The femtosecond (fs) laser ablation of metals is a precise method used to create microfeatures on the surface of the material with a minimized heat-affected zone (HAZ). Despite its many advantages, fs laser ablation often requires extensive trial-and-error experimentation before finding the optimal laser strategy for a desired geometry with minimal HAZ. The pulse-based two-temperature model (TTM) can significantly shorten this process by predicting the ablated geometry based on a set of material and laser parameters. However, this model has only been validated for percussion drilling and single lines. In this study, the pulse-based TTM is tested against parallel line experiments and subsequently modified to include geometry-dependent material parameters. More specifically, the threshold fluence and reflectivity of the material are modified to incorporate the temperature increase inside the standing features between parallel lines. The introduced geometry-dependent factors are fitted with experimental data and their inclusion in the model is shown to have a positive impact on the simulation results. The results show a clear amelioration in the shape and depth of the simulated profiles, with the error on the average depth and width of the modified TTM being lower than the average standard deviation on the experiments.

Polymer hollow microneedles (HMNs) offer significant potential in medical, diagnostic, and cosmetic applications due to their minimally invasive nature and high replication capability. However, their fabrication using injection molding with ultrashort pulsed laser ablated molds presents several challenges, particularly in predicting process outcomes such as cavity filling and replication fidelity. This study investigates the role of injection molding simulations in addressing these challenges, focusing on the influence of the venting boundary conditions. Moldex 3D 2023 and 2024 versions are compared with and without the inclusion of venting boundary conditions, showing the importance of venting for the prediction of HMN heights. The 2023 version underestimates the filling height by 45%, while the 2024 version overestimates it by 18%. Furthermore, manual air volume calculations using the ideal gas law revealed deviations in both versions: the 2023 version significantly overestimates the entrapped air volume, while the 2024 version underestimates it. These findings indicate the necessity for more accurate algorithms to model compressible air dynamics in micro-scale geometries effectively. By addressing these challenges and improving the predictive accuracy of injection molding simulations, further research can pave the way for reducing trial-and-error in process development, lowering manufacturing costs, and enabling scalable production of HMNs.