approaching 18% efficiency," Advanced Materials, vol. 32, no. 19, p. 1908205, 2020. [45] Q. Liu, Y. Jiang, K. Jin, J. Qin, J. Xu, W. Li, J. Xiong, J. Liu, Z. Xiao, and K. Sun, "18% Efficiency organic solar cells," Science Bulletin, vol. 65, no. 4, pp. 272-275, 2020. [46] R. Ramprasad, R. Batra, G. Pilania, A. Mannodi-Kanakkithodi, and C. Kim, "Machine learning in materials informatics: recent applications and prospects," npj Computational Materials, vol. 3, no. 1, p. 54, 2017. [47] R. Olivares-Amaya, C. Amador-Bedolla, J. Hachmann, S. Atahan-Evrenk, R. S. Sanchez-Carrera, L. Vogt, and A. Aspuru-Guzik, "Accelerated computational discovery of high-performance materials for organic photovoltaics by means of cheminformatics," Energy & Environmental Science, vol. 4, no. 12, pp. 4849-4861, 2011. [48] H. Sahu, F. Yang, X. Ye, J. Ma, W. Fang, and H. Ma, "Designing promising molecules for organic solar cells via machine learning assisted virtual screening," Journal of Materials Chemistry A, vol. 7, no. 29, pp. 17480-17488, 2019. [49] H. Sahu, W. Rao, A. Troisi, and H. Ma, "Toward predicting efficiency of organic solar cells via machine learning and improved descriptors," Advanced Energy Materials, vol. 8, no. 24, p. 1801032, 2018. [50] H. Sahu and H. Ma, "Unraveling correlations between molecular properties and device parameters of organic solar cells using machine learning," The journal of physical chemistry letters, vol. 10, no. 22, pp. 7277-7284, 2019. [51] D. Padula, J. D. Simpson, and A. Troisi, "Combining electronic and structural features in machine learning models to predict organic solar cells properties," Materials Horizons, vol. 6, no. 2, pp. 343-349, 2019. [52] M.-H. Lee, "Robust random forest based non-fullerene organic solar cells efficiency prediction," Organic Electronics, vol. 76, p. 105465, 2020. [53] M.-H. Lee, "Identifying correlation between the open-circuit voltage and the frontier orbital energies of non-fullerene organic solar cells based on interpretable machine-learning approaches," Solar Energy, vol. 234, pp. 360-367, 2022. [54] M.-H. Lee, "Frontier molecular orbital offset as an empirical descriptor for predicting short circuit current of nonfullerene organic solar cells," Solar RRL, vol. 7, no. 18, p. 2300533, 2023. [55] M.-H. Lee, "Predicting and analyzing the fill factor of non-fullerene organic solar cells based on material properties and interpretable machine-learning strategies," Solar Energy, vol. 267, p. 112191, 2024. [56] W. Sun, Y. Zheng, K. Yang, Q. Zhang, A. A. Shah, Z. Wu, Y. Sun, L. Feng, D. Chen, and Z. Xiao, "Machine learning–assisted molecular design and efficiency prediction for high-performance organic photovoltaic materials," Science advances, vol. 5, no. 11, p. eaay4275, 2019. [57] T. Zhou, Z. Song, and K. Sundmacher, "Big data creates new opportunities for materials research: a review on methods and applications of machine learning for materials design," Engineering, vol. 5, no. 6, pp. 1017-1026, 2019. [58] P. Malhotra, J. C. Verduzco, S. Biswas, and G. D. Sharma, "Active discovery of donor: Acceptor combinations for efficient organic solar cells," ACS Applied Materials & Interfaces, vol. 14, no. 49, pp. 54895-54906, 2022. [59] J. Hachmann, R. Olivares-Amaya, S. Atahan-Evrenk, C. Amador-Bedolla, R. S. Sánchez-Carrera, A. Gold-Parker, L. Vogt, A. M. Brockway, and A. Aspuru-Guzik, "The Harvard clean energy project: large-scale computational screening and design