Machine Learning for Organic Photovoltaic Polymers: A Minireview

Asif Mahmood; Ahmad Irfan; Jin-Liang Wang

doi:10.1007/s10118-022-2782-5

Your Location：

Home >

Browse articles >

Machine Learning for Organic Photovoltaic Polymers: A Minireview

REVIEW | Updated：2022-07-21

- Machine Learning for Organic Photovoltaic Polymers: A Minireview
- Machine Learning for Organic Photovoltaic Polymers: A Minireview
- Chinese Journal of Polymer Science 2022年40卷第8期页码：870-876
- Affiliations：
  
  a.Key Laboratory of Cluster Science of Ministry of Education, Beijing Key Laboratory of Photoelectronic/Electrophotonic Conversion Materials, Key Laboratory of Medical Molecule Science and Pharmaceutics Engineering in Ministry of Industry and Information Technology, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing 100081, China
  b.Department of Chemistry, College of Science, King Khalid University, Abha 61413, Saudi Arabia
- Author bio：
  
  jinlwang@bit.edu.cn
- Funds：
  
  This work was financially supported by the National Natural Science Foundation of China (Nos. 21971014, 21672023 and 21950410533). Jin-Liang Wang was supported by BIT Teli Young Fellow Recruitment Program. The authors thank the Analysis & Testing Center, Beijing Institute of Technology, for the characterization. A. Irfan express appreciation to the Deanship of Scientific Research at King Khalid University Saudi Arabia through a research groups program under grant number RGP1/36/43.
- DOI：10.1007/s10118-022-2782-5
  中图分类号：
Scan for full text
Asif Mahmood, Ahmad Irfan, Jin-Liang Wang. Machine Learning for Organic Photovoltaic Polymers: A Minireview[J]. Chinese Journal of Polymer Science, 2022,40(8):870-876.

Asif Mahmood, Ahmad Irfan, Jin-Liang Wang. Machine Learning for Organic Photovoltaic Polymers: A Minireview[J]. Chinese Journal of Polymer Science, 2022,40(8):870-876.
Asif Mahmood, Ahmad Irfan, Jin-Liang Wang. Machine Learning for Organic Photovoltaic Polymers: A Minireview[J]. Chinese Journal of Polymer Science, 2022,40(8):870-876. DOI： 10.1007/s10118-022-2782-5.

Asif Mahmood, Ahmad Irfan, Jin-Liang Wang. Machine Learning for Organic Photovoltaic Polymers: A Minireview[J]. Chinese Journal of Polymer Science, 2022,40(8):870-876. DOI： 10.1007/s10118-022-2782-5.

摘要

Machine learning is a powerful tool that can guide the experimentalists to discover and develop new high-performance polymeric materials. In this mini-review, various case studies related to the use of machine learning for polymer solar cells research are discussed. Various challenges and opportunities are also discussed.

Abstract

Machine learning is a powerful tool that can provide a way to revolutionize the material science. Its use for the designing and screening of materials for polymer solar cells is also increasing. Search of efficient polymeric materials for solar cells is really difficult task. Researchers have synthesized and fabricated so many materials. Sorting the results and get feedback for further research requires an innovative approach. In this minireview, we provides brief introduction of machine learning. The importance of machine learning is also mentioned, and the application of machine learning for polymeric material design is discussed. The key challenges that are hindering the wide spread use of machine are discussed. Suggestions are also given to improve the use of data science. The predictions using machine learning maybe not highly accurate but it definitely better than no prediction at all.

关键词

Keywords

Machine learningPolymer solar cellsData scienceDescriptorsPolymers

references

Mahmood, A.; Irfan, A.; Wang, J. L . Developing efficient small molecule acceptors with sp2-hybridized nitrogen at different positions by density functional theory calculations, molecular dynamics simulations and machine learning . Chem. Eur. J. , 2022 . 28 e202103712 .

Rasool, A.; Zahid, S.; Ans, M.; Iqbal, J.; Adnan, M.; Sherif, E. S. M.; Al-Buriahi, M. S . Synergistic engineering of end-capped acceptor and bridge on arylborane-arylamine macrocycles to boost the photovoltaic properties of organic solar cells . Opt. Mater. , 2022 . 123 111907 DOI:10.1016/j.optmat.2021.111907http://doi.org/10.1016/j.optmat.2021.111907 .

