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Öğe Cyclotriphosphazene based dendrimeric epoxy resin as an anti-corrosive material for copper in 3% NaCl: Experimental and computational demonstrations(Elsevier, 2020) Dagdag, O.; El Harfi, A.; Safi, Zaki; Guo, Lei; Kaya, Savas; Verma, Chandrabhan; Ebenso, E. E.Present study deals with the synthesis, characterization and corrosion inhibition effect of a hexafunctional cyclotriphosphazene derivative, namely 2,2,4,4,6,6-hexakis(oxiran-2-ylmethoxy)-1,3,5,2 delta, 4 delta,6 delta-triazatriphosphinine(HPGCP)for copper in 3 wt% NaCl medium. The synthesized HPGCP was characterized using numerous spectral techniques such as H-1, C-13, P-31 NMR (Nuclear magnetic resonance) and Fouriertransform infrared spectroscopy (FT-IR) methods. Anti-corrosive effect of the HPGCP was measured using electrochemical and computational methods. Results showed that HPGCP exhibited highest protection efficiency of 95% at as low as 10(-3) M concentration. Polarization studies showed that HPGCP acted as mixed type inhibitor and its adsorption obeyed the Langmuir adsorption isotherm model. Density Functional Theory (DFT) based computational studies demonstrate that HPGCP interacts with copper surface using donor-acceptor interactions inwhich three nitrogen atoms and six p-electrons of the cyclotriphosphazene ring play significant role in metalinhibitor interactions. Molecular dynamic (MD) simulations study demonstrated that HPGCP spontaneously interacts withmetallic surface using its electron rich centers and acquires the planar orientation. Experimental results were well corroborated with the computational results. (C) 2020 Elsevier B.V. All rights reserved.Öğe Development of QSAR-based (MLR/ANN) predictive models for effective design of pyridazine corrosion inhibitors(Elsevier, 2022) Quadri, Taiwo W.; Olasunkanmi, Lukman O.; Akpan, Ekemini D.; Fayemi, Omolola E.; Lee, Han-Seung; Lgaz, Hassane; Verma, ChandrabhanTwenty pyridazine derivatives with previously reported experimental data were utilized to develop predictive models for the anticorrosion abilities of pyridazine-based compounds. The models were developed by using quantitative structure-activity relationship (QSAR) as a tool to relate essential molecular descriptors of the pyridazines with their experimental inhibition efficiencies. Chemical descriptors associated with frontier molecular orbitals (FMOs) were obtained using density functional theory (DFT) calculations, while others were obtained from additional calculations effected on Dragon 7 software. Five descriptors together with concentrations of the pyridazine inhibitors were used to develop the multiple linear regression (MLR) and artificial neural network (ANN) models. The optimal ANN model yielded the best results with 111.5910, 10.5637 and 10.2362 for MSE, RMSE and MAPE respectively. The results revealed that ANN gave better results than MLR model. The proposed models suggested that the adsorption of pyridazine derivatives is dependent on the five descriptors.Five pyridazine compounds were theoretically designed.Öğe Epoxy prepolymer as a novel anti-corrosive material for carbon steel in acidic solution: Electrochemical, surface and computational studies(Elsevier, 2020) Dagdag, O.; Safi, Zaki; Erramli, H.; Wazzan, Nuha; Guo, Lei; Verma, Chandrabhan; Ebenso, E. E.Atetra-functional aromatic epoxy prepolymer namely, 4, 4'-(ethane-1, 2-diyl) bis (N, N-bis (oxiran-2-ylmethyl) aniline) (AA1) was synthesized as evaluated corrosion inhibitor for carbon steel. TheAA1 was characterized using H-1 NMR and FT-IR methods. The anti-corrosive property of AA1 for carbon steel corrosion in 1M HCl solution was evaluated using several experimental and computational techniques. The AA1 showed highest efficiency of 96.5 % at 10(-3)M concentration. PDP study suggested that AA1 behaves slight anodic predominance and its adsorption of the AA1 obeyed the Langmuir adsorption isotherm model. DFT study conducted in neutral as well as protonated forms suggested that AA1 acts as efficient anti-corrosive material under both the conditions and its adsorption mainly takes place through polar heteroatoms (N and O) and two aromatic rings as HOMO and LUMO are mainly localized over the center part of the AA1 molecule. MDS suggested that AA1 adsorbs using its flat orientation and its adsorption decreases with rise in temperature. Adsorption energies were in negative indicating that AA1 adsorption occurs spontaneously as all studied temperatures.