Machine-Learning-Assisted Investigation of the Diffusion of Hydrogen in Brine by Performing Molecular Dynamics Simulation-Reference-Cited by-同舟云学术

Machine-Learning-Assisted Investigation of the Diffusion of Hydrogen in Brine by Performing Molecular Dynamics Simulation

Published:2023-12-04 Issue:49 Volume:62 Page:21385-21396
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Bhimineni Sree Harsha¹,Zhou Tianhang²^ORCID,Mahmoodpour Saeed³^ORCID,Singh Mrityunjay³^ORCID,Li Wei⁴,Bag Saientan²^ORCID,Sass Ingo³,Müller-Plathe Florian²^ORCID

Affiliation:

1. Chemical Engineering Department, National Institute of Technology, Warangal 506004, Telangana, India

2. Eduard-Zintl-Institut für Anorganische und Physikalische Chemie, Technische Universität Darmstadt, Alarich-Weiss-Str. 8, 64287 Darmstadt, Germany

3. Technische Universität Darmstadt, Institute of Applied Geosciences, Group of Geothermal Science and Technology, Schnittspahnstrasse 9, 64287 Darmstadt, Germany

4. Department of Materials and Earth Sciences, Technische Universität Darmstadt, Darmstadt 64287, Germany

Funder

Technische Universit?t Darmstadt

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.3c01957

Reference81 articles.

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4. IRENA, International Renewable Energy Agency. Hydrogen from Renewable Power, 2010. https://www.irena.org/Statistics/View-Data-by-Topic/Capacity-and-Generation/Statistics-Time-Series.

5. Power to gas: Technological overview, systems analysis and economic assessment for a case study in Germany

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