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Optimization of Tensile Strength of Poly(Lactic Acid)/Graphene Nanocomposites Using Response Surface Methodology

Buong Woei Chieng, Nor Azowa Ibrahim, Wan Md Zin Wan Yunus

Open publisher page 77 citations

Abstract

Response surface methodology (RSM) coupled with central composite design (CCD) was employed to optimize the tensile strength of poly(lactic acid) (PLA)/graphene nanocomposites. The interaction between four variables was studied and modeled. The statistical analysis of the results showed that graphene loading and temperature had a significant effect on tensile strength. Quadratic model was obtained and developed to correlate the process parameter to the tensile strength. The optimum combination predicted via RSM was confirmed through experiment and in good agreement with experimental values. The model was able to accurately predict the response of tensile strength with less than 2% error.

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What this paper is about

Response surface methodology (RSM) coupled with central composite design (CCD) was employed to optimize the tensile strength of poly(lactic acid) (PLA)/graphene nanocomposites. The interaction between four variables was studied and modeled. The statistical analysis of the results showed that graphene loading and temperature had a significant effect on tensile strength. Quadratic model was obtained and developed to correlate the process parameter to the tensile strength. The optimum combination predicted via RSM was confirmed through experiment and in good agreement with experimental values. The model was able to accurately predict the response of tensile strength with less than 2% error.

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OpenAlex reports 77 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Response surface methodology (RSM) coupled with central composite design (CCD) was employed to optimize the tensile strength of poly(lactic acid) (PLA)/graphene nanocomposites. The interaction between four variables was studied and modeled. The statistical analysis of the results showed that graphene loading and temperature had a significant effect on tensile strength. Quadratic model was obtained and developed to correlate the process parameter to the tensile strength. The optimum combination predicted via RSM was confirmed through experiment and in good agreement with experimental values. The model was able to accurately predict the response of tensile strength with less than 2% error.

Key concepts: Response surface methodology, Ultimate tensile strength, Central composite design, Materials science, Lactic acid, Composite material, Composite number, Nanocomposite

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