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Modeling dislocation dynamics data using semantic web technologies
No full textThe research in Materials Science and Engineering focuses on the design, synthesis, properties, and performance of materials. An important class of materials that is widely investigated are crystalline materials, including metals and semiconductors. Crystalline material typically contains a specific type of defect called “dislocation”. This defect significantly affects various material properties, including bending strength, fracture toughness, and ductility. Researchers have devoted a significant effort in recent years to understanding dislocation behaviour through experimental characterization techniques and simulations, e.g., dislocation dynamics simulations. This paper presents how data from dislocation dynamics simulations can be modelled using semantic web technologies through annotating data with ontologies. We extend the dislocation ontology by adding missing concepts and aligning it with two other domain-related ontologies (i.e., the Elementary Multi-perspective Material Ontology and the Materials Design Ontology), allowing for efficiently representing the dislocation simulation data. Moreover, we present a real-world use case for representing the discrete dislocation dynamics data as a knowledge graph (DisLocKG) which can depict the relationship between them. We also developed a SPARQL endpoint that brings extensive flexibility for querying DisLocKG
Tuning Proton Exchange Membrane Electrolytic Cell Performance by Conditioning Nafion N115‐Based Membrane Electrode Assemblies
No full textConditioning of the membrane electrode assembly (MEA) is an important step to establish functionality and obtain a consistent performance of the proton exchange membrane electrolytic cell (PEMEC) when setting it into operation. On a laboratory scale in an academic context, conditioning encompasses primary pre-treatment of the MEA by chemical or thermal procedures under defined mechanical conditions and, secondarily, the break-in procedure, during which the PEMEC is subjected to initial electrical loads before actual operation. This study demonstrates the effect of MEA conditioning on the short-term performance of PEMEC. The impact of mechanical, chemical and thermal conditions during pre-treatment was investigated for Nafion N115-based MEAs while keeping the break-in procedure invariant for all pre-treatment conditions. The electrochemical characterisation was performed using polarisation curves and electrochemical impedance spectroscopy. The impact of ex situ–before assembly of the cell–versus in situ–after assembly of the cell–conditioning resulted in markedly different mechanical conditions. The experimental results showed an improvement in PEMEC performance by pre-treating the MEA after cell assembly. Compared to pre-treatment with deionised water (DI water) at 60°C, treatment with acidic solution improved the performance, evidenced by a 21 mV reduction in cell voltage at 2 A·cm−2. When compared with DI water at 60°C, a pre-treatment at 90°C with DI water reduced cell voltage by 23 mV
Pulsed‐Current Operation Enhances H 2 O 2 Production on a Boron‐Doped Diamond Mesh Anode in a Zero‐Gap PEM Electrolyzer
No full textComputational study of active polar polymer melts: From active reptation to activity induced local alignment
No full textInbound licensing with ease
No full textManaging projects with external collaborators sometimes comes with the burden of ensuring inbound contributions respect legal obligations. Where a low-level 'Developer Certificate of Origin (DCO)' approach only introduces certain checks, a 'Contributor License Agreements (CLAs)', on the other hand, relies on documenting signed CLAs and thus dedicated book-keeping.In this poster, we showcase our initial approach to a 'CLA Bot' that checks merge requests on compliance with either a DCO or CLA. While this is work in progress, our goal is to provide a similar functionality already available on Github also for community instances of Gitlab. We show the interaction between the bot and users, its limitations, and list steps taken for the automation via CI pipelines. Here, the somewhat simpler approach to pipelines in Gitlab vs Github necessitates working with webhooks that act on events within Gitlab. Our setup does not rely on a central server (in fact any additional server) and can be used by individual projects without having to share data. By using webhooks and CI pipelines, our approach can be used for similar automation tasks, offering the potential to interact with users
The influence of small mass loss rate peaks on the rate of spread of predictive flame spread simulations: A theoretical study
