Deciphering the anticorrosion performance of Arnica montana extract for mild steel in 1.5 M HCl using experimental and computational insights

The increasing demand for environmentally benign alternatives to conventional corrosion inhibitors has stimulated interest in plant-derived materials. This study explores Arnica montana extract (AME) as a sustainable corrosion inhibitor for mild steel (MS) exposed to 1.5 M HCl, employing an integrated experimental and computational strategy. The novelty of the work lies in coupling a renewable botanical inhibitor with advanced soft-computing and molecular simulation approaches to simultaneously optimise, predict, and explain corrosion inhibition behaviour. The metal corrosion processes were evaluated using parameters such as AME concentration, immersion time and temperature, which were optimised by response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) models. Moreover, the results confirmed a remarkable decrease in both weight loss and corrosion rate as AME concentration increased, in parallel with improvement in inhibition efficiency; this suggests good surface coverage and better interaction of molecules of AME at high concentration. Mathematical assessment of all generated models demonstrated ANFIS being the best predictor with high predictive accuracy (R 2 = 0.9803), with values of AARE, RMSE and SD being 0.0108, 0.0024 and 0.0019, respectively, compared to others. Electrochemical investigation via potentiodynamic polarisation and electrochemical impedance spectroscopy showed that AME acted as a mixed-type inhibitor. Calculations based on quantum chemical descriptors indicated interaction at the molecular level between MS and AME, and molecular dynamics simulations showed an optimum binding energy of the adsorption configuration, as well as formation of a denser protective film through O, N, and Br group interactions. These indicate that the good predictive capability of the ANFIS model and excellent adsorption ability of phytochemical constituents contribute to the usage of AME as a sustainable corrosion inhibitor for acidising industry applications.