TY - JOUR

T1 - Tailoring interfacial properties of 3D-printed continuous natural fiber reinforced polypropylene composites through parameter optimization using machine learning methods

AU - Cai, R.

AU - Wen, W.

AU - Wang, K.

AU - Peng, Y.

AU - Ahzi, S.

AU - Chinesta, F.

N1 - This is the author’s version of a work that was accepted for publication in MATERIALS TODAY COMMUNICATIONS. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in MATERIALS TODAY COMMUNICATIONS, 32, 2022 DOI: 10.1016/j.mtcomm.2022.103985

PY - 2022/8/31

Y1 - 2022/8/31

N2 - 3D-printed continuous ramie fiber reinforced polypropylene composites (CRFRPP) are expected to ensure good mechanical properties while meeting the requirements of environmental friendliness and sustainability. To promote the wide industrial application of CRFRPP, this work investigated the effects of printing parameters (extrusion flow rate, printing temperature, layer thickness and printing speed) on the interfacial properties of CRFRPP. The interlayer and intralayer interfacial properties of CRFRPP with different printing parameters were studied using the design of experiment approach. Machine learning methods and response surface methodology prediction were also carried out based on the experimental results to bridge the printing parameters and interfacial properties. According to the prediction results, the printing parameters were optimized to improve the production efficiency while ensuring the desired interfacial performance. At last, the bending tests were conducted to investigate how the difference in interfacial properties can be translated to the mechanical performance. The results found that printed specimens with weak interfacial strength suffered interlaminar delamination failure when subjected to bending loads, greatly weakening the mechanical properties of the composites.

AB - 3D-printed continuous ramie fiber reinforced polypropylene composites (CRFRPP) are expected to ensure good mechanical properties while meeting the requirements of environmental friendliness and sustainability. To promote the wide industrial application of CRFRPP, this work investigated the effects of printing parameters (extrusion flow rate, printing temperature, layer thickness and printing speed) on the interfacial properties of CRFRPP. The interlayer and intralayer interfacial properties of CRFRPP with different printing parameters were studied using the design of experiment approach. Machine learning methods and response surface methodology prediction were also carried out based on the experimental results to bridge the printing parameters and interfacial properties. According to the prediction results, the printing parameters were optimized to improve the production efficiency while ensuring the desired interfacial performance. At last, the bending tests were conducted to investigate how the difference in interfacial properties can be translated to the mechanical performance. The results found that printed specimens with weak interfacial strength suffered interlaminar delamination failure when subjected to bending loads, greatly weakening the mechanical properties of the composites.

KW - Additive manufacturing

KW - Interfacial properties

KW - Continuous natural fiber

KW - Machine learning

KW - Polypropylene-based composites

U2 - 10.1016/j.mtcomm.2022.103985

DO - 10.1016/j.mtcomm.2022.103985

M3 - Journal article

VL - 32

JO - MATERIALS TODAY COMMUNICATIONS

JF - MATERIALS TODAY COMMUNICATIONS

SN - 2352-4928

M1 - 103985

ER -