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The human placenta is a unique organ serving as the lung, gut, liver, and kidney of the fetus, mediating the exchange of different endogenous as well as exogenous substances and gases between the mother and fetus during pregnancy. Additionally, the placental barrier protects the fetus from a range of environmental toxins, bacterial and viral infections, since any contaminant bridging the placenta may have unforeseeable effects on embryonal and fetal development. A more recent concern in placenta research, however, involves the ability of engineered nanoparticles to cross the placental barrier and/or affect its barrier function. To advance nanoparticle risk assessment at the human placental barrier, we have developed as proof-of-principle a highly integrated placenta-on-a-chip system containing embedded membrane-bound impedance microsensor arrays capable of non-invasively monitoring placental barrier integrity. Barrier integrity is continuously and label-free evaluated using porous membrane-based interdigitated electrode structures located on top of a porous PET membrane supporting a barrier of trophoblast-derived BeWo cell barrier in the absence and presence of standardized silicon dioxide (SiO2), titanium dioxide (TiO2), and zinc oxide (ZnO) nanomaterials., This work has been funded by the European Union’s Horizon 2020 research and innovation program under grant agreement No. 685817.

FIB technologies possess a unique ability to form topographies that are difficult or impossible to generate with binary etching through typical photo-lithography. The ability to arbitrarily vary the spatial dose distribution and therefore the amount of milling opens possibilities for the production of a wide range of functional structures with applications in biology, chemistry, and optics. However in practice, the realization of these goals is made difficult by the angular dependence of the sputtering yield and redeposition effects that vary as the topography evolves. An inverse modeling algorithm that optimizes dose profiles, defined as the superposition of time invariant pixel dose profiles (determined from the beam parameters and pixel dwell times), is presented. The response of the target to a set of pixel dwell times in modeled by numerical continuum simulations utilizing 1st and 2nd order sputtering and redeposition, the resulting surfaces are evaluated with respect to a target topography in an error minimization routine. Two algorithms for the parameterization of pixel dwell times are presented, a direct pixel dwell time method, and an abstracted method that uses a refineable piecewise linear cage function to generate pixel dwell times from a minimal number of parameters. The cage function method demonstrates great flexibility and efficiency as compared to the direct fitting method with performance enhancements exceeding ∼10× as compared to direct fitting for medium to large simulation sets. Furthermore, the refineable nature of the cage function enables solutions to adapt to the desired target function. The optimization algorithm, although working with stationary dose profiles, is demonstrated to be applicable also outside the quasi-static approximation. Experimental data confirms the viability of the solutions for 5 × 7 μm deep lens like structures defined by 90 pixel dwell times.

In this article we explore the application of scanning capacitance microscopy (SCM) for studying focused ion beam (FIB) induced damage in silicon. We qualitatively determine the technologically important beam shape by measuring the SCM image of FIB processed implantation spots and by comparison of topographical and SCM data. Further, we investigate the question how deep impinging ions generate measurable damage below the silicon surface. For this purpose, trenches were manufactured using FIB and analyzed by SCM in cross-sectional geometry.

In Raman spectroscopy, detection limits for organic pollutants in water can be lowered by several orders of magnitude when surface enhanced techniques are applied. In this work a continuous analytical device based on flow injection analysis using SERS detection is proposed. This system was tested with model analytes such as pyridine and nicotinic acid as well as several pesticides (carbendazim, metazachlorine).

The presence of rough metal surfaces is known to increase the infrared absorption of selected analytes. It could be shown that this surface enhancement effect applies to a wide range of chemical substrates with different molecular structure, although the observed enhancement is not equivalent for all absorption bands. For carboxyl groups, interactions with the metal surface were observed suggesting the formation of an adsorption complex. Furthermore, the potential of surface enhanced infrared absorption (SEIRA) as quantitative method is demonstrated.