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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:

Artificial Chemist: An Autonomous Quantum Dot Synthesis Bot
Robert W. Epps, Michael Bowen, Amanda A. Volk, et al.
Advanced Materials (2020) Vol. 32, Iss. 30
Closed Access | Times Cited: 250

Showing 1-25 of 250 citing articles:

Nanoparticle synthesis assisted by machine learning
Huachen Tao, Tianyi Wu, Matteo Aldeghi, et al.
Nature Reviews Materials (2021) Vol. 6, Iss. 8, pp. 701-716
Closed Access | Times Cited: 295
The Role of Machine Learning in the Understanding and Design of Materials
Seyed Mohamad Moosavi, Kevin Maik Jablonka, Berend Smit
Journal of the American Chemical Society (2020) Vol. 142, Iss. 48, pp. 20273-20287
Open Access | Times Cited: 284
Autonomous experimentation systems for materials development: A community perspective
Eric A. Stach, Brian DeCost, A. Gilad Kusne, et al.
Matter (2021) Vol. 4, Iss. 9, pp. 2702-2726
Open Access | Times Cited: 244
The rise of self-driving labs in chemical and materials sciences
Milad Abolhasani, Eugenia Kumacheva
Nature Synthesis (2023) Vol. 2, Iss. 6, pp. 483-492
Open Access | Times Cited: 235
Selective, sensitive, and stable NO2 gas sensor based on porous ZnO nanosheets
Myung Sik Choi, Min Young Kim, Ali Mirzaei, et al.
Applied Surface Science (2021) Vol. 568, pp. 150910-150910
Closed Access | Times Cited: 211
Data-driven materials research enabled by natural language processing and information extraction
Elsa Olivetti, Jacqueline M. Cole, Edward Kim, et al.
Applied Physics Reviews (2020) Vol. 7, Iss. 4
Open Access | Times Cited: 206
Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning
Aditya Nandy, Chenru Duan, Michael G. Taylor, et al.
Chemical Reviews (2021) Vol. 121, Iss. 16, pp. 9927-10000
Closed Access | Times Cited: 197
Machine learning for a sustainable energy future
Zhenpeng Yao, Yanwei Lum, Andrew Johnston, et al.
Nature Reviews Materials (2022) Vol. 8, Iss. 3, pp. 202-215
Open Access | Times Cited: 195
Machine learning in materials science: From explainable predictions to autonomous design
Ghanshyam Pilania
Computational Materials Science (2021) Vol. 193, pp. 110360-110360
Open Access | Times Cited: 165
MatSciBERT: A materials domain language model for text mining and information extraction
Tanishq Gupta, Mohd Zaki, N. M. Anoop Krishnan, et al.
npj Computational Materials (2022) Vol. 8, Iss. 1
Open Access | Times Cited: 148
Two-step machine learning enables optimized nanoparticle synthesis
Flore Mekki‐Berrada, Zekun Ren, Tan Huang, et al.
npj Computational Materials (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 133
Machine Learning‐Driven Biomaterials Evolution
Ady Suwardi, Fuke Wang, Kun Xue, et al.
Advanced Materials (2021) Vol. 34, Iss. 1
Closed Access | Times Cited: 123
A data fusion approach to optimize compositional stability of halide perovskites
Shijing Sun, Armi Tiihonen, Felipe Oviedo, et al.
Matter (2021) Vol. 4, Iss. 4, pp. 1305-1322
Open Access | Times Cited: 122
A self-driving laboratory advances the Pareto front for material properties
Benjamin P. MacLeod, Fraser G. L. Parlane, Connor C. Rupnow, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 113
Material Evolution with Nanotechnology, Nanoarchitectonics, and Materials Informatics: What will be the Next Paradigm Shift in Nanoporous Materials?
Watcharop Chaikittisilp, Yusuke Yamauchi, Katsuhiko Ariga
Advanced Materials (2021) Vol. 34, Iss. 7
Closed Access | Times Cited: 112
Ready, Set, Flow! Automated Continuous Synthesis and Optimization
C. Breen, Anirudh M. K. Nambiar, Timothy F. Jamison, et al.
Trends in Chemistry (2021) Vol. 3, Iss. 5, pp. 373-386
Open Access | Times Cited: 102
Recent advances in quantum dot catalysts for hydrogen evolution: Synthesis, characterization, and photocatalytic application
Haiwei Su, Weikang Wang, Run Shi, et al.
Carbon Energy (2023) Vol. 5, Iss. 9
Open Access | Times Cited: 94
Data‐Driven Materials Innovation and Applications
Zhuo Wang, Zhehao Sun, Hang Yin, et al.
Advanced Materials (2022) Vol. 34, Iss. 36
Closed Access | Times Cited: 92
An artificial intelligence enabled chemical synthesis robot for exploration and optimization of nanomaterials
Y. Jiang, Daniel Salley, Abhishek Sharma, et al.
Science Advances (2022) Vol. 8, Iss. 40
Open Access | Times Cited: 89
Artificial intelligence to bring nanomedicine to life
Nikita Serov, Vladimir V. Vinogradov
Advanced Drug Delivery Reviews (2022) Vol. 184, pp. 114194-114194
Closed Access | Times Cited: 76
AlphaFlow: autonomous discovery and optimization of multi-step chemistry using a self-driven fluidic lab guided by reinforcement learning
Amanda A. Volk, Robert W. Epps, Daniel T. Yonemoto, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 76
Machine Learning Guided Synthesis of Flash Graphene
Jacob L. Beckham, Kevin M. Wyss, Yunchao Xie, et al.
Advanced Materials (2022) Vol. 34, Iss. 12
Open Access | Times Cited: 70
Bridging Multiscale Characterization Technologies and Digital Modeling to Evaluate Lithium Battery Full Lifecycle
Xinhua Liu, Lisheng Zhang, Hanqing Yu, et al.
Advanced Energy Materials (2022) Vol. 12, Iss. 33
Closed Access | Times Cited: 66
Self-Driving Laboratory for Polymer Electronics
Aikaterini Vriza, Henry Chan, Jie Xu
Chemistry of Materials (2023) Vol. 35, Iss. 8, pp. 3046-3056
Closed Access | Times Cited: 44
Machine learning accelerates the investigation of targeted MOFs: Performance prediction, rational design and intelligent synthesis
Jing Lin, Zhimeng Liu, Yujie Guo, et al.
Nano Today (2023) Vol. 49, pp. 101802-101802
Closed Access | Times Cited: 36
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