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Citation: Qian Peng, Pengfei Yao, Zicong Wang, Xiufang Xu, Hongwei Sun. Promote the Training of Top Talents by Optimizing the Theoretical Computational Chemistry Curriculum System[J]. University Chemistry, ;2025, 40(5): 261-267. doi: 10.12461/PKU.DXHX202408012 shu

Promote the Training of Top Talents by Optimizing the Theoretical Computational Chemistry Curriculum System

Qian Peng ^1,, ,
Pengfei Yao ^1,2 ,
Zicong Wang ¹ ,
Xiufang Xu ¹ ,
Hongwei Sun ¹

1.
College of Chemistry, Nankai University, Tianjin 300071, China;
2.
Baise University, Baise 533000, Guangxi Zhuang Autonomous Region, China

Corresponding author: Qian Peng, qpeng@nankai.edu.cn
Received Date: 10 August 2024
Revised Date: 6 September 2024

Recognizing the significant role of theoretical computational chemistry in advancing chemistry and related fields, the chemistry teaching team in Nankai University has developed a training model as part of the “Pilot Plan for Cultivating Top Students in Basic Disciplines”. This model centers around an “Introduction to Computational Chemistry” course, integrating theory, practice, and cutting-edge research to enhance the cultivation of top talents. Over four years of teaching practice, the team has explored and refined aspects of training modes, curriculum design, and interdisciplinary integration. Student feedback data indicates that this optimized curriculum system significantly fosters the development of outstanding talent in the field.
- Top-notch talent training,
- Theoretical computational chemistry,
- Guidance course,
- Student survey data
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