Filtern
Erscheinungsjahr
Dokumenttyp
- Wissenschaftlicher Artikel (237)
- Konferenzveröffentlichung (216)
- Teil eines Buches (Kapitel) (32)
- Sonstiges (31)
- Video (14)
- Buch (Monographie) (13)
- Preprint (12)
- Dissertation (4)
- Bericht (4)
- Arbeitspapier (4)
Sprache
- Englisch (572) (entfernen)
Schlagworte
- Robotik (8)
- Flugkörper (7)
- UAV (7)
- Rettungsrobotik (5)
- Dissipative Particle Dynamics (4)
- Polymer-Elektrolytmembran-Brennstoffzelle (4)
- adhesion (4)
- Bionik (3)
- Deep Learning (3)
- Erweiterte Realität <Informatik> (3)
- Gespenstschrecken (3)
- Haftorgan (3)
- OCSR (3)
- stick insects (3)
- Augmented Reality (2)
- CDK (2)
- Competency-Oriented Exams (2)
- DECIMER (2)
- Deep learning (2)
- Electrodeposition (2)
- Field measurement (2)
- Human-Robot Interaction (2)
- OCSR, Optical Chemical Structure Recognition (2)
- Solar modules (2)
- Transformer (2)
- Twitter <Softwareplattform> (2)
- biomimicry (2)
- hydraulic compression (2)
- modular stack design (2)
- open quantum systems (2)
- social innovation (2)
- water electrolysis (2)
- carbon nanofibers, platinum electrodeposition, ele ctrochemical surface area (1)
- 360 degree Feedback (1)
- 360° Panorama (1)
- AEM-Electrolysis (1)
- AI (1)
- API 1130 (1)
- Additive manufacturing Directed energy deposition-arc 316L stainless steel Corrosion behavior Electrochemical corrosion (1)
- Aerosol (1)
- Aggregation-prone (1)
- Air handling unit (1)
- AlphaFold, ColabFold, PyMOL (1)
- Alternative Geschäftsmodelle (1)
- Amylase, Enzymcharakterisierung (1)
- Anorganische Analyse (1)
- Artificial Intelligence (1)
- Assessment Center (1)
- Assisted living technologies (1)
- Assistive robotics (1)
- Augmented (1)
- Augmented Electromagnetic Accelerators (1)
- Augmented Multiphase (1)
- Augmented Multiphase Rail Launcher (1)
- Augmented Three-Phase AC-Railgun (1)
- Autonomous Agents (1)
- Bildverarbeitung (1)
- Biomechanics (1)
- Biomedical monitoring, Hospitals, Electrocardiography, Wireless communication, Patient monitoring, Wireless sensor networks (1)
- Biomimetics (1)
- Bone Morphogenetic Protein, BMP, BMP2 (1)
- Bone morphogenetic protein 2 (1)
- Brand theory (1)
- CFD Simulation (1)
- COIL (1)
- CPM (1)
- Carboxylate (1)
- Case-Study (1)
- Catalysis (1)
- Cell-free implant (1)
- Chemical image depiction (1)
- Chemical space (1)
- Chemical structure depictions (1)
- Cheminformatics (1)
- Chemistry Development Kit (1)
- Chemistry Development Kit, CDK, Molecule fragmentation, In silico fragmentation, Scaffolds, Functional groups, Glycosidic moieties, Rich client, Graphical user interface, GUI (1)
- Chief Executive Officer (1)
- Climate change (1)
- Clustering (1)
- Codegenerierung (1)
- Communication management (1)
- Constructive Alignment (1)
- Continuous Assessment (1)
- Continuous Queries (1)
- Cookie <Internet> (1)
- Cr(VI) and Zn(II) cations (1)
- Crowdfunding (1)
- Current Pulses (1)
- DPD, Dissipative Particle Dynamics (1)
- Data Collection (1)
- Data Journalism (1)
- Datalog (1)
- Datenjournalismus (1)
- Datensatz (1)
- Datenschutz (1)
- Deductive Databases (1)
- Depiction generator image augmentation (1)
- Deutschland / Technische Regeln für brennbare Flüssigkeiten (1)
- Dissipative particle dynamics, DPD, Surfactant, Bilayer, Lamellar, Simulation, Mesoscopic (1)
- Distributed Software Development (1)
- E. coli SHuffle® T7 (1)
- Elastizitätsmodul (1)
- Electrolysis (1)
- Electromagnetic Launcher (1)
- Elektrodenvorbereitung (1)
- Energy Storage Mode (1)
- Enterprise JavaBeans (1)
- Erneuerbare Energien (1)
- Europe (1)
- Evidence-based Management (1)
- Exams with Third-Party Applications (1)
- Fehlererkennung (1)
- Fehlerortung (1)
- Flat-Channel (1)
- Flipped Classroom (1)
- Flory-Huggins parameter (1)
- Flügelform (1)
- Formative Assessment (1)
- Fragmentation (1)
- Future capacity needs (1)
- Gas Diffusion Electrode (1)
- Greek dept crisis (1)
- Hand-drawn chemical structures (1)
- Hand-drawn images (1)
- Hands-free Interaction (1)
- High Reynold Numer (1)
- Homogene Kühlung (1)
- Human-centered computing (1)
- Hydraulic cell compression (1)
- Hydraulic compression, Carbon Nano Fibers, PEM Fuel Cells, Catalyst utilization (1)
- Hydrogen evolution reaction (1)
- Hydrophilicity enhanced hBMP2 variant (1)
- ICP-Massenspektrometrie (1)
- Implantat (1)
- In-silico-design (1)
- Incremental Evaluation (1)
- Indigo (1)
- Interactive Voting Systems (1)
- Intercultural Collaboration (1)
- Journalismus (1)
- Juristenausbildung (1)
- Kalman filter (1)
- Kernspintomografie (1)
- Kohlenstoff (1)
- Kohlenstoff-Nanoröhre (1)
- Laser Synthesis Electrocatalytic Water Splitting (1)
- Launcher (1)
- Leadership Competencies (1)
- Leak detection (1)
- Leckerkennung (1)
- Leckortung (1)
- Lecksuchgerät (1)
- Lecküberwachung (1)
- Linear Electromagnetic Accelerator (1)
- Lüftungsanlage (1)
- MITRE (1)
- Machine Learning (1)
- Magnetic Pressure (1)
- Mapping (1)
- Maus (1)
- Media Brands (1)
- Media brand characteristics (1)
- Media positioning (1)
- Membrane (1)
- Methodology (1)
- Middle-range Theory (1)
