3D-inkjet-printing is just beginning to take off in the optical field. Advantages of this technique include its fast and cost-efficient fabrication without tooling costs. However, there are still obstacles preventing 3D inkjet-printing from a broad usage in optics, e.g., insufficient form fidelity. In this article, we present the formulation of a digital twin by the enhancement of an optical model by integrating geometrical measurement data. This approach strengthens the high-precision 3D printing process to fulfil optical precision requirements. A process flow between the design of freeform components, fabrication by inkjet printing, the geometrical measurement of the fabricated optical surface, and the feedback of the measurement data into the simulation model was developed, and its interfaces were defined. The evaluation of the measurements allowed for the adaptation of the printing process to compensate for process errors and tolerances. Furthermore, the performance of the manufactured component was simulated and compared with the nominal performance, and the enhanced model could be used for sensitivity analysis. The method was applied to a highly complex helical surface that allowed for the adjustment of the optical power by rotation. We show that sensitivity analysis could be used to define acceptable tolerance budgets of the process.

Artificial intelligence (AI) has emerged as a powerful set of tools for engineering innovative materials. However, the AI-aided design of materials textures has not yet been researched in depth. In order to explore the potentials of AI for discovering innovative biointerfaces and engineering materials surfaces, especially for biomedical applications, this study focuses on the control of wettability through design-controlled hierarchical surfaces, whose design is supported and its performance predicted thanks to adequately structured and trained artificial neural networks (ANN). The authors explain the creation of a comprehensive library of microtextured surfaces with well-known wettability properties. Such a library is processed and employed for the generation and training of artificial neural networks, which can predict the actual wetting performance of new design biointerfaces. The present research demonstrates that AI can importantly support the engineering of innovative hierarchical or multiscale surfaces when complex-to-model properties and phenomena, such as wettability and wetting, are involved.

Peptide microarrays are a fast-developing field enabling the mapping of linear epitopes in the immune response to vaccinations or diseases and high throughput studying of protein-protein interactions. In this respect, a rapid label-free measurement of protein layer topographies in the array format is of great interest but is also a great challenge due to the extremely low aspect ratios of the peptide spots. We have demonstrated the potential of vertical scanning interferometry (VSI) for a detailed morphological analysis of peptide arrays and binding antibodies. The VSI technique is shown to scan an array area of 5.1 square millimeters within 3–4 min at a resolution of 1.4 μm lateral and 0.1 nm vertical in the full automation mode. Topographies obtained by VSI do match the one obtained by AFM measurements, demonstrating the accuracy of the technique. A detailed topology of peptide-antibody layers on single spots was measured. Two different measurement regions are distinguished according to the antibody concentration. In the case of weakly diluted serum, the thickness of the antibody layer is independent of the serum dilution and corresponds to the physical thickness of the accumulated antibody layer. In strongly diluted serum, the thickness measured via VSI is linearly proportional to the serum dilution.

Recent studies have speculated that some snakes developed white venters to avoid overheating caused by highly radiative soil and rocks. Here, we present the scale-embedded porous nanostructures through which some snake species of the genus Bitis achieve such whiteness. Our analysis reveals nanopores causing scattering underneath the external surface of the white ventral scales of Bitis rubida and Bitis armata . Such nanopores are not present in the scales of Bitis parviocula, Bitis arietans and Bitis rhinoceros that appear transparent or translucent to the naked eye. White ventral scales with nanopores reflect up to 40% of light in the visible regime. The reflection, however, decreases for longer wavelengths and drastically reduces in the infrared. In contrast, a much lower, almost constant reflection around 8% between 250 and 2500 nm is observed for the transparent or translucent ventral scales without nanopores. Our study demonstrates that some snake species of the genus Bitis utilize a light-scattering network of nanopores underneath their external surfaces to create white ventral scales.

Insects optimize friction in their joints by combining microstructures with a—so far unknown—lubricant. To develop environmentally friendly lubricants, we research the sophisticated tribological system found in the joints of beetles. We characterize the lubricant as well as the microstructure of the joints to gain inspiration for the development of a degradable and—hopefully—superior alternative to mineral-oil-based lubricants. However, restrained by the tiny quantities of beetle lubricant and the compactness of their joints, this tribological analysis is challenging. Therefore, we apply atomic force microscopy (AFM) to record the joints' microstructures and the lubricant's frictional properties. Furthermore, we research the inner structure of the bearing surface in beetle joints by focused ion beam (FIB) tomography. With this approach, we discover a network of channels supplying the lubricant to pores which represent the inlets of the hinged joint system. As a subsequent step, we analyze different types of presently available plant mucilage using AFM friction measurements to compare the suitability of plant mucilage as an alternative lubricant to the tiny quantities of beetle lubricant. Finally, we develop an artificial surface mimicking the microstructure of beetle joints. We determine its frictional properties utilizing colloidal AFM probes in the dry state as well as the lubricated state with plant mucilage as the lubricant.