Publikationen

While viscoelastic, adhesive contact rupture of simple indenters is well studied, contact formation has received much less attention. Here, we present simulations of the formation of contact between various power law indenters and an adhesive, viscoelastic foundation. For all investigated indenters, we find that the macroscopic relaxation time τ scales approximately with 1/ρ1.8, where ρ is the range of adhesion. The prolongation of contact formation with Tabor parameter is rationalized by the increased dissipation that short-range adhesion causes on a moving crack.

Bioinspired fibrillar adhesives have been proposed for novel gripping systems with enhanced scalability and resource efficiency. Here, we propose an in-situ optical monitoring system of the contact signatures, coupled with image processing and machine learning. Visual features were extracted from the contact signature images recorded at maximum compressive preload and after lifting a glass object. The algorithm was trained to cope with several degrees of misalignment and with unbalanced weight distributions by off-center gripping. The system allowed an assessment of the picking process for objects of various mass (200, 300, and 400 g). Several classifiers showed a high accuracy of about 90 % for successful prediction of attachment, depending on the mass of the object. The results promise improved reliability of handling objects, even in difficult situations.

Nanostructured earth abundant metal catalysts that mediate important chemical reactions with high efficiency and selectivity are of great interest. This study introduces a synthesis protocol for nanostructured earth abundant metal catalysts. Three components, an inexpensive metal precursor, an easy to synthesize N/C precursor, and a porous support material undergo pyrolysis to give the catalyst material in a simple, single synthesis step. By applying this catalyst synthesis, a highly active cobalt catalyst for the general and selective hydrogenation of aromatic heterocycles could be generated. The reaction is important with regard to organic synthesis and hydrogen storage. The mild reaction conditions observed for quinolines permit the selective hydrogenation of numerous classes of N-, O- and S-heterocyclic compounds such as: quinoxalines, pyridines, pyrroles, indoles, isoquinoline, aciridine amine, phenanthroline, benzofuranes, and benzothiophenes.

Background: Due to COVID-19, pandemic preparedness emerges as a key imperative, necessitating new approaches to accelerate development of reagents against infectious pathogens. Methods: Here, we developed an integrated approach combining synthetic, computational and structural methods with in vitro antibody selection and in vivo immunization to design, produce and validate nature-inspired nanoparticle-based reagents against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
Results: Our approach resulted in two innovations: (i) a thermostable nasal vaccine called ADDoCoV, displaying multiple copies of a SARS-CoV-2 receptor binding motif derived epitope and (ii) a multivalent nanoparticle superbinder, called Gigabody, against SARS-CoV-2 including immune-evasive variants of concern (VOCs). In vitro generated neutralizing nanobodies and electron cryo-microscopy established authenticity and accessibility of epitopes displayed by ADDoCoV. Gigabody comprising multimerized nanobodies prevented SARS-CoV-2 virion attachment with picomolar EC50. Vaccinating mice resulted in antibodies cross-reacting with VOCs including Delta and Omicron.
Conclusion: Our study elucidates Adenovirus-derived dodecamer (ADDomer)-based nanoparticles for use in active and passive immunization and provides a blueprint for crafting reagents to combat respiratory viral infections.

An unresolved issue in contemporary biomedicine is the overwhelming
number and diversity of complex images that require annotation, analysis and
interpretation. Recent advances in Deep Learning have revolutionized the field
of computer vision, creating algorithms that compete with human experts in
image segmentation tasks. However, these frameworks require large human-
annotated datasets for training and the resulting “black box” models are dif-
ficult to interpret. In this study, we introduce Kartezio, a modular Cartesian
Genetic Programming-based computational strategy that generates fully
transparent and easily interpretable image processing pipelines by iteratively
assembling and parameterizing computer vision functions. The pipelines thus
generated exhibit comparable precision to state-of-the-art Deep Learning
approaches on instance segmentation tasks, while requiring drastically smaller
training datasets. This Few-Shot Learning method confers tremendous flex-
ibility, speed, and functionality to this approach. We then deploy Kartezio to
solve a series of semantic and instance segmentation problems, and demon-
strate its utility across diverse images ranging from multiplexed tissue histo-
pathology images to high resolution microscopy images. While the flexibility,
robustness and practical utility of Kartezio make this fully explicable evolu-
tionary designer a potential game-changer in the field of biomedical image
processing, Kartezio remains complementary and potentially auxiliary to
mainstream Deep Learning approaches.