- Mikrofotografie (1)
- Mixed Reality (1)
- Modular Augmented Launcher (1)
- Modular Design (1)
- Molecule images (1)
- Multi-Agent System (1)
- Multiphase Rail Launcher (1)
- Mund-Nasen-Schutz (1)
- Muzzle Velocity (1)
- N,N,O Ligands (1)
- N,N′ Ligands (1)
- Nanofaser (1)
- Natural products (1)
- Naturstoff (1)
- NeRF (1)
- New Public Governance (1)
- New Public Management (1)
- New Work, Information and Communication Industry, Innovation, Organizational Goals, Survey (1)
- Ni-Mo alloy Catalyst (1)
- NiCrBSi coatings; flame spraying; induction remelting; wear resistance (1)
- Normalisierung (1)
- ORR OER (1)
- OSINT (1)
- Object Recognition (1)
- Object-relational Mapping (1)
- Objektverfolgung (1)
- Ohrwurm (1)
- Online Programming Exams (1)
- Online Supervision (1)
- Online-Werbung (1)
- Optical Chemical Structure Recognition (1)
- Ortsbestimmung (1)
- PEM Electrolysis, Hydrogen, Hydraulic Compression, High Pressure (1)
- PEM electrolysis (1)
- PEM fuel cell (1)
- PEM fuel cell electrocatalysts, Carbon nanofibers, Oxygen plasma activation, Pulsed electroplating. (1)
- PEM fuel cells (1)
- PEM water electrolysis (1)
- PEM-Brennstoffzelle (1)
- PEMWE (1)
- Peer Assessment (1)
- Peer Instruction (1)
- People with disabilities (1)
- Performance prediction (1)
- Persistenz <Informatik> (1)
- Physics-Informed Deep Learning (1)
- Physics-informed deep learning; unsupervised learning; Reynolds-averaged Navier-Stokesequations; high Reynolds number flow; turbulence modeling (1)
- Politische Berichterstattung (1)
- Polymere (1)
- Porous Transport Layers (1)
- Powder feed rate HVOF Cermet Wear Corrosion (1)
- Privatsphäre (1)
- Project-based Learning (1)
- PtCoMn (1)
- RDKit (1)
- RIS (1)
- Rail Launcher (1)
- Railgun (1)
- Regeln der Technik (1)
- Rescue Robotics (1)
- Robot assistive drinking (1)
- Robot assistive eating (1)
- Rwanda (1)
- SARS-CoV-2 (1)
- Sauerstoffplasmaaktivierung (1)
- Scaffold (1)
- Scaffold network (1)
- Scaffold tree (1)
- Segmentation; Correlation; Diseases; Convolutional Neural Networks (1)
- Semi-Infinite Plate (1)
- Sinusoidal (1)
- Small UAVs (1)
- Smart Grid (1)
- Social Innovation (1)
- Social Learning (1)
- Social Media (1)
- Spondylodese (1)
- Stack <Brennstoffzelle> (1)
- Stellite 6; HVOF-spraying; Laser remelting; Cavitation erosion; Coatings (1)
- Student Activation (1)
- TRFL (1)
- Temperature coefficients (1)
- Ternary alloy catalyst preparation (1)
- Tetraplegie (1)
- Thermal Performance (1)
- Thermal Stress (1)
- Titanium; Al2O3–TiO2 coatings; Nanoindentation (1)
- Tracking (1)
- Transformative Teaching (1)
- Twitter (1)
- Update Propagation (1)
- Upscaling laboratory models (1)
- Urban heat island (1)
- Visual Monocular SLAM (1)
- Young´s modulus (1)
- Zinc (1)
- Zustandsmaschine (1)
- academic and job-related self-control demands (1)
- activated sludge (1)
- additive manufacturing; polylactic acid (PLA); fused filament fabrication (FFF); fused deposition modeling (FDM); printing temperature; filament color; dimensional accuracy; tensile strength; friction performance; wear (1)
- advanced persistent threats (1)
- aerosol (1)
- air hygiene (1)
- airborne infection (1)
- antecedents (1)
- artificial intelligence (1)
- assistive robotics (1)
- augmented reality (1)
- bacterial toxicity (1)
- balance (1)
- barrel cortex, cell types, multielectrode recordings, perception, psychophysics (1)
- bio-inspired functional surface (1)
- bioinspired (1)
- biomimetic (1)
- biomimetic materials (1)
- biomimetics; functional morphology; plant biomechanics; plant motion; strain analysis; structure–function relationship; 3D digital image correlation (3D-DIC); Hakea sericea; Hakea salicifolia (1)
- bipolar plate (1)
- blockchain (1)
- bloxberg (1)
- carbon nano fibres (1)
- carbon nanofibers, platinum electrodeposition, electrocatalysts (1)
- cartilage defect (1)
- cartilage regeneration (1)
- chlorinated phenols (1)
- cluster (1)
- co-based alloys; hot corrosion; solid particle erosion; microstructure; brazing (1)
- coatings (1)
- cobot (1)
- collaborative online international learning (COIL) (1)
- compassionate love (1)
- composition (1)
- conical intersection (1)
- consent banner (1)
- cookie banner (1)
- cookies (1)
- corrosion resistance (1)
- corrosion; self-fluxing alloys; NiCrBSi; WC-12Co; cavitation; hard metals (1)
- critical review (1)
- cyber kill chain (1)
- demagnetization cooling (1)
- design process (1)
- distributed software development (1)
- diversity (1)
- dlt (1)
- dynamic capabilities (1)
- education; skills; competences; pandemic; online or face-to-face (1)
- efficiency of exciton transfer (1)
- electrode preparation (1)
- empowerment (1)
- entrepreneurial diversity (1)
- entrepreneurship (1)
- ethereum (1)
- ethics (1)
- excitation energy transfer (1)
- expert interviews (1)
- face mask (1)
- farming (1)
- fused deposition modeling (FDM); fused filament fabrication (FFF); polylactic acid (PLA); layer height; layer thickness; filament color; PLA color; dimensional accuracy; tensile strength (1)
- gender stereotypes (1)
- gender-sensitive design (1)
- gender-specific design (1)
- human robot interaction (1)
- human-centered design (1)
- human-robot collaboration (1)
- hybrid sensor system (1)
- hydraulic cell compression (1)
- infrared heating panel (1)
- ingots (1)
- innovation (1)
- intercultural collaboration (1)
- interdisciplinary students project (1)
- intermolecular interaction (1)
- international comparative study (1)
- intersectionality (1)
- irritation (1)
- leak locating (1)
- leak monitoring (1)
- long-term toxicity (1)
- luminescent bacteria (1)
- machine learning (1)
- managerial vs. non-managerial actors (1)
- measurement study (1)
- media accountability (1)
- microfoundations (1)
- molecular force field (1)
- multi-level model of competence (1)
- narcissism (1)
- neutrality (1)
- nonadiabatic dynamics (1)
- noncommuting fluctuations (1)
- nonequilibrium quantum transport (1)
- normalisation (1)
- novel (1)
- open science (1)
- optical chemical structure recognition (1)
- oxygen plasma activation (1)
- pH-shift elution (1)
- participatory design (1)
- phishing (1)
- photovoltaic power systems (1)
- poa (1)
- poe (1)
- policymakers (1)
- political journalism (1)
- polymer electrolyte membrane (1)
- privacy (1)
- product development (1)
- project-based learning (1)
- projection (1)
- protein structure prediction (1)
- public policy (1)
- quality standards (1)
- quantum dissipation (1)
- reconnaissance (1)
- relevance (1)
- respiration inhibition (1)
- risk management (1)
- role identity (1)
- self-fluxing; ZrO2; NiCrBSi; vacuum post-treatment; thermal spraying (1)
- sensor fusion (1)
- servant leadership (1)
- shared user control (1)
- silicon (1)
- solar cells (1)
- solution finding (1)
- spatial policy (1)
- state machine (1)
- study and working time per week (1)
- sustainable development (1)
- television news coverage (1)
- theorising (1)
- trait self-control (1)
- transport (1)
- tree frog (1)
- user acceptance (1)
- ventilation (1)
- vibronic coupling (1)
- virtual reality (1)
- visual cues (1)
- visualization techniques (1)
- watchblogs (1)
- web measurement (1)
- Änderung (1)
Institut
- Westfälisches Institut für Gesundheit (115)
- Westfälisches Energieinstitut (61)
- Institut für Internetsicherheit (56)
- Informatik und Kommunikation (51)
- Elektrotechnik und angewandte Naturwissenschaften (50)
- Wirtschaft und Informationstechnik Bocholt (46)
- Institut für biologische und chemische Informatik (44)
- Maschinenbau Bocholt (37)
- Institut Arbeit und Technik (15)
- Wirtschaftsingenieurwesen (15)
- Maschinenbau und Facilities Management (13)
- Institut für Innovationsforschung und -management (11)
- Fachbereiche (9)
- Wirtschaftsrecht (9)
- Mechatronik-Institut Bocholt (2)
- Strategische Projekte (2)
- Institute (1)
The translation of images of chemical structures into machine-readable representations of the depicted molecules is known as optical chemical structure recognition (OCSR). There has been a lot of progress over the last three decades in this field, but the development of systems for the recognition of complex hand-drawn structure depictions is still at the beginning. Currently, there is no data for the systematic evaluation of OCSR methods on hand-drawn structures available. Here we present DECIMER - Hand-drawn molecule images, a standardised, openly available benchmark dataset of 5088 hand-drawn depictions of diversely picked chemical structures. Every structure depiction in the dataset is mapped to a machine-readable representation of the underlying molecule. The dataset is openly available and published under the CC-BY 4.0 licence which applies very few limitations. We hope that it will contribute to the further development of the field.
For proton exchange membrane water electrolysis (PEMWE) to become competitive, the cost of stack components, such as bipolar plates (BPP), needs to be reduced. This can be achieved by using coated low-cost materials, such as copper as alternative to titanium. Herein we report on highly corrosion-resistant copper BPP coated with niobium. All investigated samples showed excellent corrosion resistance properties, with corrosion currents lower than 0.1 µA cm−2 in a simulated PEM electrolyzer environment at two different pH values. The physico-chemical properties of the Nb coatings are thoroughly characterized by scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), X-ray photoelectron spectroscopy (XPS), and atomic force microscopy (AFM). A 30 µm thick Nb coating fully protects the Cu against corrosion due to the formation of a passive oxide layer on its surface, predominantly composed of Nb2O5. The thickness of the passive oxide layer determined by both EIS and XPS is in the range of 10 nm. The results reported here demonstrate the effectiveness of Nb for protecting Cu against corrosion, opening the possibility to use it for the manufacturing of BPP for PEMWE. The latter was confirmed by its successful implementation in a single cell PEMWE based on hydraulic compression technology.
The present paper presents one- and two-step approaches for electrochemical Pt and Ir deposition on a porous Ti-substrate to obtain a bifunctional oxygen electrode. Surface pre-treatment of the fiber-based Ti-substrate with oxalic acid provides an alternative to plasma treatment for partially stripping TiO2 from the electrode surface and roughening the topography. Electrochemical catalyst deposition performed directly onto the pretreated Ti-substrates bypasses unnecessary preparation and processing of catalyst support structures. A single Pt constant potential deposition (CPD), directly followed by pulsed electrodeposition (PED), created nanosized noble agglomerates. Subsequently, Ir was deposited via PED onto the Pt sub-structure to obtain a successively deposited PtIr catalyst layer. For the co-deposition of PtIr, a binary PtIr-alloy electrolyte was used applying PED. Micrographically, areal micro- and nano-scaled Pt sub-structure were observed, supplemented by homogenously distributed, nanosized Ir agglomerates for the successive PtIr deposition. In contrast, the PtIr co-deposition led to spherical, nanosized PtIr agglomerates. The electrochemical ORR and OER activity showed increased hydrogen desorption peaks for the Pt-deposited substrate, as well as broadening and flattening of the hydrogen desorption peaks for PtIr deposited substrates. The anodic kinetic parameters for the prepared electrodes were found to be higher than those of a polished Ir-disc.
Various aqueous citrate electrolyte compositions for the Ni-Mo electrodeposition are explored in order to deposit Ni-Mo alloys with Mo-content ranging from 40 wt% to 65 wt% to find an alloy composition with superior catalytic activity towards the hydrogen evolution reaction (HER). The depositions were performed on copper substrates mounted onto a rotating disc electrode (RDE) and were investigated via scanning electron microscopy (SEM), X-ray fluorescence (XRF) and X-ray diffraction (XRD) methods as well as linear sweep voltammetry (LSV) and impedance spectroscopy. Kinetic parameters were calculated via Tafel analysis. Partial deposition current densities and current efficiencies were determined by correlating XRF measurements with gravimetric results. The variation of the electrolyte composition and deposition parameters enabled the deposition of alloys with Mo-content over the range of 40-65 wt%. An increase in Mo-content in deposited alloys was recorded with an increase in rotation speed of the RDE. Current efficiency of the deposition was in the magnitude of <1%, which is characteristic for the deposition of alloys with high Mo-content. The calculated kinetic parameters were used to determine the Mo-content with the highest catalytic activity for use in the HER.
Flame-sprayed NiCrBSi/WC-12Co composite coatings were deposited in different ratios on the surface of stainless steel. Oxyacetylene flame remelting treatment was applied to surfaces for refinement of the morphology of the layers and improvement of the coating/substrate adhesion.
The performance of the coated specimens to cavitation erosion and electrochemical corrosion was evaluated by an ultrasonic vibratory method and, respectively, by polarization measurements. The microstructure was investigated by means of scanning electron microscopy (SEM) combined with energy dispersive X-ray analysis (EDX). The obtained results demonstrated that the addition of 15 wt.% WC-12Co to the self-fluxing alloy improves the resistance to cavitation erosion (the terminal erosion rate (Vs) decreased with 15% related to that of the NiCrBSi coating) without influencing the good corrosion resistance in NaCl solution. However, a further increase in WC-Co content led to a deterioration of these coating properties (the Vs has doubled related to that of the NiCrBSi coating).
Moreover, the corrosion behavior of the latter composite coating was negatively influenced, a fact confirmed by increased values for the corrosion current density (icorr). Based on the achieved experimental results, one may summarize that NiCrBSi/WC-Co composite coatings are able to increase the life cycle of expensive, high-performance components exposed to severe cavitation conditions.
The printing variable least addressed in previous research aiming to reveal the effect of the FFF process parameters on the printed PLA part’s quality and properties is the filament color. Moreover, the color of the PLA, as well as its manufacturer, are rarely mentioned when the experimental conditions for the printing of the samples are described, although current existing data reveal that their influence on the final characteristics of the print should not be neglected. In order to point out the importance of this influential parameter, a natural and a black-colored PLA filament, produced by the same manufacturer, were selected. The dimensional accuracy, tensile strength, and friction properties of the samples were analyzed and compared for printing temperatures ranging from 200 C up to 240 C. The experimental results clearly showed different characteristics depending on the polymer color of samples printed under the same conditions. Therefore, the optimization of the FFF process parameters for the 3D-printing of PLA should always start with the proper selection of the type of the PLA material, regarding both its color and the fabricant.
Tape brazing constitutes a cost-effective alternative surface protection technology for complex-shaped surfaces. The study explores the characteristics of high-temperature brazed coatings using a cobalt-based powder deposited on a stainless-steel substrate in order to protect parts subjected to hot temperatures in a wear-exposed environment. Microstructural imaging corroborated with x-ray diffraction analysis showed a complex phased structure consisting of intermetallic Cr-Ni, C-Co-W Laves type, and chromium carbide phases. The surface properties of the coatings, targeting hot corrosion behavior, erosion, wear resistance, and microhardness, were evaluated. The high-temperature corrosion test was performed for 100 h at 750 C in a salt mixture consisting of 25 wt.% NaCl + 75 wt.% Na2SO4. The degree of corrosion attack was closely connected with the exposure temperature, and the degradation of the material corresponding to the mechanisms of low-temperature hot corrosion. The erosion tests were carried out using alumina particles at a 90 impingement angle. The results, correlated with the microhardness measurements, have shown that Co-based coatings exhibited approximately 40% lower material loss compared to that of the steel substrate.
In this study, the characteristics of HVOF sprayed WC/Co-Cr and WC/Cr3C2/Ni coatings were investigated in correlation with the variation of the powder feed rate. For this purpose, the mass flow was adjusted to four different levels. The other process parameters were all kept constant. The morphological and mechanical properties as well as the electrochemical corrosion behaviour were investigated and associated with the achieved microstructure.
Both scanning electron microscopy and confocal laser scanning microscopical images of the cross sections demonstrated a good correlation between the selected powder feed rate and the degree of internal porosity produced, which can be attributed to the deposition process. The coatings which fulfilled the requirements of the pre-qualification step were selected for further hardness measurements, tribological tests and electrochemical corrosion measurements in a 3.5 wt% NaCl aqueous solution.
It was found that the powder feed rate strongly influenced the characteristics of the HVOF-sprayed cermet coatings. The tendency to crack formation, especially at the interface coating/substrate, was lower for the samples coated with a lower mass flow rate. These studies have shown that the applied powder feed rates had an important influence on the coatings microstructure and implicitly on the sliding wear behavior respectively on the electrochemical corrosion resistance of the investigated cermet coatings.
