Predicting the inhibition efficiencies of magnesium dissolution modulators using sparse machine learning models

The degradation behaviour of magnesium and its alloys can be tuned by small organic molecules. However, an automatic identification of effective organic additives within the vast chemical space of potential compounds needs sophisticated tools. Herein, we propose two systematic approaches of sparse feature selection for identifying molecular descriptors that are most relevant for the corrosion inhibition efficiency of chemical compounds. One is based on the classical statistical tool of analysis of variance, the other one based on random forests. We demonstrate how both can—when combined with deep neural networks—help to predict the corrosion inhibition efficiencies of chemical compounds for the magnesium alloy ZE41. In particular, we demonstrate that this framework outperforms predictions relying on a random selection of molecular descriptors. Finally, we point out how autoencoders could be used in the future to enable even more accurate automated predictions of corrosion inhibition efficiencies.

Quantum Chemical Analysis of the Corrosion Inhibition Potential by Aliphatic Amines

Destructive corrosion processes lead to the loss of primary mechanical properties of metal construction materials, which generates additional costs during their maintenance connected with repairs and protection. The effectiveness of corrosion inhibitors can be determined by using many methods, in particular quantum chemical modeling. The subject of the theoretical analyses presented in this work involves the anticorrosion properties of amines with various chemical structures. Evaluation of the corrosion inhibition properties of selected amines was performed on the basis of the HOMO–LUMO energy gap, dipole moment (µ), electronegativity (χ) determined as a result of the energy of the highest occupied molecular orbital (HOMO) and the energy of the lowest unoccupied molecular orbital (LUMO). Moreover, the HSAB (Hard and Soft Acids and Bases) theory was used to explain the reactivity of the analyzed amines, while the Mulliken population analysis was used to determine their electrostatic interactions with the surface of protected metal. The obtained results indicate that the protonation reaction of aliphatic amines leads to a change in the nature of the formation of a coordination bond with the surface of the protected metal. In turn, the quantum chemical calculations showed that the protonation reaction of aliphatic amines leads to a decrease in their corrosion inhibition efficiency. Most of the analyzed parameters indicated that tertiary amines are characterized by the highest corrosion inhibition efficiency.

Protection of Aluminum Foils against Environmental Corrosion with Graphene-Based Coatings

Commercial aluminum foils were coated by graphene oxide, and its functionalized derivatives and the corrosion performance of the coated specimens were examined in acidic conditions (lithium perchlorate and sulfuric acid). Electrochemical experiments have shown that all graphene oxide-coated specimens provided up to 96% corrosion inhibition efficiency with a corresponding lower corrosion rate compared to the bare aluminum foil. Our results clearly show that graphene-related materials offer viable alternatives for the protection of aluminum, and this opens up a number of possibilities for its use in a number of commercial applications.

Study the Corrosion behavior of AA7051 Aluminum alloy at different temperatures and inhibitor concentration in Acidic medium

This study will be investigating acidic corrosion of AA7051 alloy at a different temperature, and introduces milk thistle aqueous extract as a new and widely available green corrosion inhibitor. The electrochemical methods were used to measure weight loss, penetration loss, corrosion inhibition efficiency and other parameters. The data substituted in Langmuir adsorption isotherm as well as in kinetic equations. The finding exhibit high corrosion inhibition efficiency at 0.5g/L of milk thistle extract and the efficiency rose from around 72% at 293K to just over 86% at 333K. Langmuir model linear regression coefficient ( =0.98) and the slight change in corrosion potential refer to mixed-type inhibitor attach to the surface by chemisorption. FTIR spectra for crude extract supported by literatures shows the molecular structure of the main component of milk thistle extract and exhibit the O-H group as a major group participate in adsorption.

Analysis of the Anti-Corrosion Performance of Dextrin and Its Graft Copolymer on J55 Steel in Acid Solution

This paper studies the corrosion inhibition performance and mechanism of dextrin (Dxt) and its graft copolymer with caprolactam (Dxt-g-CPL) on J55 steel in 1 M HCl solution. Caprolactam is grafted and copolymerized with dextrin by a chemical synthesis method, to obtain a dextrin graft copolymer corrosion inhibitor. The composition of the synthesized graft copolymer was characterized by FTIR to identify whether the grafting was successful. Through weightlessness, electrochemical impedance spectroscopy (EIS), potentiodynamic polarization curve (TAFEL), scanning electrochemical microscope (SECM), scanning electron microscope (SEM), and contact angle experiments, the graft copolymer to J55 steel in 1 M HCl solution and the corrosion inhibition performance were evaluated. Moreover, we discuss its corrosion inhibition mechanism. The dextrin graft copolymer has good corrosion inhibition performance for J55 in 1 M HCl solution. When the concentration of the corrosion inhibitor increases, the corrosion inhibition efficiency will also increase. At a certain concentration, when the temperature rises, the corrosion inhibition efficiency will gradually decrease. When the concentration is 300 mg/L, it has a better corrosion inhibition effect, and the corrosion inhibition efficiency is 82.38%. Potential polarization studies have shown that Dxt-g-CPL is a mixed corrosion inhibitor, which inhibits both the cathode and the anode of the electrode reaction. SEM, SECM, and contact angle analysis results show that Dxt-g-CPL can significantly inhibit corrosion. Compared with Dxt, Dxt-g-CPL has a better inhibitory effect.

Preparation of Eco-Friendly Acidic Corrosion Inhibitors from Ilex Chinensis Sims Leaves

Preparing chemicals from natural product is a simple way to green chemistry. May flavonoids and protocatechuic acid have been found in Ilex Chinensis Sims leaves extracts, which indicates its extracts suitable to be used as an effective corrosion inhibitor. Extracts of Ilex Chinensis Sims leaves (HE) were modified with hydroxymethylation reaction and Mannich reaction to produce the relative stable green acidic corrosion inhibitors (HM1 and HM2). The extracts of Ilex Chinensis Sims leaves and the modified samples were investigated on the corrosion inhibition of A3 steel accordingly. The results show that these inhibitors have effective corrosion inhibition effect on A3 steel. The HM2 are the most effective for corrosion inhibition, and the inhibition efficiency can reach to 78.36%. At 60 °C, the corrosion inhibition efficiency of these three extracts is HM2 > HM1 > HE. And the extracts inhibit corrosion mainly by adsorption mechanism. This adsorption accords with Langmuir adsorption isotherm.

Henna Leaves Extract as Green Corrosion Inhibitor for 304 Stainless Steel in Sulphuric Acid Solution

The corrosion inhibition of 304 stainless steel in 1.0 M H2SO4 has been investigated in the presence of Henna leaves (Lawsonia Inermis) extract using weight loss measurement and Scanning Electron Microscope (SEM) analysis. The study indicates that the corrosion inhibition efficiency increases with the increase in concentration of Henna leaves extract and decreases with increase in temperature. SEM analysis indicated the changes in metal surface morphology in the presence of inhibitor. The result obtained indicated that Henna leaves extract act as an efficient green corrosion inhibitor for 304 Stainless Steel.