No full textPeaks in the mass loss rate (MLR) curve derived from thermogravimetric analysis (TGA) are commonly used to infer the pyrolysis rates of solid fuels. While the main peaks are often modelled, smaller MLR fluctuations are typically neglected, leading to discrepancies between models and experiments. The impact of these small fluctuations on key simulation predictions, however, remains unclear. This study systematically explores a specific scenario in which a small MLR fluctuation significantly affects the predicted rate of spread (ROS) of a simplified flame spread simulation. The MaCFP-recommended pyrolysis model for poly(methyl methacrylate) (PMMA) is adapted to incorporate a small MLR peak accounting for 0.5 % to 2 % of the sample’s total mass. Results from sensitivity analyses show that the peak position has the greatest impact on the ROS, followed by the peak mass fraction, while the peak width has negligible effect. Adding a small peak at lower temperatures increased the ROS by up to 6 % to 13 %, depending on the peak’s mass fraction, whereas peaks at higher temperatures had little to no effect. These results indicate that fluctuations at lower temperatures, w.r.t. the main peak, could significantly enhance the predicted spread rates and should be considered in flame spread simulations
Understanding and Developing dimensional stable Anodes (DSA) for low molar chlor-alkali electrolysis
No full textDevelopment of a cascade reaction system to high-throughput screening of amine transaminase activity
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Methodological Approach Enabling the Two-phase Flow Investigation in Alkaline Electrolysis under Demanding Conditions
No full textIn this examination, a methodological approach is developed for the investigation of the two-phase flow behavior of an alkaline electrolysis cell using multiphase particle image velocimetry. Typically, imaging techniques or transparent cells are used to investigate the gas bubble behavior inside electrochemical cells. Certain drawbacks of these methods urge the necessity for a universally applicable two-phase flow investigation method for alkaline electrolysis cells. Therefore, a method is developed which is able to investigate both phases (liquid and gaseous) using a transparent half-cell. The half cell is capable of simulating the alkaline electrolysis two-phase flow behavior on anode or cathode side separately. By exchanging the electrolyte solution for a model electrolyte solution with the same density and viscosity as potassium hydroxide, the two-phase flow investigation can be done at lower temperatures than the usual alkaline electrolysis operation temperature. This is especially advantageous at temperatures above boiling point where pressurized operation is necessary because, with the proposed measurement method, the necessity of operating the electrolysis cell under pressure is avoided. Additionally, the exchange of potassium hydroxide to a less corrosive model electrolyte solution prevents the used transparent cell from getting dull from highly concentrated lye. The simulated cell is operated with equivalent volumes of nitrogen gas instead of hydrogen and oxygen for safety reasons. For method validation, the NeXT (Neutron and X-Ray Tomograph) device at Institute Laue-Langevin (ILL) in Grenoble is used to observe the gas bubbles forming and moving inside the flow channel of an alkaline electrolysis cell. For the first time, a temporal resolution of 0.02 seconds could be achieved for an active cell area of several cm2. Measurement methods like neutron radiography are a powerful tool to analyze the gas bubble behavior inside alkaline electrolysis flow cells, but has limited accessibility. For both measurement methods, neutron radiography measurements and multiphase particle image measurements, cells of the same flowfield geometry are used. For the comparison of both investigation methods, an alkaline water electrolysis single cell is operated at different operation conditions. In this work, the results of both measurement methods are shown and compared. The applicability of an experimentally ”simulated” electrolysis cell, measured with multiphase particle image velocimetry measurements, is shown, as well as the assumptions, prerequisites, and limitations of the simulation of the two-phase flow of an alkaline electrolysis cell. Using the simulated electrolysis half-cell is advantageous compared to neutron radiography measurements because smaller gas bubbles can be identified. Especially for difficult operation conditions like in alkaline electrolysis at intermediate temperatures, where measurements like neutron radiography are extremely difficult to realize, a flow behavior analysis method, which is easy to apply, is helpful. Additionally, the flow behavior of electrochemical flow cells can be optimized for improved electrolysis cell designs and higher efficiencies. This examination is the first step towards a simpler investigation of the two-phase flow behavior of electrochemical cells with the application example of a low temperature alkaline electrolysis zero-gap cell, with the potential to extend the method to intermediate temperature alkaline electrolysis or any other electrochemical device that forms gas bubbles