TY - CONF A1 - Müller, Ralf T1 - Glass Sintering with Concurrent Crystallization and Foaming N2 - 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. T2 - 7th Int Congress on Ceramics, Symposium Frontiers of Glass Science CY - Iguacu, Brazil DA - 17.06.2018 KW - Glass KW - Powder KW - Sintering KW - Foaming PY - 2018 AN - OPUS4-45670 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Müller, Ralf A1 - Agea Blanco, Boris A1 - Blaeß, Carsten A1 - Waurischk, Tina A1 - Reinsch, Stefan A1 - Behrens, H. T1 - Sintering and foaming of silicate N2 - 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 properties and complex shape. Powder processing, however, can substantially affect sinterability, e.g. by promoting surface crystallization. On the other hand, densification can be hindered by gas bubble formation for slow crystallizing glass powders. Against this background, we studied sintering and foaming of silicate glass powders with different crystallization tendency for wet milling and dry milling in air, Ar, N2, and CO2 by means of heating microscopy, DTA, Vacuum Hot Extraction (VHE), SEM, IR spectroscopy, XPS, and ToF-SIMS. In any case, foaming activity increased significantly with progressive milling. For moderately milled glass powders, subsequent storage in air could also promote foaming. Contrarily, foaming could be substantially reduced by milling in water and 10 wt% HCl. Although all powder compacts were uniaxially pressed and sintered in air, foaming was significantly affected by different milling atmosphere and was found most pronounced for milling in CO2 atmosphere. Conformingly, VHE studies revealed that foaming is mainly driven by carbonaceous species, even for powders milled in other gases. Current results of this study thus indicate that foaming is caused by carbonaceous species trapped on the glass powder surface. T2 - ICG Annual Meeting 2018 CY - Yokohama, Japan DA - 23.09.2018 KW - Foaming KW - Glass KW - Powder KW - Sintering PY - 2018 AN - OPUS4-46474 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Reinsch, Stefan A1 - Welter, T. A1 - Müller, Ralf A1 - Deubener, J. T1 - Hydrogen Permeability of Tectosilicate Glasses for Tank Barrier Liners N2 - The permeation of hydrogen gas was studied in meta-aluminous (tectosilicate) glass powders of Li2O×Al2O3×SiO2 (LAS), Na2O×Al2O3×SiO2 (NAS) and MgO×Al2O3×SiO2 (MAS) systems by pressure loading and vacuum extraction in the temperatures range 210–310 °C. With this method, both the solubility S and the diffusivity D were determined, while the permeability was given by the product SD. For all glasses, S was found to decrease with temperature, while D increased. Since the activation energy of diffusion of H2 molecules exceeded that of dissolution, permeation increased slightly with temperature. When extrapolated to standard conditions (25 °C), the permeability of tectosilicate glasses was found to be only 10-22–10-24 mol H2 (m s Pa)-1, which is 8–10 magnitudes lower than most polymers. Thin glass liners of these compositions are expected to be the most effective barrier for tanks of pressurised hydrogen. KW - Hydrogen permeation KW - Aluminosilicate glasses KW - Hydrogen storage tank KW - Glass liner PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-587284 DO - https://doi.org/10.52825/glass-europe.v1i.425 VL - 1 SP - 1 EP - 11 AN - OPUS4-58728 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Gomes Fernandes, Roger A1 - Al-Mukadam, Raschid A1 - Bornhöft, Hansjörg A1 - Reinsch, Stefan A1 - Müller, Ralf A1 - Selle, Susanne A1 - Deubener, Joachim T1 - Viscous Sintering of Acid Leached Glass Powders N2 - The process of viscous flow sintering is a phenomenon that is closely linked to the surface properties of the glass particles. In this work, we studied the extreme case of acid-leaching of soda-lime-silicate glass beads of two different particle size distributions and its effects on non-isothermal viscous sintering of powder compacts. Depth profiling of the chemical composition after leaching revealed a near-surface layer depleted in alkali and alkaline earth ions, associated with concurrent hydration as mass loss was detected by thermogravimetry. Heating microscopy showed that acid treatment of glasses shifted the sinter curves to higher temperatures with increasing leaching