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Reconstruction and practice of an AI-empowered cultivation system for energy chemical engineering

Renbo Wei, Jingmei Yang, Yongxian Liu, Lingling Wang, Xiaoyan Zheng, Xiufu Hua   

  1. Institute of Low-Carbon Technology Application, School of Chemical Engineering, Northwest University, Xi'an 710127, Shaanxi Province, China
  • Received:2026-04-22 Accepted:2026-06-30
  • Contact: Xiufu Hua E-mail:huaxf@nwu.edu.cn

Abstract: In response to the pressing demand for the transformation of China’s energy and chemical industry toward “high-end, intelligent, and green” development, this study aligns with the core principles of “competency orientation and innovation leadership” in the construction of emerging engineering education. Centered on the synergistic enhancement of students’ knowledge, competencies, and qualities, we systematically develop an integrated cultivation model that unifies theory, practice, and AI (artificial intelligence) empowerment. Building on this foundation, an innovative “3+1+X” progressive and continuous training pathway is established. Leveraging an industry–education integration innovation base and an intelligent virtual simulation training platform co-created by universities and enterprises, this model drives a paradigm shift in traditional energy chemical engineering education toward the deep convergence of engineering, technology, and science. The proposed cultivation system is designed to produce interdisciplinary top-tier talents who possess solid theoretical foundations, proficiency in AI applications, and innovative industrial thinking. It offers a replicable and scalable theoretical framework and practical pathway for the systematic reconstruction of energy chemical engineering education within the context of emerging engineering disciplines.

Key words: Artificial intelligence, Cultivation system, Energy chemical engineering, Talent cultivation, Emerging engineering education