Accurately Predicting Multiple Performance of 3D Printing Photopolymers Using Ensemble Learning-Reference-Cited by-同舟云学术

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Accurately Predicting Multiple Performance of 3D Printing Photopolymers Using Ensemble Learning

Published:2024-04-09 Issue:8 Volume:6 Page:4501-4508
ISSN:2637-6105
Container-title:ACS Applied Polymer Materials
language:en
Short-container-title:ACS Appl. Polym. Mater.

Author:

Gao Wenjie¹,Wang Honglei¹,Xu Yuanhang¹,Yang Yaping¹,Gu Quanchao¹,Duan Xiaojun²,Wang Binglin²,Zhou Xingui¹^ORCID

Affiliation:

1. Science and Technology on Advanced Ceramic Fibers and Composites Laboratory, College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China

2. College of Science, National University of Defense Technology, Changsha 410073, China

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acsapm.3c03102

Reference37 articles.

1. Additive manufacturing of silica aerogels

2. Additive manufacturing: scientific and technological challenges, market uptake and opportunities

3. Material-structure-performance integrated laser-metal additive manufacturing

4. Volumetric additive manufacturing of silica glass with microscale computed axial lithography

5. Recent Advances on High‐Performance Polyaryletherketone Materials for Additive Manufacturing

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