Long Han
Impact in
- Organic Chemistry top 10%
- Catalytic C–H Functionalization Methods
- Asymmetric Synthesis and Catalysis
- Oxidative Organic Chemistry Reactions
- Synthetic Organic Chemistry Methods
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- Asymmetric Hydrogenation and Catalysis
Papers in
-
- Advanced Neural Network Applications 5
- Robotic Path Planning Algorithms 3
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- Robotics and Sensor-Based Localization 7
- Advanced SAR Imaging Techniques 3
- Co-authors
- Shu‐Li You (4 shared papers)Xiǎo Zhang (1 shared paper)Wei Zhang (1 shared paper)Wei Zhang (2 shared papers)Chuan Liu (1 shared paper)Xiaochu Zhang (6 shared papers)Xiao‐Xin Shi (1 shared paper)Zhengde Wei (4 shared papers)
In The Last Decade
Long Han
23 papers receiving 491 citations
Peers
Comparison fields: 5 of 70
- Organic Chemistry 283
- Inorganic Chemistry 74
- Pharmacology 37
- General Decision Sciences 7
- Cognitive Neuroscience 65
Countries citing papers authored by Long Han
This map shows the geographic impact of Long Han'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 Long Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Long Han more than expected).
Fields of papers citing papers by Long Han
This network shows the impact of papers produced by Long Han. 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 Long Han. The network helps show where Long Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Long Han, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 122 | |
| 2 | 2013 | 77 | |
| 3 | 2012 | 44 | |
| 4 | 2016 | 31 | |
| 5 | 2015 | 30 | |
| 6 | 2018 | 27 | |
| 7 | 2016 | 25 | |
| 8 | 2017 | 20 | |
| 9 | 2019 | 19 | |
| 10 | 2016 | 19 | |
| 11 | 2016 | 16 | |
| 12 | 2013 | 14 | |
| 13 | 2020 | 10 | |
| 14 | 2004 | 8 | |
| 15 | 2017 | 8 | |
| 16 | 2020 | 6 | |
| 17 | 2020 | 6 | |
| 18 | 2019 | 6 | |
| 19 | 2020 | 4 | |
| 20 | 2008 | 2 |
About Long Han
Long Han is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Organic Chemistry, Cognitive Neuroscience and Molecular Biology, having authored 25 papers that have together received 499 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (7 papers), Advanced Neural Network Applications (5 papers), Asymmetric Synthesis and Catalysis (4 papers), Functional Brain Connectivity Studies (4 papers), Robotic Path Planning Algorithms (3 papers), Catalytic C–H Functionalization Methods (3 papers), Advanced SAR Imaging Techniques (3 papers) and Neural and Behavioral Psychology Studies (2 papers). The work is most often cited by research in Organic Chemistry (283 citations), Inorganic Chemistry (74 citations), Pharmacology (37 citations), General Decision Sciences (7 citations) and Cognitive Neuroscience (65 citations). Long Han has collaborated with scholars based in China, Hong Kong and Germany. Frequent co-authors include Shu‐Li You, Xiǎo Zhang, Wei Zhang, Wei Zhang, Chuan Liu, Xiaochu Zhang, Xiao‐Xin Shi, Zhengde Wei, Rujing Zha and Lizhuang Yang. Their work appears in journals such as NeuroImage, Organic & Biomolecular Chemistry, Scientific Reports, Chemical Communications and Chemical Science.
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.