A5014436855- Scientific Computing and Data Management
- Semantic Web and Ontologies
- Open Source Software Innovations
- Machine Learning in Materials Science
- Research Data Management Practices
- Educational Games and Gamification
- Software Engineering Research
- Open Education and E-Learning
- Sensor Technology and Measurement Systems
- Environmental Monitoring and Data Management
- Model-Driven Software Engineering Techniques
- Technology Use by Older Adults
- Dielectric materials and actuators
- Data Management and Algorithms
- Advanced MEMS and NEMS Technologies
- Constraint Satisfaction and Optimization
- Advanced Sensor and Energy Harvesting Materials
- Wikis in Education and Collaboration
- Vibration Control and Rheological Fluids
- Real-time simulation and control systems
- Digital Games and Media
- Artificial Intelligence in Games
- Advanced Thermodynamic Systems and Engines
- Plasma Diagnostics and Applications
- Knowledge Management and Sharing
Technische Universität Berlin
2022-2025
Research Institute for Telecommunication Cooperation
2017-2023
Mahle (Germany)
2019
The MaterialDigital initiative represents a major driver toward the digitalization of material science. Next to providing prototypical infrastructure required for building shared data space and working on semantic interoperability data, core focus area Platform (PMD) is utilization workflows encapsulate processing simulation steps in accordance with findable, accessible, interoperable, reusable principles. In collaboration funded projects initiative, workflow group strives establish...
Smart materials react to physical fields (e.g., electric, magnetic, and thermal fields) can be used as sensors, actuators, generators due their bidirectional behavior. Easy multiscale access material data models enables efficient research development with regard the selection of appropriate optimization towards specific applications. However, different working principles, measurement analysis methods, well storage approaches lead heterogeneous partly inconsistent datasets. The ontology‐based...
The internet surpassed the zettabyte order of magnitude traffic in 2016. With growth internet, information categorization becomes even more important than before. By matching to existing categories, humans as well machines are able organize, manage, access and re-use knowledge resources a efficient effective way. Categorization also helps narrow choices among content, information, resources. Content, can be browsed, searched, accessed faster if they appropriately categorized. In make...
Smart Materials (SMat) promise to open new opportunities in the area of Intelligent Environments (IE), whether as part dedicated smart devices or fabric constituting everyday appliances and building infrastructure. Through use ontologies both IE engineers IEs themselves can be aware of, predict, how novel configurable changing materials react under different conditions. In contrast conventional Objects, however, computational software/hardware-systems, lending object-oriented perspective...
In general, materials for dielectric elastomer (DE) transducers, i.e. and electrode materials, are characterized by their electromechanical behavior. Whereas previous works frequently focus on the mechanical characterization of material, this contribution deals with two ELASTOSIL ® LR 3162 (EL 3162) POWERSIL® 466 (PS 466), as well material 2030 2030). The behavior is determined elastic viscous properties such creep relaxation. addition, exhibit a significant rate-independent hysteresis,...
Abstract A current research topic for dielectric elastomer (DE) materials is the reduction of thickness DE layer in order to achieve a lower operating voltage with same electric field strength. As ratio thicknesses electrode therefore more important, mechanical properties layers are greater significance. Several articles deal investigations, exploring influence on behavior transducer and emphasizing its importance. In analytical models, however, electrodes not usually considered separately,...
Dielectric Elastomer (DE) transducers are characterized by their geometrical dimensions and in particular the properties of elastomer electrode materials. Therefore, addition to dimensions, it is advantageous consider optimization material fulfill transducer requirements, such as blocking force, free stroke, or response time. A big challenge describing DE materials deals with utilizing different but commonly used hyperelastic models parameters, which differ complexity corresponding model...