Functional laser surface texturing (LST) arose in recent years as a very powerful tool for tailoring the surface properties of parts and components to their later application. As a result, self-cleaning surfaces with an improved wettability, efficient engine components with optimized tribological properties, and functional implants with increased biocompatibility can be achieved today. However, with increasing capabilities in functional LST, the prediction of resulting surface properties becomes more and more important in order to reduce the development time of those functionalities. Consequently, advanced approaches for the prediction of the properties of laser-processed surfaces—the so-called predictive modelling—are required. This work introduces the concept of predictive modelling with respect to LST by means of direct laser writing (DLW). Fundamental concepts for the prediction of surface properties are presented employing machine learning approaches, theoretical concepts, and statistical methods. The modelling takes into consideration the used laser parameters, the analysis of topographical, and other process-relevant information in order to predict the resulting surface roughness. For this purpose, two different algorithms, namely artificial neural network and random forest, were trained with experimental data for stainless steel and Stavax surfaces. Statistical results indicate that both models can predict the desired surface topography with high accuracy, despite the use of a small dataset for the training process. The approaches can be used to further optimize the laser process regarding the process efficiency, overall throughput, and other process outcomes.

Titanium-based Metal Matrix Composites (MMCs) manufactured by additive manufacturing offer tremendous lightweighting opportunities. However, processing the high reinforcement contents needed to substantially improve elastic modulus while conserving significant ductility remains a challenge. Ti-TiC MMCs fabricated in this study reported fracture strains in tension up to 1.7% for a Young’s modulus of 149 GPa. This fracture strain is 30% higher than the previously reported values for Ti-based MMCs produced by Laser Powder Bed Fusion (LPBF) displaying similar Young’s moduli. The heat treatment used after the LPBF process leads to the doubling of the fracture strain thanks to the conversion of TiC_x dendrites into equiaxed TiC_x grains. The as-built microstructure shows both un-dissolved TiC particles and sub-stoichiometric TiC dendrites resulting from the partial dissolution of TiC particles. The reduction of the C/Ti ratio in TiC during the process results in an increase in the reinforcement content, from a nominal 12 vol% to an effective 21.5 vol%. The variation of the TiC lattice constant with its stoichiometry is measured, and an empirical expression is proposed for its effect on TiC’s Young’s modulus. The lower TiC powder size distribution displayed higher mechanical properties thanks to a reduced number of intrinsic flaws.

Titanium-based Metal Matrix Composites (MMCs) manufactured by additive manufacturing offer tremendous lightweighting opportunities. However, processing the high reinforcement contents needed to substantially improve elastic modulus while conserving significant ductility remains a challenge. Ti-TiC MMCs fabricated in this study report fracture strains in tension up to 1.7% for a Young’s modulus of 149 GPa. This fracture strain is 30% higher than previously reported values for Ti-based MMCs produced by Laser Powder Bed Fusion (LPBF) displaying similar Young’s moduli. The heat treatment used after the LPBF process leads to the doubling of the fracture strain due to the conversion of TiCx dendrites into equiaxed TiCx grains. As-built microstructure shows both un-dissolved TiC particles and sub-stoichiometric TiC dendrites resulting from a partial dissolution of TiC particles. Reduction of the C/Ti ratio in TiC during the process results in an increase in the reinforcement content, from a nominal 12 vol% to an effective 21.5 vol%. The variation of the TiC lattice constant with its stoichiometry is measured, and an empirical expression is proposed for its effect on TiC’s Young’s modulus. The lower TiC initial powder size distribution displayed the best mechanical performance.

Here, we present a two-step annealing procedure to imprint nanofeatures on SiO ₂ starting from metallic microfeatures. The first annealing transforms the microfeatures into gold nanoparticles and the second imprints these nanoparticles into the SiO ₂ layer with nanometric control. The resulting nanohole arrays show a high ensemble uniformity. As a potential application, the nanohole mask is used as a selective mask for the Ga self-assisted growth of GaAs nanowires (NWs). Thus, for the first time, a successful implementation of nano-self-imprinting that links high-throughput microlithography with bottom-up NW growth is shown. The beneficial hole morphology of the SiO ₂ mask promotes high Ga droplet contact angles with the silicon substrate and the formation of single droplets in the mask holes. This droplet predeposition configuration enables a high vertical yield of NWs. Thus, this article describes a new protocol to grow NW devices that combines simultaneously nanosized holes and parallel processing.

The production of high stiffness Ti-based Metal Matrix Composites (Ti-MMCs) displaying significant ductility by additive manufacturing technologies is not yet at the level of conventionally produced Ti-MMCs. This study outlines the production process of stiffness-driven Ti-TiC MMCs displaying a remarkable ductility. The process consists in powder Mechanical Blending, Laser Powder Bed Fusion (LPBF), and a heat treatment. A TiC fraction of more than 20 vol% was formed in-situ through the reaction of titanium with carbon during the LPBF process. The as-built sub-stoichiometric TiC dendrites are converted in equiaxed TiC grains during the heat treatment. The TiC C/Ti ratio was found to be close to 0.5 in as-built conditions, and 0.7 in heat treated conditions, resulting in an effective reinforcement content nearly twice the one expected for stoichiometric TiC, leading to stronger reinforcement. The mechanical analysis revealed a Young’s modulus of up to 149 GPa and total elongations of up to 2.8%. The former represents a 27% improvement compared to commercially pure Titanium and the latter exceeds by 115% reported values for LPBF Ti-MMCs with similar Young’s modulus. It is enabled by the in-situ formation of defect-free TiC reinforcements combined with their globularisation through heat treatment.