The influence of GNP on the mechanical and thermomechanical properties of epoxy adhesive: Pearson correlation matrix and heatmap application in data interpretation

Author:

Khalil Nur Zalikha1,Kong Nurziana1,Fricke Holger2

Affiliation:

1. Faculty of Mechanical and Automotive Engineering Technology Universiti Malaysia Pahang Al‐Sultan Abdullah Gambang, Kuantan Pahang Malaysia

2. Department of Adhesive Bonding Technology Fraunhofer Institute for Manufacturing Technology and Advanced Materials (IFAM) Bremen Germany

Abstract

AbstractThis article explores the impact of Graphene Nanoplatelet (GNP) reinforcement on the mechanical and thermomechanical properties of epoxy adhesive. The impact of GNPs on the structural adhesive largely depends on factors like dispersion stability and GNP concentration. Given the complexity of these interactions, it is imperative to obtain indicators for the degree of each interaction. In this study, Pearson correlation matrix and heatmaps analysis were used to analyze the relationship between various variables and the strength of the connection. The addition of GNP at various concentrations to the epoxy adhesive led to a reduction in storage modulus, loss modulus, and glass transition temperature, attributed to the agglomeration of GNP. In bulk specimens, the incorporation of GNP, regardless of its content, has decreased tensile stress up to 70.7% while increasing its fracture elongation up to 396.3%. Within joining specimens with GNP, specimens with 1.5 wt% GNP content showed the highest cohesive fracture mode and largest shear strength. Pearson correlation matrix and heatmaps have demonstrated very good accuracy in reflecting the experimental data. They offer a comprehensive assessment of the relationship between various variables while indicating the degree of influence each variable has on the properties of the adhesive and joining specimens.Highlights GNP effects in adhesive can be accurately analyzed with Pearson correlation matrix & heatmaps. Connections strength for various variables can be shown by Pearson correlation matrix & heatmaps. Pearson correlation matrix & heatmaps assess variable relationships comprehensively.

Funder

Ministry of Higher Education, Malaysia

Publisher

Wiley

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