陆文聪

男， 上海大学理学院化学系， 教授/研究员/教授级高工或同等级别

学习/工作经历

教育经历
起止年月 毕业学校 所学专业 学历/学位
1997.7-2000.3 中科院上海冶金研究所 材料物理与化学 研究生/博士
1988.9-1991.2 上海科学技术大学 物理化学 研究生/硕士
1981.9-1986.7 清华大学 物理化学 本科生/学士
工作经历
起止年月 工作经历
1986.8-1988.8 上海科学技术大学，助教
1991.3-2000.2 上海（科学技术）大学，讲师（1992年起）、副教授（1996年起）
2002.3至今 上海大学，教授

研究领域和兴趣

计算机化学

主要业绩

现任中国化学会计算机化学专业委员会委员、《Advances in Manufacturing》SCI期刊副主编。曾获上海市优秀青年教师奖（1997年）、上海市育才奖（2002年、2004年）。长期从事基于机器学习/数据挖掘的材料设计和工业优化等研究工作，开发了材料数据挖掘在线计算平台（OCPMDM：http://materials-data-mining.com/ocpmdm/），为材料大数据的机器学习提供了在线计算方法和模型共享功能；开发了基于大数据挖掘的工业优化系统（BDMOS），利用化工生产大数据建立机器学习模型，用于产品质量和产量的优化控制。先后主持国家自然科学基金项目4项，国家重点研发计划课题1项，上海科委项目5项，企业合作项目20余项。目前在研上海市科委国际合作项目“基于数据挖掘的有机/无机杂化钙钛矿太阳能电池材料的高通量筛选”。已培养博士毕业生16名，硕士毕业生54名。已发表学术论文230余篇、研究专著3本，获得省部级科技奖4项，获得国家发明专利授权12项。

