Optimization of avocado seed nanoparticle extract (ASNE) as green inhibitor on API X65 steel corrosion using response surface methodology

Abstract

The use of natural products as inhibitors has become increasingly popular due to environmental concerns and the need for sustainable corrosion solutions. In this investigation, response surface methodology (RSM) was utilized to optimize the process variable of ASNE on API X65 steel in 1M HCl acid solution through gravimetric and surface analysis. The influence of concentration, temperature, and exposure time on the inhibition efficiency of avocado seed nanoparticle extract (ASNE) was examined using a central composite design (CCD). The optimum values obtained for the highest inhibition of 95.7% were a temperature condition of 25 °C, a concentration of 5 g/L, and exposure time of 24 hours. Microstructural examination of the studied samples showed a significant surface difference, confirming the formation of a protective layer on the steel surface. Experimental data was in good agreement with the model hence, the study provides valuable insights into the use of ASNE as an inhibitor for API X65 steel and demonstrates the effectiveness of RSM in optimizing the inhibition process variables.