Hyunjun Ji

5.2k citations
13 papers · 652 · h-index 9

Impact in

    • MXene and MAX Phase Materials
    • 2D Materials and Applications
    • Graphene research and applications
    • Machine Learning in Materials Science
    • Advancements in Battery Materials
    • Advanced Battery Materials and Technologies
    • Advanced battery technologies research

Papers in

Hyunjun Ji

12 papers receiving 645 citations

Peers

Hyunjun Ji
Comparison fields: 5 of 45
  • Materials Chemistry 456
  • Electrical and Electronic Engineering 445
  • Electronic, Optical and Magnetic Materials 89
  • Renewable Energy, Sustainability and the Environment 51
  • Inorganic Chemistry 38
Replace Jieqiong Wan with:
Jieqiong Wan China
Zun‐Yi Deng China
Grant C. B. Alexander United States
Jiangkun Chen Hong Kong
Jing-Hua Chen China
Hongyu Wen China
Wenfei Liang China
Tianyue Li United Kingdom
Syeda Rabab Naqvi Sweden
Hyunjun Ji relative to Jieqiong Wan China Jieqiong Wan's profile →
Citations per field
00.5×3.9×
Jieqiong Wan · 1×
Citations per year

Countries citing papers authored by Hyunjun Ji

Since Specialization
Citations

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

Fields of papers citing papers by Hyunjun Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 2015320
2 2015179
3 201248
4 201736
5 201316
6 201812
7 201411
8 201710
9 20138
10 20246
11 20165
12 20191
13 20250

About Hyunjun Ji

Hyunjun Ji is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics, Electrical and Electronic Engineering and Inorganic Chemistry, having authored 13 papers that have together received 652 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (5 papers), Advanced Chemical Physics Studies (3 papers), Computational Drug Discovery Methods (3 papers), Metal-Organic Frameworks: Synthesis and Applications (2 papers), Advancements in Battery Materials (2 papers), Graphene research and applications (2 papers), 2D Materials and Applications (1 paper) and Zeolite Catalysis and Synthesis (1 paper). The work is most often cited by research in Materials Chemistry (456 citations), Electrical and Electronic Engineering (445 citations), Electronic, Optical and Magnetic Materials (89 citations), Renewable Energy, Sustainability and the Environment (51 citations) and Inorganic Chemistry (38 citations). Hyunjun Ji has collaborated with scholars based in South Korea, United States and Germany. Frequent co-authors include Yousung Jung, Eunjeong Yang, Heejin Kim, Jaehoon Kim, Sangryun Kim, Yihan Shao, Jang Wook Choi, In Kim, Jee Hyun Baek and Jeong Min Lee. Their work appears in journals such as The Journal of Chemical Physics, Physical Chemistry Chemical Physics, Chemical Science, Journal of Chemical Theory and Computation and Scientific Reports.

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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