of organic photovoltaics on the world community grid," The Journal of Physical Chemistry Letters, vol. 2, no. 17, pp. 2241-2251, 2011. [60] A. Eibeck, D. Nurkowski, A. Menon, J. Bai, J. Wu, L. Zhou, S. Mosbach, J. Akroyd, and M. Kraft, "Predicting power conversion efficiency of organic photovoltaics: models and data analysis," ACS omega, vol. 6, no. 37, pp. 23764-23775, 2021. [61] S. Nagasawa, E. Al-Naamani, and A. Saeki, "Computer-aided screening of conjugated polymers for organic solar cell: classification by random forest," The Journal of Physical Chemistry Letters, vol. 9, no. 10, pp. 2639-2646, 2018. [62] 陳德安, "運用機器學習分析影響高分子太陽能電池元件性能之關鍵因素," 高分子科學與工程學研究所, 國立臺灣大學, 2023. [63] H. Benten, D. Mori, H. Ohkita, and S. Ito, "Recent research progress of polymer donor/polymer acceptor blend solar cells," Journal of Materials Chemistry A, vol. 4, no. 15, pp. 5340-5365, 2016. [64] C. B. Nielsen, S. Holliday, H.-Y. Chen, S. J. Cryer, and I. McCulloch, "Non-fullerene electron acceptors for use in organic solar cells," Accounts of chemical research, vol. 48, no. 11, pp. 2803-2812, 2015. [65] 蔡孟宏, "檢視異質接面高分子太陽能電池光電轉換效率之關鍵影響因素," 高分子科學與工程學研究所, 國立臺灣大學, 2019. [66] 楊鎰鴻, "藉由動態蒙地卡羅模擬方法探討高效率高分子太陽能電池其高轉換效率之關鍵因素," 高分子科學與工程學研究所, 國立臺灣大學, 2020. [67] M. S. Vezie, S. Few, I. Meager, G. Pieridou, B. Dörling, R. S. Ashraf, A. R. Goñi, H. Bronstein, I. McCulloch, and S. C. Hayes, "Exploring the origin of high optical absorption in conjugated polymers," Nature materials, vol. 15, no. 7, pp. 746-753, 2016. [68] J. Yan, X. Rodríguez-Martínez, D. Pearce, H. Douglas, D. Bili, M. Azzouzi, F. Eisner, A. Virbule, E. Rezasoltani, and V. Belova, "Identifying structure–absorption relationships and predicting absorption strength of non-fullerene acceptors for organic photovoltaics," Energy & Environmental Science, vol. 15, no. 7, pp. 2958-2973, 2022. [69] L. A. Pettersson, L. S. Roman, and O. Inganäs, "Modeling photocurrent action spectra of photovoltaic devices based on organic thin films," Journal of Applied Physics, vol. 86, no. 1, pp. 487-496, 1999. [70] L. Liu and G. Li, "Thickness optimization of organic solar cells by optical transfer matrix," in 2011 11th IEEE International Conference on Nanotechnology, 2011: IEEE, pp. 332-336. [71] D. Rogers and M. Hahn, "Extended-connectivity fingerprints," Journal of chemical information and modeling, vol. 50, no. 5, pp. 742-754, 2010. [72] L. Breiman, "Random forests," Machine learning, vol. 45, pp. 5-32, 2001. [73] S. Lundberg, "A unified approach to interpreting model predictions," arXiv preprint arXiv:1705.07874, 2017. [74] E. Libowitzky and G. R. Rossman, "Principles of quantitative absorbance measurements in anisotropic crystals," Physics and Chemistry of Minerals, vol. 23, no. 6, pp. 319-327, 1996. [75] G. F. Burkhard, E. T. Hoke, and M. D. McGehee, "Accounting for interference, scattering, and electrode absorption to make accurate internal quantum efficiency measurements in organic and other thin solar cells," Advanced Materials, vol. 22, no. 30, pp. 3293-3297, 2010. [76] T. Chai and R. R. Draxler, "Root mean square error (RMSE) or mean absolute error (MAE)?–Arguments against avoiding RMSE in the literature," Geoscientific model development, vol. 7, no. 3, pp. 1247-1250, 2014. [77] W. Li, T. Lee, S. J. Oh, and C. R. Kagan, "Diketopyrrolopyrrole-based π-bridged donor–acceptor polymer for photovoltaic applications," ACS Applied Materials & Interfaces, vol. 3, no. 10, pp. 3874-3883, 2011. [78] Y. Qin, M. A. Uddin, Y. Chen, B. Jang, K. Zhao, Z. Zheng, R. Yu, T. J. Shin, H. Y. Woo, and J. Hou, "Highly efficient fullerene‐free polymer solar cells fabricated with polythiophene derivative," Advanced Materials, vol. 28, no. 42, pp. 9416-9422, 2016. [79] G.