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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:

Comparative Study of Experimental and Modeling of Fly Ash-Based Concrete
Kaffayatullah Khan, Ayaz Ahmad, Muhammad Nasir Amin, et al.
Materials (2022) Vol. 15, Iss. 11, pp. 3762-3762
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

Testing and modeling methods to experiment the flexural performance of cement mortar modified with eggshell powder
Muhammad Nasir Amin, Waqas Ahmad, Kaffayatullah Khan, et al.
Case Studies in Construction Materials (2022) Vol. 18, pp. e01759-e01759
Open Access | Times Cited: 42
Investigating the feasibility of using waste eggshells in cement-based materials for sustainable construction
Kaffayatullah Khan, Waqas Ahmad, Muhammad Nasir Amin, et al.
Journal of Materials Research and Technology (2023) Vol. 23, pp. 4059-4074
Open Access | Times Cited: 39
Optimizing compressive strength prediction models for rice husk ash concrete with evolutionary machine intelligence techniques
Muhammad Nasir Amin, Waqas Ahmad, Kaffayatullah Khan, et al.
Case Studies in Construction Materials (2023) Vol. 18, pp. e02102-e02102
Open Access | Times Cited: 34
Evaluating the effectiveness of waste glass powder for the compressive strength improvement of cement mortar using experimental and machine learning methods
Kaffayatullah Khan, Waqas Ahmad, Muhammad Nasir Amin, et al.
Heliyon (2023) Vol. 9, Iss. 5, pp. e16288-e16288
Open Access | Times Cited: 31
Experimental and machine learning approaches to investigate the effect of waste glass powder on the flexural strength of cement mortar
Muhammad Nasir Amin, Hassan Ali Alkadhim, Waqas Ahmad, et al.
PLoS ONE (2023) Vol. 18, Iss. 1, pp. e0280761-e0280761
Open Access | Times Cited: 28
Experimental investigation and AI prediction modelling of ceramic waste powder concrete – An approach towards sustainable construction
Jianyu Yang, Pengxiao Jiang, Roz‐Ud‐Din Nassar, et al.
Journal of Materials Research and Technology (2023) Vol. 23, pp. 3676-3696
Open Access | Times Cited: 28
Predictive modelling for the acid resistance of cement-based composites modified with eggshell and glass waste for sustainable and resilient building materials
Zhiqiang Chen, Muhammad Nasir Amin, Bawar Iftikhar, et al.
Journal of Building Engineering (2023) Vol. 76, pp. 107325-107325
Closed Access | Times Cited: 28
Evaluating the relevance of eggshell and glass powder for cement-based materials using machine learning and SHapley Additive exPlanations (SHAP) analysis
Muhammad Nasir Amin, Waqas Ahmad, Kaffayatullah Khan, et al.
Case Studies in Construction Materials (2023) Vol. 19, pp. e02278-e02278
Open Access | Times Cited: 27
Strength Reduction Due to Acid Attack in Cement Mortar Containing Waste Eggshell and Glass: A Machine Learning-Based Modeling Study
Fei Zhu, Xiangping Wu, Yijun Lü, et al.
Buildings (2024) Vol. 14, Iss. 1, pp. 225-225
Open Access | Times Cited: 15
Machine and Deep Learning Methods for Concrete Strength Prediction: A Bibliometric and Content Analysis Review of Research Trends and Future Directions
Raman Kumar, Essam Althaqafi, S. Gopal Krishna Patro, et al.
Applied Soft Computing (2024) Vol. 164, pp. 111956-111956
Closed Access | Times Cited: 14
Sustainable innovation in self-compacted concrete: Integrating by-products and waste rubber for green construction practices
Yarivan J. Zrar, Payam Ismael Abdulrahman, Aryan Far H. Sherwani, et al.
Structures (2024) Vol. 62, pp. 106234-106234
Closed Access | Times Cited: 10
Evaluating the Strength and Impact of Raw Ingredients of Cement Mortar Incorporating Waste Glass Powder Using Machine Learning and SHapley Additive ExPlanations (SHAP) Methods
Hassan Ali Alkadhim, Muhammad Nasir Amin, Waqas Ahmad, et al.
