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110th Anniversary: Using Data to Bridge the Time and Length Scales of Process Systems

  • Published:2019-08-10 Issue:36 Volume:58 Page:16696-16708
  • ISSN:0888-5885
  • Container-title:Industrial & Engineering Chemistry Research
  • language:en
  • Short-container-title:Ind. Eng. Chem. Res.

Author:

Tsay Calvin1,Baldea Michael1ORCID

Affiliation:

1. McKetta Department of Chemical Engineering The University of Texas at Austin, Austin, Texas 78712, United States

Funder

University of Texas at Austin

U.S. Department of Energy

Division of Chemical, Bioengineering, Environmental, and Transport Systems

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Reference115 articles.

1. The promise of artificial intelligence in chemical engineering: Is it here, finally?

2. Intelligent systems in process engineering: a review

3. Survey on data-driven industrial process monitoring and diagnosis

4. Complex systems

5. Marquardt, W.; von Wedel, L.; Bayer, B. Perspectives on lifecycle process modeling; AIChE Symposium Series; AIChE, 2000; pp 192–214.
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