-U. Kim, Y. W. Lee, B. S. Ma, J. Kim, J. S. Park, S. Lee, T. L. Nguyen, M. Song, T.-S. Kim, and H. Y. Woo, "Triad-type, multi-functional compatibilizers for enhancing efficiency, stability and mechanical robustness of polymer solar cells," Journal of Materials Chemistry A, vol. 8, no. 27, pp. 13522-13531, 2020. [80] H. Sun, B. Liu, Y. Ma, J. W. Lee, J. Yang, J. Wang, Y. Li, B. Li, K. Feng, and Y. Shi, "Regioregular narrow‐bandgap n‐type polymers with high electron mobility enabling highly efficient all‐polymer solar cells," Advanced Materials, vol. 33, no. 37, p. 2102635, 2021. [81] J. S. Park, N. Choi, C. Lee, S. Lee, J.-W. Ha, D.-H. Hwang, and B. J. Kim, "Elucidating roles of polymer donor aggregation in all-polymer and non-fullerene small-molecule–polymer solar cells," Chemistry of Materials, vol. 32, no. 8, pp. 3585-3596, 2020. [82] R. Li, G. Liu, R. Xie, Z. Wang, X. Yang, K. An, W. Zhong, X.-F. Jiang, L. Ying, and F. Huang, "Introducing cyclic alkyl chains into small-molecule acceptors for efficient polymer solar cells," Journal of Materials Chemistry C, vol. 6, no. 26, pp. 7046-7053, 2018. [83] Q. Fan, W. Su, X. Meng, X. Guo, G. Li, W. Ma, M. Zhang, and Y. Li, "High‐Performance Non‐Fullerene Polymer Solar Cells Based on Fluorine Substituted Wide Bandgap Copolymers Without Extra Treatments," Solar Rrl, vol. 1, no. 5, p. 1700020, 2017. [84] H. Guo, "A simple algorithm for fitting a Gaussian function [DSP tips and tricks]," IEEE Signal Processing Magazine, vol. 28, no. 5, pp. 134-137, 2011. [85] J. R. Quinlan, "Induction of decision trees," Machine learning, vol. 1, pp. 81-106, 1986. [86] M.-C. Popescu, V. E. Balas, L. Perescu-Popescu, and N. Mastorakis, "Multilayer perceptron and neural networks," WSEAS Transactions on Circuits and Systems, vol. 8, no. 7, pp. 579-588, 2009. [87] L. Yang and A. Shami, "On hyperparameter optimization of machine learning algorithms: Theory and practice," Neurocomputing, vol. 415, pp. 295-316, 2020. [88] J. M. Kernbach and V. E. Staartjes, "Foundations of machine learning-based clinical prediction modeling: Part II—Generalization and overfitting," Machine Learning in Clinical Neuroscience: Foundations and Applications, pp. 15-21, 2022. [89] J. Lee Rodgers and W. A. Nicewander, "Thirteen ways to look at the correlation coefficient," The American Statistician, vol. 42, no. 1, pp. 59-66, 1988. [90] C. Sun, S. Qin, R. Wang, S. Chen, F. Pan, B. Qiu, Z. Shang, L. Meng, C. Zhang, and M. Xiao, "High efficiency polymer solar cells with efficient hole transfer at zero highest occupied molecular orbital offset between methylated polymer donor and brominated acceptor," Journal of the American Chemical Society, vol. 142, no. 3, pp. 1465-1474, 2020. [91] J.-W. Lee, D. Jeong, D. J. Kim, T. N.-L. Phan, J. S. Park, T.-S. Kim, and B. J. Kim, "Flexible-spacer incorporated polymer donors enable superior blend miscibility for high-performance and mechanically-robust polymer solar cells," Energy & Environmental Science, vol. 14, no. 7, pp. 4067-4076, 2021. [92] G. Li, X. Zhang, L. O. Jones, J. M. Alzola, S. Mukherjee, L.