Dexin Zhu

848 total citations
19 papers, 682 citations indexed

About

Dexin Zhu is a scholar working on Mechanical Engineering, Materials Chemistry and Metals and Alloys. According to data from OpenAlex, Dexin Zhu has authored 19 papers receiving a total of 682 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Mechanical Engineering, 10 papers in Materials Chemistry and 5 papers in Metals and Alloys. Recurrent topics in Dexin Zhu's work include Intermetallics and Advanced Alloy Properties (6 papers), Machine Learning in Materials Science (5 papers) and Hydrogen embrittlement and corrosion behaviors in metals (5 papers). Dexin Zhu is often cited by papers focused on Intermetallics and Advanced Alloy Properties (6 papers), Machine Learning in Materials Science (5 papers) and Hydrogen embrittlement and corrosion behaviors in metals (5 papers). Dexin Zhu collaborates with scholars based in China, United States and Hong Kong. Dexin Zhu's co-authors include W.J. van Ooij, Jarel K. Gandhi, A. Seth, P. Puomi, Z.W. Huang, Xiaosong Jiang, Hong‐Hui Wu, Hong Sun, Yongpeng Ren and Kunming Pan and has published in prestigious journals such as Journal of Alloys and Compounds, Scripta Materialia and Materials.

In The Last Decade

Dexin Zhu

19 papers receiving 655 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dexin Zhu China 11 519 209 154 144 96 19 682
P. Campestrini Netherlands 13 865 1.7× 294 1.4× 215 1.4× 131 0.9× 176 1.8× 19 997
Barbara Kapun Slovenia 10 402 0.8× 63 0.3× 148 1.0× 79 0.5× 56 0.6× 24 512
Zhifeng Lin China 13 346 0.7× 161 0.8× 115 0.7× 58 0.4× 83 0.9× 31 630
Saeid Mersagh Dezfuli Iran 15 452 0.9× 480 2.3× 85 0.6× 221 1.5× 171 1.8× 19 894
Pablo Ricardo Seré Argentina 12 389 0.7× 105 0.5× 192 1.2× 78 0.5× 149 1.6× 32 545
Cheng Luo China 17 929 1.8× 729 3.5× 127 0.8× 91 0.6× 52 0.5× 46 1.3k
Mingan Chen China 15 390 0.8× 269 1.3× 47 0.3× 115 0.8× 89 0.9× 39 604
Shicheng Wei China 18 445 0.9× 228 1.1× 49 0.3× 97 0.7× 119 1.2× 100 1.1k
S. Esmailzadeh Iran 7 218 0.4× 147 0.7× 63 0.4× 60 0.4× 165 1.7× 11 472

Countries citing papers authored by Dexin Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Dexin Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dexin Zhu

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

All Works

19 of 19 papers shown
1.
Zhu, Dexin, Hong‐Hui Wu, Xiaoye Zhou, et al.. (2025). An optimized strategy for density prediction of intermetallics across varied crystal structures via graph neural network. 5(1). 1 indexed citations
2.
Wu, Hong‐Hui, Dexin Zhu, Jinyong Zhang, et al.. (2025). Interpretable material descriptors for critical pitting temperature in austenitic stainless steel via machine learning. npj Materials Degradation. 9(1). 1 indexed citations
3.
Zhu, Dexin, Hong‐Hui Wu, Jinyong Zhang, et al.. (2024). A transfer learning strategy for tensile strength prediction in austenitic stainless steel across temperatures. Scripta Materialia. 251. 116210–116210. 15 indexed citations
4.
Zhu, Dexin & Nan Cui. (2024). Design of intelligent control for flexible linear double inverted pendulum based on particle swarm optimization algorithm. Systems Science & Control Engineering. 12(1). 5 indexed citations
5.
Zhu, Dexin, Haitao Zhao, Yufan Liu, et al.. (2024). The interpretable descriptors for fatigue performance of wrought aluminum alloys. Journal of Materials Research and Technology. 32. 3423–3431. 11 indexed citations
6.
Li, Xiangyue, Dexin Zhu, Xiaoye Zhou, et al.. (2024). Identifying key determinants of discharge capacity in ternary cathode materials of lithium-ion batteries. Chinese Chemical Letters. 36(5). 109870–109870. 5 indexed citations
7.
Zhu, Dexin, Hong‐Hui Wu, Jiaye Li, et al.. (2024). A quantitative relation for the ductile-brittle transition temperature in pipeline steel. Scripta Materialia. 244. 116023–116023. 16 indexed citations
8.
Zhang, Xinyuan, Dexin Zhu, Chaolei Zhang, et al.. (2024). A review of crystal defect-induced element segregation in multi-component alloy steels. Progress in Natural Science Materials International. 34(5). 840–858. 5 indexed citations
9.
Li, Xiangyue, et al.. (2023). Exploring interpretable features of hardness for intermetallic compounds prepared by spark plasma sintering. International Journal of Refractory Metals and Hard Materials. 117. 106386–106386. 6 indexed citations
10.
Zhu, Dexin, Kunming Pan, Yuan Wu, et al.. (2023). Improved material descriptors for bulk modulus in intermetallic compounds via machine learning. Rare Metals. 42(7). 2396–2405. 22 indexed citations
11.
Zhu, Dexin, Kunming Pan, Hong‐Hui Wu, et al.. (2023). Identifying intrinsic factors for ductile-to-brittle transition temperatures in Fe–Al intermetallics via machine learning. Journal of Materials Research and Technology. 26. 8836–8845. 15 indexed citations
12.
Zhu, Dexin, Cheng Zhang, Xiaodong Wang, et al.. (2023). Predictive Modeling of Tensile Strength in Aluminum Alloys via Machine Learning. Materials. 16(22). 7236–7236. 9 indexed citations
13.
Zhu, Dexin, et al.. (2018). Microstructure and mechanical properties of Al-Ti-Zr intermetallic compounds prepared by vacuum hot pressing. Vacuum. 150. 166–172. 13 indexed citations
14.
Zhu, Dexin, et al.. (2018). Reliability Analysis of the High-speed Train Bearing Based on Wiener Process. Information. 9(1). 15–15. 6 indexed citations
15.
Gao, Yang, et al.. (2018). Research on the effect of the waveform on the droplet injection behavior of a piezoelectric printhead and the forming accuracy of casting sand molds. The International Journal of Advanced Manufacturing Technology. 100(1-4). 251–261. 14 indexed citations
16.
Sun, Hong, Z.W. Huang, Dexin Zhu, & Xiaosong Jiang. (2012). Dendrite core grain refining and interdendritic coarsening behaviour in W-containing γ-TiAl based alloys. Journal of Alloys and Compounds. 552. 213–218. 34 indexed citations
17.
Huang, Z.W. & Dexin Zhu. (2007). Thermal stability of Ti–44Al–8Nb–1B alloy. Intermetallics. 16(2). 156–167. 59 indexed citations
18.
Ooij, W.J. van, et al.. (2005). Corrosion protection properties of organofunctional silanes — An overview. Tsinghua Science & Technology. 10(6). 639–664. 289 indexed citations
19.
Ooij, W.J. van & Dexin Zhu. (2001). Electrochemical Impedance Spectroscopy of Bis-[Triethoxysilypropyl]Tetrasulfide on Al 2024-T3 Substrates. CORROSION. 57(5). 413–427. 156 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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