The understanding of the fundamental physical properties of metal-organic and organic-organic interfaces is crucial for improving the performance of organic electronic devices. This is particularly true for (multilayer) systems containing several molecular species due to their relevance for donor-acceptor systems. A prototypical heteromolecular bilayer system is copper-II-phthalocyanine (CuPc) on 3,4,9,10-perylene-tetra-carboxylic-dianhydride (PTCDA) on Ag(111). In an earlier work we have reported a commensurate registry between both organic layers and an enhanced charge transfer from the Ag substrate into the organic bilayer film [ Phys. Rev. Lett. 108, 106103 (2012)], which both indicate an unexpectedly strong intermolecular interaction across the organic-organic interface. Here we present new details regarding electronic and geometric structure for the same system. In particular, we provide evidence that the enhanced charge transfer from the substrate into the organic bilayer does not involve CuPc electronic states, hence, there is no significant charge transfer into the second organic layer. Furthermore, we report vertical bonding distances revealing a shortening of the PTCDA-Ag(111) distance upon CuPc adsorption. Thus, electronic and geometric properties (charge transfer and bonding distance, respectively) both indicate a strengthening of the PTCDA-Ag(111) bond upon CuPc adsorption. We explain these findings—in particular the correlation between CuPc adsorption and increased charge transfer into PTCDA—in a model involving an intermolecular screening mechanism.

The touch-feel sensation of product surfaces arouses growing interest in various industry branches. To entangle the underlying physical and material parameters responsible for a specific touch-feel sensation, a new measurement system has been developed. This system aims to record the prime physical interaction parameters at a time, which is considered a necessary prerequisite for a successful physical description of the haptic sensation. The measurement setup enables one to measure the dynamic coefficient of friction, the macroscopic contact area of smooth and rough surfaces, the angle enclosed between the human finger and the soft-touch surfaces and the vibrations induced in the human finger during relative motion at a time. To validate the measurement stand, a test series has been conducted on two soft-touch surfaces of different roughness. While the individual results agree well with the literature, their combination revealed new insights. Finally, the investigation of the haptics of polymer coatings with the presented measuring system should facilitate the design of surfaces with tailor-made touch-feel properties.

The detection of the contact area formed between a human finger and a counter surface is of great interest because it is the key parameter for various interaction parameters. Adhesional friction forces and the thermal contact conductance critically depend on the contact area, further influencing the tactile sensation of stickiness and warmth. The contact area is also of concern regarding safety issues. Injuries caused by objects slipping out of our hands might be prevented by optimizing the contact area and the concomitant grip through appropriate surface structures and material choice. Until now the contact area is mainly studied on smooth and transparent materials. The contact area is recorded optically and rule-based image processing methods can be used for detection. These methods might be insufficient for rough surfaces where the contact area is optically unclear due to light scattering. In this paper we demonstrate the successful analysis of such optically unclear contact area images via convolutional neural networks to identify the fingerprint ridges in contact with structured surfaces. The proposed method relies on the generation of synthetic contact images that provide the pixelwise ground truth for the efficient training of a segmentation pipeline based on convolutional neural networks.

Structured surfaces, which are the basis of the lotus blossom effect, have great potential to serve/operate as functionalised surfaces, i.e., surfaces with specific and/or adjustable properties. In the present study, the aim is to use micro-structured elastomeric surfaces to specifically influence the friction and deformation behaviours on the basis of the shape and arrangement of the structures. Thiol-acrylate-based photopolymers patterned via nanoimprint lithography were investigated by using an in situ tribological measurement set-up. A clear influence of the different structures on the surface’s friction behaviour could be shown, and, furthermore, this could be brought into relation with the real area of contact. This finding provides an important contribution to further development steps, namely, to give the structures switchable properties in order to enable the control of friction properties in a targeted manner.

Haptic qualities of surfaces play an important role for the user's experience with a system. In that context, soft touch surfaces are important as they are often used for surfaces of industrial products. For assessing related experiences, research is often focusing on physical properties of the surfaces rather than the (quality of) experience of the user. Therefore, we set out to analyze how people describe their experience of surface properties in a bottom-up approach. In an Open Profiling study we let people self-describe, cluster and rate surface properties. Based on these ratings we applied a Principal Component Analysis to identify characteristics and related perception dimensions of soft touch surfaces. Furthermore, we complement this with an expert clustering of user self-descriptions. Our analysis shows that descriptions can be categorized in pragmatic and hedonic (and/or affective) dimensions. With this research we contribute to better understanding the quality of material related experiences.