Gichang Noh

723 citations
21 papers · 439 indexed · h-index 10
Topics
Advanced Memory and Neural Computing (13 papers)2D Materials and Applications (8 papers)Ferroelectric and Negative Capacitance Devices (7 papers)
Journals
SHILAP Revista de lepidopterologíaNano LettersACS Nano

In The Last Decade

Gichang Noh

19 papers receiving 425 citations

Peers

Gichang Noh
Comparison fields: 5 of 27
  • Materials Chemistry 300
  • Electrical and Electronic Engineering 217
  • Atomic and Molecular Physics, and Optics 102
  • Biomedical Engineering 63
  • Artificial Intelligence 46
Replace Weijun Cheng with:
Weijun Cheng China
Seokhyeong Lee United States
Zhuiri Peng China
Guilherme Migliato Marega Switzerland
Xun Ge China
Manh‐Ha Doan South Korea
Qixiao Zhao China
Chawina De-Eknamkul United States
Minh Dao Tran South Korea
Xiangnan Xie China
Gichang Noh relative to Weijun Cheng China Weijun Cheng's profile →
Citations per field
00.5×
Weijun Cheng · 1×
Citations per year

Countries citing papers authored by Gichang Noh

Since Specialization
Citations

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

Fields of papers citing papers by Gichang Noh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gichang Noh

This figure shows the co-authorship network connecting the top 25 collaborators of Gichang Noh. A scholar is included among the top collaborators of Gichang Noh 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 Gichang Noh. Gichang Noh 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 2
2 2
3 1
4 9
5 1
6 3
7 0
8 5
9 9
10 5
11 2
12 32
13 19
14 11
15 37
16 40
17 1
18 45
19 44
20 144

About Gichang Noh

Gichang Noh is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Cognitive Neuroscience, having authored 21 papers that have together received 439 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (13 papers), 2D Materials and Applications (8 papers) and Ferroelectric and Negative Capacitance Devices (7 papers). The work is most often cited by research in Materials Chemistry (300 citations), Electrical and Electronic Engineering (217 citations) and Atomic and Molecular Physics, and Optics (102 citations). Gichang Noh has collaborated with scholars based in South Korea, United States and Russia. Frequent co-authors include Jieun Lee, Hosung Seo, Yoon-Ho Kim, Joon Young Kwak, Eunpyo Park, Je‐Hyung Kim, Hyoju Kim, Kibum Kang, YeonJoo Jeong and Minsoo Kang. Their work appears in journals such as SHILAP Revista de lepidopterología, Nano Letters and ACS Nano.

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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