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:

Modeling thermal conductivity of hydrogen-based binary gaseous mixtures using generalized regression neural network
Arefeh Naghizadeh, Behnam Amiri-Ramsheh, Saeid Atashrouz, et al.
International Journal of Hydrogen Energy (2024) Vol. 59, pp. 242-250
Closed Access | Times Cited: 7

Showing 7 citing articles:

Modeling thermo-physical properties of hydrogen utilizing machine learning schemes: Viscosity, density, diffusivity, and thermal conductivity
Qichao Lv, Zhaomin Li, Xiaochen Li, et al.
International Journal of Hydrogen Energy (2024) Vol. 72, pp. 1127-1142
Closed Access | Times Cited: 7

Exploring advanced artificial intelligence techniques for efficient hydrogen storage in metal organic frameworks
Arefeh Naghizadeh, Fahimeh Hadavimoghaddam, Saeid Atashrouz, et al.
Adsorption (2025) Vol. 31, Iss. 2
Closed Access

White-box methodologies for achieving robust correlations in hydrogen storage with metal-organic frameworks
Arefeh Naghizadeh, Fahimeh Hadavimoghaddam, Saeid Atashrouz, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access

Applying artificial intelligence for forecasting behavior in a liquefied hydrogen unit
Dongmei Jing, Azher M. Abed, Pinank Patel, et al.
International Journal of Hydrogen Energy (2025) Vol. 114, pp. 31-51
Closed Access

EFFECT OF SEASONAL-TREND DECOMPOSITION ON MACHINE LEARNING-BASED SUSPENDED SEDIMENT LOAD PREDICTION PERFORMANCE
Cihangir Köyceğiz, Meral Büyükyıldız
Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi (2025) Vol. 28, Iss. 1, pp. 1-18
Open Access

A comparative study of machine learning frameworks for predicting CO2 conversion into light olefins
Mehdi Sedighi, Majid Mohammadi, Forough Ameli, et al.
Fuel (2024) Vol. 379, pp. 133017-133017
Closed Access | Times Cited: 3

Research on quantitative analysis method of shale oil reservoir sensitivity based on mineral analysis
Xiaojun Wang, Xiaofeng Zhou
Geoenergy Science and Engineering (2024) Vol. 239, pp. 212952-212952
Closed Access | Times Cited: 2

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