Mahmood, A.; Wang, J. L . A time and resource efficient machine learning assisted design of non-fullerene small molecule acceptors for P3HT-based organic solar cells and green solvent selection . J. Mater. Chem. A , 2021 . 9 15684 -15695 . DOI:10.1039/D1TA04742Fhttp://doi.org/10.1039/D1TA04742F .

Mahmood, A.; Irfan, A.; Wang, J. L . Machine learning and molecular dynamics simulation-assisted evolutionary design and discovery pipeline to screen efficient small molecule acceptors for PTB7-Th-based organic solar cells with over 15% efficiency . J. Mater. Chem. A , 2022 . 10 4170 -4180 . DOI:10.1039/D1TA09762Hhttp://doi.org/10.1039/D1TA09762H .

Wang, J. L.; Liu, K. K.; Hong, L.; Ge, G . Y.; Zhang, C.; Hou, J. Selenopheno[3,2-b]thiophene-based narrow-bandgap nonfullerene acceptor enabling 13.3% efficiency for organic solar cells with thickness-insensitive feature . ACS Energy Lett. , 2018 . 3 2967 -2976 . DOI:10.1021/acsenergylett.8b01808http://doi.org/10.1021/acsenergylett.8b01808 .

Afzal, Q. Q.; Jaffar, K.; Ans, M.; Rafique, J.; Iqbal, J.; Shehzad, R. A.; Mahr, M. S . Designing benzothiadiazole based highly efficient non-fullerene acceptor molecules for organic solar cells . Polymer , 2022 . 238 124405 DOI:10.1016/j.polymer.2021.124405http://doi.org/10.1016/j.polymer.2021.124405 .

Ans, M.; Ayub, K.; Muhammad, S.; Iqbal, J . Development of fullerene free acceptors molecules for organic solar cells: a step way forward toward efficient organic solar cells . Comput. Theor. Chem. , 2019 . 1161 26 -38 . DOI:10.1016/j.comptc.2019.06.003http://doi.org/10.1016/j.comptc.2019.06.003 .

Zahid, S.; Rasool, A.; Shehzad, R. A.; Bhatti, I. A.; Iqbal, J . Tuning the optoelectronic properties of triphenylamine (TPA) based small molecules by modifying central core for photovoltaic applications . J. Mol. Model. , 2021 . 27 237 DOI:10.1007/s00894-021-04867-1http://doi.org/10.1007/s00894-021-04867-1 .

Sharif, A.; Jabeen, S.; Iqbal, S.; Iqbal, J . Tuning the optoelectronic properties of dibenzochrysene (DBC) based small molecules for organic solar cells . Mater. Sci. Semicond. Process. , 2021 . 127 105689 DOI:10.1016/j.mssp.2021.105689http://doi.org/10.1016/j.mssp.2021.105689 .

Zahid, S.; Rasool, A.; Ans, M.; Yaseen, M.; Iqbal, J . Quantum chemical approach of donor-π-acceptor based arylborane-arylamine macrocycles with outstanding photovoltaic properties toward high-performance organic solar cells . Energy & Fuels , 2021 . 35 15018 -15032. .

Mahmood, A.; Irfan, A . Effect of fluorination on exciton binding energy and electronic coupling in small molecule acceptors for organic solar cells . Comput. Theor. Chem. , 2020 . 1179 112797 DOI:10.1016/j.comptc.2020.112797http://doi.org/10.1016/j.comptc.2020.112797 .

Mahmood, A.; Irfan, A . Computational analysis to understand the performance difference between two small-molecule acceptors differing in their terminal electron-deficient group . J. Comput. Electron. , 2020 . 19 931 -939 . DOI:10.1007/s10825-020-01494-6http://doi.org/10.1007/s10825-020-01494-6 .

Ans, M.; Iqbal, J.; Ayub, K.; Ali, E.; Eliasson, B . Spirobifluorene based small molecules as an alternative to traditional fullerene acceptors for organic solar cells . Mater. Sci. Semicond. Process. , 2019 . 94 97 -106 . DOI:10.1016/j.mssp.2019.01.039http://doi.org/10.1016/j.mssp.2019.01.039 .

