AI for AM: machine learning approach to design the base binder formulation for vat-photopolymerisation 3D printing of zirconia ceramics

Additive manufacturing of ceramics, specifically through vat-photopolymerization, offers significant potential due to its high precision and ability to produce complex geometries. This study addresses the primary challenge in vat-photopolymerization: developing binder formulations that optimise both...

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Bibliographic Details
Main Authors: Fatih Tarak, Leah Okoruwa, Basar Ozkan, Farzaneh Sameni, Gerald Schaefer, Ehsan Sabet
Format: Default Article
Published: 2025
Subjects:
Design
Automotive engineering
Materials engineering
Mechanical engineering
LCD ceramic 3D printing
Vat-photopolymerization
Binder design
Rheology
Rheology prediction
Machine learning
Online Access:https://hdl.handle.net/2134/28830227.v1
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