Promoting Nanosecond Laser Micromachining of Honeycomb Microstructure by In situ Tailoring Laser Power
Source abstract
Abstract
While the functionality of textured surface is largely affected by the texturing quality, how to precisely fabricate honeycomb microstructures with high material utilization and structural stability is crucial for their application potential. In the present work, a strategy of preprogramming‐based in situ tailoring laser power in different pulses is proposed for improving the processing quality of honeycomb microstructures by nanosecond laser micromachining. Firstly, a finite element (FE) model of tailoring laser power based on the thermodynamic diffusion equation of nanosecond laser ablation is established. Secondly, the effects of different laser parameters on the processing quality of honeycomb microstructures are investigated by FE simulations and experiments, which derive the rational range of laser processing parameters for the highest surface quality. Thirdly, the effectiveness of in situ tailoring laser power is demonstrated through FE simulation and experiment. Finally, nanosecond laser micromachining experiments with the proposed scheme of in situ tailoring laser power are carried out, with which a significant 40% improvement in the processing quality of honeycomb microstructures is obtained. Current work provides a feasible solution for enhancing processing quality of complex microstructures by laser micromachining.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Tribology and Lubrication Engineering · Laser Material Processing Techniques · Adhesion, Friction, and Surface Interactions
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Center for Precision Engineering Harbin Institute of Technology Harbin 150001 China
Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou 450000 China
References (49)
Show source-provided references
1. 10.1016/j.colsurfa.2024.13521210.1016/j.colsurfa.2024.135212 ↗
2. 10.1016/j.ceramint.2023.08.14710.1016/j.ceramint.2023.08.147 ↗
3. 10.1016/j.jmapro.2023.12.03710.1016/j.jmapro.2023.12.037 ↗
4. 10.1016/j.optmat.2023.11445310.1016/j.optmat.2023.114453 ↗
5. 10.1016/j.ceramint.2019.09.10110.1016/j.ceramint.2019.09.101 ↗
6. 10.1016/j.jallcom.2023.17090710.1016/j.jallcom.2023.170907 ↗
7. 10.1038/s41598-018-26234-610.1038/s41598-018-26234-6 ↗
8. 10.1016/j.ces.2021.11700610.1016/j.ces.2021.117006 ↗
9. 10.1016/j.mtcomm.2024.11068010.1016/j.mtcomm.2024.110680 ↗
10. 10.1016/j.ijleo.2019.16295310.1016/j.ijleo.2019.162953 ↗
11. 10.1016/j.jmapro.2020.10.01110.1016/j.jmapro.2020.10.011 ↗
12. 10.1080/02670844.2020.174246910.1080/02670844.2020.1742469 ↗
13. 10.1098/rsif.2014.011310.1098/rsif.2014.0113 ↗
14. 10.1016/j.optlastec.2023.10947410.1016/j.optlastec.2023.109474 ↗
15. 10.1088/1748-3190/10/4/04400110.1088/1748-3190/10/4/044001 ↗
16. 10.1021/acsami.5b0303910.1021/acsami.5b03039 ↗
17. 10.1080/10426914.2021.190689810.1080/10426914.2021.1906898 ↗
18. 10.1016/j.triboint.2018.08.01010.1016/j.triboint.2018.08.010 ↗
19. 10.1080/02670844.2021.195204110.1080/02670844.2021.1952041 ↗
20. 10.1016/j.apsusc.2013.02.01310.1016/j.apsusc.2013.02.013 ↗
21. 10.1108/ILT-03-2020-008110.1108/ILT-03-2020-0081 ↗
22. 10.1115/1.404555410.1115/1.4045554 ↗
23. 10.1039/c1sm00015b10.1039/c1sm00015b ↗
24. A.Ancona G.Carbone M.Scaraggi F. P.Mezzapesa P. M.Lugarà inProc. Volume 8968 Laser‐Based Micro‐ and Nanoprocessing VIII International Society for Optics and Photonics San Francisco2014 p.890806.10.1117/12.2039006 ↗
25. 10.1002/adem.20180101610.1002/adem.201801016 ↗
26. 10.1016/j.procir.2024.05.07910.1016/j.procir.2024.05.079 ↗
27. 10.1016/j.matdes.2024.11300710.1016/j.matdes.2024.113007 ↗
28. 10.1016/j.jmapro.2024.09.08310.1016/j.jmapro.2024.09.083 ↗
29. 10.1016/j.diamond.2024.11159410.1016/j.diamond.2024.111594 ↗
30. 10.1016/j.heliyon.2024.e3780810.1016/j.heliyon.2024.e37808 ↗
31. 10.3390/machines1104047310.3390/machines11040473 ↗
32. 10.1016/j.optlastec.2023.10970610.1016/j.optlastec.2023.109706 ↗
33. 10.1016/j.matlet.2016.05.03810.1016/j.matlet.2016.05.038 ↗
34. 10.1016/j.msea.2022.14457610.1016/j.msea.2022.144576 ↗
35. 10.1016/j.mtcomm.2024.10843010.1016/j.mtcomm.2024.108430 ↗
36. 10.1016/j.jmrt.2024.07.13510.1016/j.jmrt.2024.07.135 ↗
37. 10.1016/j.jmrt.2023.10.26810.1016/j.jmrt.2023.10.268 ↗
38. 10.1016/j.optlastec.2024.11094010.1016/j.optlastec.2024.110940 ↗
39. 10.1016/j.optlastec.2024.11086110.1016/j.optlastec.2024.110861 ↗
40. 10.1016/j.rineng.2024.10218210.1016/j.rineng.2024.102182 ↗
41. 10.1016/j.jmatprotec.2024.11852010.1016/j.jmatprotec.2024.118520 ↗
42. 10.1016/j.addma.2019.04.02110.1016/j.addma.2019.04.021 ↗
43. 10.1016/j.optlastec.2024.11068310.1016/j.optlastec.2024.110683 ↗
44. Wang N. · Chin. J. Mech. Eng. · 2022 · 1 · 100038
45. 10.1016/j.optlastec.2023.11010010.1016/j.optlastec.2023.110100 ↗
46. 10.1002/adem.20190019310.1002/adem.201900193 ↗
47. 10.1016/j.ijleo.2019.16324410.1016/j.ijleo.2019.163244 ↗
48. 10.1016/j.ijmecsci.2022.10804610.1016/j.ijmecsci.2022.108046 ↗
49. Zhao L. · Mater. Sci. · 2024 · 913 · 147053