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Enzyme und Biosensorik
(2018)
Enzymbasierte Biosensoren finden seit mehr als fünf Jahrzehnten einen prosperierenden Wachstumsmarkt und werden zunehmend auch in biotechnologischen Prozessen eingesetzt. In diesem Kapitel werden, ausgehend vom Sensorbegriff und typischen Kenngrößen für Biosensoren (Abschn. 18.1), elektrochemische Enzym-Biosensoren vorgestellt und deren typischen Einsatzgebiete diskutiert (Abschn. 18.2). Ein Blick über den „Tellerrand“ hinaus zeigt alternative Transduktorprinzipien (Abschn. 18.3) und führt abschließend in aktuelle Forschungstrends ein (Abschn. 18.4).
Macroporous silicon has been etched from n-type Si, using a vertical etching cell where no rear side contact on the silicon wafer is necessary. The resulting macropores have been characterised by means of Scanning Electron Microscopy (SEM). After etching, SiO₂ was thermally grown on the top of the porous silicon as an insulating layer and Si₃N₄ was deposited by means of Low Pressure Chemical Vapour Deposition (LPCVD) as transducer material to fabricate a capacitive pH sensor. In order to prepare porous biosensors, the enzyme penicillinase has been additionally immobilised inside the porous structure. Electrochemical measurements of the pH sensor and the biosensor with an Electrolyte/Insulator/Semiconductor (EIS) structure have been performed in the Capacitance/Voltage (C/V) and Constant capacitance (ConCap) mode.
The demand of replacements for inoperable organs exceeds the amount of available organ transplants. Therefore, tissue engineering developed as a multidisciplinary field of research for autologous in-vitro organs. Such three dimensional tissue constructs request the application of a bioreactor. The UREPLACE bioreactor is used to grow cells on tubular collagen scaffolds OPTIMAIX Sponge 1 with a maximal length of 7 cm, in order to culture in vitro an adequate ureter replacement. With a rotating unit, (urothelial) cells can be placed homogeneously on the inner scaffold surface. Furthermore, a stimulation is combined with this bioreactor resulting in an orientation of muscle cells. These culturing methods request a precise control of several parameters and actuators. A combination of a LabBox and the suitable software LabVision is used to set and conduct parameters like rotation angles, velocities, pressures and other important cell culture values. The bioreactor was tested waterproof successfully. Furthermore, the temperature controlling was adjusted to 37 °C and the CO2 - concentration regulated to 5 %. Additionally, the pH step responses of several substances showed a perfect functioning of the designed flow chamber. All used software was tested and remained stable for several days.
In collaborative research projects, both researchers and practitioners work together solving business-critical challenges. These projects often deal with ETL processes, in which humans extract information from non-machine-readable documents by hand. AI-based machine learning models can help to solve this problem.
Since machine learning approaches are not deterministic, their quality of output may decrease over time. This fact leads to an overall quality loss of the application which embeds machine learning models. Hence, the software qualities in development and production may differ.
Machine learning models are black boxes. That makes practitioners skeptical and increases the inhibition threshold for early productive use of research prototypes. Continuous monitoring of software quality in production offers an early response capability on quality loss and encourages the use of machine learning approaches. Furthermore, experts have to ensure that they integrate possible new inputs into the model training as quickly as possible.
In this paper, we introduce an architecture pattern with a reference implementation that extends the concept of Metrics Driven Research Collaboration with an automated software quality monitoring in productive use and a possibility to auto-generate new test data coming from processed documents in production.
Through automated monitoring of the software quality and auto-generated test data, this approach ensures that the software quality meets and keeps requested thresholds in productive use, even during further continuous deployment and changing input data.
Companies often build their businesses based on product information and therefore try to automate the process of information extraction (IE). Since the information source is usually heterogeneous and non-standardized, classic extract, transform, load techniques reach their limits. Hence, companies must implement the newest findings from research to tackle the challenges of process automation. They require a flexible and robust system that is extendable and ensures the optimal processing of the different document types. This paper provides a distributed microservice architecture pattern that enables the automated generation of IE pipelines. Since their optimal design is individual for each input document, the system ensures the ad-hoc generation of pipelines depending on specific document characteristics at runtime. Furthermore, it introduces the automated quality determination of each available pipeline and controls the integration of new microservices based on their impact on the business value. The introduced system enables fast prototyping of the newest approaches from research and supports companies in automating their IE processes. Based on the automated quality determination, it ensures that the generated pipelines always meet defined business requirements when they come into productive use.
Miniaturised reference electrodes for field-effect sensors compatible to silicon chip technology
(2005)
Strategies of miniaturised reference electrodes integrated in a silicon-based „one chip“ pH sensor
(2003)
Miniaturisierte Referenzelektroden in Siliziumtechnologie für elektrochemische Sensoranwendungen
(2004)
Magnetic nanoparticles (MNP) are investigated with great interest for biomedical applications in diagnostics (e.g. imaging: magnetic particle imaging (MPI)), therapeutics (e.g. hyperthermia: magnetic fluid hyperthermia (MFH)) and multi-purpose biosensing (e.g. magnetic immunoassays (MIA)). What all of these applications have in common is that they are based on the unique magnetic relaxation mechanisms of MNP in an alternating magnetic field (AMF). While MFH and MPI are currently the most prominent examples of biomedical applications, here we present results on the relatively new biosensing application of frequency mixing magnetic detection (FMMD) from a simulation perspective. In general, we ask how the key parameters of MNP (core size and magnetic anisotropy) affect the FMMD signal: by varying the core size, we investigate the effect of the magnetic volume per MNP; and by changing the effective magnetic anisotropy, we study the MNPs’ flexibility to leave its preferred magnetization direction. From this, we predict the most effective combination of MNP core size and magnetic anisotropy for maximum signal generation.
