Papers citing Machine learning for accelerating the discovery of high-performance donor/acceptor pairs in non-fullerene organic solar cells
Novel structural feature-descriptor platform for machine learning to accelerate the development of organic photovoltaics
Nano Energy · 2022-12-14
Gyu‐Hee Kim, Chihyung Lee, Kyung‐Soo Kim, Doo‐Hyun Ko
Read original paper ↗ ·Machine learning framework for the analysis and prediction of energy loss for non-fullerene organic solar cells
Solar Energy · 2022-12-30
Rakesh Suthar, T. Abhijith, Punit Kumar Sharma, Supravat Karak
Read original paper ↗ ·CatBoost-Based Framework for Intelligent Prediction and Reaction Condition Analysis of Coupling Reaction
match Communications in Mathematical and in Computer Chemistry · 2023-01-01
Hengzhe Wang, Lichao Peng, Li Chang, Zixin Li, Yanhui Guo, Qian Li, Xiaohui Yang
Read original paper ↗ ·High-Performance Solar Cells by Machine Learning and Pareto Optimality
Springer eBooks · 2023-01-01
Giovanni Nastasi, Vittorio Romano, Giuseppe Nicosia
Read original paper ↗ ·Machine Learning for Next‐Generation Functional Materials
Springer eBooks · 2023-01-01
R. Vignesh, V. Balasubramani, T. M. Sridhar
Read original paper ↗ ·The Rise of Machine Learning in Polymer Discovery
Advanced Intelligent Systems · 2023-01-31
Cheng Yan, Guoqiang Li
Read original paper ↗ ·Virtual screening of efficient building blocks and designing of new polymers for organic solar cells
Journal of Physics and Chemistry of Solids · 2023-03-22
Fatimah Mohammed A. Alzahrani, Muhammad Saqib, Maria Arooj, Tayyaba Mubashir, Mudassir Hussain Tahir, Ziyad Awadh Alrowaili, Mohammed Sultan Al-Buriahi
Read original paper ↗ ·Screening Efficient Tandem Organic Solar Cells with Machine Learning and Genetic Algorithms
The Journal of Physical Chemistry C · 2023-03-28
Brianna L. Greenstein, Geoffrey Hutchison
Read original paper ↗ ·Prediction of large magnetic moment materials with graph neural networks and random forests
Physical Review Materials · 2023-04-14
Sékou-Oumar Kaba, Benjamin Groleau-Paré, Marc-Antoine Gauthier, A.–M. S. Tremblay, Simon Verret, C. Gauvin-Ndiaye
Read original paper ↗ ·Quantum Chemistry–Machine Learning Approach for Predicting Properties of Lewis Acid–Lewis Base Adducts
ACS Omega · 2023-05-19
Hieu Huynh, Thomas J. Kelly, Linh Vu, Tung Hoang, Phuc An Nguyen, Tu C. Le, Emily Jarvis, Hung Phan
Read original paper ↗ ·Interpretable machine-learning for predicting power conversion efficiency of non-halogenated green solvent-processed organic solar cells based on Hansen solubility parameters and molecular weights of polymers
Solar Energy · 2023-06-12
Min‐Hsuan Lee
Read original paper ↗ ·Machine Learning Assisted Analysis, Prediction, and Fabrication of High‐Efficiency CZTSSe Thin Film Solar Cells
Advanced Functional Materials · 2023-06-20
Vijay Chandrakant Karade, Santosh Shashikant Sutar, Seung Wook Shin, Mahesh P. Suryawanshi, Jun Sung Jang, Kuldeep Singh Gour, Rajanish K. Kamat, Jae Ho Yun, Tukaram Dattatray Dongale, Jin Hyeok Kim
Read original paper ↗ ·Data-driven approaches enabling the screening and design of promising materials for energy storage batteries
Scientia Sinica Technologica · 2023-06-28
Qi ZHANG, Chao Peng, Dongfeng Xue
Read original paper ↗ ·Directed Message Passing Neural Network for Predicting Power Conversion Efficiency in Organic Solar Cells
