Optimization of morphological parameters for mitigation pits on rear KDP surface: experiments and numerical modeling

Area of Science:

• Materials Science
• Optics
• Laser Physics

Background:

• High-power laser systems are susceptible to laser-induced surface damage on optical components like potassium dihydrogen phosphate (KDP) crystals.
• Damage growth on KDP crystal surfaces can negatively impact laser performance and component lifetime.
• Precision micro-machining offers a potential solution for mitigating and repairing laser-induced damage sites.

Purpose of the Study:

• To determine optimal micro-machining parameters for repairing laser-induced damage on KDP crystal rear surfaces.
• To investigate the effect of different repaired surface contours (spherical and Gaussian) on light field modulation.
• To simulate and compare the light intensity enhancement factors (LIEFs) for various repair geometries.

Main Methods:

• Development of finite element method (FEM) models to simulate light intensification on repaired KDP surfaces.
• Parametric study varying width-depth ratios of spherical and Gaussian mitigation pits.
• Comparison of simulated light intensity modulation and experimental laser damage tests.

Main Results:

• Light intensity modulation is primarily caused by interference between incident and reflected light on the KDP rear surface.
• Sharp increases in LIEFs occur near specific width-depth ratios (5.28 for spherical, 3.88 for Gaussian) due to total internal reflection.
• Optimal mitigation requires width-depth ratios >5.3 for spherical and >4.3 for Gaussian contours.
• Spherical contours with width-depth ratios >5.3 demonstrate superior performance in reducing light intensification and enhancing laser damage resistance.

Conclusions:

• Precision micro-machining with optimized parameters effectively mitigates laser-induced damage on KDP crystals.
• Spherical repaired contours with width-depth ratios exceeding 5.3 are recommended for superior light intensification reduction and laser damage resistance.
• FEM simulations accurately predict the performance of different repair geometries, guiding experimental optimization.