-w. Feng, W. Zhu, C. L. Stern, W. Huang, and J. Yu, "Systematic merging of nonfullerene acceptor π-extension and tetrafluorination strategies affords polymer solar cells with> 16% efficiency," Journal of the American Chemical Society, vol. 143, no. 16, pp. 6123-6139, 2021. [93] Y. Yu, X. Tan, S. Ning, and Y. Wu, "Machine learning for understanding compatibility of organic–inorganic hybrid perovskites with post-treatment amines," ACS Energy Letters, vol. 4, no. 2, pp. 397-404, 2019. [94] H. Yan, J. Chen, K. Zhou, Y. Tang, X. Meng, X. Xu, and W. Ma, "Lewis acid doping induced synergistic effects on electronic and morphological structure for donor and acceptor in polymer solar cells," Advanced Energy Materials, vol. 8, no. 19, p. 1703672, 2018. [95] X. Zhu, B. Guo, J. Fang, T. Zhai, Y. Wang, G. Li, J. Zhang, Z. Wei, S. Duhm, and X. Guo, "Surface modification of ZnO electron transport layers with glycine for efficient inverted non-fullerene polymer solar cells," Organic Electronics, vol. 70, pp. 25-31, 2019. [96] X. Li, R. Ma, T. Liu, Y. Xiao, G. Chai, X. Lu, H. Yan, and Y. Li, "Fine-tuning HOMO energy levels between PM6 and PBDB-T polymer donors via ternary copolymerization," Science China Chemistry, vol. 63, pp. 1256-1261, 2020. [97] Z. He, C. Zhong, S. Su, M. Xu, H. Wu, and Y. Cao, "Enhanced power-conversion efficiency in polymer solar cells using an inverted device structure," Nature photonics, vol. 6, no. 9, pp. 591-595, 2012. [98] Y. Zhao, G. Xu, X. Guo, Y. Xia, C. Cui, M. Zhang, B. Song, Y. Li, and Y. Li, "Cooperative assembly of an active layer utilizing the synergistic effect of a functional fullerene triad as an acceptor for efficient P3HT-based PSCs," Journal of Materials Chemistry A, vol. 3, no. 35, pp. 17991-18000, 2015. [99] K.-H. Kim, S. Park, H. Yu, H. Kang, I. Song, J. H. Oh, and B. J. Kim, "Determining optimal crystallinity of diketopyrrolopyrrole-based terpolymers for highly efficient polymer solar cells and transistors," Chemistry of Materials, vol. 26, no. 24, pp. 6963-6970, 2014. [100] X. Fan, J. Gao, W. Wang, S. Xiao, C. Zhan, X. Lu, and Q. Zhang, "Ladder‐Type Nonacyclic Arene Bis (thieno [3, 2‐b] thieno) cyclopentafluorene as a Promising Building Block for Non‐Fullerene Acceptors," Chemistry–An Asian Journal, vol. 14, no. 10, pp. 1814-1822, 2019. [101] H. Yao, F. Bai, H. Hu, L. Arunagiri, J. Zhang, Y. Chen, H. Yu, S. Chen, T. Liu, and J. Y. L. Lai, "Efficient all-polymer solar cells based on a new polymer acceptor achieving 10.3% power conversion efficiency," ACS Energy Letters, vol. 4, no. 2, pp. 417-422, 2019. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/96103 | - |
| dc.description.abstract | 高分子太陽能電池近年來因能量轉換效率的長足進展而備受矚目，其蓬勃前景在予體和受體材料的開發、主動層形態的優化及元件製程的改良等層面所累積之豐富研究成果中可見一斑；然而從上述多項用於提升元件性能的策略可知，影響能量轉換效率的因素錯綜複雜且息息相關，因此從中找尋關鍵因素成為一大挑戰。在眾多影響因子中，本研究聚焦於主動層材料之光吸收，運用機器學習方法結合大量數據之資料庫，以快速預測模型建立主動層材料、吸收光譜、元件性能間的關聯性，以此掌握提升能量轉換效率之關鍵。我們首先於 2010-2022 年間高分子太陽能電池實驗文獻中收集數據，並在經由和真實光譜的比對驗證光學轉換矩陣和分峰擬合技術之可信後，導入吸收係數得到可見光下的吸收度，並將其以 4 個高斯峰之和進行擬合，以此在精簡光譜參數的同時、保留完整的吸光資訊，建立首個高分子太陽能電池吸收光譜資料庫；接著，我們運用隨機森林演算法針對分子結構－吸收光譜 (Structure-Property) 和吸收光譜－PCE/ JSC (Property-Performance) 之間訓練預測模型，均獲得出色的預測表現，並基於此以 SHAP 方法回饋對於提升光吸收或 PCE/ JSC 的重要因素。面對高分子太陽能領域中、無論在實驗或人工智慧上皆較少為人所研究的材料光吸收，我們建立可直接輸入分子結構即得到可見光全波段 (400-800 nm) 吸收光譜的快速預測模型，並藉由其對於未接觸過之新材料展現和實驗相近的結果說明此模型之預測能力；此外，我們亦在吸收光譜對元件性能的影響中，揭示 PCE 和 JSC 間的高度正相關，並觀察到最大吸收峰之波長和吸收度對能量轉換效率至關重要，隨最大吸收度的提升 (最大吸收度>0.7) 將帶來較高的 PCE/ JSC 值；綜合上述發現，我們透過模型回饋使材料具高吸收度潛力之結構片段，以及高性能表現之主動層材料其最大吸收度> 0.7 的趨勢，於資料庫中進行材料篩選，並針對未存在元件性能數據的全新予體－受體組合，預測其 PCE 和 JSC，進而提供兼具優異吸光特性和元件性能之潛力的主動層材料。本研究以近十年間大量實驗數據的宏觀視角，利用機器學習快速且低成本之優勢，自鮮少為人所探討之光吸收的角度出發，從中探討結構、性質、性能間的趨勢，以期在新主動層材料開發上成為實驗學者之助力，達降低研發成本並推動高分子太陽能電池發展進程之目標。 | zh_TW |
