Discrete model for laser driven etching and microstructuring of metallic surfaces

Abstract

We present a unidimensional discrete solid-on-solid model evolving in time using a kinetic Monte Carlo method to simulate microstructuring of kerfs on metallic surfaces by means of laser-induced jet-chemical etching. The precise control of the passivation layer achieved by this technique is responsible for the high resolution of the structures. However, within a certain range of experimental parameters, the microstructuring of kerfs on stainless steel surfaces with a solution of H3PO4 shows periodic ripples, which are considered to originate from intrinsic dynamics. The model mimics a few of the various physical and chemical processes involved and within certain parameter ranges reproduces some morphological aspects of the structures, in particular ripple regimes. We analyze the range of values of laser beam power for the appearance of ripples in both experimental and simulated kerfs. The discrete model is an extension of one that has been used previously in the context of ion sputtering and is related to a noisy version of the Kuramoto-Sivashinsky equation used extensively in the field of pattern formation.

Self-Organized Surface Nanopatterning by Ion Beam Sputtering

“…Actually, this energy deposition rule has been extended even to MC studies of different physical processes, such as e.g. laser induced jet chemical etching [118]. Nevertheless, other MC models do consider more microscopic (albeit still approximate) rules for erosion, such as the binary collision approximation similar to that employed in SRIM simulations [200,201], as done in the works by Koponen and collaborators [96,97,98,99,100].…”

Evolution of slow electrostatic shock into a plasma shock mediated by electrostatic turbulence

“…Due to the favorable charge-to-mass ratio, hydrocarbon ions resulting from surface impurities are the first to be accelerated, followed, at a later time, by ions of the solid itself. These ions expand into the surrounding medium in the form of a rarefaction wave [8][9][10][11], which is characterized by decreasing density and increasing velocity as it moves further from the source. Meanwhile, xrays emanating from the laser interaction point induce photoionization of the low-density gas embedding the target.…”

A quality controlled laser-chemical process for micro metal machining

“…The forward process model is based on the analysis of cause-effect relations between the process parameters and the removal rate. Due to its complex and partly unknown performance [3], the LCM process is modelled by a Radial Basis Function (RBF) network, which is presented in [10,12]. The input quantities of this model are the four process parameters (p, m, D, Q), resulting in the form variables depth a 1 and width a 2 of the removal cross section as output quantities.…”

“…It realizes a localized material removal in specified areas without microcracks and debris [2]. However, the dynamics of laser energy absorption, heat accumulating, chemical reactions, hydrodynamics, and transport phenomena cause various disturbances during the material removal process [3].…”