Issue 36, 2022

Experimental investigation and finite element modelling of PMMA/carbon nanotube nanobiocomposites for bone cement applications

Abstract

Multi-walled carbon nanotubes (MWCNTs) are one of the preferred candidates for reinforcing polymeric nanobiocomposites, such as acrylic bone type of cement. In this study, at first, bulk samples of the reinforced polymethylmethacrylate (PMMA) matrix were prepared with 0.1, 0.25, and 0.5 wt per wt% of MWCNTs by the casting method. Tensile and three-point bending tests were performed to determine the essential mechanical properties of bone cement, such as tensile and bending strengths. The tensile fracture surfaces were investigated by scanning electron microscopy (SEM). The commercial software (Abaqus) was used to conduct finite element analysis (FEA) by constructing a representative volume element (RVE) model for numerically computing the tensile and bending parameters of PMMA-MWCNT nanocomposites. Finally, MTT assays were utilized to evaluate the cell viability on the surface of nanobiocomposites. The results show that by increasing the MWCNT amount in the PMMA-based cement, the bending strengths (BS), tensile strength (TS), and elastic modulus (EM) increased considerably. Furthermore, the disparity between the FEA and experimental TS, EM, and BS values was less than 20%. According to MTT viability experiments, adding MWCNTs to PMMA had no influence on PMMA toxicity and resulted in a negative response to interaction with mesenchymal stem cells. The cell density on the nanobiocomposite was more than pristine-PMMA.

Graphical abstract: Experimental investigation and finite element modelling of PMMA/carbon nanotube nanobiocomposites for bone cement applications

Article information

Article type
Paper
Submitted
16 may 2022
Accepted
28 iyl 2022
First published
03 avq 2022

Soft Matter, 2022,18, 6800-6811

Experimental investigation and finite element modelling of PMMA/carbon nanotube nanobiocomposites for bone cement applications

V. Sadati, M. Khakbiz, M. Chagami, R. Bagheri, F. S. Chashmi, B. Akbari, S. Shakibania and K. Lee, Soft Matter, 2022, 18, 6800 DOI: 10.1039/D2SM00637E

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