ACS Applied Materials & Interfaces · 2023-07-25
Prateek Malhotra, Subhayan Biswas, Ganesh Datt Sharma
Read original paper ↗ ·Predicting the multiple parameters of organic acceptors through machine learning using RDkit descriptors: An easy and fast pipeline
International Journal of Quantum Chemistry · 2023-08-25
Khadijah Mohammedsaleh Katubi, Muhammad Saqib, Tayyaba Mubashir, Mudassir Hussain Tahir, Mohamed Ibrahim Halawa, Alveena Akbar, Beriham Ibrahim Basha, Muhammad Sulaman, Ziyad Awadh Alrowaili, Mohammed Sultan Al-Buriahi
Read original paper ↗ ·Predicting the anion conductivities and alkaline stabilities of anion conducting membrane polymeric materials: development of explainable machine learning models
Science and Technology of Advanced Materials · 2023-10-03
Yin Kan Phua, Tsuyohiko Fujigaya, Koichiro Kato
Read original paper ↗ ·Machine learning-assisted performance prediction and molecular design of all-small-molecule organic solar cells based on the Y6 acceptor
Solar Energy · 2023-10-16
Qiming Zhao, Yuqing Shan, Hu Zhou, Guangjun Zhang, Wanqiang Liu
Read original paper ↗ ·Machine learning study on organic solar cells and virtual screening of designed non-fullerene acceptors
Journal of Applied Physics · 2023-10-20
Cai‐Rong Zhang, Ming Li, Miao Zhao, Ji-Jun Gong, Xiaomeng Liu, Yuhong Chen, Zi‐Jiang Liu, Youzhi Wu, Hongshan Chen
Read original paper ↗ ·Efficient screening framework for organic solar cells with deep learning and ensemble learning
npj Computational Materials · 2023-10-23
Hongshuai Wang, Jie Feng, Zhihao Dong, Lujie Jin, Miaomiao Li, Jianyu Yuan, Youyong Li
Read original paper ↗ ·Electrochemical Sensor to Detect Antibiotics in Milk Based on Machine Learning Algorithms
ACS Applied Materials & Interfaces · 2023-10-24
Timur A. Aliev, Vadim E. Belyaev, Anastasiya V. Pomytkina, Pavel V. Nesterov, Sergey Shityakov, R. V. Sadovnichii, Alexander S. Novikov, Olga Yu. Orlova, Maria Sergeevna Masalovich, Екатерина Владимировна Скорб
Read original paper ↗ ·Unraveling the Effect of Compositional Ratios on the Kesterite Thin-Film Solar Cells Using Machine Learning Techniques
Crystals · 2023-11-12
Vijay Chandrakant Karade, Santosh Shashikant Sutar, Jun Hwan Jang, Kuldeep Singh Gour, Seung Koo Shin, Mahesh P. Suryawanshi, Rajanish K. Kamat, Tukaram Dattatray Dongale, Jin Kim, Jae Sung Yun
Read original paper ↗ ·Predicting and analyzing the fill factor of non-fullerene organic solar cells based on material properties and interpretable machine-learning strategies
Solar Energy · 2023-12-01
Min‐Hsuan Lee
Read original paper ↗ ·Multicrystalline Informatics Applied to Multicrystalline Silicon for Unraveling the Microscopic Root Cause of Dislocation Generation
Advanced Materials · 2023-12-02
Kenta Yamakoshi, Yutaka Ohno, Kentaro Kutsukake, Takuto Kojima, Tatsuya Yokoi, 秀人 吉田, Hiroyuki Tanaka, Xin Liu, Hiroaki Kudo, Noritaka Usami
Read original paper ↗ ·Ground-State Orbital Analysis Predicts S 1 Charge Transfer in Donor–Acceptor Materials
The Journal of Physical Chemistry Letters · 2023-12-04
Ali Abou Taka, John M. Herbert, Laura M. McCaslin
Read original paper ↗ ·Investigation of the open-circuit voltage of non-fullerene acceptors-based ternary organic solar cells based on interpretable machine-learning approach and chemically inspired descriptors
Journal of Photochemistry and Photobiology A Chemistry · 2023-12-26
