Corrosion Inhibition Studies of 8-Hydroxyquinoline Derivatives for N80 Steel in a 1.0 M HCl Solution: Experimental, Computational Chemistry, and Quantitative Structure-Activity Relationship Studies

Optimization of acid modifier and its effect on the wettability of anthracite coal

This research aimed to investigate the influence of free radicals on the wettability of Guizhou anthracite coal. The best acid modifier was selected through quantum chemistry and sedimentation experiments. Infrared spectroscopy (FTIR), paramagnetic resonance spectroscopy (EPR), and wetting heat experiments were carried out to investigate the effect of acid modifiers on the wetting properties of coal. The results of the study show that, among the three modifiers tested (APG, AEO3, and NP-10), alkyl glycoside (APG) exhibited the best wetting performance and strongest reactivity with the coal molecules. The best wetting effect was achieved with 1% APG + 6% HF. The acid modifier increased the concentration of hydrophilic functional groups and free radicals. Under the action of the acid modifier, the hydrophobic functional groups in the coal samples break off to form active sites (free radicals) and then continue to be converted into hydrophilic functional groups, which in turn improves the wettability of the coal samples. The measured wetting heat of the post-modified experimental coal sample increased by 14.86%, which proved that the acid modifier could improve the wettability of the coal. This study provides theoretical insights into the quantum chemical optimization of modifiers, gas disaster prevention, and dust management of anthracite coal.

Computational Analyses of Peganum harmala Alkaloids as Green Corrosion Inhibitors on Fe(110)

One of the successful techniques developed for the inhibition of metal corrosion is the utilization of phytochemicals from plant extracts as corrosion inhibitors. Theoretical studies are utilized to predict how organic components behave on metal surfaces and can pave the way for the development and synthesis of innovative, efficient corrosion inhibitors. However, atomic-level insights into the inhibition mechanisms of these green components are still needed. In this paper, the interactions of three active components found in aqueous Peganum harmala extract (harmol, vasicinone, and harmalol) with the Fe(110) surface are theoretically investigated using density functional theory (DFT) and atomistic molecular dynamics (MD) simulations. Several analyses and quantities related to adsorption, such as adsorption energy, partial density of states, Bader charge, charge density difference, and electron localization function, are described in detail. Both DFT calculations and MD simulations reveal that these molecules favor a lateral adsorption configuration, with π-back-donation being the dominant mechanism in their adsorption onto the Fe surface. The results indicate that the polycyclic heteroaromatic compounds significantly affect the adsorption of the molecules on the Fe surface. This highlights the fact that the effectiveness of the inhibitors is closely tied to their molecular structure.

Functional Group Effects on the Interfacial Adsorption of Arylquinoline-3-Carbonitriles on Iron: A DFT-D3 Investigation of Surface Interaction Mechanisms

Reliable corrosion inhibition systems are crucial for extending the lifespan of industrial metal structures. Quinolines, with their high adsorption capacity and protective efficiency, are promising next-generation inhibitors. However, the impact of substitutions on their coordination with iron surfaces requires deeper understanding. Herein, we investigate the influence of various functional groups on the adsorption behavior of three 2-amino-4-arylquinoline-3-carbonitriles (AACs) on iron surfaces using first-principles density functional theory calculations. Results reveal that nitrophenyl and hydroxyphenyl significantly enhance the adsorption strength of AACs on the Fe(110) surface, facilitated by donor-acceptor interactions. Neutral molecules were more stable than their protonated counterparts. Key results show strong adsorption energies, with values ranging from -2.005 to -1.809 eV for the AACs, along with significant electron gains across carbon atoms as indicated by Bader charge analysis. These strong interactions result in notable charge redistribution and bond formation, as shown by projected density of states and electron density difference iso-surfaces. Furthermore, electron localization function analysis indicates that van der Waals interactions, influenced by multiple nitrogen atoms, play a crucial role in stabilizing the adsorbed molecules. Stronger adsorption through electron donation and retro-donation mechanisms suggests enhanced corrosion protection efficiency of these substituted quinolines. The conductor-like screening model for real solvents analysis provides complementary insights into the solvation characteristics. Overall, the findings demonstrate the specific role functional groups play in the coordination of arylquinoline-3-carbonitriles with iron surfaces.

Experimental and Theoretical Studies on Long Alkyl Chain-Bearing Dibenzotriazole Ionic Liquids as Eco-friendly Corrosion Inhibitors in Aqueous Hydrochloride Acid

Three long alkyl chain-bearing dibenzotriazole ionic liquids (BTA-R-BTA, R = 8, 12, and 16) were synthesized with high yield (>98%) through a simple and eco-friendly process. Their anticorrosion performance for Q235 carbon steel in 6 M hydrochloride acid was comprehensively evaluated by weight loss tests, electrochemical methods (potentiodynamic polarization and electrochemical impedance spectroscopy), and surface analysis techniques. As the length of the alkyl chain increased, the maximum corrosion inhibition efficiency enhanced from 55.02% (for BTA-8-BTA at 1.2 mM) to 97.10% (for BTA-12-BTA at 0.3 mM) and 98.84% (for BTA-16-BTA at 0.3 mM). Density functional theory calculation indicated that the alkyl chain length had little influence on the inhibitors' electronic structures, while molecular dynamics simulations revealed that the thickness, surface coverage, and compactness of adsorption films formed at the metal-electrolyte interface increased with the elongated alkyl chain. Corrosion inhibition efficiency is strongly correlated with the structures of the adsorption film.

