Printing depth modeling, printing process quantification and quick-decision of printing parameters in micro-vat polymerization

Yue Wang; Yancheng Wang; Chenhao Mao; Deqing Mei

Materials & Design (Mar 2023)

Printing depth modeling, printing process quantification and quick-decision of printing parameters in micro-vat polymerization

Yue Wang,
Yancheng Wang,
Chenhao Mao,
Deqing Mei

Affiliations

Yue Wang: State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China; Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China; School of Future Technology, Shanghai University, Shanghai, 200444, China; Institute of Artificial Intelligence, Shanghai University, Shanghai, 200444, China
Yancheng Wang: State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China; Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China; Corresponding author at: 3-309 Kaiwu Complex Building, 866 Yuhangtang Road, Hangzhou 310027, China.
Chenhao Mao: Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
Deqing Mei: State Key Laboratory of Fluid Power and Mechatronic Systems, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China; Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China

Journal volume & issue: Vol. 227
p. 111698

Abstract

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Vat photopolymerization is a widely employed additive manufacturing (AM) technique that commonly applying a digital light processing (DLP) light engine to provide a patterned light source. Notably, printing extreme-size structures is challenging, and the selection of printing parameters was currently highly reliant on repeatable trial-and-error experiments. In this work, a theoretical model for curing depth prediction was established by observing the effect of light intensity. A correction factor n was introduced to optimize the relationship among the critical curing energy, exposure time, and light intensity. Forming experiments verified the accuracy of the proposed theoretical curing depth prediction model, and a correction factor n equal to 0.75 was obtained. Optical rheological characterization experiments and Fourier transform infrared spectroscopy (FTIR) supported the quantitative characterization of the DLP printing process while revealing a stepwise transition during photocuring. Finally, a guidance for quick selection of the optimal curing time for 3D structure was obtained and applied to the high-precision microstructure printing process. High-fidelity microneedle arrays with 12 μm details were printed. This method of rapid selection of printing parameters and printing microstructures with high-precision details can potentially be used in the field of 3D bioprinting.

Published in Materials & Design

ISSN: 0264-1275 (Print); 1873-4197 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials
Website: https://www.journals.elsevier.com/materials-and-design

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