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Prediction of vacancy formation energies at tungsten grain boundaries from local structure via machine learning method 期刊论文
JOURNAL OF NUCLEAR MATERIALS, 2022, 卷号: 559
作者:  Wang, Yuxuan;  Li, Xiaolin;  Li, Xiangyan;  Zhang, Yuxiang;  Zhang, Yange;  Xu, Yichun;  Lei, Yawei;  Liu, C. S.;  Wu, Xuebang
收藏  |  浏览/下载：35/0  |  提交时间：2022/12/23
Vacancy formation energy  Machine learning  Tungsten  Symmetry tilt grain boundary  Support vector machine  Cross validation  
Calibration and Data Quality Assurance Technical Advancements for Quantitative Remote Sensing in the DRAGON 4 Project 期刊论文
REMOTE SENSING, 2021, 卷号: 13
作者:  Ma, Lingling;  Zhao, Yongguang;  Li, Chuanrong;  Goryl, Philippe;  Liu, Cheng;  He, Jieying;  Wang, Pucai;  Bouvet, Marc;  Zhao, Ran;  Wang, Ning;  Liu, Yaokai;  Gao, Caixia;  Dils, Bart;  Zhang, Chengxin;  Chan, Ka Lok;  Wang, Xinhong
收藏  |  浏览/下载：43/0  |  提交时间：2022/02/14
calibration and validation  RadCalNet  microwave sensor  NO2 retrieval