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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:

Prediction of nature of band gap of perovskite oxides (ABO3) using a machine learning approach
G. Sudha Priyanga, Manoj N. Mattur, N. Nagappan, et al.
Journal of Materiomics (2022) Vol. 8, Iss. 5, pp. 937-948
Open Access | Times Cited: 46

Showing 1-25 of 46 citing articles:

Research Progress on Photocatalytic CO2 Reduction Based on Perovskite Oxides
Qing‐shan Wang, Yi‐chao Yuan, Chu‐fan Li, et al.
Small (2023) Vol. 19, Iss. 38
Closed Access | Times Cited: 47
Machine Learning in Perovskite Solar Cells: Recent Developments and Future Perspectives
Nitin Bansal, Snehangshu Mishra, Himanshu Dixit, et al.
Energy Technology (2023) Vol. 11, Iss. 12
Open Access | Times Cited: 33
Feature Selection in Machine Learning for Perovskite Materials Design and Discovery
Junya Wang, Pengcheng Xu, Xiaobo Ji, et al.
Materials (2023) Vol. 16, Iss. 8, pp. 3134-3134
Open Access | Times Cited: 25
Evaluation of Structural, Electronic, Optical and Mechanical Properties of Na-based Oxide‐Perovskites NaXO3 (X = Co, Be, Ba): A DFT study
Ruyhan, Muhammad Usman, Nazia Bibi, et al.
Materials Today Communications (2024) Vol. 39, pp. 108908-108908
Closed Access | Times Cited: 10
Machine Learning Accelerated Discovery of Functional MXenes with Giant Piezoelectric Coefficients
Xiaowen Li, Jian Qiu, Heping Cui, et al.
ACS Applied Materials & Interfaces (2024) Vol. 16, Iss. 10, pp. 12731-12743
Closed Access | Times Cited: 8
Review of First Principles Simulations of STO/BTO, STO/PTO, and SZO/PZO (001) Heterostructures
R. I. Eglitis, Dmitry Bocharov, Sergei Piskunov, et al.
Crystals (2023) Vol. 13, Iss. 5, pp. 799-799
Open Access | Times Cited: 21
MIC-SHAP: An ensemble feature selection method for materials machine learning
Wang Jun-ya, Pengcheng Xu, Xiaobo Ji, et al.
Materials Today Communications (2023) Vol. 37, pp. 106910-106910
Closed Access | Times Cited: 17
Machine learning assisted optimization of soft magnetic properties in ternary Fe–Si–Al alloys
V. A. Milyutin, Radovan Búreš, Mária Fáberová, et al.
Journal of Materials Research and Technology (2024) Vol. 29, pp. 5060-5073
Open Access | Times Cited: 7
Predictive machine learning approaches for perovskites properties using their chemical formula: towards the discovery of stable solar cells materials
Soundous Touati, Ali Benghia, Zoulikha Hebboul, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 26, pp. 16319-16329
Closed Access | Times Cited: 7
Data-driven strategy for bandgap database construction of perovskites and the potential segregation study
Bobin Wu, Xinyu Zhang, Zixuan Wang, et al.
Journal of Materials Informatics (2024) Vol. 4, Iss. 2
Open Access | Times Cited: 7
Advanced prediction of perovskite stability for solar energy using machine learning
G. Sudha Priyanga, V. Sampath, P.V. Shravan, et al.
Solar Energy (2024) Vol. 278, pp. 112782-112782
Closed Access | Times Cited: 7
Intelligent Algorithms Enable Photocatalyst Design and Performance Prediction
Shifa Wang, Panzhong Mo, Dengfeng Li, et al.
Catalysts (2024) Vol. 14, Iss. 4, pp. 217-217
Open Access | Times Cited: 5
Accurate Prediction of HSE06 Band Structures for a Diverse Set of Materials Using Δ-Learning
Santosh Adhikari, Jacob M. Clary, Ravishankar Sundararaman, et al.
Chemistry of Materials (2023) Vol. 35, Iss. 20, pp. 8397-8405
Closed Access | Times Cited: 11
A machine learning workflow for large-scale discovery of direct bandgap double perovskites
Yuzhi Chen, Hongyu Liu, Xu Fang, et al.
Solar Energy Materials and Solar Cells (2025) Vol. 282, pp. 113402-113402
Closed Access
Quantum Circuit Learning for Predicting Nature of Band Gap of Perovskite Oxides
Muhamad Akrom, Supriadi Rustad, Hermawan Kresno Dipojono, et al.
(2025)
Closed Access
Advances and Challenges in Perovskite Oxide Design for High‐Performance Zinc–Air Batteries: Integrating Experimental Strategies and Machine Learning
H J Geng, Xiaohong Zou, Min Yi, et al.
Advanced Functional Materials (2025)
Closed Access
Enhanced mineralization of pharmaceuticals and textiles waste by Sn2Mn O3/Co(1- photocatalyst: approach, mechanism and statistical optimization
Arif Nawaz, Mahnoor Amjad, Jalwa Afreeq, et al.
Journal of environmental chemical engineering (2025), pp. 116347-116347
Closed Access
Accelerating the Discovery of Direct Bandgap Perovskites for Solar Energy via Machine Learning
Yuxin Zhan, Xiaojie Ren, Shuai Zhao, et al.
Materials Today Communications (2025), pp. 112354-112354
Closed Access
Employing Interpretable Multi-Output Machine Learning to Predict Stable Perovskites in Photovoltaics
Hong-an Lu, Yongxin Cui, Junhao Ma, et al.
Materials Today Communications (2025), pp. 112552-112552
Closed Access
Machine learning of kesterite materials using cost-effective hybrid density functional theory
Donggeon Lee, Sooran Kim, Ji‐Sang Park
Current Applied Physics (2024) Vol. 59, pp. 214-219
Open Access | Times Cited: 3
Accelerated Design for Perovskite-Oxide-Based Photocatalysts Using Machine Learning Techniques
Xiuyun Zhai, Mingtong Chen
Materials (2024) Vol. 17, Iss. 12, pp. 3026-3026
Open Access | Times Cited: 3
The mastery of details in the workflow of materials machine learning
Yingying Ma, Pengcheng Xu, Minjie Li, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 3
Thermal conductivity prediction of sintered reaction bonded silicon nitride ceramics using a machine learning approach based on process conditions
Ryoichi Furushima, Yuki Nakashima, You Zhou, et al.
Ceramics International (2023) Vol. 50, Iss. 5, pp. 8520-8526
Closed Access | Times Cited: 8
Machine learning models for the discovery of direct band gap materials for light emission and photovoltaics
Filip Dinic, Ihor Neporozhnii, Oleksandr Voznyy
Computational Materials Science (2023) Vol. 231, pp. 112580-112580
Closed Access | Times Cited: 7
Dielectric property optimization of polymer nanocomposites using BaTiO3 based high-entropy ceramic filler with Dirac-cone effect
Qihuang Deng, Hong Liu, Y.N. Wang, et al.
Physica B Condensed Matter (2024) Vol. 684, pp. 415992-415992
Closed Access | Times Cited: 2
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