Ontology‐Based Digital Infrastructure for Data‐Driven Glass Development

The development of new glasses is often hampered by inefficient trial‐and‐error approaches. The traditional glass manufacturing process is not only time‐consuming, but also difficult to reproduce with inevitable variations in process parameters. These challenges are addressed by implementing an ontology‐based digital infrastructure coupled with a robotic melting system. This system facilitates high‐throughput glass synthesis and ensures the collection of consistent process data. In addition, the digital infrastructure includes machine learning models for predicting glass properties and a tool for extracting patent information. Current glass databases have significant gaps in the relationships between compositions, process parameters, and properties due to inconsistent studies and nonconforming units. In addition, process parameters are often omitted, and even original literature references provide limited information. By continuously expanding the database with consistent, high‐quality data, it is aimed to fill these gaps and accelerate the glass development process.

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch

Erschienen in
Ontology‐Based Digital Infrastructure for Data‐Driven Glass Development ; day:06 ; month:02 ; year:2025 ; extent:12
Advanced engineering materials ; (06.02.2025) (gesamt 12)

Urheber
Chen, Ya-Fan
Arendt, Felix
Bornhöft, Hansjörg
Camargo, Andrea S.S. de
Deubener, Joachim
Diegeler, Andreas
Gogula, Shravya
Contreras Jaimes, Altair T.
Kempf, Sebastian
Kilo, Martin
Limbach, René
Müller, Ralf
Niebergall, Rick
Pan, Zhiwen
Puppe, Frank
Reinsch, Stefan
Schottner, Gerhard
Stier, Simon
Waurischk, Tina
Wondraczek, Lothar
Sierka, Marek

DOI
10.1002/adem.202401560
URN
urn:nbn:de:101:1-2502071304381.990726781122
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
15.08.2025, 07:23 MESZ

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