As a kind of typical material for mechanical structure, stainless steel is often adopted in the high-power laser facility. Iron elements in stainless steel may play an important role in resisting the effect of laser ablation. Laser ablation of stainless steel or aluminium alloy can also cause metal particle contamination in high-power laser facility. The ablation processes on iron surface under laser irradiation are investigated with molecular dynamics (MD) simulation combined with two-temperature model. The trajectories of atoms in each region of single crystal iron under laser irradiation are analyzed in terms of the interaction between laser and iron. The simulation results show that atoms absorbing different energy show the macroscopic characteristics of different phases of single crystal iron. Studies have also shown that single atom and clusters of atoms may have a backlash effect on the material and cause stress waves. The propagation of stress waves is also analyzed. It is shown that the velocity of the stress wave is about 6.094 km/s. Ablation threshold of single crystal iron is determined by the movement of surface atoms under different laser energy densities and the simulation results show that ablation threshold of single crystal iron under femtosecond laser is 0.18 J/cm<sup>2</sup>. Meanwhile, it is also found that the instantaneous loading of laser energy has a greater effect on material ablation. This study can underpin for investigating the damage and contamination of precision mechanical component with stainless steel under the effects of laser irradiation.
In high-energy laser facility, the residual nano-particles that are remained in mechanical system or produced by the
interaction of kinetic-pairs are inevitable. The generation and the propagation of particulate pollutants will seriously
reduce the performance of the laser systems. Therefore, the research about the adsorption behavior of particle
contaminants on fused silica is very important to maintain the optical components’ surface clean, reduce induced
damage, and finally prolong the life of the optical components. In this paper, the adsorption behavior between aluminum
nano-particles and fused silica was simulated by molecular dynamics method. The effect of the surface roughness of
fused silica on the state of adsorption and the state before adsorption has been studied. Then an experiment system based
on an atomic force microscope was established to measure the adsorption force and further to verify the simulated
results. Finally, the adsorption mechanism between metallic nano-particles and fused silica was revealed. The results
show that surface roughness and the size of the particles are two of the main factors to influence the adsorption force.
The rough fused silica surface can be “particle-phobic” due to the decreased contact area, which is beneficial to keep the
fused silica surface clean.
In some industrial fields, the workpiece surface need to meet not only the demand of surface roughness, but the strict requirement of multi-scale frequency domain errors. Ultra-precision machine tool is the most important carrier for the ultra-precision machining of the parts, whose errors is the key factor to influence the multi-scale frequency domain errors of the machined surface. The volumetric error modeling is the important bridge to link the relationship between the machine error and machined surface error. However, the available error modeling method from the previous research is hard to use to analyze the relationship between the dynamic errors of the machine motion components and multi-scale frequency domain errors of the machined surface, which plays the important reference role in the design and accuracy improvement of the ultra-precision machine tool. In this paper, a fourier transform based dynamic error modeling method is presented, which is also on the theoretical basis of rigid body kinematics and homogeneous transformation matrix. A case study is carried out, which shows the proposed method can successfully realize the identical and regular numerical description of the machine dynamic errors and the volumetric errors. The proposed method has strong potential for the prediction of the frequency domain errors on the machined surface, extracting of the information of multi-scale frequency domain errors, and analysis of the relationship between the machine motion components and frequency domain errors of the machined surface.