| dc.description.abstract | Polymer solar cells have recently attracted considerable attention due to significant progress in power conversion efficiency (PCE), driven by breakthroughs in material development, active layer optimization, and device fabrication. However, the complex interplay of factors affecting PCE poses a major challenge in pinpointing the most critical ones. This study focuses on the optical absorption of active layers and aims to develop predictive models to correlate molecular structures, absorption spectra, and device performance via machine learning. We collect data from polymer solar cell experiments published between 2010 and 2022. After validating the optical transfer matrix method and peak fitting technique against experimental spectra, we create the first absorption spectrum database for polymer solar cells. Employing the random forest algorithm, we develop structure-property and property-performance models that achieve excellent predictive accuracy. SHAP analysis further identifies key factors that enhance absorbance, power conversion efficiency (PCE), and short-circuit current density (JSC). Our model, capable of predicting visible light absorption (400–800 nm) from molecular structures, demonstrates remarkable accuracy with previously unexplored materials. Additionally, we reveal a strong positive correlation between PCE and JSC, with materials exhibiting a maximum absorbance greater than 0.7 generally achieving higher performance. Finally, we identify key structural fragments that contribute to high absorbance and screen donor-acceptor pairs with no existing performance data to predict their PCE and JSC, providing potential donor-acceptor pairs. Our study offers insights into trends among structures, properties, and performance, aiming to guide material selection and accelerate development, reduce costs, and advance the field of polymer solar cells. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-10-15T16:05:10Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-10-15T16:05:10Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 中文摘要 i
英文摘要 ii 目次 iii 圖次 iv 表次 vii 第1章 前言 1 第2章 研究方法 9 2.1 吸收光譜資料庫 11 2.2 機器學習方法 18 第3章 結果與討論 21 3.1 吸收光譜預測模型之建立 22 3.2 探討吸收光譜對元件性能之影響 28 3.3 探討分子結構、最大吸收峰、PCE/ JSC 間之關係 43 第4章 結論 56 第5章 參考文獻 57 第6章 附錄 64 S1. 各模型表現評估指標：R 和 RMSE 64 S2. 「分子結構－吸收光譜」模型資料庫數值—模型預測值關係圖 66 S3. 「分子結構－最大吸收峰吸收度」模型之重要結構片段 70 | - |
| dc.language.iso | zh_TW | - |
| dc.title | 運用機器學習探討影響高分子太陽能電池光吸收和元件性能的關鍵因素 | zh_TW |
| dc.title | Exploring the Key Factors for Light Absorption and Device Performance of Polymer Solar Cells via Machine Learning | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 李旻軒;林昆翰 | zh_TW |
| dc.contributor.oralexamcommittee | Min-Hsuan Lee;Kun-Han Lin | en |
| dc.subject.keyword | 高分子太陽能電池,機器學習,隨機森林,光學轉換矩陣,吸收光譜, | zh_TW |
| dc.subject.keyword | Polymer solar cells,Machine learning,Random forest,Optical transfer matrix method,Absorption spectra, | en |
| dc.relation.page | 73 | - |
| dc.identifier.doi | 10.6342/NTU202404460 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2024-10-09 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 高分子科學與工程學研究所 | - |
| 顯示於系所單位： | 高分子科學與工程學研究所 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-113-1.pdf | 7.62 MB | Adobe PDF | 檢視/開啟 |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。