Suet To

11.7k total citations · 1 hit paper
460 papers, 9.0k citations indexed

About

Suet To is a scholar working on Mechanical Engineering, Biomedical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Suet To has authored 460 papers receiving a total of 9.0k indexed citations (citations by other indexed papers that have themselves been cited), including 321 papers in Mechanical Engineering, 316 papers in Biomedical Engineering and 88 papers in Electrical and Electronic Engineering. Recurrent topics in Suet To's work include Advanced Surface Polishing Techniques (289 papers), Advanced machining processes and optimization (236 papers) and Advanced Measurement and Metrology Techniques (78 papers). Suet To is often cited by papers focused on Advanced Surface Polishing Techniques (289 papers), Advanced machining processes and optimization (236 papers) and Advanced Measurement and Metrology Techniques (78 papers). Suet To collaborates with scholars based in Hong Kong, China and United Kingdom. Suet To's co-authors include Wing Bun Lee, Shaojian Zhang, Chi Fai Cheung, Wai Sze Yip, Zhiwei Zhu, Zhiwei Zhu, Gaobo Xiao, Zhanwen Sun, Hao Wang and C. Y. Chan and has published in prestigious journals such as Nature, Advanced Materials and PLoS ONE.

In The Last Decade

Suet To

436 papers receiving 8.7k citations

Hit Papers

align trajectories

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.

Inhibiting the Leidenfrost effect above 1,000 °C for sustained thermal cooling

2022 228 citations Suet To et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Suet To Hong Kong	47	6.1k	5.4k	2.1k	1.5k	1.4k	460	9.0k
Shreyes N. Melkote United States	51	5.8k 0.9×	4.0k 0.7×	2.3k 1.1×	1.4k 0.9×	625 0.5×	248	7.6k
Kornel F. Ehmann United States	48	6.4k 1.0×	3.5k 0.6×	1.9k 0.9×	1.0k 0.7×	1.2k 0.9×	313	8.7k
Dragoş Axinte United Kingdom	57	7.7k 1.3×	6.2k 1.1×	2.8k 1.3×	1.6k 1.1×	1.0k 0.8×	268	10.8k
Xuesong Mei China	47	3.2k 0.5×	2.6k 0.5×	2.9k 1.4×	1.5k 1.0×	2.5k 1.8×	505	9.4k
Konrad Wegener Switzerland	53	10.5k 1.7×	4.2k 0.8×	2.4k 1.2×	1.4k 1.0×	1.7k 1.3×	535	13.3k
Xichun Luo United Kingdom	47	3.6k 0.6×	4.5k 0.8×	1.7k 0.8×	2.6k 1.8×	822 0.6×	234	6.7k
E. Brinksmeier Germany	46	6.7k 1.1×	4.9k 0.9×	2.8k 1.3×	1.3k 0.9×	669 0.5×	220	7.8k
Placid M. Ferreira United States	52	2.3k 0.4×	5.0k 0.9×	4.7k 2.2×	1.4k 0.9×	1.1k 0.8×	185	9.7k
Steven Y. Liang United States	57	10.6k 1.7×	5.3k 1.0×	3.9k 1.9×	1.4k 0.9×	754 0.6×	512	12.5k
Yung C. Shin United States	66	13.6k 2.2×	5.0k 0.9×	3.0k 1.4×	3.1k 2.1×	3.1k 2.3×	373	17.9k

Countries citing papers authored by Suet To

Since Specialization

Citations

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

Fields of papers citing papers by Suet To

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suet To

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Huang, Min‐Hsin, et al.. (2025). Scarcity and Power in Sensory Marketing: The Counterintuitive Impact of Resource Constraints on Shape Preferences. Psychology and Marketing. 43(3). 609–621.

