Lead determination in glasses by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy (LIBS) has been used to determine the lead content of different types of lead silicate glasses commercially designed as sonorous glass (which contain ∼ 10 wt.% PbO); crystal glass (with at least 24 wt.% PbO) and superior crystal glass (with at least 30 wt.% PbO). Seven different types of glass samples were selected, including historic-original, model and commercially available. The selected samples were artificially weathered under neutral, acid and alkaline attack. Analysis by LIBS was carried out in vacuum under excitation at 266 nm and results were compared with those obtained by conventional techniques used for glass characterization. Composition of the bulk glasses was analyzed by XRF (X-ray fluorescence) and the corroded surfaces were characterized by SEM/EDX (scanning electron microscopy/energy dispersive X-ray microanalysis). A linear correlation was obtained between the intensity of selected Pb lines in the LIB spectra and the PbO content. The effect of corrosion could be characterized by comparing successive LIB spectra recorded on the same area; acid attack resulted in a decrease of PbO, CaO and Na₂O content in the surface with respect to the bulk of the sample, while minor changes in the composition were noticed under alkaline attack. These results show LIBS as a useful technique to classify the different types of lead glasses by their lead content and to determine and asses the degree and type of corrosion.     

A sustainable method of mitigating acid corrosion of mild steel using jackfruit pectin (JP) as green inhibitor: Theoretical and electrochemical studies

This study is attempted to develop a green corrosion inhibitor from a waste material of Jack fruit (Artocarpus heterophyllus). This method is therefore quite valuable to health, environment, and economic point of view. Pectin is isolated from the jackfruit peel waste using 0.05 ?N oxalic acid and used as an inhibitor for mild steel corrosion in acidic environment as it is highly water soluble. 250–1000 ?ppm of pectin was used in this study at a temperature range of 303–323 ?K. The protection efficiency of jack fruit pectin (JP) in 0.5 ?M HCl was evaluated by conventional weight loss and electrochemical techniques. The potentiodynamic polarization results revealed that JP could effectively reduce the corrosion of mild steel in acidic medium at 1000 ?ppm concentration with an inhibition efficiency of 89.75% and corrosion rate of 2.392 mpy. The mixed type behavior of the inhibitor is identified from Tafel polarization studies. Electrochemical impedance spectroscopy (EIS) measurements suggest that the corrosion inhibition process is kinetically controlled. adsorption and kinetic behavior of the inhibitor also have been studied. Surface manifestations were followed using FESEM and AFM techniques. DFT calculations and Monte Carlo simulations were also carried out to corroborate the experimental results with theoretical outputs and succeeded to a great extent.     

Improve Corrosion Resistance of Zircaloy by Copper–Graphene Nanocomposite Coatings

In this study, the corrosion behavior of Zircaloy was investigated in the presence and absence of copper–graphene nanocomposites coating. The coating was prepared employing Hummers’ and electrochemical reduction methods. The morphology of copper–graphene nanocomposites coating was studied using scanning electron microscopy (SEM). Corrosion behavior was investigated employing dynamic polarization and electrochemical impedance spectroscopy (EIS) tests in a solution containing lithium hydroxide (LiOH), boric acid (H₃BO₃), and deionized water. The results showed that corrosion resistance of Zircaloy increased with introduction of copper–graphene nanocomposites coatings. The lowest corrosion rate was attained in the Zircaloy with copper–graphene nanocomposites coating (corrosion rate: 0.040 mm/year). An approximately 20 times decrease in the corrosion rate was observed in the Zircaloy with copper–graphene nanocomposites coating when compared to the un-coated Zircaloy (corrosion rate: 0.831 mm/year).

     

Electrodeposition and characterization of Zn–Sn alloy coatings from a deep eutectic solvent based on choline chloride for corrosion protection

With the aim of obtaining high corrosion resistant Zn–Sn alloy coatings from an ionic liquid, the effects of electrodeposition potential and electrolyte composition on the electrodeposition behavior, film composition, morphology and corrosion performance were investigated. Cyclic voltammograms indicate that Zn and Sn were co‐deposited at distinct reduction potentials as pure Zn and Sn elements. In addition, the phase composition analysis also showed that the obtained Zn–Sn alloy deposits (8 wt.%–45 wt.% Zn) consist of a two‐phase mechanical mixture of small aggregates of Zn and Sn metals. The Zn content of the alloy significantly increases as the electrodeposition potential and electrolyte Zn (II)/Sn (II) ratio increase. The corrosion performance study of the obtained Zn–Sn coatings showed that they have a passivation behavior and their corrosion resistance increases as the alloy‐Sn content increases. To improve their morphological properties, ethylene diamine tetraacetic acid additive was introduced into the electrolyte and greatly improved the morphology and corrosion resistance of the deposits. For the first time, it was shown that high corrosion resistance Zn–Sn coatings can be obtained from ionic liquids. Copyright © 2014 John Wiley & Sons, Ltd.     

