Machine Learning Approaches for Predicting Power Conversion Efficiency in Organic Solar Cells: A Comprehensive Review DOI
Yang Jiang, Chuang Yao,

Yezi Yang

и другие.

Solar RRL, Год журнала: 2024, Номер unknown

Опубликована: Окт. 9, 2024

Organic solar cells (OSCs), renowned for their lightweight, cost efficiency, and adaptability nature, stand out as a promising option developing renewable energy. Improving the power conversion efficiency (PCE) of OSCs is essential, researchers are delving into novel materials to achieve this. Traditional approaches often laborious costly, highlighting need predictive modeling. Machine learning (ML), especially via quantitative structure–property relationship (QSPR) models, streamlining material development, with goal exceed 20% PCE. In this review, application ML in explored, recent studies utilizing PCE prediction reviewed, encompassing empirical functions, algorithms, self‐devised frameworks, combination automated experimental technologies. First, benefits predicting addressed. Second, development high‐efficiency models both fullerene nonfullerene acceptors delved into. The impact various algorithm on then assessed, taking account construction models. Moreover, quality databases selection descriptors considered. Databases based further categorized. Finally, prospects future proposed.

Язык: Английский

The prediction of donor number and acceptor number of electrolyte solvent molecules based on machine learning DOI

Huaping Hu,

Yuqing Shan,

Qiming Zhao

и другие.

Journal of Energy Chemistry, Год журнала: 2024, Номер 98, С. 374 - 382

Опубликована: Июль 6, 2024

Язык: Английский

Процитировано

14

Development of Organic Semiconductor Materials for Organic Solar Cells via the Integration of Computational Quantum Chemistry and AI-Powered Machine Learning DOI

Shafidah Shafian,

Faizus Salehin, Sojeong Lee

и другие.

ACS Applied Energy Materials, Год журнала: 2025, Номер unknown

Опубликована: Янв. 13, 2025

Язык: Английский

Процитировано

1

Multiscale computational analysis of the effect of end group modification on PM6:BTP-x OSCs performance DOI

Qingxing Wu,

Chongchen Xiang,

Guangjun Zhang

и другие.

Journal of Materials Chemistry C, Год журнала: 2024, Номер 12(34), С. 13311 - 13324

Опубликована: Янв. 1, 2024

Theoretical computational simulation are used to analyse the molecular stacking characteristics of PM6:BTP- x OSCs and role end group modifications.

Язык: Английский

Процитировано

7

Design and computational analysis of benzothiadiazole-fluorene based molecules for organic light-emitting diodes and high-efficiency organic solar cells DOI
Rchid Kacimi, R. Hayn, Ahmed Azaid

и другие.

Materials Science in Semiconductor Processing, Год журнала: 2025, Номер 190, С. 109356 - 109356

Опубликована: Янв. 30, 2025

Язык: Английский

Процитировано

1

Microstructural evolution, high temperature tensile deformation behavior, and deformation mechanism in an Mg–Zn–Y–Ca–Zr alloy processed by multidirectional forging and hot rolling DOI Creative Commons
Furong Cao, Renjie Liu,

Shuting Kong

и другие.

Journal of Materials Research and Technology, Год журнала: 2023, Номер 27, С. 6729 - 6743

Опубликована: Ноя. 1, 2023

To explore high temperature ductility, a new Mg-2.70Zn-1.34Y-0.37Ca-0.02Zr (wt.%) alloy has been fabricated by novel multidirectional forging (MDF) and hot rolling. The microstructure mechanical properties were investigated. average grain size of MDF + rolled is 10.89 ± 0.90 μm refined from the as-cast 60.03 0.72 μm. ultimate tensile strength 260.51 1.03 MPa, yield 192.29 1.21 elongation 17.83 % obtained at room temperature. For behavior, microstructural examination revealed that continuous dynamic recrystallization discontinuous are main softening mechanism in range 573–673 K, while growth with bimodal grains twins discovered 723 K this alloy. X-ray diffraction scanning electron microscopy –energy dispersive spectroscopy examinations constituent phases composed α-Mg solid solution intermetallic compounds Ca2Mg6Zn3, Mg3YZn6 (I-phase), Mg3Zn3Y2 (W-phase). evolution, such as desired temperatures, related to thermal stability phases. failure 215.4 was demonstrated 673 1.67 × 10−2 s−1, exhibiting strain rate quasi-superplasticity. A power-law constitutive equation established. deformation activation energy 177.948 kJ/mol stress exponent 4.494 dominant elevated temperatures 573–723 dislocation climb controlled lattice diffusion.

Язык: Английский

Процитировано

11

Designing Donors and Nonfullerene Acceptors for Organic Solar Cells Assisted by Machine Learning and Fragment‐Based Molecular Fingerprints DOI Open Access
Cai‐Rong Zhang, Rui Cao,

Xiao‐Meng Liu

и другие.

Solar RRL, Год журнала: 2025, Номер unknown

Опубликована: Янв. 13, 2025

The molecular structures and properties of donor acceptor materials for organic solar cells (OSCs) determine their photovoltaic performance; however, the complex relationship between them has hindered development OSC materials. To study this, we constructed database comprising 544 non‐fullerene pairs. Based on principle minimal rings units, each molecule in is cut into different fragments defined as a new fingerprint, where bit corresponds to fragment number molecule. Accordingly, fingerprint length 234 723 bits donors acceptors, respectively. Random forest extreme tree regression (ETR) are applied predict parameters, with ETR being most effective. Through SHapley Additive exPlanations (SHAP) importance analysis, eight (10) important (acceptor) identified. Furthermore, by computing similarities that obtained from SHAP similarity exceeding 0.6 collected order design molecules. By assembling fragments, designed 21 168 D‐ π ‐A‐ ‐type 1 156 400 A‐ ‐D‐ ‐A‐type nonfullerene generating 24 478 675 200 donor–acceptor predictions using trained model, highest power conversion efficiency reaches 13.2%.

Язык: Английский

Процитировано

0

Machine learning-aided algorithm for predicting spectral properties and cytotoxicity of BODIPY-appended platinum complexes DOI

Michael M. Lukanov,

Ksenia V. Ksenofontova,

Anastasia A. Kerner

и другие.

Optical Materials, Год журнала: 2025, Номер unknown, С. 116703 - 116703

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Transfer learning accelerated discovery of conjugated oligomers for advanced organic photovoltaics DOI Creative Commons
Siyan Deng,

J. Ng,

Shuzhou Li

и другие.

Molecular Systems Design & Engineering, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Transfer learning followed by density functional theory accelerates material discovery of conjugated oligomers for high-efficiency organic photovoltaic materials.

Язык: Английский

Процитировано

0

Effect of oxide diffusion barrier and substrate on the reliability of stainless-steel-based CIGS solar cells DOI
Hansung Kim,

Szymon P. Cias

Solar Energy Materials and Solar Cells, Год журнала: 2024, Номер 272, С. 112888 - 112888

Опубликована: Май 4, 2024

Язык: Английский

Процитировано

2

Substituting effect with end-capped groups on the photoelectric properties of non-fullerene acceptors for all-polymer solar cell DOI

Cong Shen,

Zifu Zang,

Peng Song

и другие.

Solar Energy, Год журнала: 2024, Номер 279, С. 112794 - 112794

Опубликована: Авг. 8, 2024

Язык: Английский

Процитировано

2