Machine learning in materials science
Jing Wei(Beijing University of Posts and Telecommunications), Ming Lei(Shenyang Ligong University), Ji-Gen Chen(Taizhou University), Hui‐Xiong Deng(Institute of Semiconductors), Xiangyu Sun(Beijing University of Posts and Telecommunications), Xuan Chu(Beijing University of Posts and Telecommunications), Zhongming Wei(Institute of Semiconductors), Kun Xu(Beijing University of Posts and Telecommunications)
Cited by 999
Related Papers
Initializing film homogeneity to retard phase segregation for stable perovskite solar cells
|Science|2022|285
Efficient spectrum prediction and inverse design for plasmonic waveguide systems based on artificial neural networks
|Photonics Research|2019|166
Deep-FSMN for Large Vocabulary Continuous Speech Recognition
|Unknown|2018|128
A Steel Surface Defect Recognition Algorithm Based on Improved Deep Learning Network Model Using Feature Visualization and Quality Evaluation
|IEEE Access|2020|76
Identification of technology development trends based on subject–action–object analysis: The case of dye-sensitized solar cells
|Technological Forecasting and Social Change|2015|71