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Optimization of 3D Printing Parameters of High Viscosity PEEK/30GF Composites.
Stepanov, Dmitry Yu; Dontsov, Yuri V; Panin, Sergey V; Buslovich, Dmitry G; Alexenko, Vladislav O; Bochkareva, Svetlana A; Batranin, Andrey V; Kosmachev, Pavel V.
Afiliação
  • Stepanov DY; Microelectronics of Multispectral Quantum Introscopy Laboratory of the R&D Center "Advanced Electronic Technologies", National Research Tomsk State University, 634050 Tomsk, Russia.
  • Dontsov YV; Department of Materials Science, Engineering School of Advanced Manufacturing Technologies, National Research Tomsk Polytechnic University, 634050 Tomsk, Russia.
  • Panin SV; Department of Materials Science, Engineering School of Advanced Manufacturing Technologies, National Research Tomsk Polytechnic University, 634050 Tomsk, Russia.
  • Buslovich DG; Laboratory of Mechanics of Polymer Composite Materials, Institute of Strength Physics and Materials Science of Siberian Branch of Russian Academy of Sciences, 634055 Tomsk, Russia.
  • Alexenko VO; Laboratory of Nanobioengineering, Institute of Strength Physics and Materials Science of Siberian Branch of Russian Academy of Sciences, 634055 Tomsk, Russia.
  • Bochkareva SA; Laboratory of Mechanics of Polymer Composite Materials, Institute of Strength Physics and Materials Science of Siberian Branch of Russian Academy of Sciences, 634055 Tomsk, Russia.
  • Batranin AV; Laboratory of Mechanics of Polymer Composite Materials, Institute of Strength Physics and Materials Science of Siberian Branch of Russian Academy of Sciences, 634055 Tomsk, Russia.
  • Kosmachev PV; Engineering School of Non Destructive Testing, National Research Tomsk Polytechnic University, 634050 Tomsk, Russia.
Polymers (Basel) ; 16(18)2024 Sep 14.
Article em En | MEDLINE | ID: mdl-39339072
ABSTRACT
The aim of this study was to optimize a set of technological parameters (travel speed, extruder temperature, and extrusion rate) for 3D printing with a PEEK-based composite reinforced with 30 wt.% glass fibers (GFs). For this purpose, both Taguchi and finite element methods (FEM) were utilized. The artificial neural networks (ANNs) were implemented for computer simulation of full-scale experiments. Computed tomography of the additively manufactured (AM) samples showed that the optimal 3D printing parameters were the extruder temperature of 460 °C, the travel speed of 20 mm/min, and the extrusion rate of 4 rpm (the microextruder screw rotation speed). These values correlated well with those obtained by computer simulation using the ANNs. In such cases, the homogeneous micro- and macro-structures were formed with minimal sample distortions and porosity levels within 10 vol.% of both structures. The most likely reason for porosity was the expansion of the molten polymer when it had been squeezed out from the microextruder nozzle. It was concluded that the mechanical properties of such samples can be improved both by changing the 3D printing strategy to ensure the preferential orientation of GFs along the building direction and by reducing porosity via post-printing treatment or ultrasonic compaction.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article