Xiao‐Gang Lu

2.9k total citations · 1 hit paper
133 papers, 2.4k citations indexed

About

Xiao‐Gang Lu is a scholar working on Mechanical Engineering, Materials Chemistry and General Materials Science. According to data from OpenAlex, Xiao‐Gang Lu has authored 133 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 103 papers in Mechanical Engineering, 61 papers in Materials Chemistry and 30 papers in General Materials Science. Recurrent topics in Xiao‐Gang Lu's work include Intermetallics and Advanced Alloy Properties (61 papers), High Temperature Alloys and Creep (47 papers) and Metallurgical and Alloy Processes (30 papers). Xiao‐Gang Lu is often cited by papers focused on Intermetallics and Advanced Alloy Properties (61 papers), High Temperature Alloys and Creep (47 papers) and Metallurgical and Alloy Processes (30 papers). Xiao‐Gang Lu collaborates with scholars based in China, Sweden and France. Xiao‐Gang Lu's co-authors include Bo Sundman, Malin Selleby, Yanlin He, Weisen Zheng, Lin Li, Shibo Li, Yuwen Cui, Nan Zou, Yang Zhou and Lijun Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Acta Materialia and Materials Science and Engineering A.

In The Last Decade

Xiao‐Gang Lu

126 papers receiving 2.3k citations

Hit Papers

Predicting creep rupture life of Ni-based single crystal ... 2020 2026 2022 2024 2020 50 100 150
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. Predicting creep rupture life of Ni-based single crystal superalloys using divide-and-conquer approach based machine learning
    2020 193 citations Yue Liu, Zhichao Wang et al. Acta Materialia profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiao‐Gang Lu China 25 1.6k 1.3k 424 370 259 133 2.4k
Mitsuhiro Hasebe Japan 28 1.4k 0.9× 881 0.7× 260 0.6× 235 0.6× 152 0.6× 87 2.0k
Thomas Helander Sweden 11 3.1k 1.9× 1.8k 1.3× 1.1k 2.6× 462 1.2× 313 1.2× 19 3.8k
A. P. Miodownik United Kingdom 30 2.5k 1.5× 1.7k 1.3× 548 1.3× 610 1.6× 195 0.8× 93 3.2k
Aloke Paul India 27 2.0k 1.2× 844 0.6× 886 2.1× 223 0.6× 267 1.0× 126 2.6k
P. Pérez Spain 32 2.6k 1.6× 1.9k 1.4× 757 1.8× 581 1.6× 117 0.5× 163 3.6k
William Yi Wang China 36 3.4k 2.1× 2.3k 1.8× 1.4k 3.3× 624 1.7× 304 1.2× 188 4.5k
Emmanuel Bouzy France 26 1.5k 0.9× 1.4k 1.0× 284 0.7× 406 1.1× 121 0.5× 87 2.0k
Rajib Saha India 27 1.4k 0.9× 1.1k 0.8× 493 1.2× 411 1.1× 178 0.7× 137 2.2k
Taichi Abe Japan 22 940 0.6× 888 0.7× 225 0.5× 121 0.3× 122 0.5× 82 1.6k
E. Ricci Italy 29 1.5k 0.9× 987 0.8× 412 1.0× 152 0.4× 205 0.8× 92 2.3k

Countries citing papers authored by Xiao‐Gang Lu

Since Specialization
Citations

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

Fields of papers citing papers by Xiao‐Gang Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiao‐Gang Lu. 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 Xiao‐Gang Lu. The network helps show where Xiao‐Gang Lu may publish in the future.

