Weihao Tang

818 total citations
31 papers, 566 citations indexed

About

Weihao Tang is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Weihao Tang has authored 31 papers receiving a total of 566 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Computational Theory and Mathematics and 6 papers in Materials Chemistry. Recurrent topics in Weihao Tang's work include Computational Drug Discovery Methods (6 papers), Chemistry and Chemical Engineering (4 papers) and Nanoparticles: synthesis and applications (3 papers). Weihao Tang is often cited by papers focused on Computational Drug Discovery Methods (6 papers), Chemistry and Chemical Engineering (4 papers) and Nanoparticles: synthesis and applications (3 papers). Weihao Tang collaborates with scholars based in China, United States and Denmark. Weihao Tang's co-authors include Jingwen Chen, Zhongyu Wang, Hong‐Bin Xie, Huixiao Hong, Yiling Cao, Wanxin Tang, Deming Xia, Tong Xu, Xuehua Li and Qing Zhao and has published in prestigious journals such as Angewandte Chemie International Edition, Nature Communications and Environmental Science & Technology.

In The Last Decade

Weihao Tang

29 papers receiving 560 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Weihao Tang China 15 114 105 92 86 82 31 566
Ruiwen Chen United States 16 78 0.7× 45 0.4× 62 0.7× 84 1.0× 140 1.7× 53 778
Fubo Yu China 12 235 2.1× 59 0.6× 149 1.6× 160 1.9× 66 0.8× 19 726
Diego Baderna Italy 17 72 0.6× 200 1.9× 99 1.1× 283 3.3× 346 4.2× 32 958
Giuseppe Nano Italy 19 70 0.6× 15 0.1× 131 1.4× 118 1.4× 144 1.8× 50 847
Wenfang Zhou China 16 170 1.5× 140 1.3× 266 2.9× 33 0.4× 85 1.0× 24 803
Ryo Shoji Japan 12 59 0.5× 29 0.3× 54 0.6× 176 2.0× 117 1.4× 77 545
Mengchen Xu China 15 128 1.1× 16 0.2× 210 2.3× 153 1.8× 183 2.2× 38 673
Mingyang Jing China 14 135 1.2× 26 0.2× 231 2.5× 332 3.9× 386 4.7× 21 946
Rob Onderwater Belgium 14 75 0.7× 51 0.5× 118 1.3× 129 1.5× 58 0.7× 27 675
Xabier Arzuaga United States 18 110 1.0× 21 0.2× 163 1.8× 135 1.6× 448 5.5× 23 957

Countries citing papers authored by Weihao Tang

Since Specialization
Citations

This map shows the geographic impact of Weihao Tang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Weihao Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weihao Tang more than expected).

Fields of papers citing papers by Weihao Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Weihao Tang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Weihao Tang. The network helps show where Weihao Tang may publish in the future.

Co-authorship network of co-authors of Weihao Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Weihao Tang. A scholar is included among the top collaborators of Weihao Tang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Weihao Tang. Weihao Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhang, Xuejiao, Jin Zeng, Jason C. White, et al.. (2025). Mechanistic evaluation of enhanced graphene toxicity to Bacillus induced by humic acid adsorption. Nature Communications. 16(1). 184–184. 4 indexed citations
2.
3.
Tang, Weihao, Xuejiao Zhang, Huixiao Hong, et al.. (2024). Computational Nanotoxicology Models for Environmental Risk Assessment of Engineered Nanomaterials. Nanomaterials. 14(2). 155–155. 15 indexed citations
4.
Chen, Xi, Jingwen Chen, Huaijun Xie, et al.. (2024). Composition and release rates of chemicals in inkjet fabrics determined by non-targeted screening and targeted analysis. Environmental Pollution. 344. 123312–123312. 1 indexed citations
5.
Ma, Fangfang, Weihao Tang, Rongjie Zhang, et al.. (2024). Sulfuric Acid-Driven Nucleation Enhanced by Amines from Ethanol Gasoline Vehicle Emission: Machine Learning Model and Mechanistic Study. Environmental Science & Technology. 58(50). 22278–22287. 3 indexed citations
6.
Ma, Fangfang, Hong‐Bin Xie, Rongjie Zhang, et al.. (2023). Enhancement of Atmospheric Nucleation Precursors on Iodic Acid-Induced Nucleation: Predictive Model and Mechanism. Environmental Science & Technology. 57(17). 6944–6954. 19 indexed citations
7.
Wang, Haiyan, et al.. (2023). A Network Fault Prediction-Based Service Migration Approach for Unstable Mobile Edge Environment. Wireless Communications and Mobile Computing. 2023. 1–13.
8.
Zhao, Qing, Weihao Tang, Mengjie Han, et al.. (2023). Estimation of reduced greenhouse gas emission from municipal solid waste incineration with electricity recovery in prefecture- and county-level cities of China. The Science of The Total Environment. 875. 162654–162654. 19 indexed citations
9.
Liu, Zonghao, et al.. (2023). Zinc and selenium status in coronavirus disease 2019. BioMetals. 36(5). 929–941. 9 indexed citations
10.
Zhong, Haiyi, et al.. (2023). Multiple response behaviors of curcumin-loaded ammonium alginate/polyvinyl alcohol hydrogel and its application. Biomass Conversion and Biorefinery. 14(14). 16121–16139. 14 indexed citations
11.
Xu, Tong, Jingwen Chen, Deming Xia, et al.. (2022). Prediction model on hydrolysis kinetics of phthalate monoester: A density functional theory study. Journal of Environmental Sciences. 135. 51–58. 2 indexed citations
12.
Li, Jing, Le Yue, Qing Zhao, et al.. (2022). Prediction models on biomass and yield of rice affected by metal (oxide) nanoparticles using nano-specific descriptors. NanoImpact. 28. 100429–100429. 5 indexed citations
13.
Wang, Jiayu, Jingwen Chen, Weihao Tang, et al.. (2021). [Dynamic Material Flow Analysis of Perfluorooctane Sulfonate in China: 1985-2019].. Huan jing ke xue= Huanjing kexue. 42(9). 4566–4574. 2 indexed citations
14.
Tang, Weihao, et al.. (2021). Machine learning models on chemical inhibitors of mitochondrial electron transport chain. Journal of Hazardous Materials. 426. 128067–128067. 12 indexed citations
15.
16.
Tang, Weihao, Jingwen Chen, & Huixiao Hong. (2020). Development of classification models for predicting inhibition of mitochondrial fusion and fission using machine learning methods. Chemosphere. 273. 128567–128567. 13 indexed citations
17.
Tang, Weihao, Jingwen Chen, & Huixiao Hong. (2020). Discriminant models on mitochondrial toxicity improved by consensus modeling and resolving imbalance in training. Chemosphere. 253. 126768–126768. 22 indexed citations
18.
Zhang, Liang, et al.. (2019). Identification of prognosis‐related alternative splicing events in kidney renal clear cell carcinoma. Journal of Cellular and Molecular Medicine. 23(11). 7762–7772. 14 indexed citations
19.
Liu, Cong, Fangfang Ma, Jonas Elm, et al.. (2019). Mechanism and predictive model development of reaction rate constants for N-center radicals with O2. Chemosphere. 237. 124411–124411. 14 indexed citations
20.
Wang, Ya, Jingwen Chen, Weihao Tang, et al.. (2018). Modeling adsorption of organic pollutants onto single-walled carbon nanotubes with theoretical molecular descriptors using MLR and SVM algorithms. Chemosphere. 214. 79–84. 39 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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