Machine Learning in 3D and 4D Printing of Polymer Composites: A Review DOI Open Access
Ivan Malashin, Igor Masich, В С Тынченко

et al.

Polymers, Journal Year: 2024, Volume and Issue: 16(22), P. 3125 - 3125

Published: Nov. 8, 2024

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

Language: Английский

Theoretical and experimental approach with inverse problems for the thermal characterization of parts printed by FDM DOI
José Carlos Camargo, Antônio José da Silva Neto, Diego C. Knupp

et al.

The International Journal of Advanced Manufacturing Technology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 2, 2025

Language: Английский

Citations

0

Comparison of Thermal and Fire Properties of Pla-Based Composites Based on Fdm Printed Graphite / Molybdenum Disulfide and Siloxene DOI
Anna Łapińska, Andrzej Panas, Robert E. Przekop

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0

Spiral kinematics: A biomimetic approach to enhancing demolding efficiency in 3D-printed polymeric formworks for customized hollow concrete structures DOI Creative Commons
Zhong-Rong Lu, Shawn Owyong, Xin Tian

et al.

Materials & Design, Journal Year: 2025, Volume and Issue: unknown, P. 113763 - 113763

Published: Feb. 1, 2025

Language: Английский

Citations

0

The Evolution of Thermoplastic Raw Materials in High-Speed FFF/FDM 3D Printing Era: Challenges and Opportunities DOI Open Access
Antreas Kantaros,

Meropi Katsantoni,

Theodore Ganetsos

et al.

Materials, Journal Year: 2025, Volume and Issue: 18(6), P. 1220 - 1220

Published: March 9, 2025

The evolution of thermoplastic materials has played a critical role in advancing high-speed Fused Filament Fabrication (FFF) and Deposition Modeling (FDM) 3D printing technologies. This study explores the performance challenges associated with next-generation thermoplastics specifically designed for printing, such as PLA, ABS, PETG, comparison to conventional materials. A systematic analysis was conducted evaluate key parameters, including mechanical properties, layer adhesion, surface finish, dimensional accuracy, under varying conditions. results reveal that thermoplastics, when coupled advanced hardware optimized motion control systems, achieve up 70% reduction time without significant trade-offs integrity or precision. Additionally, identifies challenges, increased thermal stresses, warping, need precise cooling strategies, which can impact material at elevated speeds. Opportunities future development are also discussed, design novel polymer formulations innovations further enhance reliability scalability FFF/FDM printing. work underscores potential adopting era highlights interplay between science engineering achieving manufacturing capabilities.

Language: Английский

Citations

0

Highly toughening of PLLA-Based micropart via stretching induced stereocomplex crystal microstructure evolution DOI Creative Commons

Yeping Xie,

Jiayu Tan, S. Fang

et al.

Materials & Design, Journal Year: 2025, Volume and Issue: unknown, P. 113862 - 113862

Published: March 1, 2025

Language: Английский

Citations

0

Machine Learning in 3D and 4D Printing of Polymer Composites: A Review DOI Open Access
Ivan Malashin, Igor Masich, В С Тынченко

et al.

Polymers, Journal Year: 2024, Volume and Issue: 16(22), P. 3125 - 3125

Published: Nov. 8, 2024

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

Language: Английский

Citations

2