(V) Effects of Surface Area on the Corrosion Susceptibility of Nitinol

Wednesday, May 18, 2022: 9:00 AM
Carlsbad A&B (Westin Carlsbad Resort)
Ms. Grazziela Sena , U.S. Food and Drug Administration, Silver Spring, MD
Dr. Shiril Sivan , U.S. Food and Drug Administration, Silver Spring, MD
Dr. Jason D Weaver , U.S. Food and Drug Administration, Silver Spring, MD
Dr. Matthew Di Prima , U.S. Food and Drug Administration, Silver Spring, MD
Corrosion resistance testing is an important pre-clinical assessment to help ensure implant durability in the physiological environment. Nitinol is a passive metal alloy that is commonly used in medical device design to leverage its shape memory and psuedoelastic properties. Nitinol implants vary in size which highlights the importance of understanding the influence of surface area on its corrosion susceptibility. In this study, we used ASTM F2129 to evaluate the corrosion susceptibility of amber oxide, mechanically polished and chemically etched nitinol wires with surface areas ranging from 0.05 to 10.0 cm2. Results showed that as the surface area increased, the corrosion resistance decreased. Cyclic potentiodynamic polarization measurements demonstrated that the breakdown potential decreased with increasing surface area, with breakdown potentials plateauing for amber oxide and chemically etched samples with larger surface areas. Additional testing on stents and electropolished wires confirmed this trend. Optical microscope images were taken to analyze the presence of pitting corrosion on the surface of the samples. After analyzing the images of corrosion pits, we used a Poisson distribution model to predict the occurrence of pits. This model was validated to be a good fit for predicting the number of pits for smaller surface areas; however, it had more uncertainty for larger surface areas. Overall, increasing the surface area was found to reduce the corrosion resistance of nitinol samples representative of small devices. This study indicates that there may be a threshold surface area that could predict the corrosion resistance performance of larger devices.