Xianbin Yang

423 total citations
11 papers, 293 citations indexed

About

Xianbin Yang is a scholar working on Automotive Engineering, Electrical and Electronic Engineering and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Xianbin Yang has authored 11 papers receiving a total of 293 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Automotive Engineering, 11 papers in Electrical and Electronic Engineering and 1 paper in Safety, Risk, Reliability and Quality. Recurrent topics in Xianbin Yang's work include Advanced Battery Technologies Research (11 papers), Advancements in Battery Materials (10 papers) and Advanced Battery Materials and Technologies (6 papers). Xianbin Yang is often cited by papers focused on Advanced Battery Technologies Research (11 papers), Advancements in Battery Materials (10 papers) and Advanced Battery Materials and Technologies (6 papers). Xianbin Yang collaborates with scholars based in China, United Kingdom and Hong Kong. Xianbin Yang's co-authors include Siyan Chen, Haicheng Xie, Xinhua Liu, Bin Ma, Lisheng Zhang, Hanqing Yu, Zhenhai Gao, Shichun Yang, Huizhi Wang and Shen Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Power Sources and Journal of Energy Storage.

In The Last Decade

Xianbin Yang

11 papers receiving 281 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xianbin Yang China 10 249 229 61 41 19 11 293
Haicheng Xie China 10 252 1.0× 238 1.0× 51 0.8× 39 1.0× 16 0.8× 17 297
Yangjie Zhou China 7 294 1.2× 255 1.1× 65 1.1× 30 0.7× 16 0.8× 13 354
Xujian Cui China 10 301 1.2× 292 1.3× 30 0.5× 30 0.7× 36 1.9× 14 350
Marcel Held Switzerland 7 166 0.7× 240 1.0× 29 0.5× 41 1.0× 23 1.2× 25 318
A. V. V. Sudhakar India 8 98 0.4× 231 1.0× 48 0.8× 17 0.4× 20 1.1× 30 285
Long Chang China 11 416 1.7× 363 1.6× 65 1.1× 28 0.7× 63 3.3× 29 462
Benjamin Juba United States 3 345 1.4× 342 1.5× 40 0.7× 31 0.8× 27 1.4× 4 385
Joris de Hoog Belgium 8 453 1.8× 430 1.9× 44 0.7× 37 0.9× 14 0.7× 13 486
Yuebo Yuan China 10 268 1.1× 250 1.1× 41 0.7× 26 0.6× 43 2.3× 18 306
Antti Aitio United Kingdom 3 334 1.3× 301 1.3× 50 0.8× 40 1.0× 22 1.2× 7 354

Countries citing papers authored by Xianbin Yang

Since Specialization
Citations

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

Fields of papers citing papers by Xianbin Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xianbin Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Xianbin Yang. A scholar is included among the top collaborators of Xianbin 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 Xianbin Yang. Xianbin 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.
Yang, Xianbin, Xinhong Wang, Yu Shi, et al.. (2025). Small-Sample Battery Capacity Prediction Using a Multi-Feature Transfer Learning Framework. Batteries. 11(2). 62–62. 2 indexed citations
2.
Yang, Xianbin, Haicheng Xie, Lisheng Zhang, et al.. (2024). Early-stage degradation trajectory prediction for lithium-ion batteries: A generalized method across diverse operational conditions. Journal of Power Sources. 612. 234808–234808. 14 indexed citations
3.
Gao, Zhenhai, Haicheng Xie, Xianbin Yang, et al.. (2023). Electric vehicle lifecycle carbon emission reduction: A review. SHILAP Revista de lepidopterología. 2(5). 528–550. 34 indexed citations
4.
Yang, Xianbin, Bin Ma, Haicheng Xie, et al.. (2023). Lithium-Ion Battery State of Health Estimation with Multi-Feature Collaborative Analysis and Deep Learning Method. Batteries. 9(2). 120–120. 22 indexed citations
5.
Gao, Zhenhai, Haicheng Xie, Xianbin Yang, et al.. (2023). SOH estimation method for lithium-ion batteries under low temperature conditions with nonlinear correction. Journal of Energy Storage. 75. 109690–109690. 25 indexed citations
6.
Zhang, Lisheng, Wentao Wang, Hanqing Yu, et al.. (2022). Remaining useful life and state of health prediction for lithium batteries based on differential thermal voltammetry and a deep learning model. iScience. 25(12). 105638–105638. 17 indexed citations
7.
Ma, Bin, Shichun Yang, Lisheng Zhang, et al.. (2022). Remaining useful life and state of health prediction for lithium batteries based on differential thermal voltammetry and a deep-learning model. Journal of Power Sources. 548. 232030–232030. 77 indexed citations
8.
9.
Gao, Zhenhai, et al.. (2022). The Dilemma of C-Rate and Cycle Life for Lithium-Ion Batteries under Low Temperature Fast Charging. Batteries. 8(11). 234–234. 39 indexed citations
10.
Wang, Wentao, Lisheng Zhang, Hanqing Yu, et al.. (2022). Early Prediction of the Health Conditions for Battery Cathodes Assisted by the Fusion of Feature Signal Analysis and Deep-Learning Techniques. Batteries. 8(10). 151–151. 12 indexed citations
11.
Ma, Bin, Lisheng Zhang, Wentao Wang, et al.. (2022). Application of deep learning for informatics aided design of electrode materials in metal-ion batteries. Green Energy & Environment. 9(5). 877–889. 28 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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