Prediction of tensile performance for 3D printed photopolymer gyroid lattices using structural porosity, base material properties, and machine learning

• Published in: Materials & design Vol. 232; p. 112126
• Main Authors: Peloquin, Jacob, Kirillova, Alina, Rudin, Cynthia, Brinson, L.C., Gall, Ken
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2023; Elsevier
• Subjects: Additive manufacturing; Diverse materials; Lattice structures; Machine learning; Mechanical performance; Diverse materials; Lattice structures; Additive manufacturing; Mechanical performance; Machine learning

[Display omitted] •The ability of a simple machine learning model to predict mechanical properties of 3D printed lattices is demonstrated.•The effect of printing defects on photopolymer lattice sample mechanical and geometric properties is highlighted.•A framework is presented for including both str...