In this work, a novel polymer electrolyte membrane water electrolyzer (PEMWE) test cell based on hydraulic single-cell compression is described. In this test cell, the current density distribution is almost homogeneous over the active cell area due to hydraulic cell clamping. As the hydraulic medium entirely surrounds the active cell components, it is also used to control cell temperature resulting in even temperature distribution. The PEMWE single-cell test system based on hydraulic compression offers a 25 cm2 active surface area (5.0 × 5.0 cm) and can be operated up to 80°C and 6.0 A/cm2. Construction details and material selection for the designed test cell are given in this document. Furthermore, findings related to pressure distribution analyzed by utilizing a pressure-sensitive foil, the cell performance indicated by polarization curves, and the reproducibility of results are described. Experimental data indicate the applicability of the presented testing device for relevant PEMWE component testing and material analysis.
Even though we live in a period when the word digitization is prevalent in many social areas, the COVID-19 pandemic has divided mankind into two main categories: some people have seen this crisis as an opportunity to move the activities online and, furthermore, to accelerate digitization in as many areas as possible, while others have been reluctant, keeping their preferences for face-to-face activities. The current work presents the results of an analysis on 249 students from 11 engineering faculties. The study aims to identify the impact of the COVID-19 pandemic on students’ educational experiences when switching from face-to-face to online education during a public health emergency or COVID 19-related state of alert. The overall conclusion was that, although the pandemic has brought adverse consequences on the health and life quality of many people, the challenges that humankind has been subjected to have led to personal and professional development and have opened up new perspectives for carrying out the everyday activities.
Impact of cobalt content and grain growth inhibitors in laser-based powder bed fusion of WC-Co
(2022)
Processing of tungsten carbide‑cobalt (WC-Co) by laser-based powder bed fusion (PBF-LB) can result in characteristic microstructure defects such as cracks, pores, undesired phases and tungsten carbide (WC) grain growth, due to the heterogeneous energy input and the high thermal gradients. Besides the processing conditions, the material properties are affected by the initial powder characteristics. In this paper, the impact of powder composition on microstructure, phase formation and mechanical properties in PBF-LB of WC-Co is studied.
Powders with different cobalt contents from 12 wt.-% to 25 wt.-% are tested under variation of the laser parameters.
Furthermore, the impact of vanadium carbide (VC) and chromium (Cr) additives is investigated. Both are known as grain growth inhibitors for conventional sintering processes. The experiments are conducted at a pre-heating temperature of around 800 ◦C to prevent crack formation in the samples. Increasing laser energy input reduces porosity but leads to severe embrittlement for low cobalt content and to abnormal WC grain growth for high cobalt content. It is found that interparticular porosity at low laser energy is more severe for low cobalt content due to poor wetting of the liquid phase. Maximum bending strength of σB > 1200 MPa and Vickers hardness of approx. 1000 HV3 can be measured for samples generated from WC-Co 83/17 powder with medium laser energy input. The addition of V and Cr leads to increased formation of additional phases such as Co3W3C, Co3V and Cr23C6 and to increased lateral and multi-laminar growth of the WC grains. In contrast to conventional sintering, a grain growth inhibiting effect of V and Cr in the laser molten microstructure is not achieved.
Developing and implementing computational algorithms for the extraction of specific substructures from molecular graphs (in silico molecule fragmentation) is an iterative process. It involves repeated sequences of implementing a rule set, applying it to relevant structural data, checking the results, and adjusting the rules. This requires a computational workflow with data import, fragmentation algorithm integration, and result visualisation. The described workflow is normally unavailable for a new algorithm and must be set up individually. This work presents an open Java rich client Graphical User Interface (GUI) application to support the development of new in silico molecule fragmentation algorithms and make them readily available upon release. The MORTAR (MOlecule fRagmenTAtion fRamework) application visualises fragmentation results of a set of molecules in various ways and provides basic analysis features. Fragmentation algorithms can be integrated and developed within MORTAR by using a specific wrapper class. In addition, fragmentation pipelines with any combination of the available fragmentation methods can be executed. Upon release, three fragmentation algorithms are already integrated: ErtlFunctionalGroupsFinder, Sugar Removal Utility, and Scaffold Generator. These algorithms, as well as all cheminformatics functionalities in MORTAR, are implemented based on the Chemistry Development Kit (CDK).
The influence of molecular fragmentation and parameter settings on a mesoscopic dissipative particle dynamics (DPD) simulation of lamellar bilayer formation for a C10E4/water mixture is studied. A “bottom-up” decomposition of C10E4 into the smallest fragment molecules (particles) that satisfy chemical intuition leads to convincing simulation results which agree with experimental findings for bilayer formation and thickness. For integration of the equations of motion Shardlow’s S1 scheme proves to be a favorable choice with best overall performance. Increasing the integration time steps above the common setting of 0.04 DPD units leads to increasingly unphysical temperature drifts, but also to increasingly rapid formation of bilayer superstructures without significantly distorted particle distributions up to an integration time step of 0.12. A scaling of the mutual particle–particle repulsions that guide the dynamics has negligible influence within a considerable range of values but exhibits apparent lower thresholds beyond which a simulation fails. Repulsion parameter scaling and molecular particle decomposition show a mutual dependence. For mapping of concentrations to molecule numbers in the simulation box particle volume scaling should be taken into account. A repulsion parameter morphing investigation suggests to not overstretch repulsion parameter accuracy considerations.
