C. Gu
Impact in
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- MXene and MAX Phase Materials
- 2D Materials and Applications
- Advanced Nanomaterials in Catalysis
Papers in
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- Topic Modeling 2
- Adversarial Robustness in Machine Learning 1
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- Advanced Photocatalysis Techniques 2
- Co-authors
- Minghua Wang (1 shared paper)Sijie Zhou (1 shared paper)Zhihong Zhang (1 shared paper)Longyu Yang (1 shared paper)Nan Zhou (1 shared paper)Linghao He (1 shared paper)Xiaoyu Huang (1 shared paper)Zhenzhen Li (1 shared paper)
- Journals
- Applied Surface Science (3 papers)Environmental Research Letters (1 paper)Educational Psychology (1 paper)Journal of Evolution Equations (1 paper)Palaeogeography Palaeoclimatology Palaeoecology (1 paper)
- Partner nations
- ChinaItalyUnited Kingdom
In The Last Decade
C. Gu
7 papers receiving 167 citations
Peers
Comparison fields: 5 of 44
- Leadership and Management 3
- Materials Chemistry 95
- Renewable Energy, Sustainability and the Environment 32
- Biomedical Engineering 38
- Electrical and Electronic Engineering 44
Countries citing papers authored by C. Gu
This map shows the geographic impact of C. Gu'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 C. Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C. Gu more than expected).
Fields of papers citing papers by C. Gu
This network shows the impact of papers produced by C. Gu. 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 C. Gu. The network helps show where C. Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside C. Gu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 109 | |
| 2 | 2024 | 29 | |
| 3 | 2022 | 18 | |
| 4 | 2022 | 7 | |
| 5 | 2024 | 4 | |
| 6 | 2025 | 2 | |
| 7 | 2025 | 1 | |
| 8 | 2025 | 0 | |
| 9 | 2026 | 0 | |
| 10 | 2023 | 0 | |
| 11 | 2025 | 0 |
About C. Gu
C. Gu is a scholar working on Artificial Intelligence, Renewable Energy, Sustainability and the Environment, Materials Chemistry, Molecular Biology and Social Psychology, having authored 11 papers that have together received 170 indexed citations. Recurring topics across this work include Advanced Photocatalysis Techniques (2 papers), Topic Modeling (2 papers), Psychological Well-being and Life Satisfaction (1 paper), Advanced Mathematical Modeling in Engineering (1 paper), 2D Materials and Applications (1 paper), Resilience and Mental Health (1 paper), Adversarial Robustness in Machine Learning (1 paper) and Mathematical Biology Tumor Growth (1 paper). The work is most often cited by research in Leadership and Management (3 citations), Materials Chemistry (95 citations), Renewable Energy, Sustainability and the Environment (32 citations), Biomedical Engineering (38 citations) and Electrical and Electronic Engineering (44 citations). C. Gu has collaborated with scholars based in China, Italy and United Kingdom. Frequent co-authors include Minghua Wang, Sijie Zhou, Zhihong Zhang, Longyu Yang, Nan Zhou, Linghao He, Xiaoyu Huang, Zhenzhen Li, Tao Sun and Chao Liu. Their work appears in journals such as Applied Surface Science, Environmental Research Letters, Educational Psychology, Journal of Evolution Equations and Palaeogeography Palaeoclimatology Palaeoecology.
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.