Ndeke Musee

1.8k total citations
48 papers, 1.3k citations indexed

About

Ndeke Musee is a scholar working on Materials Chemistry, Biomedical Engineering and Pollution. According to data from OpenAlex, Ndeke Musee has authored 48 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Materials Chemistry, 19 papers in Biomedical Engineering and 16 papers in Pollution. Recurrent topics in Ndeke Musee's work include Nanoparticles: synthesis and applications (27 papers), Graphene and Nanomaterials Applications (8 papers) and Microplastics and Plastic Pollution (7 papers). Ndeke Musee is often cited by papers focused on Nanoparticles: synthesis and applications (27 papers), Graphene and Nanomaterials Applications (8 papers) and Microplastics and Plastic Pollution (7 papers). Ndeke Musee collaborates with scholars based in South Africa, India and United States. Ndeke Musee's co-authors include Melusi Thwala, Johann W. Wiechers, L. Lorenzen, Chris Aldrich, Lucky Sikhwivhilu, Victor Wepener, Stephen J. Klaine, Don A. Cowan, Walter W. Focke and Anna‐Maria Botha and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and Journal of Hazardous Materials.

In The Last Decade

Ndeke Musee

44 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ndeke Musee South Africa 21 770 343 298 200 135 48 1.3k
Weicheng Zhang China 20 551 0.7× 186 0.5× 402 1.3× 100 0.5× 255 1.9× 42 1.0k
Muniyandi Biruntha India 22 346 0.4× 223 0.7× 337 1.1× 92 0.5× 306 2.3× 33 1.5k
Bin Dong China 21 283 0.4× 275 0.8× 460 1.5× 166 0.8× 367 2.7× 61 1.5k
Woojin Chung South Korea 20 279 0.4× 325 0.9× 328 1.1× 101 0.5× 340 2.5× 55 1.6k
Pouran Makhdoumi Iran 16 299 0.4× 186 0.5× 685 2.3× 188 0.9× 461 3.4× 29 1.3k
Hooshyar Hossini Iran 21 386 0.5× 292 0.9× 828 2.8× 238 1.2× 614 4.5× 77 1.8k
Amina Amina China 11 248 0.3× 161 0.5× 226 0.8× 134 0.7× 68 0.5× 24 728
Zahra Khodaparast Portugal 13 211 0.3× 265 0.8× 215 0.7× 127 0.6× 190 1.4× 22 961
Mazhar Iqbal Zafar Pakistan 19 172 0.2× 105 0.3× 277 0.9× 270 1.4× 105 0.8× 44 999
Simona Schiavo Italy 18 424 0.6× 111 0.3× 530 1.8× 272 1.4× 216 1.6× 23 1.0k

Countries citing papers authored by Ndeke Musee

Since Specialization
Citations

This map shows the geographic impact of Ndeke Musee'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 Ndeke Musee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ndeke Musee more than expected).

Fields of papers citing papers by Ndeke Musee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ndeke Musee. 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 Ndeke Musee. The network helps show where Ndeke Musee may publish in the future.