Effects of serum proteins on corrosion behavior of ISO 5832–9 alloy modified by titania coatings

Stainless steel ISO 5832–9 type is often used to perform implants which operate in protein-containing physiological environments. The interaction between proteins and surface of the implant may affect its corrosive properties. The aim of this work was to study the effect of selected serum proteins (albumin and γ-globulins) on the corrosion of ISO 5832–9 alloy (trade name M30NW) which surface was modified by titania coatings. These coatings were obtained by sol–gel method and heated at temperatures of 400 and 800 °C. To evaluate the effect of the proteins, the corrosion tests were performed with and without the addition of proteins with concentration of 1 g L^?1 to the physiological saline solution (0.9 % NaCl, pH 7.4) at 37 °C. The tests were carried out within 7 days. The following electrochemical methods were used: open circuit potential, linear polarization resistance, and electrochemical impedance spectroscopy. In addition, surface analysis by optical microscopy and X-ray photoelectron spectroscopy (XPS) method was done at the end of weekly corrosion tests. The results of corrosion tests showed that M30NW alloy both uncoated and modified with titania coatings exhibits a very good corrosion resistance during weekly exposition to corrosion medium. The best corrosion resistance in 0.9 % NaCl solution is shown by alloy samples modified by titania coating annealed at 400 °C. The serum proteins have no significant effect onto corrosion of investigated biomedical steel. The XPS results confirmed the presence of proteins on the alloy surface after 7 days of immersion in protein-containing solutions.     

Effect of sodium vanadate on corrosion of AD31 aluminum alloy in acid media

Scanning electron microscopy, potentiodynamic polarization method, and electrochemical impedance spectroscopy were used to study the corrosion behavior of AD31 (AA6063) aluminum alloy in acid (pH 3) 0.05 M NaCl solutions containing 3 mmol dm^–3 of NaVO₃ inhibitor. It was found that the corrosion of AD31 alloy in acid sodium chloride solutions predominantly occurs locally at aluminum/intermetallic particle phase boundaries and is limited by the electrochemical stage of charge transfer. It was shown that introduction of sodium vanadate can reduce the rate of selective dissolution of magnesium from the alloy and provides a protective effect on the level of 7–10%.     

Artificial neural network for the evaluation of CO2 corrosion in a pipeline steel

This paper presents a predictive model for the determination of different types of corrosion by using electrochemical impedance spectroscopy curves and artificial neural network. This proposed model obtains predictions for three different types of corrosion by using Nyquist impedance curves from four input variables: inhibitor concentration, time of exposure, and the real and imaginary experimental component of these curves. The model takes into account the variations of inhibitor concentration over steel to decrease the corrosion rate. For the network, the Levenberg–Marquardt learning algorithm, the hyperbolic tangent sigmoid transfer function and the linear transfer function were used. The best fitting training data set was obtained with five neurons in the hidden layer, which made possible to predict satisfactory efficiency (R > 0.99). On the validation of the data set, simulations and theoretical data tests were in good agreement (R > 0.9905). The developed model can be used for the determination of the type of curves related to the nature phenomena and rate of corrosion at the metal surface.     

VoteDock: Consensus docking method for prediction of protein–ligand interactions

Molecular recognition plays a fundamental role in all biological processes, and that is why great efforts have been made to understand and predict protein–ligand interactions. Finding a molecule that can potentially bind to a target protein is particularly essential in drug discovery and still remains an expensive and time‐consuming task. In silico, tools are frequently used to screen molecular libraries to identify new lead compounds, and if protein structure is known, various protein–ligand docking programs can be used. The aim of docking procedure is to predict correct poses of ligand in the binding site of the protein as well as to score them according to the strength of interaction in a reasonable time frame. The purpose of our studies was to present the novel consensus approach to predict both protein–ligand complex structure and its corresponding binding affinity. Our method used as the input the results from seven docking programs (Surflex, LigandFit, Glide, GOLD, FlexX, eHiTS, and AutoDock) that are widely used for docking of ligands. We evaluated it on the extensive benchmark dataset of 1300 protein–ligands pairs from refined PDBbind database for which the structural and affinity data was available. We compared independently its ability of proper scoring and posing to the previously proposed methods. In most cases, our method is able to dock properly approximately 20% of pairs more than docking methods on average, and over 10% of pairs more than the best single program. The RMSD value of the predicted complex conformation versus its native one is reduced by a factor of 0.5 Å. Finally, we were able to increase the Pearson correlation of the predicted binding affinity in comparison with the experimental value up to 0.5. © 2010 Wiley Periodicals, Inc. J Comput Chem 32: 568–581, 2011     

Influence of binary interactions on phase behavior of water/ dimethylsulfoxide/ polyethersulfone casting solution: Thermodynamic modeling

Prediction and control of membrane morphology using multi‐phase thermodynamic knowledge are of growing interest. The water/dimethylsulfoxide/polyethersulfone ternary system is a widely used casting dope for the preparation of MF, UF, and NF membranes. In the current study, Flory–Huggins (F–H) model was applied to predict the behavior of this ternary system during phase inversion. Titration method was applied to generate cloud point data. The prediction accuracy of the F–H model was directly dependent on the binary interactions of the system components. The compressible regular solution (CRS) model predicts the binodal location using only the pure component properties as the input parameters. Accordingly, the influence of binary parameters on the location of the binodal curves was investigated. The predicted binodal points showed superior accordance with the experimental data, where the binary interaction between nonsolvent (water) and solvent (DMSO) was overlooked. In addition, the modelling results emphasized on the pivotal importance of the interactions between polymer (PES) and nonsolvent (water) on the phase inversion and thus, on the control of the membrane morphology. The CRS model offered a greater conformity with the experimental results in comparison with the F–H theory. Copyright © 2013 John Wiley & Sons, Ltd.     

