Laser‐induced periodic surface structures (LIPSS) represent a unique route for functionalizing materials through the fabrication of surface nanostructures. Commercial AISI 316L stainless steel (SS316L) surfaces are laser treated by ultraviolet 300 ps laser pulses in a laser line scanning (LLS) approach. Processing parameters are optimized (pulse energy of 2.08 µJ, pulse repetition frequency of 300 kHz, and suitable laser scan and sample displacement rates) for the generation of low spatial frequency LIPSS over a large 25 × 25 mm² area. Different angles of incidence of the laser radiation (0°, 30°, and 45°) and different linear laser beam polarizations (s and p) produce a plethora of rippled surface morphologies at distinct grains. Scanning electron microscopy and 2D Fourier transforms, together with calculations of the optical energy deposited at the treated surfaces using Sipe's first‐principles electromagnetic scattering theory, are used to study and analyze in detail these surface morphologies. Combined with electron backscattering diffraction, analyses allow associating site‐selectively various laser‐induced‐surface morphologies with the underlying crystalline grain orientation. Resulting grain orientation maps reveal a strong impact of the grain crystallographic orientation on LIPSS formation and point toward possible strategies, like multi‐step processes, for improving the manufacturing of LIPSS and their areal coverage of polycrystalline technical materials.

Ultra-short-pulse laser radiation has been used to modulate the electrical conductivity of ZnO thin films deposited by spatial atomic layer deposition. Resistance time evolution exhibits high sensitivity to oxygen concentration in the environment.

Surface topography plays a critical role in the functional performance of machined freeform components, yet its assessment traditionally takes place only after manufacturing. This work presents a simulation-assisted framework for predicting the surface topography generated during freeform ball-end milling and using these predictions to support machining-strategy selection. Three finishing strategies (3-axis square, SQ3, 3-axis spiral, SP3, and 5-axis spiral, SP5) were investigated on a representative freeform benchmark by combining high-resolution UVRMAP simulations with experimental topography measurements. Surface signatures were characterized using ISO 25178 areal parameters together with two- and one-dimensional Fast Fourier Transform (FFT) analyses, enabling quantitative evaluation of surface amplitude, preferential orientations, anisotropy, and characteristic spatial periodicities. The results demonstrate that machining strategy and local surface geometry produce distinctive topographical signatures that cannot be fully described by conventional roughness parameters alone.Theproposed UVRMAP methodology accurately reproduces the primary spatial organization of the geometric texture generated by the programmed toolpath, while the incorporation of a controlled non-ideal cutter-edge representation improves the prediction of experimentally observed fine-scale features. The combined experimental–simulation methodology provides a robust framework for comparing and validating the spatial and morphological characteristics of predicted surface topographies, providing a basis for future machining-strategy selection according to application-specific surface requirements.