Superhydrophobic and self-cleaning aluminium surfaces via affordable nanosecond fibre laser and vacuum treatment

Abstract Self-cleaning surfaces have a great potential for applications in the construction, aviation, food and energy industries. A common strategy for achieving self-cleaning functionality is to render the surface superhydrophobic, enabling water droplets to roll off and remove dirt particles. In this article the aluminium sample was treated using an affordable nanosecond laser combined with vacuum processing to induce superhydrophobicity. Various processing parameters were investigated, including structural geometry, hatch distance, and additional defocused irradiation. Following fabrication, the surfaces were evaluated for self-cleaning performance by applying MnO 2 and polyamide particles of defined sizes and tilting the samples by 15 ∘ . A specified number of 20 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mstyle scriptlevel="0"/> <mml:mi>μ</mml:mi> </mml:mrow> </mml:math> l water droplets was allowed to roll over the contaminated surfaces and the cleaning efficacy was quantitatively analysed through optical imaging and image processing. The most effective configuration, rhombic structures with 80 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mstyle scriptlevel="0"/> <mml:mi>μ</mml:mi> </mml:mrow> </mml:math> m hatch distance, removed over 95% MnO 2 particles after only three droplets. The confocal and electron microscopy characterisation of the surface was used to understand the relation between surface topography and the cleaning effect.