Neural Network-Based Tensor Completion: Advancing Predictions of Activity Coefficients and Beyond-Reference-Cited by-同舟云学术

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Neural Network-Based Tensor Completion: Advancing Predictions of Activity Coefficients and Beyond

Published:2024-07-08 Issue:28 Volume:63 Page:12648-12655
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Averbeck T.¹,Sadowski G.²,Held C.²^ORCID,Seidensticker T.¹^ORCID

Affiliation:

1. Department for Biochemical and Chemical Engineering, Laboratory of Industrial Chemistry, TU Dortmund University, Emil-Figge-Str. 66, 44227 Dortmund, Germany

2. Department for Biochemical and Chemical Engineering, Laboratory of Thermodynamics, TU Dortmund University, Emil-Figge-Str. 70, 44227 Dortmund, Germany

Funder

Fachagentur Nachwachsende Rohstoffe

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.4c00352

Reference29 articles.

1. Group-contribution estimation of activity coefficients in nonideal liquid mixtures

2. On the combinatorial part of the UNIFAC and UNIQUAC models

3. A modified UNIFAC model. 1. Prediction of VLE, hE, and .gamma..infin.

4. A modified UNIFAC model. 2. Present parameter matrix and results for different thermodynamic properties

5. A Modified UNIFAC (Dortmund) Model. 3. Revision and Extension

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