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In this paper, a 256-channel, 10-GHz arrayed waveguide gratings demultiplexer for ultra-dense wavelength division multiplexing was designed using an in-house developed tool called AWG-Parameters. The AWG demultiplexer was designed for a central wavelength of 1550 nm and the structure was simulated in PHASAR tool from Optiwave. Two different AWG designs were developed and the influence of the design parameters on the AWG performance was studied.
Purpose – The purpose of this study is to explore the exogenous and endogenous drivers of the high-growth of Unicorn start-ups along their life cycle, with a particular focus on Unicorns in the fintech industry.
Design/methodology/approach – The study employs an explorative longitudinal analysis with a matched pair of two cases of Unicorns start-ups with similar antecedent features to understand holistically drivers over the longer term.
Findings – High-growth patterns over the longer term are the result of a combined industry- and company-life cycle perspective. Drivers and growth patterns vary significantly according to the time of entry in the industry and
its development status. The findings are systematised within a set of propositions to be tested in future research.
Research limitations/implications – The limitations lie in empirical evidence, as the analysis is limited to one matched-pair. The revealed Unicorns’ drivers for long-term growth might encourage future research to further investigate these drivers on a larger scale.
Practical implications – The study offers practical recommendations for start-ups with high-growth ambitions and advice to policy makers regarding the development of tailor-made support programs.
Originality/value – The study significantly extends extant work on growth and high-growth by examining endogenous and exogenous triggers over time and by linking the Unicorn-life cycle to the industry life cycle, an approach which has, to the best of the authors’ knowledge, not yet been applied.
Synthetic polymers, such as polyamide (PA), inherently possess a moderate number of surface functionalities compared to natural polymers, which negatively impacts the uniformity of metallic coatings obtained through wet-chemical methods like electroless plating. The paper presents the use of a siloxane interlayer formed from the condensation of the hydrolyzed 3-triethoxysilylpropyl succinic anhydride (TESPSA) precursor as a strategy to modify the surface properties of polyamide 6.6 (PA66) fabrics and improve the uniformity of the copper surface coating. The application of the siloxane intermediate coating demonstrates a significant improvement in electrical conductivity, up to 20 times higher than fabrics without the interlayer. The morphology of the coatings was investigated using scanning electron (SEM) and laser confocal scanning microscopy (LSM). In addition, dye adsorption, flexural rigidity, air permeability and contact angle measurements were conducted to monitor the change in the PA66 properties after the siloxane functionalization.
Armut im Blick?
(2023)
Ausrechnen oder aushandeln?
(2023)
The usage of data gathered for Industry 4.0 and smart factory scenarios continues to be a problem for companies of all sizes. This is often the case because they aim to start with complicated and time-intensive Machine Learning scenarios. This work evaluates the Process Capability Analysis (PCA) as a pragmatic, easy and quick way of leveraging the gathered machine data from the production process. The area of application considered is injection molding. After describing all the required domain knowledge, the paper presents an approach for a continuous analysis of all parts produced. Applying PCA results in multiple key performance indicators that allow for fast and comprehensible process monitoring. The corresponding visualizations provide the quality department with a tool to efficiently choose where and when quality checks need to be performed. The presented case study indicates the benefit of analyzing whole process data instead of considering only selected production samples. The use of machine data enables additional insights to be drawn about process stability and the associated product quality.
Demand-side management approaches that exploit the temporal flexibility of electric vehicles have attracted much attention in recent years due to the increasing market penetration. These demand-side management measures contribute to alleviating the burden on the power system, especially in distribution grids where bottlenecks are more prevalent. Electric vehicles can be defined as an attractive asset for distribution system operators, which have the potential to provide grid services if properly managed. In this thesis, first, a systematic investigation is conducted for two typically employed demand-side management methods reported in the literature: A voltage droop control-based approach and a market-driven approach. Then a control scheme of decentralized autonomous demand side management for electric vehicle charging scheduling which relies on a unidirectionally communicated grid-induced signal is proposed. In all the topics considered, the implications on the distribution grid operation are evaluated using a set of time series load flow simulations performed for representative Austrian distribution grids. Droop control mechanisms are discussed for electric vehicle charging control which requires no communication. The method provides an economically viable solution at all penetrations if electric vehicles charge at low nominal power rates. However, with the current market trends in residential charging equipment especially in the European context where most of the charging equipment is designed for 11 kW charging, the technical feasibility of the method, in the long run, is debatable. As electricity demand strongly correlates with energy prices, a linear optimization algorithm is proposed to minimize charging costs, which uses next-day market prices as the grid-induced incentive function under the assumption of perfect user predictions. The constraints on the state of charge guarantee the energy required for driving is delivered without failure. An average energy cost saving of 30% is realized at all penetrations. Nevertheless, the avalanche effect due to simultaneous charging during low price periods introduces new power peaks exceeding those of uncontrolled charging. This obstructs the grid-friendly integration of electric vehicles.
Beyond the Four-Level Model: Dark and Hot States in Quantum Dots Degrade Photonic Entanglement
(2023)
Entangled photon pairs are essential for a multitude of quantum photonic applications. To date, the best performing solid-state quantum emitters of entangled photons are semiconductor quantum dots operated around liquid-helium temperatures. To favor the widespread deployment of these sources, it is important to explore and understand their behavior at temperatures accessible with compact Stirling coolers. Here we study the polarization entanglement among photon pairs from the biexciton–exciton cascade in GaAs quantum dots at temperatures up to ∼65 K. We observe entanglement degradation accompanied by changes in decay dynamics, which we ascribe to thermal population and depopulation of hot and dark states in addition to the four levels relevant for photon pair generation. Detailed calculations considering the presence and characteristics of the additional states and phonon-assisted transitions support the interpretation. We expect these results to guide the optimization of quantum dots as sources of highly entangled photons at elevated temperatures.