📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Enhancing the 3D printing fidelity of vat photopolymerization with machine learning-driven boundary prediction (2024)

First Author: Ma Y

Attributed to: Dialling up performance for on demand manufacturing funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1016/j.matdes.2024.112978

Publication URI: http://dx.doi.org/10.1016/j.matdes.2024.112978

Type: Journal Article/Review

Parent Publication: Materials & Design