Nan Xin

856 citations
34 papers · 612 · h-index 13

Impact in

Papers in

Nan Xin

30 papers receiving 608 citations

Peers

Nan Xin
Comparison fields: 5 of 101
  • Aging 104
  • Fluid Flow and Transfer Processes 88
  • Filtration and Separation 18
  • Cell Biology 67
  • Statistical and Nonlinear Physics 49
Replace H. Ohta with:
H. Ohta Japan
Linfeng Li China
Xiaobing Xie China
Chetan Poudel United States
David B. Brückner Germany
Walter Meixner United States
Jiyoung Kang South Korea
Nannan Ye China
Erin A. Henslee United Kingdom
Huahui Li China
Nan Xin relative to H. Ohta Japan H. Ohta's profile →
Citations per field
00.5×20×40×52×
H. Ohta · 1×
Citations per year

Countries citing papers authored by Nan Xin

Since Specialization
Citations

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

Fields of papers citing papers by Nan Xin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018179
2 201754
3 201451
4 202245
5 201531
6 201130
7 201720
8 202220
9 201419
10 202117
11 201516
12 202116
13 201115
14 202212
15 201812
16 201812
17 201510
18 20189
19 20167
20
Simulation analysis of working process and performance of cell wheel metering device.
20116

About Nan Xin

Nan Xin is a scholar working on Fluid Flow and Transfer Processes, Electrical and Electronic Engineering, Biomedical Engineering, Materials Chemistry and Organic Chemistry, having authored 34 papers that have together received 612 indexed citations. Recurring topics across this work include Thermodynamic properties of mixtures (8 papers), Advanced Thermoelectric Materials and Devices (8 papers), Phase Equilibria and Thermodynamics (7 papers), Chemical Thermodynamics and Molecular Structure (6 papers), Chalcogenide Semiconductor Thin Films (4 papers), Wnt/β-catenin signaling in development and cancer (3 papers), 2D Materials and Applications (3 papers) and Genetics, Aging, and Longevity in Model Organisms (3 papers). The work is most often cited by research in Aging (104 citations), Fluid Flow and Transfer Processes (88 citations), Filtration and Separation (18 citations), Cell Biology (67 citations) and Statistical and Nonlinear Physics (49 citations). Nan Xin has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Andrew Dillin, Xueying Wu, Qian Zhang, Peng Chen, Ye Tian, Ying Zhang, Maogang He, Yang Liu, John M. Prausnitz and Yanjun Sun. Their work appears in journals such as The Journal of Supercritical Fluids, Journal of Chemical & Engineering Data, PLoS Genetics, The Journal of Chemical Thermodynamics and Sensors.

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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