Dissolution of Metals in Different Bromide-Based Systems: Electrochemical Measurements and Spectroscopic Investigations

Ultrafast recovery of Zn from waste galvanized iron sheet by ultrasound-assisted acid pickling and ion flotation techniques

High-efficiency dezincification from waste galvanized iron sheets is crucial for resource recovery and environmental protection. In this work, ultrasound-assisted acid pickling and ion flotation techniques were combined to intensify the Zn extraction and separation from the waste galvanized iron sheets. The effects of leaching parameters on the leaching rate of Zn and Fe, Zn leaching kinetics and leaching electrochemistry were compared between conventional leaching and ultrasonic-assisted leaching. It's demonstrated that ultrafast dezincification is realized as the acid pickling time can be reduced from 10 min to 60 s with ultrasound assistance, and the Zn and Fe leaching rates are 99.9 % and 0.02 %, respectively. Ion flotation was adopted to recover the Zn ion from the circulated leaching solution using sodium dodecyl benzene sulfonate (SDBS) as the collector. After the Zn ion flotation, powdery ZnO with size distribution of 1-3 μm is prepared from the froth product after calcining at 600 ℃ for 2 h. In addition, various characterizations involving thermodynamics, XRD, XPS, SEM-EDS, TG-DSC, and FTIR analyses were employed to elucidate the mechanisms underlying the enhancement of Zn dissolution through ultrasound assistance and the Zn capture mechanism via ion flotation. Eventually, the combination of ultrasonic-assisted acid pickling and ion flotation techniques can achieve the rapid selective Zn extraction from waste galvanized iron sheet and fast separation of Zn ion from leachate, which can provide technical reference for the resource utilization of other waste metal coating plates.

Diatomite supported highly-dispersed ZnO/Zn-co-embedded ZIF-8 derived porous carbon composites for adsorption desulfurization

The metal organic framework (MOFs)-derived porous carbon materials with highly dispersed metal active sites were of the exclusive application foreground in many field, such as catalyst, electrochemistry, adsorption desulfurization and so on. However, the loss issue of metal active sites in MOFs frame was indispensable during the high temperature carbonization because of the lower boiling point of many metals, thus fundamentally affecting the atom-scale uniform distribution merit of MOFs-derived porous carbon materials. This work was to provide a novel strategy to address the loss issue of the active metal volatilization in the fabrication of MOFs-derived porous carbon materials. The ZnO nanosheets were pre-grown on the surface of diatomite by using in-situ microwave-assisted preparation, and thereafter the Zn-containing ZIF-8 particles covered the surface of ZnO nanosheets by virtue of the ZnO-induced growth. The results affirmed that the high content Zn-doped porous carbon materials were achieved and the Zn volatilization in MOFs was restrained on account of the occurrence of ZnO on diatomite (DE) surface during the carbonization. The adsorption desulfurization performance of the ZnO/Zn-embedded porous carbon materials/DE (ZnO/Zn/C@DE) was examined by the sulfur-containing compounds in simulated oil. The adsorption desulfurization performance investigation indicated that the ZnO/Zn/C@DE had the optimum adsorption capacities of 45.3 mg/g for benzothiophene and 37.4 mg/g for thiophene. Nonetheless, the competitive adsorption desulfurization finding of toluene in simulated oil showed that the adsorption capacities of ZnO/Zn/C@DE for TH and BT were dramatically descended, suggesting the presence of S-M interaction, wherein S stood for the S atom in a thiophene molecule and their analogs, and M for Zn atoms in porous carbon materials.

Overview and Recent Advances in Hyphenated Electrochemical Techniques for the Characterization of Electroactive Materials

A hyphenated electrochemical technique consists of the combination of the coupling of an electrochemical technique with a non-electrochemical technique, such as spectroscopical and optical techniques, electrogravimetric techniques, and electromechanical techniques, among others. This review highlights the development of the use of this kind of technique to appreciate the useful information which can be extracted for the characterization of electroactive materials. The use of time derivatives and the acquisition of simultaneous signals from different techniques allow extra information from the crossed derivative functions in the dc-regime to be obtained. This strategy has also been effectively used in the ac-regime, reaching valuable information about the kinetics of the electrochemical processes taking place. Among others, molar masses of exchanged species or apparent molar absorptivities at different wavelengths have been estimated, increasing the knowledge of the mechanisms for different electrode processes.

Combined Electrochemical, Raman Analysis and Machine Learning Assessments of the Inhibitive Properties of an 1,3,4-Oxadiazole-2-Thiol Derivative against Carbon Steel Corrosion in HCl Solution

The inhibiting properties of 5-(4-pyridyl)-1,3,4-oxadiazole-2-thiol (PyODT) on the corrosion of carbon steel in 1.0 M HCl solution were investigated by potentiodynamic polarization, electrochemical impedance spectroscopy, Raman spectroscopy, and SEM-EDX analysis. An approach based on machine learning algorithms and Raman data was also applied to follow the carbon steel degradation in different experimental conditions. The electrochemical measurements revealed that PyODT behaves as a mixed-type corrosion inhibitor, reaching an efficiency of about 93.1% at a concentration of 5 mM, after 1 h exposure to 1.0 M HCl solution. Due to the molecular adsorption and structural organization of PyODT molecules on the C-steel surface, higher inhibitive effectiveness of about 97% was obtained at 24 h immersion. The surface analysis showed a significantly reduced degradation state of the carbon steel surface in the presence of PyODT due to the inhibitor adsorption revealed by Raman spectroscopy and the presence of N and S atoms in the EDX spectra. The combination of Raman spectroscopy and machine learning algorithms was proved to be a facile and reliable tool for an incipient identification of the corrosion sites on a metallic surface exposed to corrosive environments.