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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:

Screening Priority Factors Determining and Predicting the Reproductive Toxicity of Various Nanoparticles
Zhan Ban, Qixing Zhou, Anqi Sun, et al.
Environmental Science & Technology (2018) Vol. 52, Iss. 17, pp. 9666-9676
Closed Access | Times Cited: 60

Showing 1-25 of 60 citing articles:

Machine learning prediction of biochar yield and carbon contents in biochar based on biomass characteristics and pyrolysis conditions
Xinzhe Zhu, Yinan Li, Xiaonan Wang
Bioresource Technology (2019) Vol. 288, pp. 121527-121527
Closed Access | Times Cited: 325
Prediction of Soil Heavy Metal Immobilization by Biochar Using Machine Learning
Kumuduni Niroshika Palansooriya, Jie Li, Pavani Dulanja Dissanayake, et al.
Environmental Science & Technology (2022) Vol. 56, Iss. 7, pp. 4187-4198
Open Access | Times Cited: 290
Machine learning predicts the functional composition of the protein corona and the cellular recognition of nanoparticles
Zhan Ban, Peng Yuan, Fubo Yu, et al.
Proceedings of the National Academy of Sciences (2020) Vol. 117, Iss. 19, pp. 10492-10499
Open Access | Times Cited: 200
Machine learning prediction of pyrolytic gas yield and compositions with feature reduction methods: Effects of pyrolysis conditions and biomass characteristics
Qinghui Tang, Yingquan Chen, Haiping Yang, et al.
Bioresource Technology (2021) Vol. 339, pp. 125581-125581
Closed Access | Times Cited: 126
Deep exploration of random forest model boosts the interpretability of machine learning studies of complicated immune responses and lung burden of nanoparticles
Fubo Yu, Changhong Wei, Peng Deng, et al.
Science Advances (2021) Vol. 7, Iss. 22
Open Access | Times Cited: 117
Environmental behavior, human health effect, and pollution control of heavy metal(loid)s toward full life cycle processes
Haoyu Deng, Yuling Tu, Han Wang, et al.
Eco-Environment & Health (2022) Vol. 1, Iss. 4, pp. 229-243
Open Access | Times Cited: 75
Design of experiments in the optimization of nanoparticle-based drug delivery systems
Riccardo Rampado, Dan Peer
Journal of Controlled Release (2023) Vol. 358, pp. 398-419
Closed Access | Times Cited: 55
Exposure to PbSe Nanoparticles and Male Reproductive Damage in a Rat Model
Qixing Zhou, Zongkai Yue, Qingzhao Li, et al.
Environmental Science & Technology (2019) Vol. 53, Iss. 22, pp. 13408-13416
Open Access | Times Cited: 96
Practices and Trends of Machine Learning Application in Nanotoxicology
Irini Furxhi, Finbarr Murphy, Martin Mullins, et al.
Nanomaterials (2020) Vol. 10, Iss. 1, pp. 116-116
Open Access | Times Cited: 89
Machine learning may accelerate the recognition and control of microplastic pollution: Future prospects
Fubo Yu, Xiangang Hu
Journal of Hazardous Materials (2022) Vol. 432, pp. 128730-128730
Closed Access | Times Cited: 43
Machine learning in the identification, prediction and exploration of environmental toxicology: Challenges and perspectives
Xiaotong Wu, Qixing Zhou, Mu Li, et al.
Journal of Hazardous Materials (2022) Vol. 438, pp. 129487-129487
Closed Access | Times Cited: 40
Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation
Xiliang Yan, Tongtao Yue, David A. Winkler, et al.
Chemical Reviews (2023) Vol. 123, Iss. 13, pp. 8575-8637
Closed Access | Times Cited: 33
Development potential of nanoenabled agriculture projected using machine learning
Peng Deng, Yiming Gao, Mu Li, et al.
Proceedings of the National Academy of Sciences (2023) Vol. 120, Iss. 25
Open Access | Times Cited: 24
Predicting the binding configuration and release potential of heavy metals on iron (oxyhydr)oxides: A machine learning study on EXAFS
Junqin Liu, Jiang Zhao, Jiapan Du, et al.
Journal of Hazardous Materials (2024) Vol. 468, pp. 133797-133797
Closed Access | Times Cited: 9
Nanotoxicology data for in silico tools: a literature review
Irini Furxhi, Finbarr Murphy, Martin Mullins, et al.
Nanotoxicology (2020) Vol. 14, Iss. 5, pp. 612-637
Closed Access | Times Cited: 62
Quo Vadis, Nanoparticle-Enabled In Vivo Fluorescence Imaging?
Erving Ximendes, Antonio Benayas, Daniel Jaque, et al.
ACS Nano (2021) Vol. 15, Iss. 2, pp. 1917-1941
Open Access | Times Cited: 42
Algal community structure prediction by machine learning
Muyuan Liu, Yuzhou Huang, Jing Hu, et al.
Environmental Science and Ecotechnology (2022) Vol. 14, pp. 100233-100233
Open Access | Times Cited: 37
Using Machine Learning to make nanomaterials sustainable
Janeck J. Scott‐Fordsmand, Mónica J.B. Amorim
The Science of The Total Environment (2022) Vol. 859, pp. 160303-160303
Open Access | Times Cited: 33
Calcium Nanoparticles Induce Oxidative Stress in Erythrocytes, Neurotoxicity and Testicular Toxicity in Albino Rats (Rattus norvegicus)
Ahsan Ullah, Fatimah A. Al‐Saeed, Alduwish Manal Abduallah, et al.
Pakistan Veterinary Journal (2023) Vol. 43, Iss. 2, pp. 241-247
Open Access | Times Cited: 20
Knowledge gaps in immune response and immunotherapy involving nanomaterials: Databases and artificial intelligence for material design
Ruihong Feng, Fubo Yu, Jing Xu, et al.
Biomaterials (2020) Vol. 266, pp. 120469-120469
Closed Access | Times Cited: 41
Untargeted Metabolic Pathway Analysis as an Effective Strategy to Connect Various Nanoparticle Properties to Nanoparticle-Induced Ecotoxicity
Xiaokang Li, Zhan Ban, Fubo Yu, et al.
Environmental Science & Technology (2020) Vol. 54, Iss. 6, pp. 3395-3406
Closed Access | Times Cited: 40
Toxicity mechanisms of nanoparticles in the male reproductive system
Khaled Habas, Eşref Demir, Chongye Guo, et al.
Drug Metabolism Reviews (2021) Vol. 53, Iss. 4, pp. 604-617
Open Access | Times Cited: 39
Predicting Bioaccumulation of Nanomaterials: Modeling Approaches with Challenges
Hang Zeng, Zhuoyan Lv, Xiaoyan Sun, et al.
Environment & Health (2024) Vol. 2, Iss. 4, pp. 189-201
Open Access | Times Cited: 5
Predicting nanotoxicity by an integrated machine learning and metabolomics approach
Ting Peng, Changhong Wei, Fubo Yu, et al.
Environmental Pollution (2020) Vol. 267, pp. 115434-115434
Closed Access | Times Cited: 37
Super-learner model realizes the transient prediction of CO2 and NOx of diesel trucks: Model development, evaluation and interpretation
Ning Wei, Qijun Zhang, Yanjie Zhang, et al.
Environment International (2021) Vol. 158, pp. 106977-106977
Open Access | Times Cited: 30
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