Scientific Deep Machine Learning Concepts for the Prediction of Concentration Profiles and Chemical Reaction Kinetics: Consideration of Reaction Conditions-Reference-Cited by-同舟云学术

Scientific Deep Machine Learning Concepts for the Prediction of Concentration Profiles and Chemical Reaction Kinetics: Consideration of Reaction Conditions

Published:2024-01-25 Issue:5 Volume:128 Page:929-944
ISSN:1089-5639
Container-title:The Journal of Physical Chemistry A
language:en
Short-container-title:J. Phys. Chem. A

Author:

Adebar Niklas¹,Keupp Julian¹,Emenike Victor N.²,Kühlborn Jonas¹,vom Dahl Lisa³,Möckel Robert¹,Smiatek Jens⁴⁵^ORCID

Affiliation:

1. Development NCE, Chemical Development, Boehringer Ingelheim Pharma GmbH & Co. KG, D-55218 Ingelheim (Rhein), Germany

2. HP BioP Launch and Innovation, Boehringer Ingelheim Pharma GmbH & Co. KG, D-55218 Ingelheim (Rhein), Germany

3. Development NCE, Analytical Development, Boehringer Ingelheim Pharma GmbH & Co. KG, D-55218 Ingelheim (Rhein), Germany

4. Institute for Computational Physics, University of Stuttgart, D-70569 Stuttgart, Germany

5. Development NCE, Strategy NCEs, Boehringer Ingelheim Pharma GmbH & Co. KG, D-88397 Biberach (Riss), Germany

Funder

Boehringer Ingelheim

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpca.3c06265

Reference84 articles.

1. The application of modern reactions in large-scale synthesis

2. Reinventing Chemistry

3. Artificial intelligence in the modeling of chemical reactions kinetics

4. The Exploration of Chemical Reaction Networks

5. Kinetic Modeling of Large‐Scale Reaction Systems

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