| Abstract Scope |
Epoxy-based, 1K structural adhesives are essential in automotive assembly due to their strong capabilities to bond and stiffen load-bearing frames, bond hard-to-weld substrates, and seal out moisture to decrease corrosion. Structural adhesives contain multiple compositions to achieve the desired performance. Corrosion testing, which depends on substrate selection and corrosion cycle conditions, makes the formulation development complex and time-consuming. Formulation development can be accelerated using machine learning to study what compositions induce corrosion and deteriorate adhesive performance. Thirty formulations were designed, evaluated, and analyzed for lap-shear strength, adhesion failure mode, and corrosion retention after soaking metal substrate & 1K structural adhesive test pieces in 70oC water for 20 days. The results demonstrated that formulations with suitable adhesive and corrosion resistance performance are governed by the onset Tg of the adhesive, the amount of cyano group in the toughener, and the ratio of epoxy to the curing agent (DICY). |