TY - CONF A1 - Waurischk, Tina T1 - Vacuum crack growth in silicate glasses N2 - Although the slow crack growth in glass is dominated by stress-corrosion phenomena, it also should reflect the underlaying intrinsic fracture behavior controlled by glass chemistry and structure. To investigate such underlaying phenomena, crack growth velocity in alkali silicate glasses was measured in vacuum across 10 orders of magnitude with double cantilever beam technique. Measured and literature crack growth data were compared with calculated intrinsic fracture toughness data obtained from Young’s moduli and theoretical fracture surface energy. Data analysis reveals slight correlation with the packing density and significant deviations from the intrinsic brittle fracture behavior. These deviations do not follow simple compositional trends. Two opposing processes may explain this finding: a decrease in the apparent fracture surface energy due to stress-induced chemical changes at the crack tip and its increase due to energy dissipation during fracture. T2 - 26th International Congress on Glass CY - Berlin, Germany DA - 03.07.2022 KW - Oxide glass KW - Fracture toughness KW - Fracture surface PY - 2022 AN - OPUS4-56485 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Waurischk, Tina T1 - Digital infrastructure 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. 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. This includes software tools for data mining as well as property and process modelling. The presentation provides an overview of how all these tools merge into a digital infrastructure and illustrates their usability using examples. All infrastructural parts were developed by a consortium consisting of 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) as part of a joint project of the German research initiative MaterialDigital. T2 - 97. Glass-Technology Conference CY - Aachen, Germany DA - 27.05.2024 KW - Glass KW - Robotic melting KW - Ontologie KW - Simulation KW - Workflow KW - Data Space KW - Digital Twin PY - 2024 AN - OPUS4-60387 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -