Laser cleaning enables selective, non-contact removal of contaminants and coatings, but coating color alone cannot reliably predict cleaning behavior because laser–material coupling depends on wavelength-dependent absorption, scattering, and energy deposition. This review develops a spectral-selectivity framework linking measured absorptance/reflectance, coating–substrate optical contrast, removal mechanisms, and process-window design. Radiation-pressure effects, shock-wave loading, thermoelastic vibration, plasma expansion, recoil, and ablation are discussed to explain mechanical, thermal, and chemical removal pathways. Representative studies of dark carbonaceous deposits, light-colored oxide and polymer coatings, chromatic paints, and multilayer coatings are critically compared. The analysis integrates spectral selectivity, separation of coating-removal and substrate-damage thresholds, thermal confinement, and endpoint recognition. These considerations provide guidance for wavelength selection, process-window design, and adaptive parameter optimization in the laser cleaning of colored and multilayer coatings.
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Yang et al. (2026) studied this question.
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