化工进展 ›› 2023, Vol. 42 ›› Issue (7): 3325-3330.DOI: 10.16085/j.issn.1000-6613.2023-0530

• 专栏:智能化工装备与安全 • 上一篇    下一篇

化工科研范式智能化转型的思考与展望

李蓝宇(), 黄新烨, 王笑楠(), 邱彤   

  1. 清华大学化学工程系,北京 100084
  • 收稿日期:2023-04-06 修回日期:2023-05-23 出版日期:2023-07-15 发布日期:2023-08-14
  • 通讯作者: 王笑楠
  • 作者简介:李蓝宇(1994—),女,博士后,研究方向为智慧系统工程。E-mail:lilanyu@mail.tsinghua.edu.cn
  • 基金资助:
    科技创新2030——“新一代人工智能”重大项目(2022ZD0117501)

Reflection and prospects on the intelligent transformation of chemical engineering research

LI Lanyu(), HUANG Xinye, WANG Xiaonan(), QIU Tong   

  1. Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
  • Received:2023-04-06 Revised:2023-05-23 Online:2023-07-15 Published:2023-08-14
  • Contact: WANG Xiaonan

摘要:

化工行业作为国家的支柱性产业,不断地积极响应国家号召,推动行业数字化、智能化发展。实验室和研究院作为化学工程核心技术支撑,是化工行业智能化转型中必不可少的一部分。站在智能化变革的起点,本文调研归纳了目前国内外化工实验室的智能化转型最新进展,围绕科研创新展望了化工实验室的智能化转型蓝图,提出了从信息化、数字化到智能化过渡,涵盖不同发展层级的智能研究院建设大纲,为规划智能研究院建设的具体方案提供指导,并展望了人工智能全面赋能的化工科研范式变革。

关键词: 人工智能, 系统工程, 计算机模拟, 实验验证, 优化设计, 自动化

Abstract:

As a pillar industry, the chemical industry is actively responding to the national call to promote the digital and intelligent development. As an essential part of the intelligent transformation of the chemical industry, it is necessary to conduct in-depth research and propose an implementable overall technical solution to lay a solid foundation for the subsequent intelligent transformation. This paper summarizes the latest progress of the intelligent transformation of chemical laboratories in China and abroad, outlines the blueprint of the intelligent transformation of chemical laboratories around scientific research and innovation, and proposes an outline of building intelligent research institutes covering different levels of development from informationization, digitalization and transition to intelligence, so as to provide a guidance for the specific plan of intelligent research institutes. An outlook of research paradigm change empowered by artificial intelligence (AI) is also provided.

Key words: artificial intelligence, systems engineering, computer simulation, experimental validation, optimal design, automation

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