Rasool, A.; Zahid, S.; Ans, M.; Muhammad, S.; Ayub, K.; Iqbal, J . Bithieno thiophene-based small molecules for application as donor materials for organic solar cells and hole transport materials for perovskite solar cells . ACS Omega , 2022 . 7 844 -862 . DOI:10.1021/acsomega.1c05504http://doi.org/10.1021/acsomega.1c05504 .

Mahmood, A.; Abdullah Muhammad, I.; Nazar Muhammad, F . Quantum chemical designing of novel organic non-linear optical compounds . Bull. Korean Chem. Soc. , 2014 . 35 1391 -1396 . DOI:10.5012/bkcs.2014.35.5.1391http://doi.org/10.5012/bkcs.2014.35.5.1391 .

Ahmad, F.; Mahmood, A.; Muhmood, T . Machine learning-integrated omics for the risk and safety assessment of nanomaterials . Biomater. Sci. , 2021 . 9 1598 -1608 . DOI:10.1039/D0BM01672Ahttp://doi.org/10.1039/D0BM01672A .

Mahmood, A . Photovoltaic and charge transport behavior of diketopyrrolopyrrole based compounds with A-D-A-D-A skeleton . J. Cluster Sci. , 2019 . 30 1123 -1130 . DOI:10.1007/s10876-019-01573-0http://doi.org/10.1007/s10876-019-01573-0 .

Mahmood, A.; Wang, J. L . Machine learning for high performance organic solar cells: current scenario and future prospects . Energy Environ. Sci. , 2021 . 14 90 -105 . DOI:10.1039/D0EE02838Jhttp://doi.org/10.1039/D0EE02838J .

Shang, Z.; Zhou, L.; Sun, C.; Meng, L.; Lai, W.; Zhang, J.; Huang, W.; Li, Y . Non-equivalent D-A copolymerization strategy towards highly efficient polymer donor for polymer solar cells . Sci. China Chem. , 2021 . 64 1031 -1038 . DOI:10.1007/s11426-021-9988-6http://doi.org/10.1007/s11426-021-9988-6 .

Meng, B.; Wang, Z.; Ma, W.; Xie, Z.; Liu, J.; Wang, L . A cross-linkable donor polymer as the underlying layer to tune the active layer morphology of polymer solar cells . Adv. Funct. Mater. , 2016 . 26 226 -232 . DOI:10.1002/adfm.201503833http://doi.org/10.1002/adfm.201503833 .

Long, X.; Ding, Z.; Dou, C.; Zhang, J.; Liu, J.; Wang, L . Polymer acceptor based on double B←N bridged bipyridine (BNBP) unit for high-efficiency all-polymer solar cells . Adv. Mater. , 2016 . 28 6504 -6508 . DOI:10.1002/adma.201601205http://doi.org/10.1002/adma.201601205 .

Xu, J.; Feng, H.; Liang, Y.; Tang, H.; Tang, Y.; Du, Z.; Hu, Z.; Huang, F.; Cao, Y . N-alkyl chain modification in dithienobenzotriazole unit enabled efficient polymer donor for high-performance non-fullerene solar cells . J. Energy Chem. , 2022 . 66 382 -389 . DOI:10.1016/j.jechem.2021.08.033http://doi.org/10.1016/j.jechem.2021.08.033 .

Zhang, Z . G.; Bai, Y.; Li, Y. Benzotriazole based 2D-conjugated polymer donors for high performance polymer solar cells . Chinese J. Polym. Sci. , 2021 . 39 1 -13 . DOI:10.1007/s10118-020-2496-5http://doi.org/10.1007/s10118-020-2496-5 .

Chen, D.; Liu, S.; Hu, X.; Wu, F.; Liu, J.; Zhou, K.; Ye, L.; Chen, L.; Chen, Y . Printable and stable all-polymer solar cells based on non-conjugated polymer acceptors with excellent mechanical robustness . Sci. China Chem. , 2022 . 65 182 -189 . DOI:10.1007/s11426-021-1094-yhttp://doi.org/10.1007/s11426-021-1094-y .

