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  A systematic modeling methodology of deep neural network‐based structure‐property relationship for rapid and reliable prediction on flashpoints

Wen, H., Su, Y., Wang, Z., Jin, S., Ren, J., Shen, W., et al. (2022). A systematic modeling methodology of deep neural network‐based structure‐property relationship for rapid and reliable prediction on flashpoints. AIChE Journal, 68(1): 17402. doi:10.1002/aic.17402.

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Genre: Journal Article

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 Creators:
Wen, Huaqiang1, Author
Su, Yang2, Author
Wang, Zihao3, Author              
Jin, Saimeng1, Author
Ren, Jingzheng4, Author
Shen, Weifeng1, Author
Eden, Mario5, Author
Affiliations:
1School of Chemistry and Chemical Engineering, Chongqing University, Chongqing, China, ou_persistent22              
2School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing, China, ou_persistent22              
3Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738151              
4Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, ou_persistent22              
5Department of Chemical Engineering, Auburn University, Auburn, AL, United States, ou_persistent22              

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Language(s): eng - English
 Dates: 2022
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1002/aic.17402
 Degree: -

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Title: AIChE Journal
Source Genre: Journal
 Creator(s):
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Publ. Info: -
Pages: - Volume / Issue: 68 (1) Sequence Number: 17402 Start / End Page: - Identifier: ISSN: 0001-1541
ISSN: 1547-5905