Mao Su

871 total citations · 1 hit paper
21 papers, 693 citations indexed

About

Mao Su is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics and Electrical and Electronic Engineering. According to data from OpenAlex, Mao Su has authored 21 papers receiving a total of 693 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Materials Chemistry, 4 papers in Atomic and Molecular Physics, and Optics and 3 papers in Electrical and Electronic Engineering. Recurrent topics in Mao Su's work include Machine Learning in Materials Science (6 papers), Spectroscopy and Quantum Chemical Studies (2 papers) and Advanced Battery Materials and Technologies (2 papers). Mao Su is often cited by papers focused on Machine Learning in Materials Science (6 papers), Spectroscopy and Quantum Chemical Studies (2 papers) and Advanced Battery Materials and Technologies (2 papers). Mao Su collaborates with scholars based in China, United States and Hong Kong. Mao Su's co-authors include Yanting Wang, Chongmin Wang, Zihua Zhu, Donald R. Baer, Zhijie Xu, Ruiguo Cao, Jun-Gang Wang, Yufan Zhou, Wu Xu and Kang Xu and has published in prestigious journals such as Nature Communications, The Journal of Chemical Physics and Nature Materials.

In The Last Decade

Mao Su

18 papers receiving 675 citations

Hit Papers

Real-time mass spectrometric characterization of the soli... 2020 2026 2022 2024 2020 100 200 300
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. Real-time mass spectrometric characterization of the solid–electrolyte interphase of a lithium-ion battery
    2020 386 citations Yufan Zhou, Mao Su et al. Nature Nanotechnology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mao Su China 8 430 234 214 72 57 21 693
Naoki Matsui Japan 15 591 1.4× 379 1.6× 169 0.8× 106 1.5× 20 0.4× 59 895
A. D. W. Todd Canada 14 634 1.5× 141 0.6× 167 0.8× 184 2.6× 76 1.3× 38 799
Giorgio Nava United States 16 323 0.8× 273 1.2× 49 0.2× 48 0.7× 24 0.4× 27 580
Yanping Zeng China 18 627 1.5× 526 2.2× 80 0.4× 39 0.5× 21 0.4× 38 918
Yaping Yang China 15 277 0.6× 410 1.8× 110 0.5× 42 0.6× 27 0.5× 24 694
Toshio Takenaka Japan 14 340 0.8× 163 0.7× 117 0.5× 179 2.5× 50 0.9× 50 871
Sophie Poizeau United States 9 400 0.9× 290 1.2× 86 0.4× 204 2.8× 26 0.5× 12 711
Xuchu Deng China 14 596 1.4× 177 0.8× 169 0.8× 34 0.5× 91 1.6× 23 858
Raymond B. Smith United States 8 604 1.4× 117 0.5× 384 1.8× 52 0.7× 8 0.1× 8 706
Zhengjuan Wang China 19 507 1.2× 857 3.7× 24 0.1× 97 1.3× 62 1.1× 42 1.1k

Countries citing papers authored by Mao Su

Since Specialization
Citations

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

Fields of papers citing papers by Mao Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mao Su

This figure shows the co-authorship network connecting the top 25 collaborators of Mao Su. A scholar is included among the top collaborators of Mao Su 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 Mao Su. Mao Su 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.
Su, Mao, et al.. (2025). Unique proton transfer and hydrogen evolution reaction at semi-disordered interfaces in confined spaces. The Journal of Chemical Physics. 163(14).
2.
Tang, Chenyu, Jianfeng Ma, Dongzhan Zhou, et al.. (2025). Evidential deep learning for interatomic potentials. Nature Communications. 17(1). 937–937.
3.
Tang, Chenyu, Dongzhan Zhou, Yuqiang Li, et al.. (2025). Online test-time adaptation for better generalization of interatomic potentials to out-of-distribution data. Nature Communications. 16(1). 1891–1891. 4 indexed citations
4.
Tang, Chenyu, Mao Su, Shufei Zhang, et al.. (2024). Geometry-enhanced pretraining on interatomic potentials. Nature Machine Intelligence. 6(4). 428–436. 8 indexed citations
5.
Zhong, Yang, Hongyu Yu, Mao Su, Xin-Gao Gong, & Hongjun Xiang. (2023). Transferable equivariant graph neural networks for the Hamiltonians of molecules and solids. npj Computational Materials. 9(1). 50 indexed citations
6.
Su, Mao, Ji‐Hui Yang, Hongjun Xiang, & Xin-Gao Gong. (2023). Efficient determination of the Hamiltonian and electronic properties using graph neural network with complete local coordinates. Machine Learning Science and Technology. 4(3). 35010–35010. 7 indexed citations
7.
8.
Su, Mao, Ji‐Hui Yang, Zhi‐Pan Liu, & Xin-Gao Gong. (2022). Exploring Large-Lattice-Mismatched Interfaces with Neural Network Potentials: The Case of the CdS/CdTe Heterostructure. The Journal of Physical Chemistry C. 126(31). 13366–13372. 3 indexed citations
9.
Su, Mao, et al.. (2022). Gelatin sponge microparticles for transarterial chemoembolization combined with regorafenib in hepatocellular carcinoma: a single-center retrospective study. Journal of Gastrointestinal Oncology. 13(6). 3183–3192. 2 indexed citations
10.
Dai, Yuxin, et al.. (2022). Exploring Potential Causal Genes for Uterine Leiomyomas: A Summary Data-Based Mendelian Randomization and FUMA Analysis. Frontiers in Genetics. 13. 890007–890007. 4 indexed citations
11.
Su, Mao, et al.. (2022). Fault-Tolerant Guidance of Rocket Vertical Landing Phase Based on MPC Framework. International Journal of Aerospace Engineering. 2022. 1–11. 1 indexed citations
12.
Su, Mao & Yanting Wang. (2020). A brief review of continuous models for ionic solutions: the Poisson–Boltzmann and related theories. Communications in Theoretical Physics. 72(6). 67601–67601. 11 indexed citations
13.
Zhou, Yufan, Mao Su, Xiaofei Yu, et al.. (2020). Real-time mass spectrometric characterization of the solid–electrolyte interphase of a lithium-ion battery. Nature Nanotechnology. 15(3). 224–230. 386 indexed citations breakdown →
14.
Zhang, Yanyan, Mao Su, Xiaofei Yu, et al.. (2018). Investigation of Ion–Solvent Interactions in Nonaqueous Electrolytes Using in Situ Liquid SIMS. Analytical Chemistry. 90(5). 3341–3348. 47 indexed citations
15.
Luo, Langli, Mao Su, Pengfei Yan, et al.. (2018). Atomic origins of water-vapour-promoted alloy oxidation. Nature Materials. 17(6). 514–518. 146 indexed citations
16.
Su, Mao. (2013). A Blocks Placement Strategy in HDFS. Computer Technology and Development. 3 indexed citations
17.
Su, Mao. (2012). CRP Algorithms Based Resource Provisioning Policy for Cloud Computing. Computer Technology and Development.
18.
Su, Mao. (2007). Development of application for insects semiochemicals. Kunchong zhishi. 1 indexed citations
19.
Xu, Songlin, et al.. (2006). Investigation of BCN Films Deposited at Various$hboxN_2/hboxAr$Flow Ratios by DC Reactive Magnetron Sputtering. IEEE Transactions on Plasma Science. 34(4). 1199–1203. 14 indexed citations
20.
Su, Mao, et al.. (1987). An in situ observation of tensile fracture in lamellar dual-phase structure. Scripta Metallurgica. 21(6). 801–804. 2 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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