Wang, R.; Yao, Y.; Zhang, C.; Zhang, Y.; Bin, H.; Xue, L.; Zhang, Z.-G.; Xie, X.; Ma, H.; Wang, X.; Li, Y.; Xiao, M . Ultrafast hole transfer mediated by polaron pairs in all-polymer photovoltaic blends . Nat. Commun. , 2019 . 10 398 DOI:10.1038/s41467-019-08361-4http://doi.org/10.1038/s41467-019-08361-4 .

Liu, S.; Li, H.; Wu, X.; Chen, D.; Zhang, L.; Meng, X.; Tan, L.; Hu, X.; Chen, Y. . Pseudo-planar heterojunction organic photovoltaics with optimized light utilization for printable solar windows . Adv. Mater. , 2022 . 34 2201604 DOI:10.1002/adma.202201604http://doi.org/10.1002/adma.202201604 .

Zhang, Y.; Wang, Y.; Ma, R.; Luo, Z.; Liu, T.; Kang, S. H.; Yan, H.; Yuan, Z.; Yang, C.; Chen, Y . Wide band-gap two-dimension conjugated polymer donors with different amounts of chlorine substitution on alkoxyphenyl conjugated side chains for non-fullerene polymer solar cells . Chinese J. Polym. Sci. , 2020 . 38 797 -805 . DOI:10.1007/s10118-020-2435-5http://doi.org/10.1007/s10118-020-2435-5 .

Zhang, Z. G.; Li, Y . Polymerized small-molecule acceptors for high-performance all-polymer solar cells . Angew. Chem. Int. Ed. , 2021 . 60 4422 -4433 . DOI:10.1002/anie.202009666http://doi.org/10.1002/anie.202009666 .

Liu, Y. Q.; Zhi, H. F.; Bai, H. R.; Jiang, Z.; Wan, S. S.; Jiang, M.; Mahmood, A.; Yang, C.; Sun, S.; An, Q.; Wang, J. L . Two-dimensional conjugated benzo[1,2-b:4,5-b']diselenophene-based copolymer donor enables large open-circuit voltage and high efficiency in selenophene-based organic solar cells . ChemSusChem , 2021 . 14 4454 -4465 . DOI:10.1002/cssc.202101232http://doi.org/10.1002/cssc.202101232 .

Wang, T.; Sun, R.; Yang, X. R.; Wu, Y.; Wang, W.; Li, Q.; Zhang, C. F.; Min, J. . A near-infrared polymer acceptor enables over 15% efficiency for all-polymer solar cells . Chinese J. Polym. Sci. , 2022 . 40 877 -888 . DOI:10.1007/s10118-022-2697-1http://doi.org/10.1007/s10118-022-2697-1 .

Yin, B.; Chen, Z.; Pang, S.; Yuan, X.; Liu, Z.; Duan, C.; Huang, F.; Cao, Y. . The renaissance of oligothiophene-based donor-acceptor polymers in organic solar cells . Adv. Energy Mater. , 2022 . 12 2104050 DOI:10.1002/aenm.202104050http://doi.org/10.1002/aenm.202104050 .

Anthony, J. E.; Facchetti, A.; Heeney, M.; Marder, S. R.; Zhan, X . n-Type organic semiconductors in organic electronics . Adv. Mater. , 2010 . 22 3876 -3892 . DOI:10.1002/adma.200903628http://doi.org/10.1002/adma.200903628 .

Ge, G. Y.; Li, J. T.; Wang, J. R.; Xiong, M.; Dong, X.; Li, Z. J.; Li, J. L.; Cao, X. Y.; Lei, T.; Wang, J. L . Unveiling the interplay among end group, molecular packing, doping level, and charge transport in N-doped small-molecule organic semiconductors . Adv. Funct. Mater. , 2022 . 32 2108289 DOI:10.1002/adfm.202108289http://doi.org/10.1002/adfm.202108289 .

Yang, C.; An, Q.; Bai, H. R.; Zhi, H. F.; Ryu, H. S.; Mahmood, A.; Zhao, X.; Zhang, S.; Woo, H. Y.; Wang, J. L . A synergistic strategy of manipulating the number of selenophene units and dissymmetric central core of small molecular acceptors enables polymer solar cells with 17.5 % efficiency . Angew. Chem., Int. Ed. , 2021 . 60 19241 -19252 . DOI:10.1002/anie.202104766http://doi.org/10.1002/anie.202104766 .

