Longqi Yang

776 total citations · 1 hit paper
11 papers, 610 citations indexed

About

Longqi Yang is a scholar working on Aerospace Engineering, Electronic, Optical and Magnetic Materials and Electrical and Electronic Engineering. According to data from OpenAlex, Longqi Yang has authored 11 papers receiving a total of 610 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Aerospace Engineering, 7 papers in Electronic, Optical and Magnetic Materials and 2 papers in Electrical and Electronic Engineering. Recurrent topics in Longqi Yang's work include Advanced Antenna and Metasurface Technologies (7 papers), Electromagnetic wave absorption materials (7 papers) and Metamaterials and Metasurfaces Applications (5 papers). Longqi Yang is often cited by papers focused on Advanced Antenna and Metasurface Technologies (7 papers), Electromagnetic wave absorption materials (7 papers) and Metamaterials and Metasurfaces Applications (5 papers). Longqi Yang collaborates with scholars based in China, Singapore and United States. Longqi Yang's co-authors include Zhao Lu, Runrun Cheng, Yan Wang, Nian Wang, Xiaochuang Di, Yongfei Li, Xinming Wu, Yan Wang, Peihu Gao and Honghao Chen and has published in prestigious journals such as Carbon, Chemical Engineering Journal and Journal of Colloid and Interface Science.

In The Last Decade

Longqi Yang

9 papers receiving 598 citations

Hit Papers

Construction of multi-dimensional NiCo/C/CNT/rGO aerogel ... 2023 2026 2024 2025 2023 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Longqi Yang China 8 553 431 120 50 48 11 610
Xiaofen Yang China 12 474 0.9× 340 0.8× 129 1.1× 56 1.1× 38 0.8× 16 550
Yilu Xia China 13 539 1.0× 423 1.0× 117 1.0× 98 2.0× 53 1.1× 22 624
Wanru Zhao China 4 439 0.8× 358 0.8× 123 1.0× 40 0.8× 36 0.8× 10 500
Elnaz Selseleh‐Zakerin Iran 11 536 1.0× 391 0.9× 135 1.1× 76 1.5× 68 1.4× 11 604
Pinbo Li China 7 458 0.8× 356 0.8× 101 0.8× 48 1.0× 50 1.0× 9 500
Junwu Wen China 5 348 0.6× 268 0.6× 147 1.2× 20 0.4× 33 0.7× 7 408
Jiangxiao Tian China 9 437 0.8× 353 0.8× 118 1.0× 28 0.6× 58 1.2× 12 499
Mengjie Han China 9 314 0.6× 233 0.5× 94 0.8× 81 1.6× 49 1.0× 24 428
Xueheng Zhuang China 10 329 0.6× 246 0.6× 123 1.0× 89 1.8× 113 2.4× 22 464
Jianle Xu China 12 407 0.7× 313 0.7× 115 1.0× 66 1.3× 50 1.0× 25 503

Countries citing papers authored by Longqi Yang

Since Specialization
Citations

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

Fields of papers citing papers by Longqi Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Longqi Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Longqi Yang. A scholar is included among the top collaborators of Longqi Yang 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 Longqi Yang. Longqi Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
Chen, Honghao, et al.. (2024). Single-atom catalysts property prediction via Supervised and Self-Supervised pre-training models. Chemical Engineering Journal. 487. 150626–150626. 8 indexed citations
2.
Ma, Jing, Mengting Wan, Longqi Yang, et al.. (2023). Learning Causal Effects on Hypergraphs (Extended Abstract). 6463–6467.
3.
Lu, Zhao, Yan Wang, Runrun Cheng, Longqi Yang, & Nian Wang. (2023). Highly dispersed Co/Co9S8 nanoparticles encapsulated in S, N co-doped longan shell-derived hierarchical porous carbon for corrosion-resistant, waterproof high-performance microwave absorption. Journal of Colloid and Interface Science. 637. 147–158. 27 indexed citations
4.
Yang, Longqi, Yan Wang, Zhao Lu, et al.. (2023). Construction of multi-dimensional NiCo/C/CNT/rGO aerogel by MOF derivative for efficient microwave absorption. Carbon. 205. 411–421. 161 indexed citations breakdown →
5.
Yang, Longqi, et al.. (2023). Lightweight Vision Transformer with Spatial and Channel Enhanced Self-Attention. 1484–1488. 7 indexed citations
6.
Wang, Nian, Yan Wang, Zhao Lu, et al.. (2022). Hierarchical core-shell FeS2/Fe7S8@C microspheres embedded into interconnected graphene framework for high-efficiency microwave attenuation. Carbon. 202. 254–264. 62 indexed citations
7.
8.
Yang, Longqi, Yan Wang, Lu Zhao, et al.. (2022). Construction of Multi-Dimensional  Nico/C/Cnt/Rgo Aerogel By Mof Derivative For Efficient Microwave Absorption. SSRN Electronic Journal. 2 indexed citations
10.
Di, Xiaochuang, Yan Wang, Zhao Lu, et al.. (2021). Heterostructure design of Ni/C/porous carbon nanosheet composite for enhancing the electromagnetic wave absorption. Carbon. 179. 566–578. 192 indexed citations
11.
Lu, Zhao, Yan Wang, Xiaochuang Di, et al.. (2021). Design of hierarchical core-shell ZnFe2O4@MnO2@RGO composite with heterogeneous interfaces for enhanced microwave absorption. Ceramics International. 48(4). 5217–5228. 47 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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