Teng Long

22 papers and 379 indexed citations i.

About

Teng Long is a scholar working on Mechanical Engineering, Organic Chemistry and Computer Vision and Pattern Recognition. According to data from OpenAlex, Teng Long has authored 22 papers receiving a total of 379 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Mechanical Engineering, 5 papers in Organic Chemistry and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Teng Long’s work include Welding Techniques and Residual Stresses (6 papers), Catalytic C–H Functionalization Methods (4 papers) and Cyclopropane Reaction Mechanisms (4 papers). Teng Long is often cited by papers focused on Welding Techniques and Residual Stresses (6 papers), Catalytic C–H Functionalization Methods (4 papers) and Cyclopropane Reaction Mechanisms (4 papers). Teng Long collaborates with scholars based in China. Teng Long's co-authors include Junfeng Fan, Lei Yang, Zize Liang, En Li, Min Tan, Fengshui Jing, Zaojun Fang, Wen‐Dao Chu, Quan‐Zhong Liu and Yulin Li and has published in prestigious journals such as Organic Letters, AIAA Journal and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Co-authorship network of co-authors of Teng Long i

Fields of papers citing papers by Teng Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Teng Long

Since Specialization
Citations

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

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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