Effect of temperature and relative humidity on hydrolytic degradation of additively manufactured PLA: Characterization and artificial neural network modeling

Understanding the long-term durability of 3D-printed polymeric materials under varying temperature and humidity conditions is essential for expanding their industrial applications. Therefore, it is critical to assess the impact of degradation on mechanical properties such as tensile strength. In this study, we manufactured specimens with dual orientations by additive manufacturing-based 3D printing and subjected them to accelerated degradation under various temperature and humidity conditions to evaluate their durability in degradation environments. Mechanical properties significantly decreased under the most severe conditions, with a maximum reduction of 76.7 % observed in molecular weight. The deconvolution of the molecular weight distribution and its correlation with mechanical properties were thoroughly investigated. We derived an equation representing the relationship between the peaks obtained from deconvoluting the molecular weight distribution and the tensile strength. Furthermore, to expedite and simplify tensile strength assessment, we trained an artificial neural network (ANN) model using tensile test results to construct a predictive model. The ANN utilized temperature, humidity, printing angle, and time as input data, with tensile strength as the output. Validation of this model demonstrated the capability to predict tensile strength accurately under different temperature and humidity conditions.