Ionic liquids (ILs) represent an important class of liquids considered for a broad range of applications such as lubrication, catalysis, or as electrolytes in batteries. It is well-known that in the case of charged surfaces, ILs form a pronounced layer structure that can be easily triggered by an externally applied electrode potential. Information about the time required to form a stable interface under varying electrode potentials is of utmost importance in many applications. For the first time, probing of relaxation times of ILs by friction force microscopy is demonstrated. The friction force is extremely sensitive to even subtle changes in the interfacial configuration of ILs. Various relaxation processes with different time scales are observed. A significant difference dependent on the direction of switching the applied potential, i.e., from a more cation-rich to a more anion-rich interface or vice versa, is found. Furthermore, variations in height immediately after the potential step and the presence of trace amounts of water are discussed as well.

The presence of mechanoreceptors in glabrous skin allows humans to discriminate textures by touch. The amount and distribution of these receptors defines our tactile sensitivity and can be affected by diseases such as diabetes, HIV-related pathologies, and hereditary neuropathies. The quantification of mechanoreceptors as clinical markers by biopsy is an invasive method of diagnosis. We report the localization and quantification of Meissner corpuscles in glabrous skin using in vivo, non-invasive optical microscopy techniques. Our approach is supported by the discovery of epidermal protrusions which are co-localized with Meissner corpuscles. Index fingers, small fingers, and tenar palm regions of ten participants were imaged by optical coherence tomography (OCT) and laser scan microscopy (LSM) to determine the thickness of the stratum corneum and epidermis and to count the Meissner corpuscles. We discovered that regions containing Meissner corpuscles could be easily identified by LSM with an enhanced optical reflectance above the corpuscles, caused by a protrusion of the strongly reflecting epidermis into the stratum corneum with its weak reflectance. We suggest that this local morphology above Meissner corpuscles has a function in tactile perception.

Glabrous skin is hair-free skin with a high density of sweat glands, which is found on the palms, and soles of mammalians, covered with a thick stratum corneum. Dry hands are often an occupational problem which deserves attention from dermatologists. Urea is found in the skin as a component of the natural moisturizing factor and of sweat. We report the discovery of dendrimer structures of crystalized urea in the stratum corneum of palmar glabrous skin using laser scanning microscopy. The chemical and structural nature of the urea crystallites was investigated in vivo by non-invasive techniques. The relation of crystallization to skin hydration was explored. We analysed the index finger, small finger and tenar palmar area of 18 study participants using non-invasive optical methods, such as laser scanning microscopy, Raman microspectroscopy and two-photon tomography. Skin hydration was measured using corneometry. Crystalline urea structures were found in the stratum corneum of about two-thirds of the participants. Participants with a higher density of crystallized urea structures exhibited a lower skin hydration. The chemical nature and the crystalline structure of the urea were confirmed by Raman microspectroscopy and by second harmonic generated signals in two-photon tomography. The presence of urea dendrimer crystals in the glabrous skin seems to reduce the water binding capacity leading to dry hands. These findings highlight a new direction in understanding the mechanisms leading to dry hands and open opportunities for the development of better moisturizers and hand disinfection products and for diagnostic of dry skin.

Stacked hetero-structures of two-dimensional materials allow for a design of interactions with corresponding electronic and mechanical properties. We report structure, work function, and frictional properties of 1 to 4 layers of MoS2 grown by chemical vapor deposition on epitaxial graphene on SiC(0001). Experiments were performed by atomic force microscopy in ultra-high vacuum. Friction is dominated by adhesion which is mediated by a deformation of the layers to adapt the shape of the tip apex. Friction decreases with increasing number of MoS2 layers as the bending rigidity leads to less deformation. The dependence of friction on applied load and bias voltage can be attributed to variations in the atomic potential corrugation of the interface, which is enhanced by both load and applied bias. Minimal friction is obtained when work function differences are compensated.

Electrochemically responsive hydrogel networks have been obtained using printable inks made of a biopolymer, alginate (Alg), and an inorganic 2D material, MXene (titanium carbide, Ti3C2Tx) nanosheets. While MXene offers an electrically conductive pathway for electron transfer and Alg provides an interconnected framework for ion diffusion, the printed nanocomposite results, after gelation, in an extended active interface for redox reactions, being an ideal framework to design and construct flexible devices for biomedical applications. In this work, after characterization, we demonstrate that hydrogels obtained by cross-linking printed Alg/MXene inks exhibit great potential for bioelectronics. More specifically, we prove that flexible Alg/MXene hydrogels act as self-supported electroactive electrodes for the electrochemical detection of bioanalytes, such as dopamine, with a performance similar to that achieved using more sophisticated electrodes, as for example those containing conducting polymers and electrocatalytic gold nanoparticles. In addition, Alg/MXene hydrogels have been successfully used to regulate the release of a previously loaded broad spectrum antibiotic (chloramphenicol) by electrical stimulation.