大学化学

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AI赋能能源化学工程培养体系的重构与实践

危仁波, 杨景梅, 刘泳显, 王玲玲, 郑晓燕, 花秀夫   

  1. 西北大学化工学院, 低碳技术应用研究院, 陕西 西安 710127
  • 收稿日期:2026-04-22 录用日期:2026-06-30
  • 通讯作者: 花秀夫 E-mail:huaxf@nwu.edu.cn Xiufu Hua
  • 基金资助:
    陕西本科和高等继续教育教学改革研究项目(25BY079)；教育部产学合作协同育人项目(2507220511, 2507144811, 2507161552，2507143359)

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

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摘要： 面向我国能源化工产业“高端化、智能化、绿色化”转型的迫切现实需求，本研究锚定新工科建设“能力导向、创新引领”的核心要求，坚持以学生“知识-能力-素质”三维协同提升为根本导向，系统构建了“理论-实践-AI赋能”的一体化培养模型。以此为基础，创新形成了“3+1+X”的阶梯式贯通培养路径，依托校企共建的产教融合创新基地与智能化虚拟仿真实训平台，推动传统能源化工专业培养范式深度向“理工技深度融合”方向转变。本培养体系旨在造就兼具扎实理论功底、AI技术应用能力与产业创新思维的复合型拔尖人才，可为新工科背景下能源化工专业培养体系的系统性重构提供可复制推广的理论框架与实践路径。

关键词: 人工智能, 培养体系, 能源化工, 人才培养, 新工科

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