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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 in experimental materials chemistry
Balaranjan Selvaratnam, Ranjit T. Koodali
Catalysis Today (2020) Vol. 371, pp. 77-84
Open Access | Times Cited: 50

Showing 1-25 of 50 citing articles:

Machine Learning: New Ideas and Tools in Environmental Science and Engineering
Shifa Zhong, Kai Zhang, Majid Bagheri, et al.
Environmental Science & Technology (2021)
Closed Access | Times Cited: 612
Neural Network Potentials: A Concise Overview of Methods
Emir Kocer, Tsz Wai Ko, Jörg Behler
Annual Review of Physical Chemistry (2022) Vol. 73, Iss. 1, pp. 163-186
Open Access | Times Cited: 171
Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and Reactors
Li‐Tao Zhu, Xizhong Chen, Bo Ouyang, et al.
Industrial & Engineering Chemistry Research (2022) Vol. 61, Iss. 28, pp. 9901-9949
Open Access | Times Cited: 133
Machine learning methods for modeling conventional and hydrothermal gasification of waste biomass: A review
Great C. Umenweke, Inioluwa Christianah Afolabi, Emmanuel I. Epelle, et al.
Bioresource Technology Reports (2022) Vol. 17, pp. 100976-100976
Closed Access | Times Cited: 81
AI for Nanomaterials Development in Clean Energy and Carbon Capture, Utilization and Storage (CCUS)
Honghao Chen, Yingzhe Zheng, Jiali Li, et al.
ACS Nano (2023) Vol. 17, Iss. 11, pp. 9763-9792
Closed Access | Times Cited: 38
Recent advances and future prospects of thermochemical biofuel conversion processes with machine learning
Pil Rip Jeon, Jong-Ho Moon, Nafiu Olanrewaju Ogunsola, et al.
Chemical Engineering Journal (2023) Vol. 471, pp. 144503-144503
Open Access | Times Cited: 38
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
Machine Learning Aided Design and Optimization of Thermal Metamaterials
Changliang Zhu, Emmanuel Anuoluwa Bamidele, Xiangying Shen, et al.
Chemical Reviews (2024) Vol. 124, Iss. 7, pp. 4258-4331
Open Access | Times Cited: 17
Accelerated exploration of heterogeneous CO2 hydrogenation catalysts by Bayesian-optimized high-throughput and automated experimentation
Adrián Ramírez, Erwin Lam, Daniel Pacheco Gutiérrez, et al.
Chem Catalysis (2024) Vol. 4, Iss. 2, pp. 100888-100888
Closed Access | Times Cited: 14
Machine learning for design principles for single atom catalysts towards electrochemical reactions
Mohsen Tamtaji, Hanyu Gao, Md Delowar Hossain, et al.
Journal of Materials Chemistry A (2022) Vol. 10, Iss. 29, pp. 15309-15331
Open Access | Times Cited: 63
The case for data science in experimental chemistry: examples and recommendations
Junko Yano, Kelly J. Gaffney, John M. Gregoire, et al.
Nature Reviews Chemistry (2022) Vol. 6, Iss. 5, pp. 357-370
Open Access | Times Cited: 60
From prediction to design: Recent advances in machine learning for the study of 2D materials
Hua He, Yuhua Wang, Yajuan Qi, et al.
Nano Energy (2023) Vol. 118, pp. 108965-108965
Closed Access | Times Cited: 33
Deep‐Learning‐Enabled Intelligent Design of Thermal Metamaterials
Yihui Wang, Wei Sha, Mi Xiao, et al.
Advanced Materials (2023) Vol. 35, Iss. 33
Closed Access | Times Cited: 30
Insights into Preparation Methods and Functions of Carbon-Based Solid Acids
Shu Dong, Jian Zhang, Roger Ruan, et al.
Molecules (2024) Vol. 29, Iss. 1, pp. 247-247
Open Access | Times Cited: 6
Challenges and Opportunities for Renewable Ammonia Production via Plasmon‐Assisted Photocatalysis
Begoña Puértolas, Miguel Comesaña‐Hermo, Lucas V. Besteiro, et al.
Advanced Energy Materials (2022) Vol. 12, Iss. 18
Open Access | Times Cited: 35
Assessing the potential of machine learning methods to study the removal of pharmaceuticals from wastewater using biochar or activated carbon
Jude A. Okolie, Shauna Savage, Chukwuma C. Ogbaga, et al.
Total Environment Research Themes (2022) Vol. 1-2, pp. 100001-100001
Open Access | Times Cited: 31
A Smart Gas Sensor Using Machine Learning Algorithms: Sensor Types Based on IED Configurations, Fabrication Techniques, Algorithmic Approaches, Challenges, Progress, and Limitations: A Review
Abdelghaffar Nasri, Aicha Boujnah, Aïmen Boubaker, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 11, pp. 11336-11355
Closed Access | Times Cited: 18
Modeling and prediction of biodiesel production by using different artificial intelligence methods: Multi-layer perceptron (MLP), Gradient boosting (GB), and Gaussian process regression (GPR)
Abdulrahman Sumayli, Saad M. Alshahrani
Arabian Journal of Chemistry (2023) Vol. 16, Iss. 7, pp. 104801-104801
Open Access | Times Cited: 17
Status and future trends in wastewater management strategies using artificial intelligence and machine learning techniques
G. Baskar, Soghra Nashath Omer, Panchamoorthy Saravanan, et al.
Chemosphere (2024) Vol. 362, pp. 142477-142477
Closed Access | Times Cited: 4
Versatile in silico modelling of microplastics adsorption capacity in aqueous environment based on molecular descriptor and machine learning
Tengyi Zhu, Cuicui Tao, Haomiao Cheng, et al.
The Science of The Total Environment (2022) Vol. 846, pp. 157455-157455
Closed Access | Times Cited: 23
Lung cancer detection by using probabilistic majority voting and optimization techniques
Kubilay Muhammed Sünnetci, Ahmet Alkan
International Journal of Imaging Systems and Technology (2022) Vol. 32, Iss. 6, pp. 2049-2065
Closed Access | Times Cited: 19
A machine learning colorimetric biosensor based on acetylcholinesterase and silver nanoparticles for the detection of dichlorvos pesticides
Wonn Shweyi Thet Tun, Chanon Talodthaisong, Sakda Daduang, et al.
Materials Chemistry Frontiers (2022) Vol. 6, Iss. 11, pp. 1487-1498
Closed Access | Times Cited: 18
Deep learning modeling strategy for material science: from natural materials to metamaterials
Wenwen Li, Pu Chen, Bo Xiong, et al.
Journal of Physics Materials (2022) Vol. 5, Iss. 1, pp. 014003-014003
Open Access | Times Cited: 16
Intelligent analysis of carbendazim in agricultural products based on a ZSHPC/MWCNT/SPE portable nanosensor combined with machine learning methods
Xu Wang, Liang He, Lulu Xu, et al.
Analytical Methods (2023) Vol. 15, Iss. 5, pp. 562-571
Closed Access | Times Cited: 8
Advancing high-throughput combinatorial aging studies of hybrid perovskite thin films via precise automated characterization methods and machine learning assisted analysis
Alexander Wieczorek, Austin G. Kuba, Jan Sommerhäuser, et al.
Journal of Materials Chemistry A (2024) Vol. 12, Iss. 12, pp. 7025-7035
Open Access | Times Cited: 2
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