Liu, Yue, et al.. (2025). Towards understanding the machinability improvement of high-entropy alloys via ultra-precision diamond cutting technology in a magnetic field environment. Precision Engineering. 96. 398–417. 2 indexed citations

Xu, Zhicheng, et al.. (2024). Technological life-cycle analysis of ultra-precision machining technology: Forecasting perspective directions and tracking the critical transitions with evolution. Advanced Engineering Informatics. 62. 102805–102805. 12 indexed citations

Yang, Jie, et al.. (2024). Interference-enhanced micro-vision-based single-shot imaging of five degrees-of-freedom error motions for ultra-precision rotary axes. International Journal of Machine Tools and Manufacture. 200. 104184–104184. 1 indexed citations

Sun, Zhanwen, et al.. (2024). A cooperative rotary servo indenting system for machining anti-counterfeiting micro-images on titanium alloys. Journal of Manufacturing Processes. 115. 108–125. 2 indexed citations

Sun, Zhanwen, et al.. (2024). Investigation of rotational magnetic field assisted hot filament chemical vapor deposition for diamond film growth. Surface and Coatings Technology. 495. 131588–131588. 2 indexed citations

To, Suet, Muhammad Rehan, Jingjing Wu, et al.. (2024). Investigation and formulation of cobalt content of ultra-thin diamond blades and dicing performance manufactured by fused deposition modeling and sintering (FDMS). International Journal of Refractory Metals and Hard Materials. 121. 106663–106663. 2 indexed citations

Xu, Zhicheng, et al.. (2024). A review: Insight into smart and sustainable ultra-precision machining augmented by intelligent IoT. Journal of Manufacturing Systems. 74. 233–251. 17 indexed citations

Liu, Changlin, et al.. (2024). Atomic insight into the speed effect on deformation mechanisms in nano-scratching of monocrystalline iron. Precision Engineering. 92. 219–230. 3 indexed citations

10.

Liu, Changlin, Jinyang Ke, Tengfei Yin, et al.. (2024). Cutting mechanism of reaction-bonded silicon carbide in laser-assisted ultra-precision machining. International Journal of Machine Tools and Manufacture. 203. 104219–104219. 29 indexed citations

11.

Tan, Yi, et al.. (2024). Subsurface damage and brittle fracture suppression of monocrystalline germanium in ultra-precision machining by multiple ion implantation surface modification. Journal of Materials Processing Technology. 334. 118640–118640. 5 indexed citations

12.

Shen, Mingjie, Hongyu Chen, Julong Yuan, et al.. (2024). High-efficiency free-damage electrochemical shear-thickening polishing of single-crystal silicon carbide. Journal of Manufacturing Processes. 132. 532–543. 25 indexed citations

13.

Wang, Sujuan, et al.. (2024). Analytical model for the prediction of milling forces: a review. The International Journal of Advanced Manufacturing Technology. 134(3-4). 1015–1041. 10 indexed citations

14.

Rehan, Muhammad, et al.. (2024). Experimental Investigation of the Micro-Milling of Additively Manufactured Titanium Alloys: Selective Laser Melting and Wrought Ti6Al4V. Chinese Journal of Mechanical Engineering. 37(1). 6 indexed citations

15.

Zhao, Lun, et al.. (2024). LAD-Net: A lightweight welding defect surface non-destructive detection algorithm based on the attention mechanism. Computers in Industry. 161. 104109–104109. 24 indexed citations

16.

Liu, Yue, Tengfei Yin, Zhanwen Sun, et al.. (2024). Magnetic and ultrasonic vibration dual-field assisted ultra-precision diamond cutting of high-entropy alloys. International Journal of Machine Tools and Manufacture. 202. 104208–104208. 23 indexed citations

17.

Yip, Wai Sze, et al.. (2023). A novel magnetic field assisted diamond turning of Ti-6Al-4 V alloy for sustainable ultra-precision machining. Materials Today Communications. 35. 105829–105829. 18 indexed citations

18.

Liu, Mingyu, et al.. (2023). Two crucial suggestions on tool paths in slow-tool-servo diamond cutting of micro-structured functional surfaces. Journal of Manufacturing Processes. 95. 415–420. 11 indexed citations

19.

Wu, Dongbo, et al.. (2023). Adaptive acquisition and recognition system of blade surface defects during machining process. Measurement. 225. 114008–114008. 2 indexed citations

20.

Lee, Wing Bun, et al.. (2014). Mesoplasticity approach to studies of the cutting mechanism in ultra-precision machining. Chinese Journal of Mechanical Engineering. 27(2). 219–228. 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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