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- Angewandte Naturwissenschaften (F11) (29)
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- Fakultät 09 / Cologne Institute for Renewable Energy (6)
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The annual yield of bifacial photovoltaic systems is highly dependent on the albedo of the underlying soil. There are currently no published data about the albedo of red soil in western Africa. In this study, the impact of the albedo of red soil in Ghana on the energy yield of bifacial photovoltaic systems is analysed. A bifacial photovoltaic simulation model is created by combining the optical view factor matrix with an electrical output simulation. For an exact simulation, the albedo of red soil at three different locations in Ghana is measured for the first time. The average albedo of every red soil is clearly determined, as well as the measurement span including instrumentation uncertainty; values between 0.175 and 0.335 were measured. Considering these data, a state-of-the-art bifacial photovoltaic system with an average of 19.8% efficient modules in northern Ghana can achieve an annual energy yield of 508.8 kWh/m2 and a bifacial gain of up to 18.3% in comparison with monofacial photovoltaic panels. To summarise, red soil in two out of three locations in Ghana shows higher albedo values than most natural ground surfaces and therefore positively impacts the annual yield of bifacial photovoltaic systems.
Hydroxybenzene, commonly known as phenol, is one of the most important organic commodity chemicals. To produce phenol, the cumene process is the most used process worldwide. A crucial step in this process is the Hock rearrangement, which has a major impact on the overall cumene consumption rate and determines the safety level of the process. The most used catalyst for the cleavage of cumene hydroperoxide (CHP) is sulfuric acid. Besides its strong corrosive property, which increases plant investment costs, it also requires neutralization after the decomposition step to prevent side reactions. In this study, we show that high-temperature-treated Linde Type X (LTX) zeolites exhibit a high activity for the peroxide cleavage step. In addition, the structure–activity relationship responsible for this good performance in the reaction system of the HOCK rearrangement was investigated. XRPD analyses revealed the formation of a new phase after temperature treatment above 900 °C. The Si/Al ratio determined by EDX suggested the formation of extra-framework aluminum, which was confirmed by solid-state NMR analysis. The newly formed extra-framework aluminum was found to be responsible for the high catalytic activity. BET analyses showed that the surface area drops at higher calcination temperatures. This leads to a lower catalytic activity for most known reactions. However, for this study, no decrease in activity has been observed. The newfound material shows extraordinarily high activity as a catalyst in the HOCK cleavage and has the potential to be a heterogeneous alternative to sulfuric acid for this reaction.
The demand for explainable and transparent models increases with the continued success of reinforcement learning. In this article, we explore the potential of generating shallow decision trees (DTs) as simple and transparent surrogate models for opaque deep reinforcement learning (DRL) agents. We investigate three algorithms for generating training data for axis-parallel and oblique DTs with the help of DRL agents (“oracles”) and evaluate these methods on classic control problems from OpenAI Gym. The results show that one of our newly developed algorithms, the iterative training, outperforms traditional sampling algorithms, resulting in well-performing DTs that often even surpass the oracle from which they were trained. Even higher dimensional problems can be solved with surprisingly shallow DTs. We discuss the advantages and disadvantages of different sampling methods and insights into the decision-making process made possible by the transparent nature of DTs. Our work contributes to the development of not only powerful but also explainable RL agents and highlights the potential of DTs as a simple and effective alternative to complex DRL models.
Multifocal intraocular lenses incorporate a variety of design considerations, including dimensioning of the base monofocal shape and the diffraction grating. While studying three different lens models, we present a practical approach for mathematical modelling and evaluation of these geometries. Contrary to typical lens measurement methods, non-contact measurements were performed on the Alcon SN6AD1, HumanOptics MS 612 DAY and the AMO ZMA00 lenses using a confocal microscope. Subsequent data processing includes centering, tilting correction, filtering and an algorithmic decomposition into a conic and polynomial part and the diffraction grating. Lastly, evaluation of fitting parameters and grating shape is done to allow for inferences about further optical properties. Results and analysis show the confocal microscope to be a suitable imaging method for lens measurements. The processing of this data enables the reconstruction of the annular diffraction grating over the complete lens diameter. Apodization, near addition and diffraction efficiency characteristics are found utilizing the grating shape. Additionally, near-optical axis curvature, asphericity and higher order polynomials are identified qualitatively from the reconstruction of the monofocal base form. Derived properties also include the lens optical base and addition power. By making use of the surface geometries, as well as the lens’ material and thickness, a full lens model can be created for further studies. In summary, our analytical approach enables the insight to various intraocular lens design decisions. Furthermore, this procedure is suitable for lens model creation for research and simulation.
