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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 the chloride migration of recycled aggregate concrete using ensemble learners for sustainable building construction
Emadaldin Mohammadi Golafshani, Alireza Kashani, Ali Behnood, et al.
Journal of Cleaner Production (2023) Vol. 407, pp. 136968-136968
Closed Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Prediction and optimization model of sustainable concrete properties using machine learning, deep learning and swarm intelligence: A review
Shiqi Wang, Peng Xia, Keyu Chen, et al.
Journal of Building Engineering (2023) Vol. 80, pp. 108065-108065
Closed Access | Times Cited: 60
Reusing waste clay brick powder for low-carbon cement concrete and alkali-activated concrete: A critical review
Huixia Wu, Jianming Gao, Cheng Liu, et al.
Journal of Cleaner Production (2024) Vol. 449, pp. 141755-141755
Closed Access | Times Cited: 51
Data-driven modeling for residual velocity of projectile penetrating reinforced concrete slabs
X. Song, Wenwu Wang, Yongjun Deng, et al.
Engineering Structures (2024) Vol. 306, pp. 117761-117761
Closed Access | Times Cited: 29
Electrical resistivity prediction model for basalt fibre reinforced concrete: hybrid machine learning model and experimental validation
Zhen Sun, Xin Wang, Ditao Niu, et al.
Materials and Structures (2025) Vol. 58, Iss. 3
Closed Access | Times Cited: 4
Modeling strength characteristics of basalt fiber reinforced concrete using multiple explainable machine learning with a graphical user interface
W.K.V.J.B. Kulasooriya, R.S.S. Ranasinghe, Udara Sachinthana Perera, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 32
Prediction of building energy performance using mathematical gene-expression programming for a selected region of dry-summer climate
Majed Alzara, Muhammad Faisal Rehman, Furqan Farooq, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 126, pp. 106958-106958
Closed Access | Times Cited: 23
Characteristics of non-steady-state chloride migration of self-compacting concrete containing recycled concrete aggregate made of fly ash and silica fume
Gritsada Sua-iam, Natt Makul
Case Studies in Construction Materials (2024) Vol. 20, pp. e02877-e02877
Open Access | Times Cited: 13
A framework for low-carbon mix design of recycled aggregate concrete with supplementary cementitious materials using machine learning and optimization algorithms
Emadaldin Mohammadi Golafshani, Ali Behnood, Taehwan Kim, et al.
Structures (2024) Vol. 61, pp. 106143-106143
Open Access | Times Cited: 9
Nano-engineered the interfacial transition zone between recycled fine aggregates and paste with graphene oxide for sustainable cement composites
Dong Lu, Fulin Qu, Yilin Su, et al.
Cement and Concrete Composites (2024) Vol. 154, pp. 105762-105762
Closed Access | Times Cited: 9
A systematic literature review of AI-based prediction methods for self-compacting, geopolymer, and other eco-friendly concrete types: Advancing sustainable concrete
Tariq Ali, Mohamed Hechmi El Ouni, Muhammad Zeeshan Qureshi, et al.
Construction and Building Materials (2024) Vol. 440, pp. 137370-137370
Closed Access | Times Cited: 8
Using recycled aggregate and powder from high-strength mortar waste for durable cement-based materials: Microstructure and chloride transport
Zhiming Ma, Xin Liu, Ruihan Hu, et al.
Journal of Cleaner Production (2023) Vol. 417, pp. 137998-137998
Closed Access | Times Cited: 21
Performance Improvement of Recycled Concrete Aggregates and Their Potential Applications in Infrastructure: A Review
Shuxia Han, Songbo Zhao, Dong Lu, et al.
Buildings (2023) Vol. 13, Iss. 6, pp. 1411-1411
Open Access | Times Cited: 20
Utilizing machine learning approaches within concrete technology offers an intelligent perspective towards sustainability in the construction industry: a comprehensive review
Suhaib Rasool Wani, Manju Suthar
Multiscale and Multidisciplinary Modeling Experiments and Design (2024) Vol. 8, Iss. 1
Closed Access | Times Cited: 6
Prediction of compressive strength of recycled concrete using gradient boosting models
Amira Hamdy Ali Ahmed, Jin‐Ming Wu, Mosaad Ali Hussein Ali
Ain Shams Engineering Journal (2024) Vol. 15, Iss. 9, pp. 102975-102975
Open Access | Times Cited: 4
Innovative IoT-Integrated Sensors for Real-Time Monitoring of Chloride Penetration in Concrete Structures
Amin Abedini Moghanaki, Amirabbas Badiee Gavarti, Ali Akbar Shirzadi Javid, et al.
Journal of Nondestructive Evaluation (2025) Vol. 44, Iss. 2
Closed Access
AI-based framework for concrete durability assessment using generative adversarial networks and bayesian neural networks
Abobaker Ba Ragaa, Fahim Al-Neshawy, Mohamed Noureldin
Construction and Building Materials (2025) Vol. 471, pp. 140722-140722
Open Access
Explainable machine learning model for predicting compressive strength of CO2-cured concrete
Jia Chu, Bingbing Guo, Taotao Zhong, et al.
Case Studies in Construction Materials (2025), pp. e04589-e04589
Open Access
Machine Learning as an Innovative Engineering Tool for Controlling Concrete Performance: A Comprehensive Review
Fatemeh Mobasheri, Masoud Hosseinpoor, Ammar Yahia, et al.
Archives of Computational Methods in Engineering (2025)
Closed Access
A Critical Review of the Technical Characteristics of Recycled Brick Powder and Its Influence on Concrete Properties
Jinkang Hu, Wisal Ahmed, Dengwu Jiao
Buildings (2024) Vol. 14, Iss. 11, pp. 3691-3691
Open Access | Times Cited: 3
Machine learning for sustainable development: leveraging technology for a greener future
Muneza Kagzi, Sayantan Khanra, Sanjoy Kumar Paul
Journal of Systems and Information Technology (2023) Vol. 25, Iss. 4, pp. 440-479
Closed Access | Times Cited: 7
Enhanced Photoluminescence of Plasma-Treated Recycled Glass Particles
Z. Remeš, Oleg Babčenko, Vítězslav Jarý, et al.
Nanomaterials (2024) Vol. 14, Iss. 13, pp. 1091-1091
Open Access | Times Cited: 2
Use of machine learning models to predict the water penetration depth in concrete
Abdulkader El-Mir, Samer El-Zahab, Dana Nasr, et al.
Journal of Building Engineering (2024) Vol. 95, pp. 110107-110107
Closed Access | Times Cited: 1
Models for chloride diffusion of concrete employing fuzzy-based algorithms
Xiaoyu Yang, Yao Wang
Multiscale and Multidisciplinary Modeling Experiments and Design (2024)
Closed Access | Times Cited: 1
Chloride diffusion modeling of concrete using tree‐based forest models
Emadaldin Mohammadi Golafshani, Alireza Kashani, Mehrdad Arashpour
Structural Concrete (2023) Vol. 24, Iss. 4, pp. 5614-5634
Open Access | Times Cited: 3
Using the automated random forest approach for obtaining the compressive strength prediction of RCA
Yujie Wu, Xiaoming He
Multiscale and Multidisciplinary Modeling Experiments and Design (2023) Vol. 7, Iss. 2, pp. 855-867
Closed Access | Times Cited: 3
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