The ideal combination among biomolecules and nanomaterials is the key for reaching biosensing units with high sensitivity. The challenge, however, is to find out a stable and sensitive film architecture that can be incorporated on the sensor’s surface. In this paper, we report on the benefits of incorporating a layer-by-layer (LbL) nanofilm of polyamidoamine (PAMAM) dendrimer and carbon nanotubes (CNTs) on capacitive electrolyte-insulator-semiconductor (EIS) field-effect sensors for detecting urea. Three sensor arrangements were studied in order to investigate the adequate film architecture, involving the LbL film with the enzyme urease: (i) urease immobilized directly onto a bare EIS [EIS-urease] sensor; (ii) urease atop the LbL film over the EIS [EIS-(PAMAM/CNT)-urease] sensor; and (iii) urease sandwiched between the LbL film and another CNT layer [EIS-(PAMAM/CNT)-urease-CNT]. The surface morphology of all three urea-based EIS biosensors was investigated by atomic force microscopy (AFM), while the biosensing abilities were studied by means of capacitance–voltage (C/V) and dynamic constant-capacitance (ConCap) measureaments at urea concentrations ranging from 0.1 mM to 100 mM. The EIS-urease and EIS-(PAMAM/CNT)-urease sensors showed similar sensitivity (∼18 mV/decade) and a nonregular signal behavior as the urea concentration increased. On the other hand, the EIS-(PAMAM/CNT)-urease-CNT sensor exhibited a superior output signal performance and higher sensitivity of about 33 mV/decade. The presence of the additional CNT layer was decisive to achieve a urea based EIS sensor with enhanced properties. Such sensitive architecture demonstrates that the incorporation of an adequate hybrid enzyme-nanofilm as sensing unit opens new prospects for biosensing applications using the field-effect sensor platform.
Layer-by-Layer Assembly of Carbon Nanotubes Incorporated in Light-Addressable Potentiometric Sensors
(2009)
The capacitive electrolyte–insulator–semiconductor (EIS) structure is a typical device based on a field-effect sensor platform. With a simple silicon-based structure, EIS have been useful for several sensing applications, especially with incorporation of nanostructured films to modulate the ionic transport and the flat-band potential. In this paper, we report on ion transport and changes in flat-band potential in EIS sensors made with layer-by-layer films containing poly(amidoamine) (PAMAM) dendrimer and single-walled carbon nanotubes (SWNTs) adsorbed on p-Si/SiO 2 /Ta 2 O 5 chips with an Al ohmic contact. The impedance spectra were fitted using an equivalent circuit model, from which we could determine parameters such as the double-layer capacitance. This capacitance decreased with the number of bilayers owing to space charge accumulated at the electrolyte–insulator interface, up to three PAMAM/SWNTs bilayers, after which it stabilized. The charge-transfer resistance was also minimum for three bilayers, thus indicating that this is the ideal architecture for an optimized EIS performance. The understanding of the influence of nanostructures and the fine control of operation parameters pave the way for optimizing the design and performance of new EIS sensors.
Micromachined thermal heater platforms offer low electrical power consumption and high modulation speed, i.e. properties which are advantageous for realizing nondispersive infrared (NDIR) gas- and liquid monitoring systems. In this paper, we report on investigations on silicon-on-insulator (SOI) based infrared (IR) emitter devices heated by employing different kinds of metallic and semiconductor heater materials. Our results clearly reveal the superior high-temperature performance of semiconductor over metallic heater materials. Long-term stable emitter operation in the vicinity of 1300 K could be attained using heavily antimony-doped tin dioxide (SnO2:Sb) heater elements.
In industrial processes there is a variety of heavy metals (e.g., copper, zinc, cadmium, and lead) in use for wires, coatings, paints, alloys, batteries, etc. Since the application of these transition metals for industry is inevitable, it is a vital task to develop proper analytical techniques for their monitoring at low activity levels, especially because most of these elements are acutely toxic for biological organisms. The determination of ions in solution by means of a simple and inexpensive sensor array is, therefore, a promising task. In this work, a sensor array with heavy metal-sensitive chalcogenide glass membranes for the simultaneous detection of the four ions Ag⁺, Cu2⁺, Cd2⁺, and Pb2⁺ in solution is realized. The results of the physical characterization by means of microscopy, profilometry, Rutherford backscattering spectroscopy (RBS), and scanning electron microscopy (SEM) as well as the electrochemical characterization by means of potentiometric measurements are presented. Additionally, the possibility to expand the sensor array by polymeric sensor membranes is discussed.
Die Detektion von Schadstoffen repräsentiert in der Umweltanalytik eine wichtige Aufgabenstellung. Gerade die Abwasser- bzw. Brauchwasseranalytik sowie die Prozesskontrolle haben einen hohen Stellenwert. Siliziumbasierte Dünnschichtsensoren bieten eine kostengünstige Möglichkeit, „online“-Messungen bzw. Vor-Ort-Messungen zeitnah durchzuführen. In dieser Arbeit wird ein potentiometrisches Sensorarray auf der Basis von Chalkogenidgläsern zur Detektion von Schwermetallen in wässrigen Medien vorgestellt.
Die Detektion von Schadstoffen repräsentiert in der Umweltanalytik eine wichtige Aufgabenstellung. Gerade die Abwasser- bzw. Brauchwasseranalytik sowie die Prozesskontrolle haben einen hohen Stellenwert. Siliziumbasierte Dünnschichtsensoren bieten eine kostengünstige Möglichkeit, „online“-Messungen bzw. Vor-Ort-Messungen zeitnah durchzuführen. In dieser Arbeit wird ein potentiometrisches Sensorarray auf der Basis von Chalkogenidgläsern zur Detektion von Schwermetallen in wässrigen Medien vorgestellt.