Ming Gao

5.3k total citations · 1 hit paper
167 papers, 4.5k citations indexed

About

Ming Gao is a scholar working on Materials Chemistry, Electronic, Optical and Magnetic Materials and Electrical and Electronic Engineering. According to data from OpenAlex, Ming Gao has authored 167 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 109 papers in Materials Chemistry, 67 papers in Electronic, Optical and Magnetic Materials and 55 papers in Electrical and Electronic Engineering. Recurrent topics in Ming Gao's work include ZnO doping and properties (62 papers), Ga2O3 and related materials (35 papers) and Gas Sensing Nanomaterials and Sensors (32 papers). Ming Gao is often cited by papers focused on ZnO doping and properties (62 papers), Ga2O3 and related materials (35 papers) and Gas Sensing Nanomaterials and Sensors (32 papers). Ming Gao collaborates with scholars based in China, Singapore and United States. Ming Gao's co-authors include Jinghai Yang, Jihui Lang, Lili Yang, Hougang Fan, Yongjun Zhang, Maobin Wei, Guozhong Xing, Huilian Liu, Yang Liu and H. J. Yang and has published in prestigious journals such as Applied Physics Letters, Journal of Applied Physics and Advanced Functional Materials.

In The Last Decade

Ming Gao

159 papers receiving 4.3k citations

Hit Papers

Recent Advances in Doping Strategies to Improve Electroca... 2024 2026 2025 2024 25 50 75

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming Gao China 38 3.2k 1.6k 1.6k 1.1k 685 167 4.5k
Xiaopeng Hao China 43 3.5k 1.1× 2.6k 1.6× 1.5k 1.0× 1.7k 1.6× 668 1.0× 197 5.9k
Guodong Wei China 40 3.4k 1.1× 2.6k 1.6× 1.9k 1.2× 938 0.9× 1.3k 1.8× 192 5.6k
Han Liu China 31 5.1k 1.6× 2.4k 1.4× 1.3k 0.8× 950 0.9× 1.3k 1.9× 78 6.4k
Prashant Kumar India 39 3.0k 0.9× 1.6k 1.0× 763 0.5× 1.2k 1.1× 816 1.2× 125 4.4k
Weiwei Yang China 43 2.2k 0.7× 1.6k 1.0× 1.1k 0.7× 2.2k 2.0× 690 1.0× 113 5.2k
Hiang Kwee Lee Singapore 36 2.3k 0.7× 1.2k 0.7× 1.8k 1.1× 1.2k 1.2× 1.4k 2.1× 106 5.0k
Ming Yin China 23 2.6k 0.8× 1.2k 0.7× 702 0.4× 695 0.7× 573 0.8× 74 3.6k
Syed Mubeen United States 26 3.0k 0.9× 1.8k 1.1× 1.6k 1.0× 1.5k 1.5× 1.6k 2.3× 54 4.8k
Cailing Chen China 47 3.9k 1.2× 2.3k 1.4× 696 0.4× 1.4k 1.3× 1.1k 1.6× 146 6.7k