Co-authorship network of co-authors of Ndeke Musee

This figure shows the co-authorship network connecting the top 25 collaborators of Ndeke Musee. A scholar is included among the top collaborators of Ndeke Musee 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 Ndeke Musee. Ndeke Musee 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.
Musee, Ndeke, et al.. (2024). Developing machine learning algorithms to predict the dissolution of zinc oxide nanoparticles in aqueous environment. Environmental Nanotechnology Monitoring & Management. 22. 101000–101000.
2.
Musee, Ndeke, et al.. (2023). Modelling ecological risks of antiretroviral drugs in the environment. SHILAP Revista de lepidopterología. 5. 145–154. 4 indexed citations
3.
Musee, Ndeke, et al.. (2023). Occurrence, effects, and ecological risks of chemicals in sanitizers and disinfectants: A review. SHILAP Revista de lepidopterología. 5. 62–78. 22 indexed citations
4.
Musee, Ndeke, et al.. (2023). Evaluation of Apical and Molecular Effects of Algae Pseudokirchneriella subcapitata to Cerium Oxide Nanoparticles. Toxics. 11(3). 283–283. 7 indexed citations
5.
Musee, Ndeke, et al.. (2023). Meta-analysis of engineered nanoparticles dynamic aggregation in freshwater-like systems using machine learning techniques. Journal of Environmental Management. 337. 117739–117739. 4 indexed citations
6.
Kebaabetswe, Lemme P., et al.. (2022). Proteomic evaluation of nanotoxicity in aquatic organisms: A review. PROTEOMICS. 22(21). e2200008–e2200008. 3 indexed citations
7.
Musee, Ndeke, et al.. (2022). Effects of Two Antiretroviral Drugs on the Crustacean Daphnia magna in River Water. Toxics. 10(8). 423–423. 8 indexed citations
8.
Thwala, Melusi, Stephen J. Klaine, & Ndeke Musee. (2021). Exposure Media and Nanoparticle Size Influence on the Fate, Bioaccumulation, and Toxicity of Silver Nanoparticles to Higher Plant Salvinia minima. Molecules. 26(8). 2305–2305. 20 indexed citations
9.
Musee, Ndeke. (2018). Comment on “Risk Assessments Show Engineered Nanomaterials To Be of Low Environmental Concern”. Environmental Science & Technology. 52(12). 6723–6724. 7 indexed citations
10.
Musee, Ndeke. (2018). Environmental risk assessment of triclosan and triclocarban from personal care products in South Africa. Environmental Pollution. 242(Pt A). 827–838. 36 indexed citations
11.
Focke, Walter W., et al.. (2017). Kinetic interpretation of log-logistic dose-time response curves. Scientific Reports. 7(1). 2234–2234. 27 indexed citations
12.
Musee, Ndeke, et al.. (2013). Fate and behavior of ZnO- and Ag-engineered nanoparticles and a bacterial viability assessment in a simulated wastewater treatment plant. Journal of Environmental Science and Health Part A. 49(1). 59–66. 28 indexed citations
13.
Thwala, Melusi, Ndeke Musee, Lucky Sikhwivhilu, & Victor Wepener. (2013). The oxidative toxicity of Ag and ZnO nanoparticles towards the aquatic plant Spirodela punctuta and the role of testing media parameters. Environmental Science Processes & Impacts. 15(10). 1830–1830. 88 indexed citations
14.
Musee, Ndeke, Alan C. Brent, & P. J. Ashton. (2010). A South African research agenda to investigate the potential environmental, health and safety risks of nanotechnology : research article. South African Journal of Science. 106. 1–6. 10 indexed citations
15.
Musee, Ndeke, et al.. (2010). SA hopes to answer big questions around the impact of small science : emerging issues. 9(5). 14–17. 1 indexed citations
16.
Musee, Ndeke. (2010). Nanowastes and the environment: Potential new waste management paradigm. Environment International. 37(1). 112–128. 102 indexed citations
17.
Wiechers, Johann W. & Ndeke Musee. (2010). Engineered Inorganic Nanoparticles and Cosmetics: Facts, Issues, Knowledge Gaps and Challenges. Journal of Biomedical Nanotechnology. 6(5). 408–431. 122 indexed citations
18.
Musee, Ndeke, Chris Aldrich, & L. Lorenzen. (2008). New methodology for hazardous waste classification using fuzzy set theory. Journal of Hazardous Materials. 157(1). 94–105. 18 indexed citations
19.
Musee, Ndeke, L. Lorenzen, & Chris Aldrich. (2007). New methodology for hazardous waste classification using fuzzy set theory. Journal of Hazardous Materials. 154(1-3). 1040–1051. 33 indexed citations
20.
Musee, Ndeke, L. Lorenzen, & Chris Aldrich. (2006). An aggregate fuzzy hazardous index for composite wastes. Journal of Hazardous Materials. 137(2). 723–733. 20 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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