Für den erfolgreichen Ausbau der Elektromobilität nimmt die Nutzerakzeptanz eine entscheidende Rolle ein. Neben den Anschaffungskosten, Wirkungsgraden und Reichweiten fällt vor allem der Komfort des Ladevorgangs als entscheidende Einflussgröße ins Gewicht. Zum aktuellen Zeitpunkt beeinflussen eine Reihe an negativen Faktoren (z.B. Ladeinfrastruktur, Preisintransparenz und vielfältige Bezahlsysteme) den Ladekomfort und halten potenzielle Käufer eines Elektroautos letztlich vom Erwerb ab. Im Rahmen dieser Arbeit soll aus unmittelbarer Sicht der Nutzer:innen der derzeitige Stand der Ladeinfrastruktur und das aktuelle Nutzerverhalten sowie potenzielle Erfolgsfaktoren herausgearbeitet werden. Weiterhin werden verschiedene Lösungsvorschläge erprobt, die den Ladekomfort an öffentlichen Ladesäulen erhöhen soll. Dazu wird eine zweitstufige Online-Studie im Zuge des vom Bundesministerium für Wirtschaft und Klimaschutz geförderten Transformationsnetzwerk „TrendAuto2030plus“ koordiniert und von Studierenden des Master-Kurses „Technologie und Innovationsmanagement“ an der TH Köln durchgeführt. Gemessen an der bisherigen Nachfrage ist die Ladeinfrastruktur in Deutschland besser als ihr Ruf. Ein deutliches Bild der Unzufriedenheit zeigt sich derweil in Bezug auf die aktuell vorherrschende Preisintransparenz an öffentlichen Ladestationen. Die Vielfalt der Tarifmodelle und Bezahlsysteme erfordern eine großen Strukturierungs- und Informationsbedarf. Es werden Systeme der Preisanzeige gefragt sein, die der Vielfalt und Dynamik der unterschiedlichen Bezahl- und Tarifmodelle Rechnung tragen und diese transparent und nutzerfreundlich ausweisen.
This study explores the potential of robust, strongly basic type I ion exchange resins—specifically, Amberlyst® A26 OH and Lewatit® K 6465—as catalysts for the aldol condensation of citral and acetone, yielding pseudoionone. Emphasis is placed on their long-term stability and commendable performance in continuous operational settings. The aldol reaction, which traditionally is carried out using aqueous sodium hydroxide as the catalyst, holds the potential for enhanced sustainability and reduced waste production through the use of basic ion exchange resins in heterogeneous catalysis. Density Functional Theory (DFT) calculations are employed to investigate catalyst deactivation mechanisms. The result of these calculations indicates that the active sites of Amberlyst® A26 OH are cleaved more easily than the active sites of Lewatit® K 6465. However, the experimental data show a gradual decline in catalytic activity for both resins. Batch experiments reveal Amberlyst® A26 OH’s active sites diminishing, while Lewatit® K 6465 maintains relative consistency. This points to distinct deactivation processes for each catalyst. The constant count of basic sites in Lewatit® K 6465 during the reaction suggests additional factors due to its unique polymer structure. This intriguing observation also highlights an exceptional temperature stability for Lewatit® K 6465 compared to Amberlyst® A26 OH, effectively surmounting one of the prominent challenges associated with the utilization of ion exchange resins in catalytic applications.
