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The semiconductor field-effect platform represents a powerful tool for detecting the adsorption and binding of charged macromolecules with direct electrical readout. In this work, a capacitive electrolyte–insulator–semiconductor (EIS) field-effect sensor consisting of an Al-p-Si-SiO2 structure has been applied for real-time in situ electrical monitoring of the layer-by-layer formation of polyelectrolyte (PE) multilayers (PEM). The PEMs were deposited directly onto the SiO2 surface without any precursor layer or drying procedures. Anionic poly(sodium 4-styrene sulfonate) and cationic weak polyelectrolyte poly(allylamine hydrochloride) have been chosen as a model system. The effect of the ionic strength of the solution, polyelectrolyte concentration, number and polarity of the PE layers on the characteristics of the PEM-modified EIS sensors have been studied by means of capacitance–voltage and constant-capacitance methods. In addition, the thickness, surface morphology, roughness and wettabilityof the PE mono- and multilayers have been characterised by ellipsometry, atomic force microscopy and water contact-angle methods, respectively. To explain potential oscillations on the gate surface and signal behaviour of the capacitive field-effect EIS sensor modified with a PEM, a simplified electrostatic model that takes into account the reduced electrostatic screening of PE charges by mobile ions within the PEM has been proposed and discussed.
ETHICS is concerned with evaluating, measuring and making improvements in the thermal and energy performance of steel-clad and steel-framed buildings. It addresses basic building physics performance at a laboratory and full-scale level, and the preparation of design guidance for commercial, industrial and residential buildings. It includes the development of design tools to assist users in assessing whole-building performance, and calibrates these tools against whole-building measurements, which will be obtained from this research. Opportunities for renewable energy and other energy-saving features will be assessed. This project focuses on objectives that are of particular interest for the design of new steel constructions regarding energy efficiency. ETHICS investigates the as-built performance by on-site tests regarding air tightness and heat transfer properties of the building envelope and by monitoring the energy consumption and thermal comfort of selected up-to-date steel buildings. As energy efficiency is a key requirement for design and construction of buildings in the future, this project provides well-founded scientific data, which prove the high energy performance of current steel constructions and work out details for further improvements to maintain and extend the position of steel products in the construction sector.
Euler-based induced drag estimation for highly non-planar lifting systems during conceptional design
(2013)
Experimental investigation of selective laser melting of lunar regolith for in-situ applications
(2013)
Light-addressable potentiometric sensors (LAPS) are semiconductor-based potentiometric sensors, with the advantage to detect the concentration of a chemical species in a liquid solution above the sensor surface in a spatially resolved manner. The addressing is achieved by a modulated and focused light source illuminating the semiconductor and generating a concentration-depending photocurrent. This work introduces a LAPS set-up that is able to monitor the electrical impedance in addition to the photocurrent. The impedance spectra of a LAPS structure, with and without illumination, as well as the frequency behaviour of the LAPS measurement are investigated. The measurements are supported by electrical equivalent circuits to explain the impedance and the LAPS-frequency behaviour. The work investigates the influence of different parameters on the frequency behaviour of the LAPS. Furthermore, the phase shift of the photocurrent, the influence of the surface potential as well as the changes of the sensor impedance will be discussed.
The network approach towards the analysis of the dynamics of complex systems has been successfully applied in a multitude of studies in the neurosciences and has yielded fascinating insights. With this approach, a complex system is considered to be composed of different constituents which interact with each other. Interaction structures can be compactly represented in interaction networks. In this contribution, we present a brief overview about how interaction networks are derived from multivariate time series, about basic network characteristics, and about challenges associated with this analysis approach.
Biotechnological downstream processing is usually an elaborate procedure, requiring a multitude of unit operations to isolate the target component. Besides the disadvantageous space-time yield, the risks of cross-contaminations and product loss grow fast with the complexity of the isolation procedure. A significant reduction of unit operations can be achieved by application of magnetic particles, especially if these are functionalized with affinity ligands. As magnetic susceptible materials are highly uncommon in biotechnological processes, target binding and selective separation of such particles from fermentation or reactions broths can be done in a single step. Since the magnetizable particles can be produced from iron salts and low priced polymers, a single-use implementation of these systems is highly conceivable. In this article, the principles of magnetizable particles, their synthesis and functionalization are explained. Furthermore, applications in the area of reaction engineering, microfluidics and downstream processing are discussed focusing on established single-use technologies and development potential.
The chemical imaging sensor is a semiconductor-based chemical sensor that can visualize the spatial distribution of specific ions on the sensing surface. The conventional chemical imaging system based on the light-addressable potentiometric sensor (LAPS), however, required a long time to obtain a chemical image, due to the slow mechanical scan of a single light beam. For high-speed imaging, a plurality of light beams modulated at different frequencies can be employed to measure the ion concentrations simultaneously at different locations on the sensor plate by frequency division multiplex (FDM). However, the conventional measurement geometry of back-side illumination limited the bandwidth of the modulation frequency required for FDM measurement, because of the low-pass filtering characteristics of carrier diffusion in the Si substrate. In this study, a high-speed chemical imaging system based on front-side-illuminated LAPS was developed, which achieved high-speed spatiotemporal recording of pH change at a rate of 70 frames per second.
Impedance spectroscopy: A tool for real-time in situ monitoring of the degradation of biopolymers
(2013)
Investigation of the degradation kinetics of biodegradable polymers is essential for the development of implantable biomedical devices with predicted biodegradability. In this work, an impedimetric sensor has been applied for real-time and in situ monitoring of degradation processes of biopolymers. The sensor consists of two platinum thin-film electrodes covered by a polymer film to be studied. The benchmark biomedical polymer poly(D,L-lactic acid) (PDLLA) was used as a model system. PDLLA films were deposited on the sensor structure from a polymer solution by using the spin-coating method. The degradation kinetics of PDLLA films have been studied in alkaline solutions of pH 9 and 12 by means of an impedance spectroscopy (IS) method. Any changes in a polymer capacitance/resistance induced by water uptake and/or polymer degradation will modulate the global impedance of the polymer-covered sensor that can be used as an indicator of the polymer degradation. The degradation rate can be evaluated from the time-dependent impedance spectra. As expected, a faster degradation has been observed for PDLLA films exposed to pH 12 solution.
Learning- and memory-related processes are thought to result from dynamic interactions in large-scale brain networks that include lateral and mesial structures of the temporal lobes. We investigate the impact of incidental and intentional learning of verbal episodic material on functional brain networks that we derive from scalp-EEG recorded continuously from 33 subjects during a neuropsychological test schedule. Analyzing the networks' global statistical properties we observe that intentional but not incidental learning leads to a significantly increased clustering coefficient, and the average shortest path length remains unaffected. Moreover, network modifications correlate with subsequent recall performance: the more pronounced the modifications of the clustering coefficient, the higher the recall performance. Our findings provide novel insights into the relationship between topological aspects of functional brain networks and higher cognitive functions.
Introduction of RePriCo’13
(2013)