Countries citing papers authored by Ming Gao

Since Specialization
Citations

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

Fields of papers citing papers by Ming Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Gao. A scholar is included among the top collaborators of Ming Gao 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 Ming Gao. Ming Gao 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.
Jia, Yuehan, et al.. (2025). Stable metal-phase Nb-doped MoS2 nanoflowers for ultrasensitive SERS detection of food contaminants. Food Chemistry. 488. 144835–144835.
2.
Gao, Ming, Xiaoyue Zhang, Liang Yu, et al.. (2025). Ultrasensitive CEA detection using SiO2/AuNPs-mediated dual inhibition in a signal-off-type photoelectrochemical immunosensor. Analytica Chimica Acta. 1345. 343745–343745. 1 indexed citations
4.
Zhang, Yuchen, Yuehan Jia, Hongquan Xu, et al.. (2024). Investigation of overall water splitting process on the 1 T/2H-MxCS catalyst via in situ Raman and IR spectroscopy measurement. International Journal of Hydrogen Energy. 69. 1386–1393. 4 indexed citations
5.
Su, Rui, et al.. (2024). Ultrasensitive detection of contaminants in milk using a novel NMS-Ag modified water-resistant paper substrate. Food Chemistry. 461. 140843–140843. 3 indexed citations
6.
Jia, Yuehan, et al.. (2024). Snowflake Cu2S@ZIF-67: A novel heterostructure substrate for enhanced adsorption and sensitive detection in BPA. Journal of Hazardous Materials. 472. 134524–134524. 21 indexed citations
7.
Zhang, Yuchen, et al.. (2024). Design superhydrophobic no-noble metal substrates for highly sensitive and signal stable SERS sensing. Journal of Colloid and Interface Science. 660. 42–51. 13 indexed citations
8.
Gao, Ming, et al.. (2024). Topological Charge Recognition of Vortex Beams Using PDs. IEEE Photonics Technology Letters. 36(24). 1461–1464.
9.
Jia, Yuehan, Yu‐Chen Zhang, Hongquan Xu, et al.. (2024). Recent Advances in Doping Strategies to Improve Electrocatalytic Hydrogen Evolution Performance of Molybdenum Disulfide. ACS Catalysis. 14(7). 4601–4637. 87 indexed citations breakdown →
10.
Jia, Yuehan, Yanjie Li, Maobin Wei, et al.. (2024). Doping-induced band-gap shrinkage to modify the electronic structure of MoS2 for organic wastewater management. Dalton Transactions. 54(1). 318–327. 3 indexed citations
11.
Zhang, Yuchen, Yuehan Jia, Hongquan Xu, et al.. (2023). Designed bifunctional flower-like structural molybdenum disulfide doped with Ag atoms for clean energy and contaminant detection. International Journal of Hydrogen Energy. 51. 703–712. 6 indexed citations
12.
Jia, Yuehan, et al.. (2023). Design two-in-one n-MoS2/p-Cu2S heterostructures for SERS monitoring and catalytic eliminating wastewater. Applied Surface Science. 644. 158767–158767. 15 indexed citations
13.
Zhao, Wenshi, Shuo Yang, Daxin Zhang, et al.. (2023). Multi-dimensional plasmonic coupling system for efficient enrichment and ultrasensitive label-free SERS detection of bilirubin based on graphene oxide-Au nanostars and Au@Ag nanoparticles. Journal of Colloid and Interface Science. 646. 872–882. 27 indexed citations
14.
Jiang, Lijuan, Shuo Yang, Donglai Han, et al.. (2023). Neodymium doping MoS2 nanostructures with remarkable surface-enhanced Raman scattering activity. Ceramics International. 49(11). 19328–19337. 8 indexed citations
16.
Wu, Tong, Hui Zheng, Naveen Reddy Kadasala, et al.. (2021). Self-sustainable and recyclable ternary Au@Cu2O–Ag nanocomposites: application in ultrasensitive SERS detection and highly efficient photocatalysis of organic dyes under visible light. Microsystems & Nanoengineering. 7(1). 23–23. 95 indexed citations
17.
Hu, Mingyue, Yingnan Quan, Shuo Yang, et al.. (2020). Self-cleaning semiconductor heterojunction substrate: ultrasensitive detection and photocatalytic degradation of organic pollutants for environmental remediation. Microsystems & Nanoengineering. 6(1). 111–111. 26 indexed citations
18.
Quan, Yingnan, Jiacheng Yao, Shuo Yang, et al.. (2019). ZnO nanoparticles on MoS2 microflowers for ultrasensitive SERS detection of bisphenol A. Microchimica Acta. 186(8). 593–593. 60 indexed citations
19.
Gao, Ming, et al.. (2018). Practical decoy state quantum key distribution with detector efficiency mismatch. The European Physical Journal D. 72(6). 3 indexed citations
20.
Gao, Ming, et al.. (2018). Quantum man-in-the-middle attack on the calibration process of quantum key distribution. Scientific Reports. 8(1). 4283–4283. 32 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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