T. Cai
Impact in
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- Particle physics theoretical and experimental studies
- Neutrino Physics Research
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Particle Detector Development and Performance
- Dark Matter and Cosmic Phenomena
Papers in
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- Particle physics theoretical and experimental studies 4
- Dark Matter and Cosmic Phenomena 2
- Neutrino Physics Research 2
- Particle Detector Development and Performance 1
-
- Distributed and Parallel Computing Systems 1
- Co-authors
- A. Bodek (1 shared paper)D. Ruterbories (1 shared paper)X.-G. Lu (1 shared paper)Yasuyuki Sugiyama (1 shared paper)K. Pedro (1 shared paper)M. Campbell (1 shared paper)C. Carruth (1 shared paper)T. Yang (1 shared paper)
- Journals
- Physical review. D (1 paper)Materials Today Chemistry (1 paper)The European Physical Journal C (1 paper)IFAC-PapersOnLine (1 paper)PubMed (1 paper)
- Partner nations
- United StatesChinaCanada
In The Last Decade
T. Cai
5 papers receiving 17 citations
Peers
Comparison fields: 5 of 9
- Nuclear and High Energy Physics 11
- Radiation 2
- Astronomy and Astrophysics 3
- Surfaces, Coatings and Films 1
- Atomic and Molecular Physics, and Optics 3
Countries citing papers authored by T. Cai
This map shows the geographic impact of T. Cai'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 T. Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Cai more than expected).
Fields of papers citing papers by T. Cai
This network shows the impact of papers produced by T. Cai. 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 T. Cai. The network helps show where T. Cai may publish in the future.
Co-authors
The 23 scholars most cited alongside T. Cai, 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 | 2020 | 7 | |
| 2 | 2019 | 5 | |
| 3 | 2023 | 2 | |
| 4 | 2025 | 2 | |
| 5 | 2015 | 1 | |
| 6 | 2025 | 0 |
About T. Cai
T. Cai is a scholar working on Nuclear and High Energy Physics, Computer Networks and Communications, Artificial Intelligence, Electrical and Electronic Engineering and Biomedical Engineering, having authored 6 papers that have together received 17 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (4 papers), Dark Matter and Cosmic Phenomena (2 papers), Neutrino Physics Research (2 papers), Perovskite Materials and Applications (1 paper), Particle Detector Development and Performance (1 paper), Computational Physics and Python Applications (1 paper), Luminescence Properties of Advanced Materials (1 paper) and Distributed and Parallel Computing Systems (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (11 citations), Radiation (2 citations), Astronomy and Astrophysics (3 citations), Surfaces, Coatings and Films (1 citation) and Atomic and Molecular Physics, and Optics (3 citations). T. Cai has collaborated with scholars based in United States, China and Canada. Frequent co-authors include A. Bodek, D. Ruterbories, X.-G. Lu, Yasuyuki Sugiyama, K. Pedro, M. Campbell, C. Carruth, T. Yang, Hongpeng You and Jon Ameel. Their work appears in journals such as Physical review. D, Materials Today Chemistry, The European Physical Journal C, IFAC-PapersOnLine and PubMed.
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.