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Eingeladener Vortrag
- ja (114) (entfernen)
Glasses stand out by their wide and continuously tunable chemical composition and large variety of unique shaping techniques making them a key component of modern high technologies. Glass development, however, is still often too cost-, time- and energy-intensive. The use of robotic melting systems embedded in an ontology-based digital environment is intended to overcome these problems in future. As part of the German research initiative MaterialDigital, the joint project GlasDigital takes first steps in this direction. The project consortium involves the Fraunhofer ISC in Würzburg, the Friedrich Schiller University Jena (OSIM), the Clausthal University of Technology (INW), and the Federal Institute for Materials Research and Testing (BAM, Division Glasses) and aims to combine all main basic components required for accelerated data driven glass development. For this purpose, a robotic high throughput glass melting system is equipped with novel inline sensors for process monitoring, machine learning (ML)-based, adaptive algorithms for process monitoring and optimization, novel tools for high throughput glass analysis and ML-based algorithms for glass design, including software tools for data mining as well as property and process modelling. The talk gives an overview how all these tools are interconnected and illustrates their usability with some examples.
lasses stand out by their wide and continuously tunable chemical composition and large variety of unique shaping techniques making them a key component of modern high technologies. Glass development, however, is still often too cost-, time- and energy-intensive. The use of robotic melting systems embedded in an ontology-based digital environment is intended to overcome these problems in future. As part of the German research initiative MaterialDigital, the joint project GlasDigital takes first steps in this direction. The project consortium involves the Fraunhofer ISC in Würzburg, the Friedrich Schiller University Jena (OSIM), the Clausthal University of Technology (INW), and the Federal Institute for Materials Research and Testing (BAM, Division Glasses) and aims to combine all main basic components required for accelerated data driven glass development. For this purpose, a robotic high throughput glass melting system is equipped with novel inline sensors for process monitoring, machine learning (ML)-based, adaptive algorithms for process monitoring and optimization, novel tools for high throughput glass analysis and ML-based algorithms for glass design, including software tools for data mining as well as property and process modelling. The talk gives an overview how all these tools are interconnected and illustrates their usability with some examples.
Im Projekt GlasDigital sollen digitale Werkzeuge für die Hochdurchsatzentwicklung neuartiger Glaswerkstoffe erarbeitet werden. Dies soll durch die Kombination robotischer Syntheseverfahren mit selbstlernenden Maschinen und ihre Einbindung in eine Ontologie-basierte digitale Infrastruktur realisiert werden.
Rotschlamm fällt in sehr großen Mengen bei der Herstellung von Aluminiumoxid an und wird fast ausschließlich deponiert. Es wird eine neue Technologie vorgestellt bei der das im Rotschlamm enthaltene Eisenoxid mittels Wasserstoffplasma reduziert wird. Es wird ein Reaktionsmechanismus über Titanomagnetit und Hercynit vorgeschlagen.
A chemical engineer by training, Brian drifted towards physics and now focuses on a broad spectrum of activities with the aim to improve scientific reproducibility. This includes studies on holistically improving data quality, data collection efficiency and traceability, as well as concomitant laboratory automation for the preparation of consistent, well-documented sample series. The need for pragmatism led to an inexpensive, flexible laboratory automation platform that can be implemented in a modest amount of time. This talk presents that effort.
Der Vortrag gibt einen Überblick zu ultrakurzen Laserpulsen, der Ultrakurzpulslaser-Materialbearbeitung und der dabei ggf. auftretenden unerwünschten Röntgenstrahlung. Es wird die Laserbearbeitung von technischen und biologischen Materialien diskutiert. Schutzmöglichkeiten gegenüber der Röntgenstrahlung werden erörtert.
Der Vortrag gibt einen Überblick über die vielfältigen Möglichkeiten der Oberflächenfunktionalisierung mittels Mikro- und Nanostrukturierung durch Ultrakurzpuls-Lasermaterialbeabeitung. Dies schließt eine Diskussion des Phänomens der Laser-induzierten periodischen Oberflächenstrukturen (LIPSS, engl.: Laser-induced Periodic Surface Structures, Ripples), sowie deren Klassifikation und Bildungsmechanismen mit ein. Ein Schwerpunkt der Präsentation liegt auf der Diskussion verschiedener Anwendungsmöglichkeiten der LIPSS in Bereichen der Optik, Fluidik, Tribologie und Medizin, sowie auf einem Ausblick auf die industrielle Skalierbarkeit der LIPSS-Technologie.