Xue Jiang

4.1k total citations · 1 hit paper
142 papers, 3.3k citations indexed

About

Xue Jiang is a scholar working on Materials Chemistry, Mechanical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Xue Jiang has authored 142 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 72 papers in Materials Chemistry, 63 papers in Mechanical Engineering and 27 papers in Electrical and Electronic Engineering. Recurrent topics in Xue Jiang's work include Machine Learning in Materials Science (16 papers), Luminescence Properties of Advanced Materials (13 papers) and Catalysis and Hydrodesulfurization Studies (13 papers). Xue Jiang is often cited by papers focused on Machine Learning in Materials Science (16 papers), Luminescence Properties of Advanced Materials (13 papers) and Catalysis and Hydrodesulfurization Studies (13 papers). Xue Jiang collaborates with scholars based in China, United States and Pakistan. Xue Jiang's co-authors include Jidong Lu, Wenshuai Zhu, Yongsheng Yan, Huaming Li, Yanjing Su, Lining He, Jiexiang Xia, Xuanhui Qu, Haiqing Yin and Cong Zhang and has published in prestigious journals such as Advanced Materials, SHILAP Revista de lepidopterología and Journal of Applied Physics.

In The Last Decade

Xue Jiang

128 papers receiving 3.2k citations

Hit Papers

Applications of natural language processing and large lan... 2025 2026 2025 10 20 30

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xue Jiang China 32 2.0k 1.4k 661 626 366 142 3.3k
Shuang Jiang China 31 1.8k 0.9× 826 0.6× 875 1.3× 452 0.7× 408 1.1× 145 3.4k
Yu Fan China 37 2.2k 1.1× 1.9k 1.3× 472 0.7× 857 1.4× 886 2.4× 134 4.0k
Guixian Li China 24 1.4k 0.7× 460 0.3× 588 0.9× 368 0.6× 470 1.3× 152 2.6k
M. A. Wahab India 34 1.8k 0.9× 652 0.5× 693 1.0× 217 0.3× 437 1.2× 159 3.5k
Xuerui Wang China 38 2.0k 1.0× 2.2k 1.5× 751 1.1× 307 0.5× 528 1.4× 123 4.4k
Qiang Song China 37 1.8k 0.9× 916 0.6× 1.2k 1.9× 219 0.3× 562 1.5× 130 4.8k
Fei Zhang China 34 1.9k 0.9× 914 0.6× 811 1.2× 350 0.6× 450 1.2× 159 3.8k
Bin Zheng China 35 1.8k 0.9× 523 0.4× 1.3k 1.9× 1.0k 1.7× 406 1.1× 159 4.2k
Jian Jin China 30 1.2k 0.6× 710 0.5× 1.2k 1.8× 405 0.6× 379 1.0× 77 3.1k
Zhiwei Qiao China 40 2.3k 1.1× 1.3k 0.9× 505 0.8× 323 0.5× 571 1.6× 99 3.9k

Countries citing papers authored by Xue Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Xue Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xue Jiang