A novel approach to manufacture components with integrated conductor paths involves embedding and sintering an isotropic conductive adhesive (ICA) during fused filament fabrication (FFF). However, the molten plastic is deposited directly onto the adhesive path which causes an inhomogeneous displacement of the uncured ICA. This paper presents a 3D printing strategy to achieve a homogeneous cross-section of the conductor path. The approach involves embedding the ICA into a printed groove and sealing it with a wide extruded plastic strand. Three parameter studies are conducted to obtain a consistent cavity for uniform formation of the ICA path. Specimens made of polylactic acid (PLA) with embedded ICA paths are printed and evaluated. The optimal parameters include a groove printed with a layer height of 0.1 mm, depth of 0.4 mm, and sealed with a PLA strand of 700 µm diameter. This resulted in a conductor path with a homogeneous cross-section, measuring 660 µm ± 22 µm in width (relative standard deviation: 3.3%) and a cross-sectional area of 0.108 mm2 ± 0.008 mm2 (relative standard deviation 7.2%). This is the first study to demonstrate the successful implementation of a printing strategy for embedding conductive traces with a homogeneous cross-sectional area in FFF 3D printing.
To date, the establishment of high-titer stable viral packaging cells (VPCs) at large scale for gene therapeutic applications is very time- and cost-intensive. Here we report the establishment of three human suspension 293-F-derived ecotropic MLV-based VPCs. The classic stable transfection of an EGFP-expressing transfer vector resulted in a polyclonal VPC pool that facilitated cultivation in shake flasks of 100 mL volumes and yielded high functional titers of more than 1 × 106 transducing units/mL (TU/mL). When the transfer vector was flanked by transposon terminal inverted repeats (TIRs) and upon co-transfection of a plasmid encoding for the transposase, productivities could be slightly elevated to more than 3 × 106 TU/mL. In contrast and using mRNA encoding for the transposase, as a proof of concept, productivities were drastically improved by more than ten-fold exceeding 5 × 107 TU/mL. In addition, these VPC pools were generated within only 3 weeks. The production volume was successfully scaled up to 500 mL employing a stirred-tank bioreactor (STR). We anticipate that the stable transposition of transfer vectors employing transposase transcripts will be of utility for the future establishment of high-yield VPCs producing pseudotype vector particles with a broader host tropism on a large scale.
Maximising Distribution Grid Utilisation by Optimising E-Car Charging Using Smart Meter Gateway Data
(2023)
The transition towards climate neutrality will result in an increase in electrical vehicles, as well as other electric loads, leading to higher loads on electrical distribution grids. This paper presents an optimisation algorithm that enables the integration of more loads into distribution grid infrastructure using information from smart meters and/or smart meter gateways. To achieve this, a mathematical programming formulation was developed and implemented. The algorithm determines the optimal charging schedule for all electric vehicles connected to the distribution grid, taking into account various criteria to avoid violating physical grid limitations and ensuring non-discriminatory charging of all electric vehicles on the grid while also optimising grid operation. Additionally, the expandability of the infrastructure and fail-safe operation are considered through the decentralisation of all components. Various scenarios are modelled and evaluated in a simulation environment. The results demonstrate that the developed optimisation algorithm allows for higher transformer loads compared to a P(U) control approach, without causing grid overload as observed in scenarios without optimisation or P(U) control.
Positive Impact of Red Soil on Albedo and the Annual Yield of Bifacial Photovoltaic Systems in Ghana
(2023)
The annual yield of bifacial photovoltaic systems is highly dependent on the albedo of the underlying soil. There are currently no published data about the albedo of red soil in western Africa. In this study, the impact of the albedo of red soil in Ghana on the energy yield of bifacial photovoltaic systems is analysed. A bifacial photovoltaic simulation model is created by combining the optical view factor matrix with an electrical output simulation. For an exact simulation, the albedo of red soil at three different locations in Ghana is measured for the first time. The average albedo of every red soil is clearly determined, as well as the measurement span including instrumentation uncertainty; values between 0.175 and 0.335 were measured. Considering these data, a state-of-the-art bifacial photovoltaic system with an average of 19.8% efficient modules in northern Ghana can achieve an annual energy yield of 508.8 kWh/m2 and a bifacial gain of up to 18.3% in comparison with monofacial photovoltaic panels. To summarise, red soil in two out of three locations in Ghana shows higher albedo values than most natural ground surfaces and therefore positively impacts the annual yield of bifacial photovoltaic systems.