Amphiphilic Janus Graphene Oxide Acts as a Corrosion Inhibitor to Mitigate the Corrosion Caused by a 1 M HCl Solution on Mild Steel

Great aqueous dispersibility, a large specific surface area, and high impermeability make graphene oxide (GO) the ideal candidate for a high-performance corrosion inhibitor. Numerous symmetrical modification methods have been reported to enhance the adsorption of GO on metal surfaces in various corrosive media. This work aims to investigate the enhancement and mechanism of unilateral hydrophobic modification on the corrosion inhibition performance of GO. In this study, amphiphilic Janus GO (JGO) was prepared by grafting hydrophobic alkyl chains on one side of GO, and its anticorrosion performance was evaluated via weight loss experiments and electrochemical tests. The results revealed that the corrosion inhibition efficiency for Q235 mild steel (MS) in a 1 M HCl aqueous solution of 25 ppm JGO (81.08%) was much higher than that of GO at the same concentration (22.12%). Furthermore, the Langmuir adsorption isotherm and computational study demonstrated that the synergistic effect of physical adsorption and chemical adsorption promoted the hydrophilic side of JGO close to the surface of the metal, and the dense protective layer was formed by the hydrophobic chains toward the corrosive medium, which effectively hindered the corrosion of MS by the acidic liquid. This study emphasizes the significant role of asymmetrically modified hydrophobic alkyl chains in improving the corrosion prevention performance of GO and provides a perspective for the structural design of GO-based corrosion inhibitors.

Corrosion Inhibition Properties of Corrosion Inhibitors to under-Deposit Corrosion of X65 Steel in CO2 Corrosion Conditions

Under-deposit corrosion is widely present in the pipelines of oil and gas production, causing significant corrosion damage. In this paper, a novel electrochemical cathodic-polarization method was carried out to accelerate the formation of CaCO3 scale on a X65 steel surface in a simulated solution containing scaling ions. Subsequently, pre-scaled X65 steel was placed in a high temperature and pressure autoclave to conduct corrosion weight-loss experiments and in situ electrochemical measurements. The study mainly compared the corrosion inhibition behavior of four quaternary ammonium salt corrosion inhibitors, pyridinium quaternary salt (BPC), quinolinium quaternary salt (BQC), 8-hydroxyquinolinium quaternary salt (BHQ) and pyridinium (1-chloromethyl naphthalene) quaternary salt (1-CPN), in a simulated oilfield scale under corrosive conditions. The results of the weight-loss experiments demonstrated that the inhibition efficiencies of the corrosion inhibitors from high to low were as follows: 1-CPN < BHQ < BQC < BPC. The in situ electrochemical measurements showed that the immersion time and type of corrosion inhibitor had a pronounced influence on the corrosion and corrosion inhibition behavior of X65 steel with CaCO3 coating. It was also proved using both EIS and PC that 1-CPN shows the best inhibition performance in all. Lastly, the inhibition mechanism of corrosion inhibitors at under-deposit conditions was analyzed via a surface morphology observation of SEM.

Effect of Alkyl Chain Length on the Corrosion Inhibition Performance of Imidazolium-Based Ionic Liquids for Carbon Steel in 1 M HCl Solution: Experimental Evaluation and Theoretical Analysis

In this study, five kinds of 1-alkyl-3-methylimidazolium bromide ([CXami]Br) ionic liquids with different alkyl chain lengths (8, 10, 12, 14, and 16) were selected as inhibitors. Then, their corrosion inhibition performances for Q235 steel in 1.0 mol L-1 HCl solution were investigated via a weight loss test, polarization curve method, and surface analysis techniques. The results show that these five imidazolium-based ionic liquids are all mixed-type inhibitors, and they can be spontaneously adsorbed onto the Q235 steel surface. The adsorption process follows the Langmuir model and involves mixed physical-chemical adsorption. Theoretical calculations confirm that the increase in alkyl chain length is conducive to the imidazolium-based ionic liquids exhibiting stronger chemical bonding abilities and forming denser adsorption films. The inhibition efficiency significantly increases below the critical micelle concentration (CMC) with an increase in alkyl chain length, and the highest inhibition efficiency is 95.17% for the [C16ami]Br inhibitor at the concentration of 0.005 mM. However, above the CMC, the inhibition efficiency is minimally affected by the alkyl chain length since all ionic liquid inhibitors have reached adsorption saturation on the steel surface.

A novel non-linear approach for establishing a QSAR model of a class of 2-Phenyl-3-(pyridin-2-yl) thiazolidin-4-one derivatives

In this investigation, we aimed to address the pressing challenge of treating osteosarcoma, a prevalent and difficult-to-treat form of cancer. To achieve this, we developed a quantitative structure-activity relationship (QSAR) model focused on a specific class of compounds called 2-Phenyl-3-(pyridin-2-yl) thiazolidin-4-one derivatives. A set of 39 compounds was thoroughly examined, with 31 compounds assigned to the training set and 8 compounds allocated to the test set randomly. The goal was to predict the IC50 value of these compounds accurately. To optimize the compounds and construct predictive models, we employed a heuristic method of the CODESSA program. In addition to a linear model using four carefully selected descriptors, we also developed a nonlinear model using the gene expression programming method. The heuristic method resulted in correlation coefficients (R 2) of 0.603, 0.482, and 0.107 for R2 cv and S2, respectively. On the other hand, the gene expression programming method achieved higher R 2 and S2 values of 0.839 and 0.037 in the training set, and 0.760 and 0.157 in the test set, respectively. Both methods demonstrated excellent predictive performance, but the gene expression programming method exhibited greater consistency with experimental values. The successful nonlinear model generated through gene expression programming shows promising potential for designing targeted drugs to combat osteosarcoma effectively. This approach offers a valuable tool for optimizing compound selection and guiding future drug discovery efforts in the battle against osteosarcoma.