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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.
Glasig-kristalline Werkstoffe für Schlüsseltechnologien - Prozessbegleitende Prüfung und Simulation
(2017)
Eigenschaftsprofile und Kennwertstreuungen keramischer und glaskeramischer Komponenten und Bauteile werden durch ihren Herstellungsprozess wesentlich mitbestimmt. Prozessbegleitende Prüf- und Simulationsmethoden gewinnen so wachsenden Einfluss auf die Erschließung neuer Applikationsfelder dieser Werkstoffe. Eine wichtige Rol¬le spielen hierbei oft thermokinetische Prozesse, die u. a. Wärmetransport- und Diffusionsvorgänge, Phasengrenzflächenreaktionen, das rheologische Verhalten heterogener Systeme sowie deren Gefügeevolution beim Sintern umfassen. Ziel des Vortrages ist es, diesen Trend anhand ausgewählter Bei-spiele aus der Arbeit des Fachbereichs Glas der BAM zu illustrieren.
Glass powders are promising candidates for manufacturing a broad diversity of sintered materials like sintered ¬glass-ceramics, glass matrix composites or glass bonded ceramics with tailored mechanical, thermal, electrical and optical properties and complex shape. Its wide and precise adjustability makes this class of materials a key component for advanced technologies. Processing of glass or composite powders often allow even more flexibility in materials design. At the same time, however, processing can have substantial effects on the glass powder surface and sinterability. Thus, mechanical damage and surface contamination can strongly enhance surface crystallization, which may retard or even fully prevent densification. Whereas sintering and concurrent crystallization have been widely studied, partially as cooperative effort of the TC7 of the ICG, and although glass powder sintering is predominantly applied for glasses of low crystallization tendency, sintering is also limited by gas bubble formation or foaming. The latter phenomenon is much less understood and can occur even for slow crystallizing glass powders. The lecture illustrates possible consequences of glass powder processing on glass sintering, crystallization and foaming.
Glass powders are promising candidates for manufacturing a broad diversity of sintered materials like sintered glass-ceramics, glass matrix composites or glass bonded ceramics with tailored mechanical, thermal, electrical and optical properties and complex shape. Its wide and precise adjustability makes this class of materials a key component for advanced technologies. Processing of glass or composite powders often allow even more flexibility in materials design. At the same time, however, processing can have substantial effects on the glass powder surface and sinterability. Thus, mechanical damage and surface contamination can strongly enhance surface crystallization, which may retard or even fully prevent densification. Whereas sintering and concurrent crystallization have been widely studied, partially as cooperative effort of the TC7 of the ICG, and although glass powder sintering is predominantly applied for glasses of low crystallization tendency, sintering is also limited by gas bubble formation or foaming. The latter phenomenon is much less understood and can occur even for slow crystallizing glass powders. The lecture illustrates possible consequences of glass powder processing on glass sintering, crystallization and foaming.