Sang-Won Kim

1.1k citations
26 papers · 911 indexed · 1 hit paper · h-index 15
Topics
Adsorption and biosorption for pollutant removal (12 papers)Membrane Separation Technologies (8 papers)Membrane-based Ion Separation Techniques (5 papers)

In The Last Decade

Sang-Won Kim

26 papers receiving 881 citations

Hit Papers

Machine-learning-based prediction and optimization of eme...202320262024202520234080120

Peers

Sang-Won Kim
Comparison fields: 5 of 94
  • Water Science and Technology 446
  • Biomedical Engineering 296
  • Industrial and Manufacturing Engineering 193
  • Pollution 153
  • Materials Chemistry 142
Replace Omoniyi Pereao with:
Omoniyi Pereao South Africa
Felicitas U. Iwuchukwu Nigeria
Guoxue Li China
Jiahao Mo China
Shengfan Wang China
Jianguang Shao China
Haifeng Wen China
Heidi Richards South Africa
Rakesh Shrestha Nepal
Sang-Won Kim relative to Omoniyi Pereao South Africa Omoniyi Pereao's profile →
Citations per field
00.5×2.7×
Omoniyi Pereao · 1×
Citations per year

Countries citing papers authored by Sang-Won Kim

Since Specialization
Citations

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

Fields of papers citing papers by Sang-Won Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sang-Won Kim. 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 Sang-Won Kim. The network helps show where Sang-Won Kim may publish in the future.

Co-authorship network of co-authors of Sang-Won Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Sang-Won Kim. A scholar is included among the top collaborators of Sang-Won Kim 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 Sang-Won Kim. Sang-Won Kim 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
#WorkIndexed citations
1 3
2 2
3
Machine-learning-based prediction and optimization of emerging contaminants' adsorption capacity on biochar materialsbreakdown →
127
4 37
5 16
6 42
7 13
8 44
9 21
10 3
11 33
12 5
13 97
14 27
15 43
16 120
17 3
18
Effects of Welding Parameters on the Friction Stir Weldability of 5052 AI alloy
1
19 62
20 42

About Sang-Won Kim

Sang-Won Kim is a scholar working on Water Science and Technology, Industrial and Manufacturing Engineering and Energy Engineering and Power Technology, having authored 26 papers that have together received 911 indexed citations. Recurring topics across this work include Adsorption and biosorption for pollutant removal (12 papers), Membrane Separation Technologies (8 papers) and Membrane-based Ion Separation Techniques (5 papers). The work is most often cited by research in Water Science and Technology (446 citations), Industrial and Manufacturing Engineering (193 citations) and Pollution (153 citations). Sang-Won Kim has collaborated with scholars based in South Korea, Australia and Japan. Frequent co-authors include Kangmin Chon, Jaegwan Shin, Yong-Gu Lee, Jinwoo Kwak, Yongeun Park, Changgil Son, Kyung Hwa Cho, Sang-Ho Lee, Sangho Lee and Jihye Kim. Their work appears in journals such as ACS Nano, Journal of Hazardous Materials and Journal of Cleaner Production.

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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