Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Aerodynamic analysis of SARS-CoV-2 in two Wuhan hospitals
20201.4k citationsYuan Liu, Zhi Ning et al.Natureprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Xinjin Liu'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 Xinjin Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinjin Liu more than expected).
This network shows the impact of papers produced by Xinjin Liu. 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 Xinjin Liu. The network helps show where Xinjin Liu may publish in the future.
Co-authorship network of co-authors of Xinjin Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Xinjin Liu.
A scholar is included among the top collaborators of Xinjin Liu based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Xinjin Liu. Xinjin Liu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhang, Xiaojuan, et al.. (2017). Effects of godet wheel position on compact siro-spun core yarn characteristics. Indian Journal of Fibre & Textile Research (IJFTR). 42(2). 145–149.1 indexed citations
11.
Liu, Xinjin & Xuzhong Su. (2016). Yarn hairiness on ring spinning with modified yarn path. Indian Journal of Fibre & Textile Research (IJFTR). 41(2). 221–225.
12.
Liu, Xinjin, et al.. (2016). Electromagnetic shielding and wrinkle recovery property of cotton /stainless steel filament woven fabric. 37(9). 36.1 indexed citations
Liu, Xinjin & Xuzhong Su. (2015). Properties of knitted fabric made from modified ring-spun yarn. Indian Journal of Fibre & Textile Research (IJFTR). 40(3). 282–287.1 indexed citations
15.
Su, Xuzhong, et al.. (2014). Theoretical Study of Yarn Torque Caused by Fibre Tension in the Spinning Triangle. Fibres and Textiles in Eastern Europe.2 indexed citations
16.
Su, Xuzhong, et al.. (2014). Numerical analysis of the slub yarn breaking strength using finite element method. Indian Journal of Fibre & Textile Research (IJFTR). 39(4). 437–440.1 indexed citations
17.
Liu, Xinjin, et al.. (2013). Numerical Studies on a Three-dimensional Flow Field in Four-Roller Compact Spinning with a Guiding Device. Fibres and Textiles in Eastern Europe.3 indexed citations
18.
Liu, Xinjin, et al.. (2012). Simulation Model for the Absorption Coefficients of Double Layered Nonwovens. Fibres and Textiles in Eastern Europe.10 indexed citations
19.
Liu, Xinjin, et al.. (2012). Acoustic analysis for a sound-absorbing structure with multi-layered porous material. Zhendong yu chongji. 31(5). 106–110.5 indexed citations
20.
Liu, Xinjin. (2010). Reservoir-forming conditions and favorable exploration zones of shale gas in Lower Silurian Longmaxi Formation of Sichuan Basin. Acta Petrologica Sinica.51 indexed citations
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.