Jun Ai

1.3k total citations · 1 hit paper
21 papers, 1.0k citations indexed

About

Jun Ai is a scholar working on Computational Mechanics, Civil and Structural Engineering and Mechanics of Materials. According to data from OpenAlex, Jun Ai has authored 21 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computational Mechanics, 6 papers in Civil and Structural Engineering and 5 papers in Mechanics of Materials. Recurrent topics in Jun Ai's work include Granular flow and fluidized beds (10 papers), Rock Mechanics and Modeling (5 papers) and Landslides and related hazards (5 papers). Jun Ai is often cited by papers focused on Granular flow and fluidized beds (10 papers), Rock Mechanics and Modeling (5 papers) and Landslides and related hazards (5 papers). Jun Ai collaborates with scholars based in United Kingdom, China and Taiwan. Jun Ai's co-authors include J.F. Chen, Jin Y. Ooi, J. M. Rotter, Paul Langston, Hai‐Sui Yu, Luke Bisby, Tim Stratford, Z. Zhong, Yun-Chi Chung and Liang He and has published in prestigious journals such as Chemical Engineering Journal, Polymer and Energy Conversion and Management.

In The Last Decade

Jun Ai

17 papers receiving 1.0k citations

Hit Papers

Assessment of rolling resistance models in discrete eleme... 2010 2026 2015 2020 2010 250 500 750
What are hit papers?

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.

  1. Assessment of rolling resistance models in discrete element simulations
    2010 779 citations Jun Ai, J.F. Chen et al. Powder Technology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jun Ai United Kingdom 10 623 499 261 231 172 21 1.0k
Yin Wang China 15 379 0.6× 365 0.7× 163 0.6× 123 0.5× 83 0.5× 45 802
I. Cavarretta United Kingdom 10 296 0.5× 802 1.6× 307 1.2× 207 0.9× 224 1.3× 11 1.1k
Sadegh Nadimi United Kingdom 15 290 0.5× 292 0.6× 113 0.4× 352 1.5× 229 1.3× 63 866
Katalin Bagi Hungary 19 627 1.0× 1.1k 2.1× 338 1.3× 146 0.6× 448 2.6× 45 1.5k
Sacha Emam Australia 9 868 1.4× 493 1.0× 680 2.6× 74 0.3× 238 1.4× 17 1.3k
Riccardo Artoni France 18 472 0.8× 268 0.5× 296 1.1× 93 0.4× 67 0.4× 51 687
Alice Hager Austria 4 1.1k 1.8× 360 0.7× 282 1.1× 403 1.7× 133 0.8× 6 1.5k
Kazuyoshi IWASHITA Japan 9 818 1.3× 940 1.9× 620 2.4× 176 0.8× 379 2.2× 23 1.5k

Countries citing papers authored by Jun Ai

Since Specialization
Citations

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

Fields of papers citing papers by Jun Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Ai

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Ai. A scholar is included among the top collaborators of Jun Ai 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 Jun Ai. Jun Ai 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.
Ai, Jun, Siyuan Li, Min Xiao, et al.. (2025). Biodegradable PBAT/PPC-P blown film with enhanced mechanical and barrier performances via in-situ reaction compatibilization. Composites Part A Applied Science and Manufacturing. 198. 109147–109147. 1 indexed citations
2.
Qiu, Yaxin, Jun Ai, Àiyīng Liú, et al.. (2025). Dual-patterned programming of photoactive dynamically cross-linked polyester enabling customizable shape-shifting pathways. Polymer. 330. 128538–128538.
3.
Liu, Jie, Huiyue Wang, Haijin Zhu, et al.. (2025). Green synthesis of photo-Fenton-active Fe-BDC from waste polyester for co-enhancing solar interfacial evaporation with organic contaminant remediation. Chemical Engineering Journal. 526. 170839–170839.
4.
5.
He, Liang, Ming Hou, Yanyan Gao, et al.. (2020). Experimental study of the S-shaped flow fields in proton exchange membrane fuel cells. Energy Conversion and Management. 223. 113292–113292. 36 indexed citations
6.
Ai, Jun & Yun-Chi Chung. (2020). Comparative study of granular solid-structure interaction in a uni-axial compression system. Advanced Powder Technology. 31(7). 2973–2990. 3 indexed citations
7.
Ai, Jun. (2018). 考虑粒间滚动阻力的CFD-DEM流-固耦合数值模拟方法. 38(6). 1771–1780. 2 indexed citations
8.
Chung, Yun-Chi, Chih-Kuang Lin, & Jun Ai. (2016). Mechanical behaviour of a granular solid and its contacting deformable structure under uni-axial compression-Part II: Multi-scale exploration of internal physical properties. Chemical Engineering Science. 144. 421–443. 10 indexed citations
9.
Wang, Yin & Jun Ai. (2015). Coupled CFD-DEM Simulation of Upward Seepage Flow in Granular Media. The Twenty-fifth International Ocean and Polar Engineering Conference. 1 indexed citations
10.
Ai, Jun, Jin Y. Ooi, J.F. Chen, J. M. Rotter, & Z. Zhong. (2013). The role of deposition process on pressure dip formation underneath a granular pile. Mechanics of Materials. 66. 160–171. 23 indexed citations
11.
Langston, Paul, Jun Ai, & Hai‐Sui Yu. (2013). Simple shear in 3D DEM polyhedral particles and in a simplified 2D continuum model. Granular Matter. 15(5). 595–606. 13 indexed citations
12.
Ai, Jun, Paul Langston, & Hai‐Sui Yu. (2013). Discrete element modelling of material non‐coaxiality in simple shear flows. International Journal for Numerical and Analytical Methods in Geomechanics. 38(6). 615–635. 38 indexed citations
13.
Ai, Jun, J.F. Chen, & Jin Y. Ooi. (2012). Finite element simulation of the pressure dip in sandpiles. International Journal of Solids and Structures. 50(6). 981–995. 17 indexed citations
14.
Chen, J.F., et al.. (2010). FRP rupture strains in the split-disk test. Composites Part B Engineering. 42(4). 962–972. 48 indexed citations
15.
Ai, Jun, J.F. Chen, J. M. Rotter, & Jin Y. Ooi. (2010). Assessment of rolling resistance models in discrete element simulations. Powder Technology. 206(3). 269–282. 779 indexed citations breakdown →
16.
Ai, Jun, J.F. Chen, J. M. Rotter, & Jin Y. Ooi. (2010). Numerical and experimental studies of the base pressures beneath stockpiles. Granular Matter. 13(2). 133–141. 20 indexed citations
17.
Ai, Jun, J.F. Chen, J. M. Rotter, & J.Y. Ooi. (2009). Finite element prediction of progressively formed conical stockpiles. Research Portal (Queen's University Belfast). 375–387. 2 indexed citations
18.
Chen, J.F., Jun Ai, & Tim Stratford. (2009). Effect of Geometric Discontinuities on Strains in FRP-Wrapped Columns. Journal of Composites for Construction. 14(2). 136–145. 33 indexed citations
19.
Ai, Jun, et al.. (2009). Effect of anisotropy of stored solid on wall pressure in a cylindrical silo. Research Portal (Queen's University Belfast). 701–706. 1 indexed citations
20.
Ai, Jun, et al.. (1999). Polymer fiber image guide optical circuits that incorporate free-space add–drop components. Applied Optics. 38(29). 6167–6167. 4 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.

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