Corrosion Behavior in Acid and Alkaline Media of Nickel Coatings Deposited at Room Temperature

Impedance spectroscopy, chronovoltammetry, chronopotentiometry, scanning electron microscopy, and atomic-force microscopy were used to examine the corrosion behavior in acid and alkaline media and the morphology of nickel coatings electrodeposited from acetate, tartrate, and isobutyrate electrolytes at a temperature of 20–25°C. Models describing the nickel corrosion processes in H₂SO₄ and NaOH solutions were suggested. It was found that nickel coatings formed from isobutyrate electrolytes have the highest corrosion resistance.     

Odd random phase multisine EIS as a detection method for the onset of corrosion of coated steel

In this work, odd random phase multisine Electrochemical Impedance Spectroscopy (ORP-EIS) was used as a detection method for the onset of corrosion of coated steel. The possibility to use ORP-EIS as a rapid-screening test for corrosion was investigated. It is concluded that the detection of a non-linear behavior combined with a non-stationary behavior during the onset of corrosion can be used as a criterion in a rapid-screening test for corrosion of coated steel.     

Corrosion behavior of 316 stainless steel for advanced high-temperature water-cooled nuclear plant

Corrosion occurs widely in the supercritical water system materials under high temperature and pressure. To select reliable candidate materials, corrosion behavior of many alloys was investigated. This study focused on investigating the corrosion behavior of 316 stainless steel (316 SS) in supercritical water (798 K/24 MPa). After exposed to SCW for 200 h, the oxidation kinetics, surface morphology, and diffusion of elements were investigated by weight measurement, scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive spectroscopy (EDS), and X-ray photoelectron spectroscopy (XPS). The surface of 316 SS showed isolated and discontinued oxide scales. The oxide scale was determined to be a monolayer layer, and the main composition was determined to be Fe–Cr-rich spinel with a few amounts of magnetite attached to the surface. A few pores due to pitting corrosion were found on the surface, and the oxidation mechanism was also investigated.     

Effects of water contamination on the electrical properties of 18650 lithium-ion batteries

Effects of water on the voltage, internal resistance, initial capacity and cycling behavior of 18650-type lithium-ion batteries are studied. The voltage curves of the first charging can be used to judge whether cells are contaminated by water, because the voltage growth rates of cells are obviously different (>100 mV) between water-free batteries and containing water batteries at the first charging period of 10–50 min. The self-discharging performances of water contamination cells are also larger, because water-related side effects happen continuously during aging at high voltage of 4.2 V. Besides, HF corrosion on the cathode materials and Co ion dissolved out from lithium nickel cobalt manganese oxides lead to rapid capacity fading from >90% (100 cycles) to <80% (300 cycles, 0.5 C charging/0.5 C discharging).     

Systemic approach to design of liquid cleaning compositions and practical implementation of the method

The scientific basis of the development of liquid cleaning compositions is physicochemical analysis of multicomponent systems that comprise the major components of detergents. The method was implemented in Optimum software for the sulfirol-8–isobutanol–turpentine–water four-component system. After solubility in the system was studied, homogeneous mixtures were optimized by their physicochemical and functional properties (viscosity, density, refractive index, pH, detergency, and corrosion activity). The compositions having the highest detergency and neutral pH and not causing corrosion on titanium and aluminum alloys were selected and recommended for use as technical detergents.     

Evaluation of the dissolved oxygen-related electrochemical behavior of pure titanium in acidic fluoride-containing solutions

Journal of Solid State Electrochemistry - The effects of dissolved oxygen (DO) on the corrosion behavior of pure titanium in acidic fluoride-containing acids (pH = 0.6–2.0) were...     

Process prediction of Ni–SiC coatings based on RBF-BP model

The preparation of Ni–SiC coatings using magnetic field-assisted jet electrodeposition under various plating settings is described in this study. A RBF-BP composite neural network with 4 × 4 × 4 × 7 × 10 × 1 was used to predict the corrosion resistance of Ni–SiC coatings prepared by employing different plating parameters. The results show that the fitting degree between the expected value and the actual value of the RBF-BP composite neural network is 0.97497. Moreover, the hybrid neural network can accurately predict the corrosion resistance of Ni–SiC coatings prepared under different process parameters. The corrosion weight loss of the coating is the lowest at the current density of 4 A/dm², a jet rate of 3 m/s, a SiC particle concentration of 8 g/L, and at a magnetic field intensity of 0.8 T, demonstrating its corrosion resistance under these conditions. According to the coating characterization analysis, the coating's grain size was significantly refined, and the surface was smoother with a high amount of uniformly sized SiC nanoparticles.