Solution of maximum laser ablation depth based on dynamic energy distribution model

ABSTRACT

Pulsed laser ablation (PLA) is widely applied in mechanical processing with its energy distribution determining the quantity of removed material. Thus, the accurate description of energy distribution accumulated on component surface is crucial for further study of ablation morphology, such as the maximum ablation depth in laser patterning. However, there exist the overlapping area between adjacent laser spots and the non-continuity of laser energy here, which increase the inaccuracy of energy distribution description proverbially. By comprehensively considering the discrete distribution for laser spots and the non-uniform features for energy distribution, the innovative approach is proposed to establish a feasible dynamic energy distribution model in PLA quantitatively, with an idea of continuous approximation to resolve its discrete characteristic. More significantly, based on the proposed model, a new method is also presented to tackle PLA morphology prediction, just the maximum laser ablation depth in laser patterning. Finally, FEA simulations and experiments are performed to investigate the proposed model and method which endorse the robust and efficient theoretical model for reliable yet fast calculation of the maximum ablation depth.

KEYWORDS:

• Laser
• ablation
• energy
• distribution
• morphology
• depth
• copper
• frequency
• velocity
• model

Acknowledgments

The project is supported by National Natural Science Foundation of China under Grand No. 51675081, Science and Technology Innovation Fund of Dalian under Grand No. 2018J12GX038, Innovation Project for Supporting High-level Talent in Dalian under Grand No. 2016RQ012, Science Fund for Creative Research Groups under Grand No. 51621064 and the Fundamental Research Funds for the Central Universities. The authors wish to thank the anonymous reviewers for their comments which led to improvements of this paper.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [51675081];Science and Technology Innovation Fund of Dalian [2018J12GX038];Innovation Project for Supporting High-level Talent in Dalian [2016RQ012];the Fundamental Research Funds for the Central Universities;Science Fund for Creative Research Groups [51621064].