Min‐Hsuan Lee
Read original paper ↗ ·Accelerating the generation and discovery of high-performance donor materials for organic solar cells by deep learning
Journal of Materials Chemistry A · 2024-01-01
Jinyu Sun, Dongxu Li, Yue Wang, Ting Xie, Yingping Zou, Hongmei Lü, Zhimin Zhang
Read original paper ↗ ·Beyond molecular structure: critically assessing machine learning for designing organic photovoltaic materials and devices
Journal of Materials Chemistry A · 2024-01-01
Martin T. Seifrid, Stanley Lo, Dylan G. Choi, Gary Tom, My Linh Le, Kunyu Li, Rahul Sankar, Hoai‐Thanh Vuong, Hiba Wakidi, Ahra Yi, Ziyue Zhu, Nora Schopp, Aaron Peng, Benjamin R. Luginbuhl, Thuc‐Quyen Nguyen, Alán Aspuru‐Guzik
Read original paper ↗ ·Design and virtual screening of donor and non-fullerene acceptor for organic solar cells using long short-term memory model
Journal of Materials Chemistry A · 2024-01-01
Long-Fei Lv, Cai‐Rong Zhang, Rui Cao, Xiaomeng Liu, Meiling Zhang, Ji-Jun Gong, Zi‐Jiang Liu, You-Zhi Wu, Hong-Shan Chen
Read original paper ↗ ·Machine learning in the era of smart automation for renewable energy materials
e-Prime - Advances in Electrical Engineering Electronics and Energy · 2024-02-06
B. Hemavathi, Vidya G, Vaibhav, Kurupalya Shivram Anantharaju, Ranjith Krishna Pai
Read original paper ↗ ·Photovoltaic conversion of organic photovoltaic materials based on molecular fingerprint feature engineering
International Conference on Optoelectronic Materials and Devices (ICOMD) · 2024-02-08
Hongjie Chen, Xuanyu Zhang, Zengyuan Chen
Read original paper ↗ ·A bibliometric analysis of machine learning techniques in photovoltaic cells and solar energy (2014–2022)
Energy Reports · 2024-02-22
Abdelhamid Taieb Zaidi
Read original paper ↗ ·Data Cleansing and Sub‐Unit‐Based Molecular Description Enable Accurate Prediction of The Energy Levels of Non‐Fullerene Acceptors Used in Organic Solar Cells
Advanced Science · 2024-02-22
Ting Zhang, Joshua Yuk Lin Lai, Mingzhe Shi, Qing Li, Chen Zhang, He Yan
Read original paper ↗ ·Machine Learning Study on the Virtual Screening of Donor–Acceptor Pairs for Organic Solar Cells
physica status solidi (a) · 2024-03-11
Ming Li, Cai‐Rong Zhang, Meiling Zhang, Ji-Jun Gong, Xiao‐Meng Liu, Yuhong Chen, Zi‐Jiang Liu, Youzhi Wu, Hongshan Chen
Read original paper ↗ ·Machine Learning for Screening Small Molecules as Passivation Materials for Enhanced Perovskite Solar Cells
Advanced Functional Materials · 2024-03-27
Xin Zhang, Bin Ding, Yao Wang, Yan Liu, Gao Zhang, Lirong Zeng, Lijun Yang, Chang‐Jiu Li, Guan‐Jun Yang, Mohammad Khaja Nazeeruddin, Bo Chen
Read original paper ↗ ·High Glass Transition Temperature Fluorinated Polymers Based on Transfer Learning with Small Experimental Data
Macromolecular Rapid Communications · 2024-05-25
Jin‐Hoon Yang, Jiyoung Lee, Hajin Kwon, Eun‐Ho Sohn, Hyunju Chang, Seunghun Jang
Read original paper ↗ ·Multicomponent organic blend systems: A review of quaternary organic photovoltaics
Carbon Energy · 2024-06-24
Kekeli N’Konou, Souk Yoon Kim, Nutifafa Yao Doumon
Read original paper ↗ ·A systematic approach to generate polymer library: A search for polymers with high dipole moment
Chemical Physics Letters · 2024-06-27
Khadijah Mohammedsaleh Katubi, Syed Shoaib Ahmad Shah, Sumaira Naeem, Tayyaba Najam, Ziyad Awadh Alrowaili, Mohammed Sultan Al-Buriahi
