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.
Review of Recent Development of In Situ/Operando Characterization Techniques for Lithium Battery Research
2019526 citationsShuwei Wang, Ming Liu et al.profile →
A dielectric electrolyte composite with high lithium-ion conductivity for high-voltage solid-state lithium metal batteries
2023421 citationsMing Liu, Shuwei Wang et al.profile →
High entropy liquid electrolytes for lithium batteries
2023211 citationsQidi Wang, Chenglong Zhao et al.Nature Communicationsprofile →
Emerging Chemistry for Wide-Temperature Sodium-Ion Batteries
2024152 citationsFang Zhang, Bijiao He et al.Chemical Reviewsprofile →
3D Ternary Alloy Artificial Interphase Toward Ultra‐Stable and Dendrite‐Free Aqueous Zinc Batteries
202469 citationsXin Yan, Huanhuan Xie et al.Advanced Functional Materialsprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Shuwei Wang'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 Shuwei Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuwei Wang more than expected).
This network shows the impact of papers produced by Shuwei Wang. 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 Shuwei Wang. The network helps show where Shuwei Wang may publish in the future.
Co-authorship network of co-authors of Shuwei Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Shuwei Wang.
A scholar is included among the top collaborators of Shuwei Wang 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 Shuwei Wang. Shuwei Wang is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Wang, Qidi, Chenglong Zhao, Shuwei Wang, et al.. (2025). Interphase Design for Lithium-Metal Anodes. Journal of the American Chemical Society. 147(11). 9365–9377.14 indexed citations
Wang, Shuwei, et al.. (2015). An Assessment Research on the predicted model of weaving speed in the 2010 HCM. Transportation Research Board 94th Annual MeetingTransportation Research Board.1 indexed citations
17.
Wang, Shuwei, et al.. (2014). Study on Pedestrian Flow Forecasting Method in Beijing Transportation Hub Areas. Transportation Research Board 93rd Annual MeetingTransportation Research Board.1 indexed citations
18.
Wang, Shuwei, Ruifeng Xu, Bin Liu, et al.. (2014). The Construction of an Emotion Annotated Corpus on Microblog Text. Zhongwen xinxi xuebao. 28(5). 83–91.8 indexed citations
19.
Wang, Shuwei, et al.. (2014). Using Point of Interest Data from Electronic Map to Predict Transit Station Ridership. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 53(4). 327–327.1 indexed citations
20.
Wang, Shuwei, et al.. (2013). Assessing the county's rural development types and their rurality: a case study of the Three Gorges eco-economic region in Chongqing.. Chongqing Shifan Daxue xuebao. Ziran kexue ban. 30(1). 42–47.1 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.