This figure shows the co-authorship network connecting the top 25 collaborators of Xue Jiang. A scholar is included among the top collaborators of Xue Jiang 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 Xue Jiang. Xue Jiang 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.
Ding, Xiangdong, Xue Jiang, Yumei Zhou, et al.. (2025). Unlocking the black box beyond Bayesian global optimization for materials design using reinforcement learning. npj Computational Materials. 11(1). 2 indexed citations
2.
Su, Ye, Cui Li, Xue Jiang, & Bai Yang. (2025). First-principles study of non-metallic doping and noble metal loading on ZnIn2S4 semiconductor photocatalyst. Inorganic Chemistry Communications. 174. 114124–114124. 2 indexed citations
3.
Jiang, Xue, Huadong Fu, Yang Bai, et al.. (2025). Interpretable Machine Learning Applications: A Promising Prospect of AI for Materials. Advanced Functional Materials. 35(41). 10 indexed citations
4.
Jiang, Xue, Dezhen Xue, Yang Bai, et al.. (2025). AI4Materials: Transforming the landscape of materials science and enigneering. SHILAP Revista de lepidopterología. 1(1). 100010–100010. 2 indexed citations
6.
Wu, Lingzhi, Cong Zhang, Xue Jiang, et al.. (2024). Optimizing additive manufacturing parameters for martensitic stainless steel via machine learning. Materials Today Communications. 41. 110290–110290. 3 indexed citations
7.
Zhang, Liu, Haiqing Yin, Zengqiang Zhang, et al.. (2024). HfO2 doped 3Y-TZP on mechanical properties and low temperature degradation (LTD). Ceramics International. 50(10). 17890–17897. 1 indexed citations
8.
Qu, Zhihao, et al.. (2024). A hybrid machine learning strategy for pitting probability prediction of stainless steels. Materials Today Communications. 40. 109917–109917. 2 indexed citations
9.
Zhu, Jie, et al.. (2024). Polymorphic engineering in FeS2 enabling enhanced catalytic activity for oxygen evolution reaction. International Journal of Hydrogen Energy. 107. 478–487. 3 indexed citations
10.
Jiang, Xue, et al.. (2024). Microstructure and strengthening mechanisms in fine-grained and high-strength tungsten heavy alloy with a non-equiatomic Ni5.5Fe2.5CoCr high-entropy binder. Materials Science and Engineering A. 908. 146769–146769. 7 indexed citations
11.
Xu, Bin, Haiqing Yin, Xue Jiang, et al.. (2023). Data-driven design of Ni-based turbine disc superalloys to improve yield strength. Journal of Material Science and Technology. 155. 175–191. 30 indexed citations
12.
Xu, Bin, Cong Zhang, Xue Jiang, et al.. (2023). Site preference and elastic properties of L21-Ni2TiAl doped with refractory metal elements from first principles. Computational Materials Science. 232. 112594–112594. 3 indexed citations
13.
Wu, Lingzhi, Dil Faraz Khan, Cong Zhang, et al.. (2023). Microstructure and mechanical characterization of additively manufactured Fe11Cr8Ni5Co3Mo martensitic stainless steel. Materials Characterization. 203. 113106–113106. 16 indexed citations
14.
He, Jie, Xiaotong Zhang, Lei Duan, et al.. (2022). A repository for the publication and sharing of heterogeneous materials data. Scientific Data. 9(1). 787–787. 15 indexed citations
15.
Xie, Jianxin, et al.. (2021). Machine Learning for Materials Research and Development. Acta Metallurgica Sinica. 57(11). 1343–1361. 41 indexed citations
16.
Su, Yanjing, et al.. (2020). Progress in Materials Genome Engineering in China. Acta Metallurgica Sinica. 56(10). 1313–1323. 27 indexed citations
17.
Yin, Haiqing, Bin Xu, Xue Jiang, et al.. (2019). A dataset of nickel-base superalloys. China Scientific Data. 4(1). 21.86101/csdata.2018.0060.zh–21.86101/csdata.2018.0060.zh. 1 indexed citations
18.
Zhang, Qiang‐Sheng, Xue Jiang, Alexander M. Kirillov, et al.. (2019). Covalent Construction of Sustainable Hybrid UiO-66-NH2@Tb-CP Material for Selective Removal of Dyes and Detection of Metal Ions. ACS Sustainable Chemistry & Engineering. 7(3). 3203–3212. 104 indexed citations
19.
Jiang, Xue, et al.. (2017). A new family of multifunctional silicon clathrates: Optoelectronic and thermoelectric applications. Journal of Applied Physics. 121(8). 11 indexed citations
20.
Jiang, Xue, et al.. (2016). Cultural Confidence of Chinese People: Reflection on The Spirit of the Chinese People. Higher education of social science. 11(4). 8–13.

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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