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New Horizons in Glass Structure Prediction and Mechanics

Project description

A novel computational framework will support rational design of high-performance oxide glasses

Oxide glasses are a broad family of glasses with widespread and growing applications, from window and container glass to liquid crystal displays and telecommunications’ optical fibres. Despite their widespread use, brittleness remains a challenge. Moreover, basic understanding of their properties and behaviours is rather limited, impeding rational design and leading to time-intensive and inefficient trial-and-error methods. The EU-funded NewGLASS project will develop computational approaches addressing the behaviours of these inherently disordered compounds and their non-equilibrium nature at all scales, fostering future scientific breakthroughs in the design of new glasses with unprecedented performance.

Objective

Oxide glasses are one of the most important material families owing to their unique features, such as transparency, tunable properties, and formability. Emerging solutions to major global challenges related to energy, health, and electronics require new scientific breakthroughs in glass chemistry, mechanics, and processing. The realization of these goals is severely restricted by the main drawback of glass, namely high brittleness. Furthermore, new glass compositions are today developed through time-consuming trial-and-error experimentation due to their inherent non-equilibrium nature and disordered structure.

A major task is therefore to initiate a paradigm shift within the field of glass science and technology, going from empirical to model-based approaches for the design of new glass compositions and microstructures with improved fracture resistance. This requires the development of computational approaches, from ab initio calculations to artificial intelligence, to integrate structural descriptors and glass chemistry with advanced processing and mechanical properties into holistic tools.

NewGLASS challenges the current glass design strategies in order to create such tools. For this purpose, an interdisciplinary approach is proposed, in which structural descriptors at the short- and medium-range length scales are first identified and quantified based on emergent statistical mechanics and persistent homology techniques. Guided by these results, high-throughput simulations at various length scales are combined with machine learning algorithms to design novel glass compositions, tailored deformation mechanisms, and 3D-printed microstructures to achieve superior fracture resistance. By having experiments and modelling complement and advance each other reciprocally, NewGLASS will find order in disorder and provide the scientific breakthroughs for the accelerated design of glasses with outstanding mechanical performance, thus opening up for many new applications.

Host institution

AALBORG UNIVERSITET
Net EU contribution
€ 1 996 935,00
Address
FREDRIK BAJERS VEJ 7K
9220 Aalborg
Denmark

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Region
Danmark Nordjylland Nordjylland
Activity type
Higher or Secondary Education Establishments
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Total cost
€ 1 996 935,00

Beneficiaries (1)