time. Modelling of the shrinkage with the cluster model predicted a higher viscosity of the altered surface layer, while analysis of the time scales of mass transport of mobile species (Na+, Ca2+ and H2O) during isochronous sintering revealed that diffusion of Na+ can compensate for concentration gradients before sintering begins. Also, exchanged water species can diffuse out of the altered layer, but the depletion of Ca2+ in the altered surface layer persists during the sinter interval, resulting in a glass with higher viscosity, which causes sintering to slow down. KW - Glass powder KW - Viscous sintering KW - Acid-leaching KW - Sinter retardation PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-589008 DO - https://doi.org/10.52825/glass-europe.v1i.681 VL - 1 SP - 37 EP - 53 AN - OPUS4-58900 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Müller, Ralf A1 - Schottner, G. A1 - Wondraczek, L. A1 - Sierka, M. A1 - Deubener, J. A1 - Waurischk, Tina A1 - Reinsch, Stefan A1 - Contreras, A. A1 - Diegeler, A. A1 - Kilo, M. A1 - Pan, Z.-W. A1 - Arendt, F. A1 - Chen, Y.-F. A1 - Gogula, S. A1 - Bornhöft, H. T1 - GlasDigital: Data-driven workflow for accelerated glass development N2 - 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. T2 - USTV-DGG joint meeting CY - Orleans, France DA - 22.05.2023 KW - Glass KW - Ontology KW - Data Space KW - Workflow KW - Robotic melting PY - 2023 AN - OPUS4-60372 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Müller, Ralf A1 - Diegeler, A. A1 - Schottner, G. A1 - Niebergall, R. A1 - Kilo, M. A1 - Arendt, F. A1 - Chen, Y.-F. A1 - Sierka, M. A1 - Limbach, R. A1 - Pan, Z. A1 - Wondraczek, L. A1 - Gogula, S. A1 - Bornhöft, H. A1 - Deubener, J. A1 - Waurischk, Tina A1 - Reinsch, Stefan T1 - GlassDigital: Digital Infrastructure for Data-Driven High-Throughput Glass Development N2 - Gläser zeichnen sich durch eine breite und kontinuierlich abstimmbare chemische Zusammensetzung sowie einzigartige Formgebungstechniken aus, was sie oft zur Schlüsselkomponente moderner Hochtechnologien macht. Die Glasentwicklung ist jedoch oft noch zu kosten-, zeit- und energieintensiv. Der Einsatz von robotergestützten Schmelzsystemen, eingebettet in eine Ontologie-basierte digitale Umgebung, soll diese Probleme in Zukunft überwinden. Im Rahmen der BMBF Forschungsinitiative MaterialDigital unternimmt das Verbundprojekt GlasDigital „Datengetriebener Workflow für die beschleunigte Entwicklung von Glas“ erste Schritte in diese Richtung. Das Projektkonsortium, an dem das Fraunhofer ISC in Würzburg, die Friedrich-Schiller-Universität Jena (OSIM), die Technische Universität Clausthal (INW) und die Bundesanstalt für Materialforschung und -prüfung (BAM, Fachgruppe Glas) beteiligt sind, will alle wesentlichen Basiskomponenten für eine beschleunigte datengetriebene Glasentwicklung zusammenführen. Zu diesem Zweck wird ein robotergestütztes Hochdurchsatz-Glasschmelzsystem mit neuartigen Inline-Sensoren zur Prozessüberwachung, auf maschinellem Lernen (ML) basierenden adaptiven Algorithmen zur Prozessüberwachung und -optimierung, neuartigen Werkzeugen für die Hochdurchsatz-Glasanalyse sowie ML-basierten Algorithmen zum Glasdesign, Data Mining sowie Eigenschafts- und Prozessmodellierung ausgestattet. Der Vortrag gibt einen Überblick darüber, wie all diese Komponenten miteinander verzahnt sind, und veranschaulicht ihre Nutzbarkeit anhand einiger Beispiele. T2 - HVG-Fortbildungskurs CY - Offenbach, Germany DA - 27.11.2023 KW - Glas KW - Ontology KW - Workflow KW - Simulation KW - Robotic melting PY - 2023 AN - OPUS4-60386 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Müller, Ralf A1 - Niebergall, R. A1 - Schottner, G. A1 - Wondraczek, L. A1 - Sierka, M. A1 - Deubener, J. A1 - Waurischk, Tina A1 - Reinsch, Stefan A1 - Contreras, A. A1 - Diegeler, A. A1 - Kilo, M. A1 - Puppe, F. A1 - Limbach, R. A1 - Pan, Z. A1 - Arendt, F. A1 - Chen, Y.-F. A1 - Gogula, S. A1 - Bornhöft, H. T1 - GlasDigital: Data-driven workflow for accelerated glass development N2 - 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. T2 - HVG-DGG Fachausschuss I CY - Jena, Germany DA - 03.11.2023 KW - Glass KW - Robotic melting KW - Ontologie KW - Simulation KW - Workflow KW - Data Space PY - 2023 AN - OPUS4-60383 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -