Tensile strength and wear resistance of glass-reinforced PA1212 fabricated by selective laser sintering

Wu, Ting; Ren, Yaojia; Liang, Luxin; Wen, Jiebin; Wu, Hong; Tian, Yingtao; Tey, Wei Shian; Zhou, Kun

doi:10.1080/17452759.2022.2150652

Cited by 10 publications

(3 citation statements)

References 47 publications

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“…The PS matrix effectively coats the GF and HGM, ensuring their embedding within the matrix and their strong adhesion to it. Additionally, a small number of GF and HGM are exposed outside the PS matrix, contributing to improved powder bed density by filling pores between PS particles due to their small particle sizes [ 42 ]. Importantly, no phase change occurs between the GF and HGM during sintering, minimizing warping in the final parts.…”

Section: Discussionmentioning

confidence: 99%

Process Study of Selective Laser Sintering of PS/GF/HGM Composites

Liu,

Zhu,

Zhang

et al. 2024

Materials

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To address the issues of insufficient strength and poor precision in polystyrene forming parts during the selective laser sintering process, a ternary composite of polystyrene/glass fiber/hollow glass microbeads was prepared through co-modification by incorporating glass fiber and hollow glass microbeads into polystyrene using a mechanical mixing method. The bending strength and dimensional accuracy of the sintered composites were investigated by conducting an orthogonal test and analysis of variance to study the effects of laser power, scanning speed, scanning spacing, and delamination thickness. The process parameters were optimized and selected to determine the optimal combination. The results demonstrated that when considering bending strength and Z-dimensional accuracy as evaluation criteria for terpolymer sintered parts, the optimum process parameters are as follows: laser power of 24 W, scanning speed of 1600 mm/s, scanning spacing of 0.24 mm, and delamination thickness of 0.22 mm. Under these optimal process parameters, the bending strength of sintered parts reaches 6.12 MPa with a relative error in the Z-dimension of only 0.87%. The bending strength of pure polystyrene sintered parts is enhanced by 15.69% under the same conditions, while the relative error in the Z-dimension is reduced by 63.45%. It improves the forming strength and precision of polystyrene in the selective laser sintering process and achieves the effect of enhancement and modification, which provides a reference and a new direction for exploring polystyrene-based high-performance composites and expands the application scope of selective laser sintering technology.

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Section: Discussionmentioning

confidence: 99%

Process Study of Selective Laser Sintering of PS/GF/HGM Composites

Liu,

Zhu,

Zhang

et al. 2024

Materials

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“…The stiffness and hardness in the aligned direction were increased by 29% and 23% compared with the vertical direction, respectively. It also demonstrated that MF-DLP 4D printing technique could significantly improve the wear resistance and magnetic stimuli-response behavior of magnetic composites in the aligned direction, [18] showing effective enhancement of functionality through manipulation of the magnetic particles during 4D printing. Some challenges remain on the MF-DLP fabricated smart materials by remote control of the actuators using electrical and magnetic fields simultaneously or sequentially.…”

Section: Introductionmentioning

confidence: 94%

Electrically/Magnetically Dual‐Driven Shape Memory Composites Fabricated by Multi‐Material Magnetic Field‐Assisted 4D Printing

Wu,

Yu,

Chen

et al. 2024

Adv Funct Materials

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Shape memory polymers (SMPs) are smart materials that enable to transform back to their original shape from the deformed state when subjected to external stimuli. They have shown great potential used as sensors and actuators in diverse applications. However, current research on SMPs primarily focuses on the utilization of a single source of stimuli (e.g., electricity, magnetism, light, etc.), which heavily restricts their potential in complex circumstances. In this study, a novel approach is developed to fabricate multi‐layer electrically/magnetically dual‐driven shape memory composites (ML‐EMSMCs) based on a magnetic field‐assisted digital light processing (MF‐DLP) 4D printing technique. The fabricated ML‐EMSMCs contain alternating high electric conductive layers (up to 5.37 × 10−3 S cm−1) and magnetic responsive layers (10.7 emu g−1), enabling Joule heat‐based and high‐frequency magnetic field induction‐based stimuli. Furthermore, the ML‐EMSMCs exhibited excellent shape memory behavior, good formability, and magnetic properties. The developed 4D printing techniques allows for the alignment of magnetic particles with a unidirectional magnetic field, significantly improving their shape recovery speed. The developed electrically/magnetically dual‐driven and photocurable SMP composites shed light on the development of actuators and sensors with multiple functionalities.

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“…Additive manufacturing is a generic term that brings together various methods [2], such as fusion deposition modeling (FDM) using plastic filaments [3,4], stereolithography (STL) with a photopolymer liquid [5,6], selective laser synthesis of plastic or metal powders [7,8], and the manufacture of objects laminated by plastic lamination [9]. These techniques enable the creation of three-dimensional objects with a variety of materials and offer advantages such as precision, design flexibility, and prototyping speed, thereby revolutionizing industrial manufacturing processes.…”

Section: Introductionmentioning

confidence: 99%

Experimental study of the effect of different 3D printing parameters on tensile strength, using artificial neural network

Hamouti,

El Farissi,

Laouardi

2024

Mater. Res. Express

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Numerous research studies have been conducted to optimize printing parameters using the fused deposition modeling technique (FDM) to improve mechanical properties. The large number of process parameters creates a need to search for optimal combinations of parameters to improve mechanical properties. This study examines the effects of three parameters when printing 3D with melted filament of a PLA material (Polylactic Acid) on the ultimate tensile strength of the printed parts. This search combines an experimental study of the most influential printing parameters on the tensile strength property, namely layer thickness, printing temperature, and feed rate. The experimental results are then analyzed and modeled as a linear regression model. Then develop an intelligent artificial model based on ANN (Artificial Neural Network) derived from these experimental results capable of predicting the optimal combination of parameters providing maximum tensile strength. The observed results showed that the feed rate dominates among the other variables, followed by the thickness of the layer. Also, at the level of prediction, the artificial model provides a better prediction of the tensile strength with a value of 36.1625 MPa by combining the following parameters: Feed rate: 70 mm/s, temperature: 200 °C, and layer thickness: 0.26 mm, compared to the prediction obtained by the linear regression model. Neural networks enable more accurate optimization of 3D process parameters, leading to an overall improvement in the quality of finished products. predictive models, significantly reducing the iteration time required to obtain optimal parameters. The quality of the data used to train neural networks is crucial.

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Tensile strength and wear resistance of glass-reinforced PA1212 fabricated by selective laser sintering

Cited by 10 publications

References 47 publications

Process Study of Selective Laser Sintering of PS/GF/HGM Composites

Process Study of Selective Laser Sintering of PS/GF/HGM Composites

Electrically/Magnetically Dual‐Driven Shape Memory Composites Fabricated by Multi‐Material Magnetic Field‐Assisted 4D Printing

Experimental study of the effect of different 3D printing parameters on tensile strength, using artificial neural network

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