ANALYZED AND PROPOSED MECHANISM OF PHOTOCATALYTIC DEGRADATION OF FURFURAL AT TIO2 NANO-PARTICLES BY HPLC-UV AND LC-MASS METHODS

Microdroplet extraction assisted ultrasensitive Raman detection in complex oil

The Raman detection of trace substances in complex oil is still a great challenge at present because of the strong disturbance of background activity and the suppression of intensity in spectra caused by complicated components. In this work, a simple and robust approach based on microdroplet liquid-liquid extraction for the real-time Raman spectroscopy monitoring of trace substances in complex oil is reported. Based on unbalanced chemical potentials between water and oil on a microfluidic chip, a target trace molecule is extracted from complex mineral oil to a water microdroplet. Benefiting from the real-time fluorescence intensities of fluorescein in a water microdroplet, the extraction performance is investigated and optimized. The optimal water microdroplet is implemented for the Raman detection of furfural in a complex mineral oil, a typical trace performance marker in electric power equipment, and this exhibits excellent sensitivity with a limit of detection (LOD) of 26 ppb. Compared to traditional detection technology for trace substances in complex oil (high performance liquid chromatography, HPLC), this method greatly simplified the process of measurement, reduced the volume of sample required, had a fast measurement time, and exhibited the prospect of real-time monitoring applications with high sensitivity, which not only promotes the development of oil quality but also enlarges existing knowledge related to using Raman spectroscopy in chem-/bio-sensing.

Review of Fiber Optic Diagnostic Techniques for Power Transformers

Diagnostic and condition monitoring of power transformers are key actions to guarantee their safe operation. The subsequent benefits include reduced service interruptions and economic losses associated with their unavailability. Conventional test methods developed for the condition assessment of power transformers have certain limitations. To overcome such problems, fiber optic-based sensors for monitoring the condition of transformers have been developed. Flawlessly built-up fiber optic-based sensors provide online and offline assessment of various parameters like temperature, moisture, partial discharges, gas analyses, vibration, winding deformation, and oil levels, which are based on different sensing principles. In this paper a variety and assessment of different fiber optic-based diagnostic techniques for monitoring power transformers are discussed. It includes significant tutorial elements as well as some analyses.

Application of Self-Assembled Raman Spectrum-Enhanced Substrate in Detection of Dissolved Furfural in Insulating Oil

Accurate detection of dissolved aging features in transformer oil is the key to judging the aging degree of oil-paper insulation. In this work, in order to realize in situ detection of furfural dissolved in transformer oil, silver nanoparticles were self-assembled on the surface of gold film with P-aminophenylthiophenol (PATP) as a coupling agent. Rhodamine-6G (R6G) was used as the probe molecule to test the enhancement effect. By optimizing the molecular concentration, molecular deposition time, and silver sol deposition time of PATP, the nanoparticles were made more uniform and compact, and an enhanced substrate with rich hot spots was obtained. The optimum substrate was developed, and surface-enhanced Raman spectroscopy (SERS) detection of trace furfural dissolved in transformer oil was realized. The results showed that the substrate prepared under the conditions of 0.1 mol/L PATP, 5 h deposition in PATP and 12 h immersion in silver sol, had the best reinforcement effect (that is, uniform and compact particle arrangement and no particle clusters). By use of this substrate, the minimum detectable concentration of furfural in transformer oil was about 1.06 mg/L, which provides a new method for fast and nondestructive detection of transformer aging diagnosis.

Treatment of florfenicol of synthetic trout fish farm wastewater through nanofiltration and photocatalyst oxidation

The aquaculture system is a potential significant source of antibacterial agents. The removal of florfenicol (Flo) antibiotic from synthetic aqueous wastewater is performed by applying a commercial thin film composite polyamide nanofilter (NF). For concentrated wastewater treatment, the advanced oxidation process (AOP) is applied. The effects of pH, pressure and Flo concentration on removal efficiency of NF and the effects of pH, Flo concentration and dosage of hydrogen peroxide and contact time on the AOP are assessed. In the nanofiltration system, it is found that an increase in pH enhances the removal efficiency up to 99%. In this membrane, an increase of pressure between 4 and 7 bar would increase the removal percentage, followed by a decrease from 7 to 10 bar. In AOP, it is observed that the degradation efficiency of Flo increases by both an increase in its initial concentration up to values above 50 ppm and contact time. The degradation efficiency of Flo is at its highest in the pH range of 7-10. With increasing H₂O₂ dosage, from 0 to 500 ppm, the removal efficiency increases. The results of this study indicate that a combination of a polyamide nanofilteration together with an AOP introduces an effective manner of removing Flo antibiotic from synthetic trout fish farm wastewater.