Enhancing the 3D printing fidelity of vat photopolymerization with machine learning-driven boundary prediction
(2024)
Journal Article
Ma, Y., Tian, Z., Wang, B., Zhao, Y., Nie, Y., Wildman, R., …He, Y. (2024). Enhancing the 3D printing fidelity of vat photopolymerization with machine learning-driven boundary prediction. Materials and Design, 241, Article 112978. https://doi.org/10.1016/j.matdes.2024.112978
Like many pixel-based additive manufacturing (AM) techniques, digital light processing (DLP) based vat pho-topolymerization faces the challenge that the square pixel based processing strategy can lead to zigzag edges especially when feature sizes com... Read More about Enhancing the 3D printing fidelity of vat photopolymerization with machine learning-driven boundary prediction.