Papers citing Machine learning–assisted molecular design and efficiency prediction for high-performance organic photovoltaic materials
Accurate, affordable, and generalizable machine learning simulations of transition metal x-ray absorption spectra using the XANESNET deep neural network
The Journal of Chemical Physics · 2022
Conor D. Rankine, Thomas J. Penfold
Read original paper ↗ ·Computational chemistry advances on benzodithiophene-based organic photovoltaic materials
Critical reviews in solid state and materials sciences/CRC critical reviews in solid state and materials sciences · 2022
Felipe A. Angel, María Belén Camarada, Ignacio A. Jessop
Read original paper ↗ ·Interpretable Machine Learning for Investigating Photoelectrochemical Properties of Cosensitizer-Based CH3NH3PbI3/TiO2 Films in Water
The Journal of Physical Chemistry C · 2022
Lei Zhang, Wenguang Hu, Mu He, Kun Xu, Zhengwei Pan
Read original paper ↗ ·Lossless multi-scale constitutive elastic relations with artificial intelligence
npj Computational Materials · 2022
Jaber Rezaei Mianroodi, Shahed Rezaei, Nima Hamidi Siboni, Bai‐Xiang Xu, Dierk Raabe
Read original paper ↗ ·Organic Photovoltaic Efficiency Predictor: Data-Driven Models for Non-Fullerene Acceptor Organic Solar Cells
The Journal of Physical Chemistry Letters · 2022
Brianna L. Greenstein, Geoffrey Hutchison
Read original paper ↗ ·Experimental search for high-performance ferroelectric tunnel junctions guided by machine learning
Journal of Advanced Dielectrics · 2022
Jingjing Rao, Zhen Hong Fan, Qicheng Huang, Yongjian Luo, Xingmin Zhang, Haizhong Guo, Xiaobing Yan, Guo Tian, Deyang Chen, Zhipeng Hou, Minghui Qin, Min Zeng, Xubing Lu, Guofu Zhou, Xingsen Gao, Jun‐Ming Liu
Read original paper ↗ ·A combined clustering/symbolic regression framework for fluid property prediction
Physics of Fluids · 2022
Filippos D. Sofos, Avraam Charakopoulos, Konstantinos Papastamatiou, Theodoros E. Karakasidis
Read original paper ↗ ·Recent Trends and Future Prospects of Materials and Process Informatics
Seikei-Kakou · 2022
Shun Muroga
Read original paper ↗ ·Material machine learning for alloys: Applications, challenges and perspectives
Journal of Alloys and Compounds · 2022
Xiujuan Liu, Pengcheng Xu, Juanjuan Zhao, Wencong Lu, Minjie Li, Gang Wang
Read original paper ↗ ·A transfer learning approach for reaction discovery in small data situations using generative model
iScience · 2022
Sukriti Singh, Raghavan B. Sunoj
Read original paper ↗ ·An emerging machine learning strategy for electrochemical sensor and supercapacitor using carbonized metal–organic framework
Journal of Electroanalytical Chemistry · 2022
Xinyu Lu, Peng Liu, Krishna Bisetty, Yue Cai, Xuemin Duan, Yangping Wen, Yifu Zhu, Liangmei Rao, Quan Xu, Jingkun Xu
Read original paper ↗ ·Deep Learning for Additive Screening in Perovskite Light‐Emitting Diodes
Angewandte Chemie · 2022
Liang Zhang, Na Li, Dawei Liu, Guanhong Tao, Weidong Xu, Mengmeng Li, Ying Chu, Chensi Cao, Feiyue Lu, Chenjie Hao, Ju Zhang, Yu Lian Cao, Feng Gao, Nana Wang, Lin Sen Zhu, Wei Huang, Jianpu Wang
Read original paper ↗ ·Deep Learning for Additive Screening in Perovskite Light‐Emitting Diodes
Angewandte Chemie International Edition · 2022
Liang Zhang, Na Li, Dawei Liu, Guanhong Tao, Weidong Xu, Mengmeng Li, Ying Chu, Chensi Cao, Feiyue Lu, Chenjie Hao, Ju Zhang, Yu Lian Cao, Feng Gao, Nana Wang, Lin Sen Zhu, Wei Huang, Jianpu Wang
Read original paper ↗ ·Machine learning enables interpretable discovery of innovative polymers for gas separation membranes
Science Advances · 2022
Jason Yang, Lei Tao, Jinlong He, Jeffrey R. McCutcheon, Ying Li
Read original paper ↗ ·A Generative Approach to Materials Discovery, Design, and Optimization
ACS Omega · 2022
Dhruv Menon, Raghavan Ranganathan
Read original paper ↗ ·Computational Workflow for Accelerated Molecular Design Using Quantum Chemical Simulations and Deep Learning Models
ChemRxiv · 2022
