OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Artificial intelligence-driven assessment of salt caverns for underground hydrogen storage in Poland
Reza Derakhshani, Leszek Lankof, Amin GhasemiNejad, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 9

Showing 9 citing articles:

A Novel Sustainable Approach for Site Selection of Underground Hydrogen Storage in Poland Using Deep Learning
Reza Derakhshani, Leszek Lankof, Amin GhasemiNejad, et al.
Energies (2024) Vol. 17, Iss. 15, pp. 3677-3677
Open Access | Times Cited: 5

Characterization and assessment of hydrogen leakage mechanisms in salt caverns
Mojtaba Ghaedi, Raoof Gholami
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access

A Study on the Dissolution Characteristics of Salt Rock Using an Extended Rapid Cavity Creation Device
Chunqing Zha, Ruihao Pang, Wei Wang, et al.
Energies (2025) Vol. 18, Iss. 3, pp. 737-737
Open Access

Artificial intelligence in geoenergy: bridging petroleum engineering and future-oriented applications
Sungil Kim, Tea-Woo Kim, Suryeom Jo
Journal of Petroleum Exploration and Production Technology (2025) Vol. 15, Iss. 2
Open Access

AI-ML techniques for green hydrogen: A comprehensive review
Mamta Motiramani, P.S. Solanki, Vikram Patel, et al.
Next Energy (2025) Vol. 8, pp. 100252-100252
Closed Access

Cavern integrity under cyclic underground hydrogen storage in heterogeneous Brazilian pre-salt formations
Williams Dias, Eleazar Cristian Mejía Sanchez, Deane Roehl
International Journal of Hydrogen Energy (2024) Vol. 94, pp. 922-933
Closed Access | Times Cited: 4

Sequential gated recurrent and self attention explainable deep learning model for predicting hydrogen production: Implications and applicability
Chiagoziem C. Ukwuoma, Dongsheng Cai, Chibueze D. Ukwuoma, et al.
Applied Energy (2024) Vol. 378, pp. 124851-124851
Closed Access | Times Cited: 1

Page 1

Scroll to top