Öğe Insights into corrosion inhibition mechanism of mild steel in 1 M HCl solution by quinoxaline derivatives: electrochemical, SEM/EDAX, UV-visible, FT-IR and theoretical approaches(Elsevier, 2021) Ouakki, M.; Galai, M.; Benzekri, Z.; Verma, Chandrabhan; Ech-chihbi, E.; Kaya, S.; Boukhris, S.Three quinoxaline-based heterocycles namely, 6-methyl-2,3-diphenyl-quinoxaline (Q-CH3), 6-nitro-2,3-diphenylquinoxaline (Q-NO2) and 2,3-diphenylquinoxaline (Q-H) were evaluated as inhibitor for mild steel (MS) in 1 M HCl. Inhibition effectiveness of the Q-H, Q-CH3 and Q-NO2 tested using different computational simulations and experimental methods. Results showed that inhibition effectiveness of Q-H, Q-CH3 and Q-NO2 increases with their concentration. Polarization results showed that Q-H, Q-CH3 and Q-NO2 displayed anodic-type behaviour. Inhibition efficiencies of Q-H, Q-CH3 and Q-NO2 followed the order: 87.6% (Q-NO2) < 90.2% (Q-CH3)< 92.4% (Q-H) for Q-CH3. Presence of both electron withdrawing (-NO2) and donating (-CH3) substituents decrease the inhibition efficiency as compared to the parent compound however in decrease in protection power is more prominent in the presence of -NO2 substituent. Q-H, Q-CH3 and Q-NO2 inhibit corrosion by adsorbing on MS surface and their adsorption mode followed Langmuir adsorption isotherm. Adsorption of Q-H, Q-CH3 and Q-NO2 on metallic surface reinforced with SEM-EDS and UV-visible studies of MS surfaces. Interaction mechanism of QH, Q-CH3 and Q-NO(2 )with MS surface and their mode of adsorption was studies using DFT and MD (MD) simulations, respectively. Negative sign of adsorption energies (E-ads) for Q-H, Q-CH3 and Q-NO2 suggested that they adsorb spontaneously over MS surface.Öğe Molecular modelling of compounds used for corrosion inhibition studies: a review(Royal Soc Chemistry, 2021) Ebenso, Eno E.; Verma, Chandrabhan; Olasunkanmi, Lukman O.; Akpan, Ekemini D.; Verma, Dakeshwar Kumar; Lgaz, Hassane; Guo, LeiMolecular modelling of organic compounds using computational software has emerged as a powerful approach for theoretical determination of the corrosion inhibition potential of organic compounds. Some of the common techniques involved in the theoretical studies of corrosion inhibition potential and mechanisms include density functional theory (DFT), molecular dynamics (MD) and Monte Carlo (MC) simulations, and artificial neural network (ANN) and quantitative structure-activity relationship (QSAR) modeling. Using computational modelling, the chemical reactivity and corrosion inhibition activities of organic compounds can be explained. The modelling can be regarded as a time-saving and eco-friendly approach for screening organic compounds for corrosion inhibition potential before their wet laboratory synthesis would be carried out. Another advantage of computational modelling is that molecular sites responsible for interactions with metallic surfaces (active sites or adsorption sites) and the orientation of organic compounds can be easily predicted. Using different theoretical descriptors/parameters, the inhibition effectiveness and nature of the metal-inhibitor interactions can also be predicted. The present review article is a collection of major advancements in the field of computational modelling for the design and testing of the corrosion inhibition effectiveness of organic corrosion inhibitors.Öğe Multilayer perceptron neural network-based QSAR models for the assessment and prediction of corrosion inhibition performances of ionic liquids(Elsevier, 2022) Quadri, Taiwo W.; Olasunkanmi, Lukman O.; Fayemi, Omolola E.; Akpan, Ekemini D.; Lee, Han Seung; Lgaz, Hassane; Verma, ChandrabhanThe present study reports the quantum chemical studies and quantitative structure activity relationship (QSAR) modeling of thirty ionic liquids utilized as chemical additives to repress mild steel degradation in 1.0 M HCl. Five molecular descriptors obtained from standardization of calculated descriptors together with the inhibitor con-centration were employed in model building. Multiple linear regression (MLR) and multilayer perceptron neural network (MLPNN) modeling were utilized in model construction. The optimal MLPNN model was developed using a network architecture of 6-3-5-1 with Levenberg-Marquardt as the learning algorithm. The model yielded an MSE of 29.9242, RMSE of 5.4703, MAD of 4.9628, MAPE of 5.7809, rMBE of 0.1202 and CoV of 0.0052. The MLPNN model displayed better predictive performance than the MLR model. Furthermore, developed models were applied to forecast the inhibition efficiencies of five novel ionic liquids. The theoretical inhibitors were found to be effective inhibitors of steel corrosion, showing over 80% inhibition efficiency.
