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Optical splitters are passive optical components, which have found applications in a wide range of telecom, sensing, medical and many other scientific areas.
Low-index contrast optical splitters (Silica-on-Silicon (SoS) based waveguide devices) feature many advantages such as low fiber coupling losses and low propagation losses. They are considered an attractive DWDM solution in the telecommunication for all optical signal processing in optical communication systems. Nowadays the steadily increasing data volume in communication networks is driven by a rapid proliferation of home-based and business computers, storage capacities, processing capabilities and the extensive availability of Internet. The challenge is to transfer high data volumes in short periods of time over high distances as lossless as possible. The task of the optical splitters in Fiber-to-the-x (FTTx) network is to split one optical signal in many identical signals bringing for example the same TV signal in different households. Of course, the more buildings can be served by one optical splitter the lower are the installation costs.
High-index contrast optical splitters (such as silicon, silicon nitride or polymer based waveguide devices) feature much smaller waveguide size compared to low index contrast splitters. Such compact devices can easily be implemented on-chip and have already been used in the development of optical sensors, devices for DNA diagnostics and for infrared spectroscopy.
We will present the latest achievements in the design of two mostly used optical splitters (MMI and Y-branch) and discuss their advantages and disadvantages. Finally, some applications of the splitters developed in the frame of various projects will be presented.
This work was carried out in the framework of the project PHOCOP (no. SK-AT-2017-0013) and NAMOPRISIN (no. SK-AT-2017-0005) from the Slovak research and development agency of the Ministry of Education, Science, Research and Sport of the Slovak Republic and SK 16/2018 and 15/2018 from OeAD-GmbH.
Abstract: ams AG is a leading provider of sensing solutions developing semiconductor sensors in a wide variety of fields, with optical sensing as one of the key competences. Since integrated photonics is a promising technology for new sensor systems, ams AG has been developing processes for fully integrated CMOS-compatible photonic components based on Si3N4. This talk will provide an overview on the processing of basic photonic building blocks and their optical properties and performance. We will also give examples for applications in the fields of optical coherence tomography and opto-chemical gas sensing. In the 1980s photonics started its way for common use in telecommunication technology, using optical fiber technologies. In recent years, also a variety of photonic sensors has been proposed and developed. One of the major drawbacks of most of these photonic devices has been the lack of integration into existing (semiconductor) production processes, so far. This integration is feasible using SiN material systems to process monolithically integrated CMOS-compatible photonic sensors in the visible and near-infrared spectrum. We will present the basic processing steps for the SiN photonic technology, the development of some critical processing steps such as SiN deposition and SiN etching as well as several photonic components (waveguides, splitters, etc.) with their optical properties. One of the applications presented relates to optical coherence tomography (OCT), a fast growing imaging technique in ophthalmology. Drawbacks of existing OCT systems are their high costs as well as their bulkiness, which prevents a wider spread use of OCT systems.
One way to overcome both cost and size issues is to integrate optical and electrical components on a single chip.
Part of this work was carried out in the framework of the projects COHESION (funded by the Austrian Research Promotion Agency (FFG), no. 848588), OCTCHIP (funded by the EU’ Horizon 2020 research and innovation programme, no. 688173), and COLODOR (M-ERA.NET transnational Call 2015, funded by the Austrian Research Promotion Agency (FFG), no.854066, and the Bundesministerium für Bildung und Forschung, Germany).
We report resent results on the fabrication and characterization of carbon nanogap interdigitated electrode arrays (IDAs) for biosensor applications based on redox cycling. The electrochemical results of the carbon electrodes are compared to our fabricated gold electrodes with similar nanogap distances. The amplification factor and the collection efficiency were recorded by chronoamperometry. Cyclic voltammetry (CV) was utilized to determine the oxidation and reduction potentials as well as for monitoring the electron transfer process. The different deposited carbon materials were characterized by Raman spectroscopy.At present, we successfully fabricated carbon nanogaps down to 80 nm and we are convinced to reach the present fabrication limit of about 30 nm (for gold and platinum electrodes) with carbon as electrode material as well. To the best of our knowledge, this is the first IDA nanogap sensor, which features a gap distance under 100 nm with amorphous carbon as electrode material. Moreover, we present a signal amplification of 32 for carbon electrodes by redox cycling, which is the highest reported amplification so far.
Here we present the highly sensitive detection of dopamine using gold nanogap IDAs with redox-cycling amplification. Through the combination with a facile electrochemical activation and a chronoamperometric multistep protocol fouling of the gold electrode surface can be prevented and a sensitivity of 14 nA μM -1 with excellent linearity up to 10 μM is achieved. The low-cost and reproducible wafer level fabrication process of the nanogap IDAs plays a key role. Electrode and substrate materials can be nearly arbitrarily chosen. Also the gap sizes could be adjusted down to sub-100 nm dimensions with this versatile approach, allowing for very high signal amplification. In comparison to the current gold standard, fastscan cyclic voltammetry (FSCV) with carbon fiber microelectrodes (CFMEs), which suffers from high background currents, no elaborate data processing and high-end electronic equipment is needed. Employing our flexible, easy and inexpensive method, DA monitoring with a short acquisition period and a detection limit less than 200 nM is successfully demonstrated.
The electricity demand due to the increasing number of EVs presents new challenges for the operation of the electricity network, especially for the distribution grids. The existing grid infrastructure may not be sufficient to meet the new demands imposed by the integration of EVs. Thus, EV charging may possibly lead to reliability and stability issues, especially during the peak demand periods. Demand side management (DSM) is a potential and promising approach for mitigation of the resulting impacts. In this work, we developed an autonomous DSM strategy for optimal charging of EVs to minimize the charging cost and we conducted a simulation study to evaluate the impacts to the grid operation. The proposed approach only requires a one way communicated incentive. Real profiles from an Austrian study on mobility behavior are used to simulate the usage of the EVs. Furthermore, real smart meter data are used to simulate the household base load profiles and a real low voltage grid topology is considered in the load flow simulation. Day-ahead electricity stock market prices are used as the incentive to drive the optimization. The results for the optimum charging strategy is determined and compared to uncontrolled EV charging. The results for the optimum charging strategy show a potential cost saving of about 30.8% compared to uncontrolled EV charging. Although autonomous DSM of EVs achieves a shift of load as pursued, distribution grid operation may be substantially affected by it. We show that in the case of real time price driven operation, voltage drops and elevated peak to average powers result from the coincident charging of vehicles during favourable time slots.
When it comes to improving the health of the general population, mHealth technologies with self-monitoring and intervention components hold a lot of promise. We argue, however, that due to various factors such as access, targeting, personal resources or incentives, self-monitoring applications run the risk of increasing health inequalities, thereby creating a problem of social justice. We review empirical evidence for “intervention-generated” inequalities, present arguments that self-monitoring applications are still morally acceptable, and develop approaches to avoid the promotion of health inequalities through self-monitoring applications.