Zhang, Q.; Chen, Z.; Ma, W.; Xie, Z.; Han, Y . Optimizing domain size and phase purity in all-polymer solar cells by solution ordered aggregation and confinement effect of the acceptor . J. Mater. Chem. C , 2019 . 7 12560 -12571 . DOI:10.1039/C9TC03697Khttp://doi.org/10.1039/C9TC03697K .

Wang, L.; An, Q.; Yan, L.; Bai, H. R.; Jiang, M.; Mahmood, A.; Yang, C.; Zhi, H.; Wang, J. L . Non-fullerene acceptors with hetero-dihalogenated terminals induce significant difference in single crystallography and enable binary organic solar cells with 17.5% efficiency . Energy Environ. Sci. , 2022 . 15 320 -333 . DOI:10.1039/D1EE01832Ahttp://doi.org/10.1039/D1EE01832A .

Wang, J. L.; Liu, K. K.; Yan, J.; Wu, Z.; Liu, F.; Xiao, F.; Chang, Z. F.; Wu, H.-B.; Cao, Y.; Russell, T. P . Series of multifluorine substituted oligomers for organic solar cells with efficiency over 9% and fill factor of 0.77 by combination thermal and solvent vapor annealing . J. Am. Chem. Soc. , 2016 . 138 7687 -7697 . DOI:10.1021/jacs.6b03495http://doi.org/10.1021/jacs.6b03495 .

Jørgensen, P. B.; Mesta, M.; Shil, S.; Lastra, J. M. G.; Jacobsen, K. W.; Thygesen, K. S.; Schmidt, M. N . Machine learning-based screening of complex molecules for polymer solar cells . J. Chem. Phys. , 2018 . 148 241735 DOI:10.1063/1.5023563http://doi.org/10.1063/1.5023563 .

Nagasawa, S.; Al-Naamani, E.; Saeki, A . Computer-aided screening of conjugated polymers for organic solar cell: classification by random forest . J. Phys. Chem. Lett. , 2018 . 9 2639 -2646 . DOI:10.1021/acs.jpclett.8b00635http://doi.org/10.1021/acs.jpclett.8b00635 .

Ye, L.; Zhao, W.; Li, S.; Mukherjee, S.; Carpenter, J . H.; Awartani, O.; Jiao, X.; Hou, J.; Ade, H. High-efficiency nonfullerene organic solar cells: critical factors that affect complex multi-length scale morphology and device performance . Adv. Energy Mater. , 2017 . 7 1602000 DOI:10.1002/aenm.201602000http://doi.org/10.1002/aenm.201602000 .

Duong, D. T.; Walker, B.; Lin, J.; Kim, C.; Love, J.; Purushothaman, B.; Anthony, J. E.; Nguyen, T. Q . Molecular solubility and hansen solubility parameters for the analysis of phase separation in bulk heterojunctions . J. Polym. Sci., Part B: Polym. Phys. , 2012 . 50 1405 -1413 . DOI:10.1002/polb.23153http://doi.org/10.1002/polb.23153 .

Perea, J. D.; Langner, S.; Salvador, M.; Sanchez-Lengeling, B.; Li, N.; Zhang, C.; Jarvas, G.; Kontos, J.; Dallos, A.; Aspuru-Guzik, A.; Brabec, C. J . Introducing a new potential figure of merit for evaluating microstructure stability in photovoltaic polymer-fullerene blends . J. Phys. Chem. C , 2017 . 121 18153 -18161 . DOI:10.1021/acs.jpcc.7b03228http://doi.org/10.1021/acs.jpcc.7b03228 .

Huang, Y.; Zhang, J.; Jiang, E. S.; Oya, Y.; Saeki, A.; Kikugawa, G.; Okabe, T.; Ohuchi, F. S . Structure-property correlation study for organic photovoltaic polymer materials using data science approach . J. Phys. Chem. C , 2020 . 124 12871 -12882 . DOI:10.1021/acs.jpcc.0c00517http://doi.org/10.1021/acs.jpcc.0c00517 .

