Fracture Behavior of Additively Manufactured Carbon Fiber Reinforced Acrylonitrile-Styrene-Acrylate Containing Cracks and Notches

Within the context of the increasing use of additive manufacturing techniques and the corresponding need to understand the behavior of 3D-printed materials, this paper analyzes the fracture behavior of additively manufactured carbon fiber reinforced (10 wt.%) acrylonitrile-styrene-acrylate (ASA) with three different raster orientations (90/0, 45/−45, 30/−60). The analyzed material (ASA-CF10) combines the remarkable resistance to weathering agents typical of ASA with the enhanced mechanical properties resulting from the inclusion of carbon fiber reinforcement. The analysis is performed on single-edge-notched bending (SENB) specimens containing different types of defects, from cracks to U-notches with notch radii of 0.5 mm, 1 mm and 2 mm. When compared to non-reinforced ASA, the fracture resistance is noticeably higher (nearly double) for the reinforced material in all raster orientations. The notch effect, defined as the increase in the fracture resistance when the notch radius increases, is analyzed through the Theory of Critical Distances (TCD), and it is mostly higher in the reinforced material than in the pristine polymer. These observations are supported by Scanning Electron Microscopy analyses.

Authors

Institutions

Publication Details

Journal
Journal of Composites Science
Published
2025-04-11
DOI
https://doi.org/10.3390/jcs9040185
Citations
3
Primary Topic
Additive Manufacturing and 3D Printing Technologies
Type
article
Field-Weighted Citation Impact
2.05
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fracture Behavior of Additively Manufactured Carbon Fiber Reinforced Acrylonitrile-Styrene-Acrylate Containing Cracks and Notches

Borja Arroyo, Sergio Cicero, Sergio Arrieta, Fulvio Lavecchia et al.
3 citations
Journal of Composites Science
Additive Manufacturing and 3D Printing Technologies
2.05
article

Fracture Behavior of Additively Manufactured Carbon Fiber Reinforced Acrylonitrile-Styrene-Acrylate Containing Cracks and Notches

Borja Arroyo, Sergio Cicero, Sergio Arrieta, Fulvio Lavecchia, Fabrizia Devito
article en
3 citations

Abstract

Within the context of the increasing use of additive manufacturing techniques and the corresponding need to understand the behavior of 3D-printed materials, this paper analyzes the fracture behavior of additively manufactured carbon fiber reinforced (10 wt.%) acrylonitrile-styrene-acrylate (ASA) with three different raster orientations (90/0, 45/−45, 30/−60). The analyzed material (ASA-CF10) combines the remarkable resistance to weathering agents typical of ASA with the enhanced mechanical properties resulting from the inclusion of carbon fiber reinforcement. The analysis is performed on single-edge-notched bending (SENB) specimens containing different types of defects, from cracks to U-notches with notch radii of 0.5 mm, 1 mm and 2 mm. When compared to non-reinforced ASA, the fracture resistance is noticeably higher (nearly double) for the reinforced material in all raster orientations. The notch effect, defined as the increase in the fracture resistance when the notch radius increases, is analyzed through the Theory of Critical Distances (TCD), and it is mostly higher in the reinforced material than in the pristine polymer. These observations are supported by Scanning Electron Microscopy analyses.

Journal of Composites ScienceVol. 9(4)
Universidad de Cantabria (ES), Istituto Universitario di Studi Superiori di Pavia (IT)
Openalex Percentile: Top 14%
Additive Manufacturing and 3D Printing Technologies
2.05
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.