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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:

Machine-Learning-Accelerated Perovskite Crystallization
Jeffrey Kirman, Andrew Johnston, D.A. Kuntz, et al.
Matter (2020) Vol. 2, Iss. 4, pp. 938-947
Open Access | Times Cited: 121

Showing 76-100 of 121 citing articles:

Principled Exploration of Bipyridine and Terpyridine Additives to Promote Methylammonium Lead Iodide Perovskite Crystallization
Noor Titan Putri Hartono, Mansoor Ani Najeeb, Zhi Li, et al.
Crystal Growth & Design (2022) Vol. 22, Iss. 9, pp. 5424-5431
Closed Access | Times Cited: 11
Improving Data and Prediction Quality of High-Throughput Perovskite Synthesis with Model Fusion
Yuanqing Tang, Zhi Li, Mansoor Ani Najeeb Nellikkal, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 4, pp. 1593-1602
Open Access | Times Cited: 15
High throughput screening of novel tribromide perovskite materials for high-photovoltage solar cells
Shi Chen, Lihua Zhang, Yanliang Liu, et al.
Journal of Materials Chemistry A (2021) Vol. 9, Iss. 45, pp. 25502-25512
Closed Access | Times Cited: 13
Recent Advance of Machine Learning in Selecting New Materials
Xingyi Qi, Yaofeng Hu, Ruoyu Wang, et al.
Acta Chimica Sinica (2023) Vol. 81, Iss. 2, pp. 158-158
Open Access | Times Cited: 5
A robust low data solution: Dimension prediction of semiconductor nanorods
Xiaoli Liu, Yang Xu, Jiali Li, et al.
Computers & Chemical Engineering (2021) Vol. 150, pp. 107315-107315
Open Access | Times Cited: 12
High-Throughput Synthesis of Thin Films for the Discovery of Energy Materials: A Perspective
Shahram Moradi, Soumya Kundu, Makhsud I. Saidaminov
ACS Materials Au (2022) Vol. 2, Iss. 5, pp. 516-524
Open Access | Times Cited: 8
Perspective on machine learning based investigated materials to realize Stable-Efficient-Toxin free (S-E-T) perovskite solar cells
Vinitha B. Elza, V. Suresh Babu, Nelsa Abraham
Materials Today Proceedings (2023)
Closed Access | Times Cited: 4
Machine‐Learning Accelerating the Development of Perovskite Photovoltaics
Tiantian Liu, Sen Wang, Yinguang Shi, et al.
Solar RRL (2023) Vol. 7, Iss. 23
Closed Access | Times Cited: 4
Methoxy‐Based Passivator 4‐Methoxyphenethylammonium Iodide as Multifunctional Passivator for High‐Efficiency 3D/2D Flexible Perovskite Solar Cells over 23%
Ruikun Cao, Yaohua Wang, Kexuan Sun, et al.
Solar RRL (2023) Vol. 7, Iss. 23
Open Access | Times Cited: 4
Accelerated design of stable halide perovskite heterostructure film in hostile condition via surface modifier
Shenyue Li, Yiru Huang, Lei Zhang
Organic Electronics (2023) Vol. 124, pp. 106945-106945
Closed Access | Times Cited: 4
Comprehensive and Accurate Prediction of Band Gap for Lead-Free Double Perovskites through Self-Modified Machine Learning Strategy
Jing Lan, Songyang Yuan, Huiqun Zheng, et al.
The Journal of Physical Chemistry C (2023) Vol. 127, Iss. 48, pp. 23412-23419
Closed Access | Times Cited: 4
Review of computer‐aided methods in fat crystallization studies
A. Qi, Zhang Lu
Journal of the American Oil Chemists Society (2024) Vol. 101, Iss. 11, pp. 1253-1266
Closed Access | Times Cited: 1
Adapting Explainable Machine Learning to Study Mechanical Properties of 2D Hybrid Halide Perovskites
Yuxuan Yao, Dan Han, Kieran B. Spooner, et al.
Advanced Functional Materials (2024)
Open Access | Times Cited: 1
Machine learning for perovskite optoelectronics: a review
Feiyue Lu, Yanyan Liang, Nana Wang, et al.
Advanced Photonics (2024) Vol. 6, Iss. 05
Open Access | Times Cited: 1
Optical Characterization and Prediction with Neural Network Modeling of Various Stoichiometries of Perovskite Materials Using a Hyperregression Method
Soo Min Kim, Syed Dildar Haider Naqvi, Min Gu Kang, et al.
Nanomaterials (2022) Vol. 12, Iss. 6, pp. 932-932
Open Access | Times Cited: 7
High-Throughput Evaluation of Emission and Structure in Reduced-Dimensional Perovskites
Husna Anwar, Andrew Johnston, Suhas Mahesh, et al.
ACS Central Science (2022) Vol. 8, Iss. 5, pp. 571-580
Open Access | Times Cited: 7
Photocatalytic Conversion of Methane: Recent Advancements and Prospects
Qi Li, Yuxing Ouyang, Hongliang Li, et al.
Angewandte Chemie International Edition (2021) Vol. 61, Iss. 2
Closed Access | Times Cited: 9
Recent Developments in Process Digitalisation for Advanced Nanomaterial Syntheses
Diego Iglesias, Dina A Haddad, Víctor Sans
Chemistry - Methods (2022) Vol. 2, Iss. 12
Open Access | Times Cited: 6
Emerging opportunities for hybrid perovskite solar cells using machine learning
Abigail R. Hering, Mansha Dubey, Marina S. Leite
APL Energy (2023) Vol. 1, Iss. 2
Open Access | Times Cited: 3
Discovery of all-inorganic lead-free perovskites with high photovoltaic performance via ensemble machine learning
Xia Cai, Yan Li, Jianfei Liu, et al.
Materials Horizons (2023) Vol. 10, Iss. 11, pp. 5288-5297
Closed Access | Times Cited: 3
Accelerated prediction of perovskite material properties with classical machine learning and graph neural network
Zhihao Dong, Yujin Ji, Youyong Li
Materials Express (2023) Vol. 13, Iss. 4, pp. 695-703
Closed Access | Times Cited: 2
Shape‐Controlled Solution‐Epitaxial Perovskite Micro‐Crystal Lasers Rivaling Vapor Deposited Ones
Hany A. Afify, Viktor Rehm, Anastasiia Barabash, et al.
Advanced Functional Materials (2022) Vol. 32, Iss. 45
Open Access | Times Cited: 4
Spatiotemporal Route to Understanding Metal Halide Perovskitoid Crystallization
Mansoor Ani Najeeb Nellikkal, Rodolfo Keesey, Margaret Zeile, et al.
Chemistry of Materials (2022) Vol. 34, Iss. 12, pp. 5386-5396
Open Access | Times Cited: 3
Review on Perovskite-Type Compound Using Machine Learning
Taohong Zhang, Xueqiang Guo, Han Zheng, et al.
Science of Advanced Materials (2022) Vol. 14, Iss. 6, pp. 1001-1017
Closed Access | Times Cited: 3
Role of quantum technology and artificial intelligence for nano-enabled microfluidics
Surendra K. Yadav, Kolleboyina Jayaramulu
Elsevier eBooks (2024), pp. 189-208
Closed Access

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