Dft Computational Study of Organic Inhibitors on the Surface of Iron

General Background: Corrosion poses a significant global challenge, causing severe economic and structural damage, with approximately 25% of metals produced annually lost due to ongoing degradation. Specific Background: Among various mitigation strategies, organic inhibitors are promising for their efficiency and potential environmental compatibility. Knowledge Gap: Despite experimental evidence of indoline-2,3-dione derivatives as effective inhibitors, detailed quantum-level insights into their inhibition mechanisms remain limited. Aims: This study employs density functional theory (DFT) to evaluate the electronic and chemical interaction parameters of these derivatives and compare predicted performances with experimental data. Results: Calculations using Gaussian09 (B3LYP/6-31++G(d,p)) and G311-6/LYP3B basis sets revealed that 5-chloro-1-(2-(N,N-dimethylamino)ethyl)indoline-2,3-dione exhibits superior inhibition efficiency, characterized by a low energy gap (3.314 eV), high inhibitor–metal interaction energy (ΔΨ), enhanced ductility, and favorable EB-D exchange energy. Mulliken charge distribution and electrostatic potential maps confirmed strong nucleophilic and electrophilic sites, supporting a chemisorption-driven mechanism. Novelty: This is the first comprehensive DFT-based analysis linking multiple electronic properties to experimental inhibition data for indoline derivatives. Implications: The findings provide predictive guidelines for designing targeted, environmentally friendly corrosion inhibitors for acidic industrial environments, particularly in hydrochloric acid and hydrogen sulfate processing. Highlights: Demonstrates superior inhibition efficiency of specific indoline derivative. Links quantum parameters directly to experimental performance. Supports eco-friendly corrosion inhibitor design for acidic environments. Keywords: Corrosion Inhibition, Density Functional Theory, Indoline Derivatives, Quantum Parameters, Chemisorption