Recent years have seen a sharp increase in the development of deep learning and artificial intelligence-based molecular informatics. There has been a growing interest in applying deep learning to several subfields, including the digital transformation of synthetic chemistry, extraction of chemical information from the scientific literature, and AI in natural product-based drug discovery. The application of AI to molecular informatics is still constrained by the fact that most of the data used for training and testing deep learning models are not available as FAIR and open data. As open science practices continue to grow in popularity, initiatives which support FAIR and open data as well as open-source software have emerged. It is becoming increasingly important for researchers in the field of molecular informatics to embrace open science and to submit data and software in open repositories. With the advent of open-source deep learning frameworks and cloud computing platforms, academic researchers are now able to deploy and test their own deep learning models with ease. With the development of new and faster hardware for deep learning and the increasing number of initiatives towards digital research data management infrastructures, as well as a culture promoting open data, open source, and open science, AI-driven molecular informatics will continue to grow. This review examines the current state of open data and open algorithms in molecular informatics, as well as ways in which they could be improved in future.
The disruptive nature of the changing media landscape and technology-driven advances in communication have led to innovative ways of organizing work in the information and communication industry. This reorganization of work is reflected in the concept of New Work, which rethinks working concepts, styles, and employee behavior. Based on a survey among staff in the information and communication industry (n = 380), this study investigates the status quo of the implementation of New Work measures and their effectiveness in helping companies reach organizational goals. The results show that New Work measures are widely adopted although there is still unused potential. Moreover, the study demonstrates that the implementation of New Work measures supports companies in achieving New Work goals as well as overall organizational goals in the contexts of agile management, change management, internal communication, and evaluation.
The German supply chain law ( Lieferkettensorgfaltspflichtengesetz, abbreviated: LkSG) which enters into force on 1 January 2023 is part of the developing legal framework for human rights in global supply chains. Like the French vigilance law, it represents a new generation of supply chain laws which impose mandatory human rights due diligence obligations. The LkSG requires enterprises to exercise a number of due diligence obligations – from conducting risk analysis to undertaking preventive measures or remedial actions. The law is based on public enforcement via a competent authority, the Federal Office for Economic Affairs and Export Control (BAFA). The BAFA monitors and enforces compliance with the due diligence obligations. Non-compliant enterprises can be fined with up to 800,000 Euros and, in some cases, up to 2% of the annual turnover. Whilst the LkSG is an important step towards achieving greater corporate sustainability, it also has limitations. It was a political compromise and, as such, it does not include a new civil liability for non-compliance. Moreover, by default, it only applies to the enterprise’s own business area and its direct suppliers, whereas indirect suppliers are only included where the enterprise has substantiated knowledge that an obligation has been violated.
This chapter is a commentary on Principle 20 of the United Nations Guiding Principles on Business and Human Rights (UNGPs). The UNGPs, endorsed by the United Nations Human Rights Council in 2011, are the first universally accepted framework for addressing business responsibilities for human rights. They outline State obligations to protect human rights, businesses’ responsibility to respect human rights, and the importance of both States and businesses offering adequate remedies for human rights breaches.
This chapter is a commentary on Principle 21 of the United Nations Guiding Principles on Business and Human Rights (UNGPs). The UNGPs, endorsed by the United Nations Human Rights Council in 2011, are the first universally accepted framework for addressing business responsibilities for human rights. They outline State obligations to protect human rights, businesses’ responsibility to respect human rights, and the importance of both States and businesses offering adequate remedies for human rights breaches.
Dephasing in quantum systems is typically the result of their interaction with environmental degrees of freedom. We investigate within a spin-boson model the influence of a super-Ohmic environment on the dynamics of a quantum two-state system. A super-Ohmic environment thereby models typical bulk phonons which are a common disturbance for solid state quantum systems as, for example, nitrogen-vacancy centers. By applying the numerically exact quasiadiabatic path-integral approach we show that for strong system-bath coupling, pseudocoherent dynamics emerges, i.e., oscillatory dynamics at short times due to slaving of the quantum system to the bath dynamics. We extend the phase diagram known for sub-Ohmic and Ohmic environments into the super-Ohmic regime and observe a pronounced nonmonotonous behavior. Super-Ohmic purely dephasing fluctuations strongly suppress the amplitude of coherent dynamics at very short times with no subsequent further decay at later times. Nevertheless, they render the dynamics overdamped. The corresponding phase separation line shows also a nonmonotonous behavior, very similar to the pseudocoherent dynamics.
We propose a quantum-mechanical model to calculate the current through a single molecular junction immersed in a solvent and surrounded by a thin shell of bound water under an applied ac voltage. The solvent plus hydration shell are captured by a dielectric continuum model for which the resulting spectral density is determined. Here the dielectric properties, e.g., the Debye relaxation time and the dielectric constant, of the bulk solvent and the hydration shell as well as the shell thickness directly enter. We determine the charge current through the molecular junction under an ac voltage in the sequential tunneling regime where we solve a quantum master equation by a real-time diagrammatic technique. Interestingly, the Fourier components of the charge current show an exponential-like decline when the hydration shell thickness increases. Finally, we apply our findings to binary solvent mixtures with varying volume fractions and find that the current is highly sensitive to both the hydration shell thickness as well as the volume fraction of the solvent mixture, giving rise to possible applications as shell and concentration sensors on the molecular scale.
Article 134 TFEU
(2023)
Article 135 TFEU
(2023)
Design and Development of a Bioreactor System for Mechanical Stimulation of Musculoskeletal Tissue
(2023)
We report on the development of a bioreactor system for mechanical stimulation of musculoskeletal tissues. The ultimate object is to improve the quality of medical treatment following injuries of the enthesis tissue. To this end, the tissue formation process through the effect of mechanical stimulation is investigated. A six-well system was designed, 3D printed and tested. An integrated actuator creates strain by applying a force. A contactless position sensor monitors the travels. An electronic circuit controls the bioreactor using a microcontroller. An IoT platform connects the microcontroller to a smartphone, enabling the user to alter variables, trigger actions and monitor the system. The system was stabilised by implementing two PID controllers and safety measures. The results show that the bioreactor design is suited to execute mechanical stimulation and to investigate the tissue formation and regeneration process …
Problem
- How to effectively use aerial robots to support rescue forces?
- How to achieve good flight characteristics and long flight times?
- How to enable simple and intuitive control?
- How to efficiently record image data of the environment?
- How to generate flight and image data for rescue forces?
