Daeseok Lee

2.8k citations
98 papers · 2.4k indexed · h-index 27

Impact in

Papers in

Daeseok Lee

98 papers receiving 2.4k citations

Peers

Daeseok Lee
Comparison fields: 5 of 102
  • Polymers and Plastics 623
  • Electrical and Electronic Engineering 2.2k
  • Cellular and Molecular Neuroscience 589
  • Materials Chemistry 582
  • Cognitive Neuroscience 154
Replace Yifei Pei with:
Yifei Pei China
Abhishek A. Sharma United States
Hong Han China
Henrique L. Gomes Portugal
Qiu‐Xiang Liu China
J. Shappir Israel
Yaakov Tuchman United States
Zhiyuan Zhao China
Junhwan Choi South Korea
Daeseok Lee relative to Yifei Pei China Yifei Pei's profile →
Citations per field
00.5×20×40×60×83×
Yifei Pei · 1×
Citations per year

Countries citing papers authored by Daeseok Lee

Since Specialization
Citations

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

Fields of papers citing papers by Daeseok Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Daeseok Lee, 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 Daeseok Lee Line = papers co-authored together Daeseok Lee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20244
2 20241
3 20241
4 20235
5 20235
6 20225
7 20224
8 202114
9 20206
10 20208
11 201921
12 20193
13 20181
14 201520
15 201417
16 201446
17
Multi-layer tunnel barrier (Ta 2 O 5 /TaO x /TiO 2 ) engineering for bipolar RRAM selector applications
201311
18 201322
19 201232
20 20113

About Daeseok Lee

Daeseok Lee is a scholar working on Polymers and Plastics, Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Bioengineering and Materials Chemistry, having authored 98 papers that have together received 2.4k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (80 papers), Ferroelectric and Negative Capacitance Devices (52 papers), Transition Metal Oxide Nanomaterials (29 papers), Semiconductor materials and devices (25 papers), Neuroscience and Neural Engineering (16 papers), Electronic and Structural Properties of Oxides (14 papers), Neural dynamics and brain function (6 papers) and Photoreceptor and optogenetics research (6 papers). The work is most often cited by research in Polymers and Plastics (623 citations), Electrical and Electronic Engineering (2.2k citations), Cellular and Molecular Neuroscience (589 citations), Materials Chemistry (582 citations) and Cognitive Neuroscience (154 citations). Daeseok Lee has collaborated with scholars based in South Korea, United States and France. Frequent co-authors include Jiyong Woo, Hyunsang Hwang, Euijun Cha, Sangsu Park, Jubong Park, Seonghyun Kim, Wootae Lee, Jeonghwan Song, Jungho Shin and Amit Prakash. Their work appears in journals such as IEEE Electron Device Letters, Applied Physics Letters, Japanese Journal of Applied Physics, Nanotechnology and Microelectronic Engineering.

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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