Materials (2022) Vol. 15, Iss. 20, pp. 7344-7344
Open Access | Times Cited: 36
Assessment of Artificial Intelligence Strategies to Estimate the Strength of Geopolymer Composites and Influence of Input Parameters
Kaffayatullah Khan, Waqas Ahmad, Muhammad Nasir Amin, et al.
Polymers (2022) Vol. 14, Iss. 12, pp. 2509-2509
Open Access | Times Cited: 34
Sustainable use of waste eggshells in cementitious materials: An experimental and modeling-based study
Fahad Alsharari, Kaffayatullah Khan, Muhammad Nasir Amin, et al.
Case Studies in Construction Materials (2022) Vol. 17, pp. e01620-e01620
Open Access | Times Cited: 33
Sustainable strategy of eggshell waste usage in cementitious composites: An integral testing and computational study for compressive behavior in aggressive environment
Nanlan Wang, Zhengjun Xia, Muhammad Nasir Amin, et al.
Construction and Building Materials (2023) Vol. 386, pp. 131536-131536
Closed Access | Times Cited: 19
Optimizing and hyper-tuning machine learning models for the water absorption of eggshell and glass-based cementitious composite
Xiqiao Xia
PLoS ONE (2024) Vol. 19, Iss. 1, pp. e0296494-e0296494
Open Access | Times Cited: 7
Application of Ensemble Machine Learning Methods to Estimate the Compressive Strength of Fiber-Reinforced Nano-Silica Modified Concrete
M. Reshma Anjum, Kaffayatullah Khan, Waqas Ahmad, et al.
Polymers (2022) Vol. 14, Iss. 18, pp. 3906-3906
Open Access | Times Cited: 27
Predicting parameters and sensitivity assessment of nano-silica-based fiber-reinforced concrete: a sustainable construction material
Muhammad Nasir Amin, Kaffayatullah Khan, Muhammad Sufian, et al.
Journal of Materials Research and Technology (2023) Vol. 23, pp. 3943-3960
Open Access | Times Cited: 15
Comparing the efficacy of GEP and MEP algorithms in predicting concrete strength incorporating waste eggshell and waste glass powder
Dong Wang, Muhammad Nasir Amin, Kaffayatullah Khan, et al.
Developments in the Built Environment (2024) Vol. 17, pp. 100361-100361
Open Access | Times Cited: 6
Analyzing the efficacy of waste marble and glass powder for the compressive strength of self-compacting concrete using machine learning strategies
Qing Guan, Zhong Ling Tong, Muhammad Nasir Amin, et al.
REVIEWS ON ADVANCED MATERIALS SCIENCE (2024) Vol. 63, Iss. 1
Open Access | Times Cited: 5
A soft-computing-based modeling approach for predicting acid resistance of waste-derived cementitious composites
Qingyu Cao, Xiongzhou Yuan, Muhammad Nasir Amin, et al.
Construction and Building Materials (2023) Vol. 407, pp. 133540-133540
Closed Access | Times Cited: 12
Application of Soft-Computing Methods to Evaluate the Compressive Strength of Self-Compacting Concrete
Muhammad Nasir Amin, Mohammed Najeeb Al-Hashem, Ayaz Ahmad, et al.
Materials (2022) Vol. 15, Iss. 21, pp. 7800-7800
Open Access | Times Cited: 18
Strength evaluation of eco-friendly waste-derived self-compacting concrete via interpretable genetic-based machine learning models
Zhiqiang Chen, Bawar Iftikhar, Ayaz Ahmad, et al.
Materials Today Communications (2023) Vol. 37, pp. 107356-107356
Closed Access | Times Cited: 11
Evaluating the compressive strength of glass powder-based cement mortar subjected to the acidic environment using testing and modeling approaches
Majdi Ameen Alfaiad, Kaffayatullah Khan, Waqas Ahmad, et al.
PLoS ONE (2023) Vol. 18, Iss. 4, pp. e0284761-e0284761
Open Access | Times Cited: 10
Analyzing the compressive strength, eco-strength, and cost–strength ratio of agro-waste-derived concrete using advanced machine learning methods
Muhammad Nasir Amin, Bawar Iftikhar, Kaffayatullah Khan, et al.
REVIEWS ON ADVANCED MATERIALS SCIENCE (2025) Vol. 64, Iss. 1
Open Access
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