Machine Learning in 3D and 4D Printing of Polymer Composites: A Review

被引：2

作者：

Malashin, Ivan ^{[1
]}

Masich, Igor ^{[1
]}

Tynchenko, Vadim ^{[1
]}

Gantimurov, Andrei ^{[1
]}

Nelyub, Vladimir ^{[1
,2
]}

Borodulin, Aleksei ^{[1
]}

Martysyuk, Dmitry ^{[3
]}

Galinovsky, Andrey ^{[3
]}

机构：

[1] Bauman Moscow State Tech Univ, Artificial Intelligence Technol Sci & Educ Ctr, Moscow 105005, Russia

[2] Far Eastern Fed Univ, Sci Dept, Vladivostok 690922, Russia

[3] Bauman Moscow State Tech Univ, Ctr NTI Digital Mat Sci New Mat & Subst, Moscow 105005, Russia

来源：

POLYMERS | 2024年 / 16卷 / 22期

关键词：

machine learning; polymer composites; 3D printing; 4D printing; design optimization; CERAMIC-MATRIX COMPOSITES; VAT PHOTOPOLYMERIZATION; MECHANICAL-PROPERTIES; EXPANSION; STRENGTH; INDUSTRY; DESIGN; PARTS;

D O I：

10.3390/polym16223125

中图分类号：

O63 [高分子化学（高聚物）];

学科分类号：

070305 ; 080501 ; 081704 ;

摘要：

The emergence of 3D and 4D printing has transformed the field of polymer composites, facilitating the fabrication of complex structures. As these manufacturing techniques continue to progress, the integration of machine learning (ML) is widely utilized to enhance aspects of these processes. This includes optimizing material properties, refining process parameters, predicting performance outcomes, and enabling real-time monitoring. This paper aims to provide an overview of the recent applications of ML in the 3D and 4D printing of polymer composites. By highlighting the intersection of these technologies, this paper seeks to identify existing trends and challenges, and outline future directions.

引用

页数：52

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