Prediction model for laser marking colors based on color mixing

Abstract

The current techniques for coloring surfaces using lasers necessitate the identification of numerous laser marking parameters, which is a laborious process. Furthermore, the quantitative analysis of generating a wide variety of colors through fewer sets of laser marking parameters is a huge challenge. This work employs a nanosecond laser to generate mixed structural colors from micro-nano structures on the surface of stainless steel in order to address these issues. Additionally, the color mixing principle is investigated in relation to these micro-nano structures. On this basis, the spectral reflectance of the primary color is mapped to the linear mixed color space, and the linear mixed color space is constructed by minimizing the linear deviation function. In this space, a precise mathematical model for color prediction is developed, which effectively captures the correlation between the primary color and the resulting mixed color. Four primary colors are created using four sets of laser marking parameters. Mixing these primary colors in varying proportions can achieve more than 100 new tones with rich colors. The average color difference ΔE a b ∗ and ΔE00∗ are 1.98 and 1.80, respectively. By utilizing this model to adjust the proportion of primary colors in each subgraph, an image with vibrant and rich colors is generated, thereby achieving the implementation of a structural color image based on mixed colors.