Liang Chengxian

Mr. Liang Chengxian

Shanghai University, Shanghai, China

Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 January 2026 in Materials
Verified
Journal Article
Open access
PDF file
LCLiang Chengxian
Liang Chengxian
JFJiecai Feng
Jiecai Feng
HLHongfei Liu
Hongfei Liu
YSYan-Ning Sun
Yan-Ning Sun
YZYILIAN ZHANG
YILIAN ZHANG
TYTian Yingzhong
Tian Yingzhong
Sapphire (α-Al2O3) has been widely used in high-power lasers, optical windows, semiconductor substrates, radomes, and other applications due to its exceptional optical properties, high hardness, excellent chemical stability, and thermal resistance. However, machining sapphire poses significant challenges because of the material’s high hardness and brittleness. Traditional mechanical and chemical–mechanical machine methods often fail to meet the processing requirements for micro and nanoscale structures. Recently, the use of femtosecond lasers—with ultra-short pulses and extremely high peak power—has allowed for the precise machining of sapphire with minimal thermal damage, a method akin to cold processing. Femtosecond laser processing offers significant advantages in fabricating three-dimensional micro- and nanoscale structures, surface and internal modification, optical waveguide writing, grating fabrication and dissimilar materials welding. Thus, this paper systematically reviewed the research progress in femtosecond laser processing of sapphire, covering technical approaches such as ablation, hybrid processing and direct writing micro- and nanoscale fabrication. The capability of femtosecond laser processing to modulate sapphire’s optical properties, wettability and mechanical and chemical characteristics were discussed in detail. The current challenges related to efficiency, cost, process standardization and outlines future development directions, including high-power lasers, parallel processing, AI optimization and multifunctional integration were also analyzed.