Implementation:
The flying robot was designed in Autodesk Fusion360. In order to achieve high stability as well as low weight, the frame was milled from carbon. Mounts such as for GPS and 360° camera were 3D printed. A special feature is that the flying robot is not visible in the panoramic view of the 360° camera. The flight controller of the robot was set up using Ardupilot. The communication with the robot is done via MAVLink (UDP).To support different platforms, a software was realized as a web application. The front end was created using HTML, CSS and Javascript.
The back end is based on Flask-Socket-IO (Python). For the intelligent recognition of motor vehicles a micro controller with an integrated camera is used. For the post-processing of flight and video data a pipeline was implemented for automation.
The video shows a very high resolution 3D point cloud !!! of the outdoor area of the German Rescue Robotics Center. For the recording, a 25-second POI flight was performed with a Mavic 3. From the 4K video footage captured during this flight, 77 images were cropped and localized within 4 minutes using colmap and processed using Neural Radiance Fields (NeRF). The nerfacto model of Nerfstudio was trained on an Nvidia RTX 4090 for 8 minutes. In summary, a top 3D model is available to task forces after about 13 minutes. The calculation is performed locally on site by the RobLW of the DRZ. The video shown here shows a free camera path rendered at 60 hz (Full HD).
In this paper, we investigate the influence of different disease groups on the size of different 1 anatomical structures. To this end, we first modify and improve an existing anatomical segmentation 2 model. Then, we use this model to segment 104 anatomical structures from computed tomography 3 (CT) scans and compute their volumes from the segmentation. After correlating the results with each 4 other, we find no new significant correlations. After correlating the volume data with known diseases 5 for each case, we find two weak correlations, one of which has not been described before and for 6 which we present a possible explanation.
In the realm of digital situational awareness during disaster situations, accurate digital representations,
like 3D models, play an indispensable role. To ensure the
safety of rescue teams, robotic platforms are often deployed
to generate these models. In this paper, we introduce an
innovative approach that synergizes the capabilities of compact Unmaned Arial Vehicles (UAVs), smaller than 30 cm, equipped with 360° cameras and the advances of Neural Radiance Fields (NeRFs). A NeRF, a specialized neural network, can deduce a 3D representation of any scene using 2D images and then synthesize it from various angles upon request. This method is especially tailored for urban environments which have experienced significant destruction, where the structural integrity of buildings is compromised to the point of barring entry—commonly observed post-earthquakes and after severe fires. We have tested our approach through recent post-fire scenario, underlining the efficacy of NeRFs even in challenging outdoor environments characterized by water, snow, varying light conditions, and reflective surfaces.
In this paper, we present a method for detecting objects of interest, including cars, humans, and fire, in aerial images captured by unmanned aerial vehicles (UAVs) usually during vegetation fires. To achieve this, we use artificial neural networks and create a dataset for supervised learning. We accomplish the assisted labeling of the dataset through the implementation of an object detection pipeline that combines classic image processing techniques with pretrained neural networks. In addition, we develop a data augmentation pipeline to augment the dataset with utomatically labeled images. Finally, we evaluate the performance of different neural networks.
The number of publications describing chemical structures has increased steadily over the last decades. However, the majority of published chemical information is currently not available in machine-readable form in public databases. It remains a challenge to automate the process of information extraction in a way that requires less manual intervention - especially the mining of chemical structure depictions. As an open-source platform that leverages recent advancements in deep learning, computer vision, and natural language processing, DECIMER.ai (Deep lEarning for Chemical IMagE Recognition) strives to automatically segment, classify, and translate chemical structure depictions from the printed literature. The segmentation and classification tools are the only openly available packages of their kind, and the optical chemical structure recognition (OCSR) core application yields outstanding performance on all benchmark datasets. The source code, the trained models and the datasets developed in this work have been published under permissive licences. An instance of the DECIMER web application is available at https://decimer.ai.
Measurement studies are essential for research and industry alike to understand the Web’s inner workings better and help quantify specific phenomena. Performing such studies is demanding due to the dynamic nature and size of the Web. An experiment’s careful design and setup are complex, and many factors might affect the results. However, while several works have independently observed differences in
the outcome of an experiment (e.g., the number of observed trackers) based on the measurement setup, it is unclear what causes such deviations. This work investigates the reasons for these differences by visiting 1.7M webpages with five different measurement setups. Based on this, we build ‘dependency trees’ for each page and cross-compare the nodes in the trees. The results show that the measured trees differ considerably, that the cause of differences can be attributed to specific nodes, and that even identical measurement setups can produce different results.
This paper reveals various approaches undertaken over more than two decades of teaching undergraduate programming classes at different Higher Education Institutions, in order to improve student activation and participation in class and consequently teaching and learning effectiveness.
While new technologies and the ubiquity of smartphones and internet access has brought new tools to the classroom and opened new didactic approaches, lessons learned from this personal long-term study show that neither technology itself nor any single new and often hyped didactic approach ensured sustained improvement of student activation. Rather it needs an integrated yet open approach towards a participative learning space supported but not created by new tools, technology and innovative teaching methods.
This paper presents a pragmatic approach for stepwise introduction of peer assessment elements in undergraduate programming classes, discusses some lessons learned so far and directions for further work. Students are invited to challenge their peers with their own programming exercises to be submitted through Moodle and evaluated by other students according to a predefined rubric and supervised by teaching assistants. Preliminary results show an increased activation and motivation of students leading to a better performance in the final programming exams.
