This 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.

中文翻译：

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GNP 对环氧粘合剂机械和热机械性能的影响：皮尔逊相关矩阵和热图在数据解释中的应用

本文探讨了石墨烯纳米片 (GNP) 增强材料对环氧粘合剂机械和热机械性能的影响。 GNP对结构胶的影响很大程度上取决于分散稳定性和GNP浓度等因素。考虑到这些相互作用的复杂性，必须获得每种相互作用程度的指标。本研究利用皮尔逊相关矩阵和热图分析来分析各个变量之间的关系以及连接的强度。在环氧粘合剂中添加不同浓度的 GNP 会导致储能模量、损耗模量和玻璃化转变温度降低，这归因于 GNP 的团聚。在大块样品中，无论其含量如何，GNP 的加入都将拉伸应力降低了 70.7%，同时将断裂伸长率提高了 396.3%。在与 GNP 接合的试件中，GNP 含量为 1.5 wt% 的试件表现出最高的内聚断裂模式和最大的剪切强度。皮尔逊相关矩阵和热图在反映实验数据方面表现出了非常好的准确性。它们对各种变量之间的关系进行全面评估，同时表明每个变量对粘合剂和连接样本性能的影响程度。亮点 可以使用 Pearson 相关矩阵和热图准确分析粘合剂中 GNP 的影响。 各种变量的连接强度可以通过皮尔逊相关矩阵和热图显示。 皮尔逊相关矩阵和热图全面评估变量关系。