OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

From Computational Fluid Dynamics to Structure Interpretation via Neural Networks: An Application to Flow and Transport in Porous Media
Agnese Marcato, Gianluca Boccardo, Daniele Marchisio
Industrial & Engineering Chemistry Research (2022) Vol. 61, Iss. 24, pp. 8530-8541
Open Access | Times Cited: 38

Showing 26-50 of 38 citing articles:

Homogenization-Informed Convolutional Neural Networks for Estimation of Li-ion Battery Effective Properties
Ross M. Weber, Svyatoslav Korneev, Ilenia Battiato
Transport in Porous Media (2022) Vol. 145, Iss. 2, pp. 527-548
Closed Access | Times Cited: 7

Prediction of Local Concentration Fields in Porous Media with Chemical Reaction Using a Multi Scale Convolutional Neural Network
Agnese Marcato, Javier Estrada Santos, Gianluca Boccardo, et al.
SSRN Electronic Journal (2022)
Open Access | Times Cited: 4

Artificial Intelligence-Based Engineering Applications a Comprehensive Review of Application Areas, Impacts and Challenges
Bekir Aksoy, Osamah Khaled Musleh SALMAN, Özge EKREM, et al.
(2024), pp. 32-47
Closed Access

A Computationally Efficient Hybrid Neural Network Architecture for Porous Media: Integrating Convolutional and Graph Neural Networks for Improved Property Predictions
Qingqi Zhao, Xiaoxue Han, Ruichang Guo, et al.
Advances in Water Resources (2024) Vol. 195, pp. 104881-104881
Closed Access

Greedy Kernel Methods for Approximating Breakthrough Curves for Reactive Flow from 3D Porous Geometry Data
Robin Herkert, Patrick Buchfink, Tizian Wenzel, et al.
Mathematics (2024) Vol. 12, Iss. 13, pp. 2111-2111
Open Access

Rapid prediction of flow and concentration fields in solid-liquid suspensions of slurry electrolysis tanks
Tingting Lu, Kang Li, Hongliang Zhao, et al.
International Journal of Minerals Metallurgy and Materials (2024) Vol. 31, Iss. 9, pp. 2006-2016
Closed Access

ACS Editors’ Choice Virtual Collection from I&EC Research
Phillip E. Savage, Linda J. Broadbelt, Marianthi Ierapetritou, et al.
Industrial & Engineering Chemistry Research (2023) Vol. 62, Iss. 23, pp. 8993-8994
Closed Access | Times Cited: 1

CONVOLUTIONAL NEURAL NETWORKS FOR PROBLEMS IN TRANSPORT PHENOMENA: A THEORETICAL MINIMUM
Arjun Bhasin, Aashutosh Mistry
Journal of Flow Visualization and Image Processing (2022) Vol. 30, Iss. 3, pp. 1-38
Open Access | Times Cited: 2

Improving Machine Learning Predictions of Rock Electric Properties Using 3D Geometric Features
Bernard Chang, Javier E. Santos, Rodolfo Araújo Victor, et al.
SPE Annual Technical Conference and Exhibition (2022)
Closed Access | Times Cited: 1

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