In this work a mathematical approach to calculate solar panel temperature based on measured irradiance, temperature and wind speed is applied. With the calculated module temperature, the electrical solar module characteristics is determined. A program developed in MatLab App Designer allows to import measurement data from a weather station and calculates the module temperature based on the mathematical NOCT and stationary approach with a time step between the measurements of 5 minutes. Three commercially available solar panels with different cell and interconnection technologies are used for the verification of the established models. The results show a strong correlation between the measured and by the stationary model predicted module temperature with a coefficient of determination R2 close to 1 and a root mean square deviation (RMSE) of ≤ 2.5 K for a time period of three months. Based on the predicted temperature, measured irradiance in module plane and specific module information the program models the electrical data as time series in 5-minute steps. Predicted to measured power for a time period of three months shows a linear correlation with an R2 of 0.99 and a mean absolute error (MAE) of 3.5, 2.7 and 4.8 for module ID 1, 2 and 3. The calculated energy (exemplarily for module ID 2) based on the measured, calculated by the NOCT and stationary model for this time period is 118.4 kWh, resp. 116.7 kWh and 117.8 kWh. This is equivalent to an uncertainty of 1.4% for the NOCT and 0.5% for the stationary model.
n-type silicon modules
(2023)
The photovoltaic industry is facing an exponential growth in the recent years fostered by a dramatic decrease in installation prices. This cost reduction is achieved by means of several mechanisms. First, because of the optimization of the design and installation process of current PV projects, and second, by the optimization, in terms of performance, in the manufacturing techniques and material combinations within the modules, which also has an impact on both, the installation process, and the levelized cost of electricity (LCOE).
One popular trend is to increase the power delivered by photovoltaic modules, either by using larger wafer sizes or by combining more cells within the module unit. This solution means a significant increase in the size of these devices, but it implies an optimization in the design of photovoltaic plants. This results in an installation cost reduction which turns into a decrease in the LCOE.
However, this solution does not represent a breakthrough in addressing the real challenge of the technology which affects the module requirements. The innovation efforts must be focused on improving the modules capability to produce energy without enlarging the harvesting area. This challenge can be faced by approaching some of the module characteristics which are summarized in this chapter.
Advanced Determination of Temperature Coefficients of Photovoltaic Modules by Field Measurements
(2023)
In this work data from outdoor measurements, acquired over the course of up to three years on commercially available solar panels, is used to determine the temperature coefficients and compare these to the information as stated by the producer in the data sheets. A program developed in MatLab App Designer allows to import the electrical and ambient measurement data. Filter algorithms for solar irradiance narrow the irradiance level down to ~1000 W/m2 before linear regression methods are applied to obtain the temperature coefficients. A repeatability investigation proves the accuracy of the determined temperature coefficients which are in good agreement to the supplier specification if the specified values for power are not larger than -0.3%/K. Further optimization is achieved by applying wind filter techniques and days with clear sky condition. With the big (measurement) data on hand it was possible to determine the change of the temperature coefficients for varying irradiance. As stated in literature we see an increase of the temperature coefficient of voltage and a decline for the temperature coefficient of power with increasing irradiance.
The concept of “Internationalisation at Home“ has gained momentum with the increasing digitalization of education and limitations on mobility. Collaborative Online International Learning (COIL) is an innovative, cost-effective instructional method that promotes intercul-tural learning through online collaboration between faculty and students from different countries or locations. The benefits of using COIL courses have been widely recognized, with learners developing intercultural competencies, digital skills, international education experi-ence, and global awareness.
However, multicultural communication in project environments can be complex and demand awareness of cultural variations . The creation and development of effective cross-cultural collectivism, trust, communication, and empathy in leadership is an important ingredient for remote project collaborations success. This is an area that has been least explored in re-search on communication in virtual teams.
The GIPE projects are mainly carried out as so-called Collaborative Online International Learning (COIL) events. However, to gain a “real world“ experience abroad in an intercultural team, students from all partner universities can participate in the Spring School being held for two weeks in Germany and the Germany students present and hand-over the results in the country of the partner university. The main objective of this research was to examine the experiences of students participating in the GIPE project and to evaluate the effectiveness of the project in enhancing intercultural competencies and fostering collaboration among stu-dents from different continents. This paper will also explore the implications of the GIPE project for Education 2.0 considering the COVID-19 pandemic and the future of education delivery and administration transformation.
Jdpd - An open Java Simulation Kernel for Molecular Fragment Dissipative Particle Dynamics (DPD)
Jdpd is an open Java simulation kernel for Molecular Fragment Dissipative Particle Dynamics (DPD) with parallelizable force calculation, efficient caching options and fast property calculations. It is characterized by an interface and factory-pattern driven design for simple code changes and may help to avoid problems of polyglot programming. Detailed input/output communication, parallelization and process control as well as internal logging capabilities for debugging purposes are supported. The kernel may be utilized in different simulation environments ranging from flexible scripting solutions up to fully integrated “all-in-one” simulation systems like MFsim.
Since Jdpd version 1.6.1.0 Jdpd is available in a (basic) double-precision version and a (derived) single-precision version (= JdpdSP) for all numerical calculations, where the single precision version needs about half the memory of the double precision version.
Jdpd uses the Apache Commons Math and Apache Commons RNG libraries and is published as open source under the GNU General Public License version 3. This repository comprises the Java bytecode libraries (including the Apache Commons Math and RNG libraries), the Javadoc HTML documentation and the Netbeans source code packages including Unit tests.
Jdpd has been described in the scientific literature (the final manuscript 2018 - van den Broek - Jdpd - Final Manucsript.pdf is added to the repository) and used for DPD studies (see references below).
See text file JdpdVersionHistory.txt for a version history with more detailed information.
MFsim - An open Java all-in-one rich-client simulation environment for mesoscopic simulation
MFsim is an open Java all-in-one rich-client computing environment for mesoscopic simulation with Jdpd as its default simulation kernel for Molecular Fragment Dissipative Particle Dynamics (DPD). The environment integrates and supports the complete preparation-simulation-evaluation triad of a mesoscopic simulation task. Productive highlights are a SPICES molecular structure editor, a PDB-to-SPICES parser for particle-based peptide/protein representations, a support of polymer definitions, a compartment editor for complex simulation box start configurations, interactive and flexible simulation box views including analytics, simulation movie generation or animated diagrams. As an open project, MFsim enables customized extensions for different fields of research.
MFsim uses several open libraries (see MFSimVersionHistory.txt for details and references below) and is published as open source under the GNU General Public License version 3 (see LICENSE).
MFsim has been described in the scientific literature and used for DPD studies.