代表成果

1. Yang, Chen; Ren, Chang; Jia, Yuefei; Wang, Gang; Li, Minjie; Lu, Wencong, A machine learning-based alloy design system to facilitate the rational design of high entropy alloys with enhanced hardness. Acta Materialia 2022, 222: 117431.
2. Wei, Zhen; Li, Minjie; Lu, Wencong, Theoretical Study of High-Efficiency Organic Dyes with Different Electron-Withdrawing Groups Based on R6 toward Dye-Sensitized Solar Cells. Acta Physico-Chimica Sinica 2021, 37 (10): 1905084.
3. Su, Tianhao; Cui, Yaning; Lian, Zhengheng; Hu, Minglang; Li, Minjie; Lu, Wencong; Ren, Wei, Physics-Based Feature Makes Machine Learning Cognizing Crystal Properties Simple. Journal of Physical Chemistry Letters 2021, 12 (35), 8521-8527.
4. Chen, Huimin; Shang, Zhongwen; Lu, Wencong; Li, Minjie; Tan, Fuping, A Property-Driven Stepwise Design Strategy for Multiple Low-Melting Alloys via Machine Learning. Advanced Engineering Materials 2021: 2100612.
5. Li, Long; Tao, Qiuling; Xu, Pengcheng; Yang, Xue; Lu, Wencong; Li, MinJie, Studies on the regularity of perovskite formation via machine learning. Computational Materials Science 2021, 199: 110712.
6. Lu, Kailiang; Chang, Dongping; Ji, Xiaobo; Li, Minjie; Lu, Wencong, Machine Learning Aided Discovery of the Layered Double Hydroxides with the Largest Basal Spacing for Super-Capacitors. International Journal of Electrochemical Science 2021, 16 (11) : 211146.
7. Lu, Kailiang; Chang, Dongping; Lu, Tian; Ji, Xiaobo; Li, Minjie; Lu, Wencong, Machine Learning Model for High-Throughput Screening of Perovskite Manganites with the Highest Neel Temperature. Journal of Superconductivity and Novel Magnetism 2021, 34 (7), 1961-1969.
8. Lu, Tian; Li, Minjie; Yao, Zhenpeng; Lu, Wencong, Accelerated discovery of boron-dipyrromethene sensitizer for solar cells by integrating data mining and first principle. Journal of Materiomics 2021, 7 (4), 790-801.
9. Tao, Qiuling; Chang, Dongping; Lu, Tian; Li, Long; Chen, Huimin; Yang, Xue; Liu, Xiujuan; Li, Minjie; Lu, Wencong, Multiobjective Stepwise Design Strategy-Assisted Design of High-Performance Perovskite Oxide Photocatalysts. Journal of Physical Chemistry C 2021, 125 (38), 21141-21150.
10. Tao, Qiuling; Lu, Tian; Sheng, Ye; Li, Long; Lu, Wencong; Li, Minjie, Machine learning aided design of perovskite oxide materials for photocatalytic water splitting. Journal of Energy Chemistry 2021, 60, 351-359.
11. Tao, Qiuling; Xu, Pengcheng; Li, Minjie; Lu, Wencong, Machine learning for perovskite materials design and discovery. Npj Computational Materials 2021, 7 (1) : 23.
12. Wang, Xiangdong; Xu, Pengcheng; Lu, Tian; Liu, Xiujuan; Lu, Wencong, Inverse Design of Ternary Gold Alloy Materials with Low Resistivity. Materials China 2021, 40 (4), 251-256.
13. Xu, Pengcheng; Chang, Dongping; Lu, Tian; Li, Long; Li, Minjie; Lu, Wencong, Search for ABO3 Type Ferroelectric Perovskites with Targeted Multi-Properties by Machine Learning Strategies. Journal of chemical information and modeling 2021: 10.1021/acs.jcim.1c00566.
14. Xu, Pengcheng; Lu, Tian; Ju, Lifei; Tian, Lumin; Li, Minjie; Lu, Wencong, Machine Learning Aided Design of Polymer with Targeted Band Gap Based on DFT Computation. Journal of Physical Chemistry B 2021, 125 (2), 601-611.
15. Yang, Xue; Li, Long; Tao, Qiuling; Lu, Wencong; Li, Minjie, Rapid discovery of narrow bandgap oxide double perovskites using machine learning. Computational Materials Science 2021, 196: 110528.
16. Zhang, Shilin; Lu, Tian; Xu, Pengcheng; Tao, Qiuling; Li, Minjie; Lu, Wencong, Predicting the Formability of Hybrid Organic-Inorganic Perovskites via an Interpretable Machine Learning Strategy. Journal of Physical Chemistry Letters 2021, 12 (31), 7423-7430.
17. Zhao, Juanjuan; Xu, Pengcheng; Liu, Xiujuan; Ji, Xiaobo; Li, Minjie; Dev, Sooranna; Qu, Xiaosheng; Lu, Wencong; Niu, Bing, Application of machine learning methods for the development of antidiabetic drugs. Current pharmaceutical design 2021: 10.2174/1381612827666210622104428.
18. Lifei Ju, Minjie Li, Lumin Tian, Pengcheng Xu, Wencong Lu. Accelerated discovery of high-efficient N-annulated perylene organic sensitizers for solar cells via machine learning and quantum chemistry. Mater. Today Comm. 2020, 25, 101604:1-9.
19. Yueyue Shao, Zhen Wei, Mejia-Mendoza M. Luis, Tian Lu, Minjie Li, Wencong Lu, First-principles screening and design of C275-based organic dyes for highly efficient dye-sensitized solar cells. Solar Energy, 2020, 207, 759-766.
20. Xu Yongxin, Xu Xiao, Li Minjie, Lu Wencong, Prediction of photoelectric properties, especially power conversion efficiency of cells, of IQ1 and derivative dyes in high-efficiency dye-sensitized solar cells, Solar Energy. 2020, 195: 82-88.
21. Sheng Ye, Li Minjie, Flores-Leonar Martha M., Lu Wencong, Yang Jiong, Hu Yanni, Rational design of SM315-based porphyrin sensitizers for highly efficient dye-sensitized solar cells: A theoretical study, Journal of Molecular Structure. 2020, 1205: 127567.

*以上信息由高级会员个人更新和维护。