Andrew Blanchard, Pei Zhang, Debsindhu Bhowmik, Kshitij Mehta, John P. Gounley, Samuel Temple Reeve, Stephan Irle, Massimiliano Lupo Pasini
Read original paper ↗ ·VLA-SMILES: Variable-Length-Array SMILES Descriptors in Neural Network-Based QSAR Modeling
Machine Learning and Knowledge Extraction · 2022
Antonina L. Nazarova, Aiichiro Nakano
Read original paper ↗ ·Computational Workflow for Accelerated Molecular Design Using Quantum Chemical Simulations and Deep Learning Models
ChemRxiv · 2022
Andrew Blanchard, Pei Zhang, Debsindhu Bhowmik, Kshitij Mehta, John P. Gounley, Samuel Temple Reeve, Stephan Irle, Massimiliano Lupo Pasini
Read original paper ↗ ·Heterogeneous catalysis mediated by light, electricity and enzyme via machine learning: Paradigms, applications and prospects
Chemosphere · 2022
Wentao Zhang, Wenguang Huang, Jie Tan, Qingwei Guo, Bingdang Wu
Read original paper ↗ ·Rapid calculation of internal conversion and intersystem crossing rate for organic materials discovery
The Journal of Chemical Physics · 2022
Lei Shi, Xiaoyu Xie, Alessandro Troisi
Read original paper ↗ ·Bond Energy Assists Accurate Molecule Property Prediction
Journal of Physics Conference Series · 2022
Xiaoting Yang, Wenjie Du
Read original paper ↗ ·The Electrical Conductivity of Ionic Liquids: Numerical and Analytical Machine Learning Approaches
Fluids · 2022
Theodoros E. Karakasidis, Filippos D. Sofos, Christos Tsonos
Read original paper ↗ ·Deep Learning-Based Layer Identification of 2D Nanomaterials
Coatings · 2022
Yu Zhang, Heng Zhang, Shujuan Zhou, Guangjie Liu, Jinlong Zhu
Read original paper ↗ ·Machine learning assisted prediction of charge transfer properties in organic solar cells by using morphology-related descriptors
Nano Research · 2022
Lulu Fu, Haixia Hu, Qiang Zhu, Lifeng Zheng, Yuming Gu, Yaping Wen, Haibo Ma, Hang Yin, Jing Ma
Read original paper ↗ ·Machine learning for a sustainable energy future
Nature Reviews Materials · 2022
Zhenpeng Yao, Yanwei Lum, Andrew K. Johnston, L.M. Mejía-Mendoza, Xin Zhou, Yonggang Wen, Alán Aspuru‐Guzik, Edward Hartley Sargent, Zhi Wei Seh
Read original paper ↗ ·Benzothiadiazole-based push-pull copolymers – Balancing synthetic complexity against organic solar cell efficiency
Organic Electronics · 2022
Kaat Valkeneers, Koen Vandewal, Wouter Maes
Read original paper ↗ ·Deciphering the Role of Side‐Chain Engineering and Solvent Vapor Annealing for Binary All‐Small‐Molecule Organic Solar Cells
Advanced Functional Materials · 2022
Tongle Xu, Jie Lv, Zhanxiang Chen, Zhenghui Luo, Guangye Zhang, Heng Liu, Hui Huang, Dingqin Hu, Xinhui Lu, Shirong Lu, Chuluo Yang
Read original paper ↗ ·Modeling, optimization and understanding of adsorption process for pollutant removal via machine learning: Recent progress and future perspectives
Chemosphere · 2022
Wentao Zhang, Wenguang Huang, Jie Tan, Dawei Huang, Jun Ma, Bingdang Wu
Read original paper ↗ ·CIMG-BERT: Pretraining Bidirectional Transformers with Chemistry Knowledge for Molecular Property Prediction
International Conference on Electronic Information Technology and Smart Agriculture (ICEITSA) · 2022
Xin Meng, Bing-Lan Wu, Yilei Liang, Chenkai Gu, Wenjie Du, Xin Chen
Read original paper ↗ ·Active Discovery of Donor:Acceptor Combinations For Efficient Organic Solar Cells
ACS Applied Materials & Interfaces · 2022
Prateek Malhotra, Juan C. Verduzco, Subhayan Biswas, Ganesh Datt Sharma
Read original paper ↗ ·Novel structural feature-descriptor platform for machine learning to accelerate the development of organic photovoltaics
Nano Energy · 2022
Gyu‐Hee Kim, Chihyung Lee, Kyung‐Soo Kim, Doo‐Hyun Ko
Read original paper ↗ ·A computational method for the load spectra of large-scale structures with a data-driven learning algorithm
Science China Technological Sciences · 2022
XianJia Chen, Zheng Yuan, Qiang Li, Shouguang Sun, Yujie Wei
Read original paper ↗ ·Crystal structural prediction of perovskite materials using machine learning: A comparative study
Solid State Communications · 2022
