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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 51-75 of 121 citing articles:

Navigating the design space of inorganic materials synthesis using statistical methods and machine learning
Erick J. Braham, Rachel D. Davidson, Mohammed Al‐Hashimi, et al.
Dalton Transactions (2020) Vol. 49, Iss. 33, pp. 11480-11488
Closed Access | Times Cited: 35
Accelerated design of promising mixed lead-free double halide organic–inorganic perovskites for photovoltaics using machine learning
Yilei Wu, Shuaihua Lu, Ming‐Gang Ju, et al.
Nanoscale (2021)
Closed Access | Times Cited: 29
Recent advances in autonomous synthesis of materials
Yucen Li, Lingling Xia, Yi‐Ming Fan, et al.
ChemPhysMater (2021) Vol. 1, Iss. 2, pp. 77-85
Open Access | Times Cited: 27
Quantitative Predictions of Moisture-Driven Photoemission Dynamics in Metal Halide Perovskites via Machine Learning
John M. Howard, Qiong Wang, Meghna Srivastava, et al.
The Journal of Physical Chemistry Letters (2022) Vol. 13, Iss. 9, pp. 2254-2263
Closed Access | Times Cited: 21
Vision for energy material design: A roadmap for integrated data-driven modeling
Zhilong Wang, Yanqiang Han, Junfei Cai, et al.
Journal of Energy Chemistry (2022) Vol. 71, pp. 56-62
Closed Access | Times Cited: 20
Active meta-learning for predicting and selecting perovskite crystallization experiments
Venkateswaran Shekar, Gareth Nicholas, Mansoor Ani Najeeb, et al.
The Journal of Chemical Physics (2022) Vol. 156, Iss. 6
Open Access | Times Cited: 19
Process Insights into Perovskite Thin‐Film Photovoltaics from Machine Learning with In Situ Luminescence Data
Felix Laufer, Sebastian Ziegler, Fabian Schackmar, et al.
Solar RRL (2023) Vol. 7, Iss. 7
Open Access | Times Cited: 11
Machine learning-based screening of two-dimensional perovskite organic spacers
Yongxiang Mai, Jianyao Tang, Haogang Meng, et al.
Advanced Composites and Hybrid Materials (2024) Vol. 7, Iss. 3
Closed Access | Times Cited: 4
Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors
Tatiane Pretto, Sergey Dayneko, Antoine Pavesic, et al.
Advanced Functional Materials (2025)
Open Access
Accelerated Design of High-Efficiency Lead-Free Tin Perovskite Solar Cells via Machine Learning
Taeju Bak, Kyusun Kim, Eunhyeok Seo, et al.
International Journal of Precision Engineering and Manufacturing-Green Technology (2022) Vol. 10, Iss. 1, pp. 109-121
Closed Access | Times Cited: 18
Opportunities for machine learning to accelerate halide-perovskite commercialization and scale-up
Rishi E. Kumar, Armi Tiihonen, Shijing Sun, et al.
Matter (2022) Vol. 5, Iss. 5, pp. 1353-1366
Open Access | Times Cited: 17
Development and Prospects of Halide Perovskite Single Crystal Films
Wenxiu Gao, Zhuolei Zhang, Rukai Xu, et al.
Advanced Electronic Materials (2022) Vol. 8, Iss. 4
Open Access | Times Cited: 17
Using Active Learning to Develop Machine Learning Models for Reaction Yield Prediction
Simon Johansson, Hampus Gummesson Svensson, Esben Jannik Bjerrum, et al.
Molecular Informatics (2022) Vol. 41, Iss. 12
Closed Access | Times Cited: 16
Machine learning for fast development of advanced energy materials
Bita Farhadi, Jiaxue You, Dexu Zheng, et al.
Next Materials (2023) Vol. 1, Iss. 3, pp. 100025-100025
Open Access | Times Cited: 10
Probing the Low-Frequency Response of Impedance Spectroscopy of Halide Perovskite Single Crystals Using Machine Learning
Nishi Parikh, Seçkin Akın, Abul Kalam, et al.
ACS Applied Materials & Interfaces (2023) Vol. 15, Iss. 23, pp. 27801-27808
Closed Access | Times Cited: 9
A Data-Driven Platform for Two-Dimensional Hybrid Lead-Halide Perovskites
An Chen, Zhilong Wang, Jing Gao, et al.
ACS Nano (2023) Vol. 17, Iss. 14, pp. 13348-13357
Closed Access | Times Cited: 9
Surface Patterned Omniphobic Tiles (SPOTs): a versatile platform for scalable liquid handling
Samira Shiri, Mohsin Qazi, Shenghao Tan, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 3
Repeatable Perovskite Solar Cells through Fully Automated Spin-Coating and Quenching
Daniel O. Baumann, Felix Laufer, Julie Roger, et al.
ACS Applied Materials & Interfaces (2024)
Closed Access | Times Cited: 3
A machine vision tool for facilitating the optimization of large-area perovskite photovoltaics
Nina Taherimakhsousi, Mathilde Fievez, Benjamin P. MacLeod, et al.
npj Computational Materials (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 22
Accelerated innovation in developing high-performance metal halide perovskite solar cell using machine learning
Anjan Kumar, Sangeeta Singh, Mustafa K. A. Mohammed, et al.
International Journal of Modern Physics B (2022) Vol. 37, Iss. 07
Closed Access | Times Cited: 15
Accelerated chemical space search using a quantum-inspired cluster expansion approach
Hitarth Choubisa, Jehad Abed, Douglas Mendoza, et al.
Matter (2022) Vol. 6, Iss. 2, pp. 605-625
Open Access | Times Cited: 15
From Stochastic Self‐Assembly of Nanoparticles to Nanostructured (Photo)Electrocatalysts for Renewable Power‐to‐X Applications via Scalable Flame Synthesis
Thành Trần‐Phú, Rahman Daiyan, Xuan Minh Chau Ta, et al.
Advanced Functional Materials (2021) Vol. 32, Iss. 13
Open Access | Times Cited: 18
Machine Learning Methods to Improve Crystallization through the Prediction of Solute–Solvent Interactions
Aatish Kandaswamy, Sebastian P. Schwaminger
Crystals (2024) Vol. 14, Iss. 6, pp. 501-501
Open Access | Times Cited: 2
Comprehensive review of advances in machine-learning-driven optimization and characterization of perovskite materials for photovoltaic devices
Bonghyun Jo, Wenning Chen, Hyun Suk Jung
Journal of Energy Chemistry (2024) Vol. 101, pp. 298-323
Closed Access | Times Cited: 2
A Comprehensive Review of Machine Learning Applications in Perovskite Solar Cells: Materials Discovery, Device Performance, Process Optimization and Systems Integration
Ling Mao, Changying Xiang
Materials Today Energy (2024) Vol. 47, pp. 101742-101742
Closed Access | Times Cited: 2

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