Prediction model for laser marking colors based on color mixing

Area of Science:

• Materials Science
• Optics
• Nanotechnology

Background:

• Laser surface coloring traditionally requires extensive parameter optimization.
• Achieving a wide color gamut with limited laser parameters is challenging.

Purpose of the Study:

• To develop an efficient method for generating diverse structural colors on stainless steel using a nanosecond laser.
• To establish a predictive mathematical model for mixed structural colors.

Main Methods:

• Utilized a nanosecond laser to create micro-nano structures on stainless steel surfaces.
• Investigated the color mixing principle based on these structures.
• Developed a linear mixed color space model to predict spectral reflectance and color outcomes.
• Mapped primary color spectral reflectance to the color space and minimized linear deviation.

Main Results:

• Generated four primary colors using distinct laser marking parameters.
• Achieved over 100 new mixed structural colors by varying primary color proportions.
• Demonstrated high color accuracy with average color differences ΔEab* of 1.98 and ΔE00* of 1.80.
• Successfully generated a vibrant structural color image using the predictive model.

Conclusions:

• The developed mathematical model accurately predicts mixed structural colors based on primary color proportions.
• This approach simplifies laser surface coloring, enabling efficient generation of a wide color palette.
• The method allows for the creation of complex structural color images with rich, vibrant tones.