Munshi, J.; Chen, W.; Chien, T.; Balasubramanian, G . Transfer learned designer polymers for organic solar cells . J. Chem. Inf. Model. , 2021 . 61 134 -142 . DOI:10.1021/acs.jcim.0c01157http://doi.org/10.1021/acs.jcim.0c01157 .

Wu, Y.; Guo, J.; Sun, R.; Min, J . Machine learning for accelerating the discovery of high-performance donor/acceptor pairs in non-fullerene organic solar cells . Npj Comput. Mater. , 2020 . 6 120 DOI:10.1038/s41524-020-00388-2http://doi.org/10.1038/s41524-020-00388-2 .

Miyake, Y.; Saeki, A . Machine learning-assisted development of organic solar cell materials: issues, analyses, and outlooks . J. Phys. Chem. Lett. , 2021 . 12 12391 -12401 . DOI:10.1021/acs.jpclett.1c03526http://doi.org/10.1021/acs.jpclett.1c03526 .

Kranthiraja, K.; Saeki, A . Experiment-oriented machine learning of polymer:non-fullerene organic solar cells . Adv. Funct. Mater. , 2021 . 31 2011168 DOI:10.1002/adfm.202011168http://doi.org/10.1002/adfm.202011168 .

Sun, W.; Li, M.; Li, Y.; Wu, Z.; Sun, Y.; Lu, S.; Xiao, Z.; Zhao, B.; Sun, K . The use of deep learning to fast evaluate organic photovoltaic materials . Adv. Theory Simul. , 2019 . 2 1800116 DOI:10.1002/adts.201800116http://doi.org/10.1002/adts.201800116 .

Pyzer-Knapp, E . O.; Li, K.; Aspuru-Guzik, A. Learning from the Harvard Clean Energy Project: the use of neural networks to accelerate materials discovery . Adv. Funct. Mater. , 2015 . 25 6495 -6502 . DOI:10.1002/adfm.201501919http://doi.org/10.1002/adfm.201501919 .

Lee, M. H . Performance and matching band structure analysis of tandem organic solar cells using machine learning approaches . Energy Technol. , 2020 . 8 1900974 DOI:10.1002/ente.201900974http://doi.org/10.1002/ente.201900974 .

Mahmood, A.; Wang, J. L . A Review of grazing incidence small- and wide-angle X-ray scattering techniques for exploring the film morphology of organic solar cells . Solar RRL , 2020 . 4 2000337 DOI:10.1002/solr.202000337http://doi.org/10.1002/solr.202000337 .

Mahmood, A.; Abdullah, M. I.; Khan, S. U. D . Enhancement of nonlinear optical (NLO) properties of indigo through modification of auxiliary donor, donor and acceptor . Spectrochim. Acta - A: Mol. Biomol. Spectrosc. , 2015 . 139 425 -430 . DOI:10.1016/j.saa.2014.12.038http://doi.org/10.1016/j.saa.2014.12.038 .

Mahmood, A.; Saqib, M.; Ali, M.; Abdullah, M. I.; Khalid, B . Theoretical investigation for the designing of novel antioxidants . Can. J. Chem. , 2013 . 91 126 -130 . DOI:10.1139/cjc-2012-0356http://doi.org/10.1139/cjc-2012-0356 .

Mahmood, A.; Irfan, A.; Ahmad, F.; Ramzan Saeed Ashraf Janjua, M . Quantum chemical analysis and molecular dynamics simulations to study the impact of electron-deficient substituents on electronic behavior of small molecule acceptors . Comput. Theor. Chem. , 2021 . 1204 113387 DOI:10.1016/j.comptc.2021.113387http://doi.org/10.1016/j.comptc.2021.113387 .

浏览量

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

Inferring the Physics of Structural Evolution of Multicomponent Polymers via Machine-Learning-Accelerated Method

Data and Machine Learning in Polymer Science

Recent Advances in Bio-Inspired Versatile Polydopamine Platforms for “Smart” Cancer Photothermal Therapy

A Simple Building Block with Noncovalently Conformational Locks towards Constructing Low-Cost and High-Performance Nonfused Ring Electron Acceptors