Read original paper ↗ ·Explainable Prediction of Hydrophilic/Hydrophobic Property of Polymer Brush Surfaces by Chemical Modeling and Machine Learning
The Journal of Physical Chemistry B · 2024-07-01
Shiwei Su, Tsukuru Masuda, Madoka Takai
Read original paper ↗ ·The mastery of details in the workflow of materials machine learning
npj Computational Materials · 2024-07-02
Yingying Ma, Pengcheng Xu, Minjie Li, Xiaobo Ji, Wenyue Zhao, Wencong Lu
Read original paper ↗ ·Predicting Emission Wavelengths in Benzobisoxazole-Based OLEDs with Gradient Boosted Ensemble Models
The Journal of Physical Chemistry A · 2024-07-15
Shambhavi Tannir, Yuning Pan, Nathaniel Josephs, Christopher Cunningham, Nathaniel Hendrick, Annie Beckett, James Halley McNeely, Aaron B. Beeler, Malika Jeffries‐EL, Eric D. Kolaczyk
Read original paper ↗ ·Interpretable AI and Machine Learning Classification for Identifying High-Efficiency Donor–Acceptor Pairs in Organic Solar Cells
ACS Omega · 2024-07-31
Hamza Siddiqui, Tahsin Usmani
Read original paper ↗ ·Accelerating the discovery of acceptor materials for organic solar cells by deep learning
npj Computational Materials · 2024-08-14
Jinyu Sun, Dongxu Li, Jie Zou, Shaofeng Zhu, Cong Xu, Yingping Zou, Zhimin Zhang, Hongmei Lü
Read original paper ↗ ·A review on machine learning-guided design of energy materials
Progress in Energy · 2024-08-21
Seongmin Kim, Jiaxin Xu, Wenjie Shang, Zhihao Xu, Eungkyu Lee, Tengfei Luo
Read original paper ↗ ·Progress of organic photovoltaics towards 20% efficiency
Nature Reviews Electrical Engineering · 2024-08-21
Lei Zhu, Ming Zhang, Zichun Zhou, Wenkai Zhong, Tianyu Hao, Shengjie Xu, Rui Zeng, Jiaxing Zhuang, Xiaonan Xue, Jing Hao, Yongming Zhang, Feng Liu
Read original paper ↗ ·Modeling of stable and novel organic materials for high efficiency opv cells
Unknown journal · 2024-09-09
Giovana Miti Aibara Paschoal
Read original paper ↗ ·Construction frontier molecular orbital prediction model with transfer learning for organic materials
npj Computational Materials · 2024-09-11
Xinyu Peng, Jiaojiao Liang, Kuo Wang, Xiaojie Zhao, Zhiyan Peng, Zhennan Li, Jinhui Zeng, Lan Xia Zheng, Min Lei, Di Huang
Read original paper ↗ ·Design of experiments with the support of machine learning for process parameter optimization of all‐small‐molecule organic solar cells
FlexMat. · 2024-09-24
Kuo Wang, Jiaojiao Liang, Zhennan Li, Haixin Zhou, Cong Nie, Jiahao Deng, Xiaojie Zhao, Xinyu Peng, Ziye Chen, Zhiyan Peng, Di Huang, Hun Soo Jang, Jaemin Kong, Yingping Zou
Read original paper ↗ ·Machine learning-based design of electrocatalytic materials towards high-energy lithium||sulfur batteries development
Nature Communications · 2024-09-29
Zhiyuan Han, An Chen, Zejian Li, Mengtian Zhang, Zhilong Wang, Lixue Yang, Runhua Gao, Yeyang Jia, Guanjun Ji, Zhoujie Lao, Xiao Xiao, Kehao Tao, Jing Gao, Wei Zhong Lv, Tianshuai Wang, Jinjin Li, Guangmin Zhou
Read original paper ↗ ·Predictive Modeling and Design of Organic Solar Cells: A Data-Driven Approach for Material Innovation
ACS Applied Energy Materials · 2024-10-07
Bibhas Das, Anirban Mondal
Read original paper ↗ ·Machine Learning Approaches for Predicting Power Conversion Efficiency in Organic Solar Cells: A Comprehensive Review
Solar RRL · 2024-10-09
Yang Jiang, Chuang Yao, Yezi Yang, Jinshan Wang
Read original paper ↗ ·