Hai Doan

655 citations
23 papers · 552 · h-index 11

Impact in

Papers in

Hai Doan

23 papers receiving 545 citations

Peers

Hai Doan
Comparison fields: 5 of 86
  • Pollution 157
  • Health, Toxicology and Mutagenesis 149
  • Water Science and Technology 127
  • Molecular Medicine 40
  • Biomaterials 97
Replace Mohammad A. Khiyami with:
Mohammad A. Khiyami Saudi Arabia
Elvio D. Amato Australia
Sumistha Das India
Kaibin Li China
A. Ganesh Kumar India
Shweta Jaiswal India
Yong-Wook Baek South Korea
Swayamprava Dalai India
Simon Lüderwald Germany
Maria Ludovica Saccà Italy
Hai Doan relative to Mohammad A. Khiyami Saudi Arabia Mohammad A. Khiyami's profile →
Citations per field
00.5×5.1×
Mohammad A. Khiyami · 1×
Citations per year

Countries citing papers authored by Hai Doan

Since Specialization
Citations

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

Fields of papers citing papers by Hai Doan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hai Doan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hai Doan Line = papers co-authored together Hai Doan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201697
2 201679
3 201771
4 201657
5 201042
6 202030
7 201530
8 201623
9 201717
10 201817
11 201916
12 201610
13 202010
14 20159
15 20189
16 20108
17 20188
18 20207
19 20195
20 20232

About Hai Doan

Hai Doan is a scholar working on Biomedical Engineering, Health, Toxicology and Mutagenesis, Biomaterials, Pollution and Molecular Medicine, having authored 23 papers that have together received 552 indexed citations. Recurring topics across this work include Nanoparticle-Based Drug Delivery (7 papers), Graphene and Nanomaterials Applications (7 papers), Environmental Toxicology and Ecotoxicology (5 papers), Pharmaceutical and Antibiotic Environmental Impacts (4 papers), Nanoplatforms for cancer theranostics (3 papers), Curcumin's Biomedical Applications (3 papers), Flame retardant materials and properties (2 papers) and Nanoparticles: synthesis and applications (2 papers). The work is most often cited by research in Pollution (157 citations), Health, Toxicology and Mutagenesis (149 citations), Water Science and Technology (127 citations), Molecular Medicine (40 citations) and Biomaterials (97 citations). Hai Doan has collaborated with scholars based in Vietnam, Australia and China. Frequent co-authors include Anupama Kumar, Rai S. Kookana, Jun Du, Mike Williams, Bin Yang, Phuong Thu Ha, Guang‐Guo Ying, Sharon E. Hook, Melony J. Sellars and Joab Chapman. Their work appears in journals such as Advances in Natural Sciences Nanoscience and Nanotechnology, Ecotoxicology and Environmental Safety, Journal of Hazardous Materials, Water Science & Technology and Chemosphere.

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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