Co-authorship network of co-authors of Xiao‐Gang Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Xiao‐Gang Lu. A scholar is included among the top collaborators of Xiao‐Gang Lu 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 Xiao‐Gang Lu. Xiao‐Gang Lu 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.
Li, Yang, et al.. (2025). Effect of composition on microstructure and nanohardness of as-cast Al-Cr-Fe-Ni-Ti high entropy alloys. Journal of Alloys and Compounds. 1032. 181171–181171. 2 indexed citations
2.
3.
Lu, Xiao‐Gang, et al.. (2024). Effect of heat treatment on the microstructure and nanoindentation behavior of AlCoCrFeNi high entropy alloy. Intermetallics. 169. 108302–108302. 13 indexed citations
4.
Wang, Jingjing, et al.. (2024). Experimental Investigation of Phase Equilibria in the Ti-Cr-V System at 1000–1200 °C. Metals. 14(5). 498–498. 1 indexed citations
5.
He, Zhouyang, Xilei Bian, Shiwei Wu, et al.. (2024). Laser directed energy deposited eutectic high entropy alloy with tailored lamella structure via interlayer pause strategy. Additive manufacturing. 94. 104471–104471. 13 indexed citations
6.
Zhang, Yajing, Hao Wang, & Xiao‐Gang Lu. (2024). Diffusion Coefficients of the Ni-Co-Fe Alloys Studied by Molecular Dynamics Simulation and CALPHAD Assessment. Journal of Phase Equilibria and Diffusion. 45(6). 1068–1078. 1 indexed citations
7.
Li, Ying, et al.. (2024). Applying enhanced active learning to predict formation energy. Computational Materials Science. 235. 112825–112825. 6 indexed citations
8.
Luo, Tao, K. J. Zhu, Hongwei Xiong, et al.. (2024). Thermodynamic Assessment of the Mg–La–Nd System. Journal of Phase Equilibria and Diffusion. 46(1). 60–75.
9.
Lu, Xiao‐Gang, et al.. (2024). Diffusion Quadruple vs Triple: Determining Interdiffusivities for fcc Co–Ni–Ta Alloys. Metallurgical and Materials Transactions B. 55(6). 4536–4549.
10.
Zheng, Weisen, et al.. (2023). Diffusion simulation based on atomistic model and mobility determination via Kirkendall experiment for multi-component systems. Scripta Materialia. 241. 115884–115884. 6 indexed citations
11.
12.
Lu, Xiao‐Gang, et al.. (2023). Thermodynamic assessment of the Co–Cr–Fe system and atomic mobility study of its fcc phase. Calphad. 80. 102526–102526. 5 indexed citations
13.
Lu, Xiao‐Gang, et al.. (2023). Study on Diffusion and Kirkendall Effect Adopting fcc Co–Al–Ta Diffusion Triple. Metallurgical and Materials Transactions A. 54(10). 3781–3795. 3 indexed citations
14.
Liu, Wenyue, et al.. (2023). Thermodynamic reassessment of Fe–Nb–V system. Calphad. 80. 102529–102529. 4 indexed citations
15.
16.
Liu, Yue, Zhichao Wang, Xiao‐Gang Lu, et al.. (2020). Predicting creep rupture life of Ni-based single crystal superalloys using divide-and-conquer approach based machine learning. Acta Materialia. 195. 454–467. 193 indexed citations breakdown →
17.
Zou, Nan, et al.. (2019). Error assessment and optimal cross-validation approaches in machine learning applied to impurity diffusion. Computational Materials Science. 169. 109075–109075. 54 indexed citations
18.
Zheng, Weisen, Huahai Mao, Xiao‐Gang Lu, et al.. (2018). Thermodynamic investigation of the Al-Fe-Mn system over the whole composition and wide temperature ranges. Journal of Alloys and Compounds. 742. 1046–1057. 25 indexed citations
19.
Miao, Kai, et al.. (2014). Coarsening of carbides during different heat treatment conditions. Journal of Alloys and Compounds. 622. 513–523. 27 indexed citations
20.
Lu, Xiao‐Gang. (2011). Thermodynamic calculation of M_s temperature for martensitic transformation in Fe-C-Mn-Si alloys. Cailiao rechuli xuebao. 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.

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