Rojalina Priyadarshini, Hillol Joardar, Sukant Kishoro Bisoy, Tanmaya Badapanda
Read original paper ↗ ·Machine learning framework for the analysis and prediction of energy loss for non-fullerene organic solar cells
Solar Energy · 2022
Rakesh Suthar, T. Abhijith, Punit Kumar Sharma, Supravat Karak
Read original paper ↗ ·A polymer genome approach for rational design of poly(aryl ether)s with high glass transition temperature
Journal of Materials Chemistry A · 2023
Ce Song, Hongjian Gu, Linyan Zhu, Wanyuan Jiang, Zhihuan Weng, Lishuai Zong, Cheng Liu, Fangyuan Hu, Yuxi Pan, Xigao Jian
Read original paper ↗ ·An Introduction to Machine Learning in Molecular Sciences
Challenges and advances in computational chemistry and physics · 2023
Hanchao Liu, Chen Qu
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
Hengzhe Wang, Lichao Peng, Li Chang, Zixin Li, Yanhui Guo, Qian Li, Xiaohui Yang
Read original paper ↗ ·Design of polyimides with targeted glass transition temperature using a graph neural network
Journal of Materials Chemistry C · 2023
Haoke Qiu, Xuepeng Qiu, Xuemin Dai, Zhao‐Yan Sun
Read original paper ↗ ·Machine Learning Application In Modeling Organic Pollutant Adsorption on Carbonaceous Materials: A Comprehensive Review with Statistical Insights
SSRN Electronic Journal · 2023
Zichu Wang, Jianwei Yu, Qi Wang, Fan Yang, Chunmiao Wang, Min Yang
Read original paper ↗ ·Machine learning assisted identification of the matched energy level of materials for high open circuit voltage in binary organic solar cells
Molecular Systems Design & Engineering · 2023
Kuo Wang, Chaorong Guo, Zhennan Li, Rui Zhang, Zhimin Feng, Gengkun Fang, Di Huang, Jiaojiao Liang, Ling Zhao, Zicha Li
Read original paper ↗ ·Machine learning in energy chemistry: introduction, challenges and perspectives
Energy Advances · 2023
Yuzhi Xu, Jiankai Ge, Cheng‐Wei Ju
Read original paper ↗ ·Machine learning integrated photocatalysis: progress and challenges
Chemical Communications · 2023
Luyao Ge, Yuanzhen Ke, Xiaobo Li
Read original paper ↗ ·Solar Cells and Relevant Machine Learning
Springer eBooks · 2023
Muhammad Abdul Basit, Muhammad Aanish Ali, Mamoona Yasmeen
Read original paper ↗ ·Uncovering novel liquid organic hydrogen carriers: a systematic exploration of chemical compound space using cheminformatics and quantum chemical methods
Digital Discovery · 2023
Hassan Harb, Sarah N. Elliott, Logan T. Ward, Ian T Foster, Stephen J. Klippenstein, Larry A. Curtiss, Rajeev S. Assary
Read original paper ↗ ·Computational Design and Manufacturing of Sustainable Materials through First-Principles and Materiomics
Chemical Reviews · 2023
Sabrina Chin-yun Shen, Eesha Khare, Nic Lee, Michael K. Saad, David Lee Kaplan, Markus J. Buehler
Read original paper ↗ ·Machine learning modeling for the prediction of plastic properties in metallic glasses
Scientific Reports · 2023
Nicolás Amigó, Simón Palominos, Felipe J. Valencia
Read original paper ↗ ·Machine‐Learning‐Assisted Nanozyme Design: Lessons from Materials and Engineered Enzymes
Advanced Materials · 2023
Jie Zhuang, Adam C. Midgley, Yonghua Wei, Qiqi Liu, Deling Kong, Xinglu Huang
Read original paper ↗ ·Unveiling the complex structure-property correlation of defects in 2D materials based on high throughput datasets
npj 2D Materials and Applications · 2023
Pengru Huang, Ruslan Yu. Lukin, Maxim Faleev, N. Kazeev, Abdalaziz Rashid Al-Maeeni, Daria V. Andreeva, A. Ustyuzhanin, Alexander G. Tormasov, A. H. Castro Neto, Kostya S. Novoselov
Read original paper ↗ ·Machine Learning for Perovskite Solar Cells and Component Materials: Key Technologies and Prospects
Advanced Functional Materials · 2023
Yiming Liu, Xinyu Tan, Jie Liang, Hongwei Han, Peng Xiang, Wensheng Yan
Read original paper ↗ ·Machine-Learning-Assisted Screening of Interface Passivation Materials for Perovskite Solar Cells
ACS Energy Letters · 2023
Chongyang Zhi, Suo Wang, Shijing Sun, Zhen Li, Zhihao Li, Zhihao Li, Zhi Jian Wan, Hongqiang Wang, Zhen Li, Zhen Li, Zhe Liu
Read original paper ↗ ·