Effect of violent mixing on sonochemical oxidation activity under various geometric conditions in 28-kHz sonoreactor

Ultrasonic Activation of Persulfate for the Removal of BPA in 20, 28, and 300 kHz Systems

The effect of ultrasound (US) on persulfate (PS) activation was investigated to determine whether acoustic cavitation can effectively induce PS activation for bisphenol A (BPA) degradation at 20, 28, and 300 kHz under various temperature conditions. The optimal liquid volume in the vessel was geometrically determined to be 400, 900, and 420 mL at 20, 28, and 300 kHz, respectively, using KI dosimetry and sonochemiluminescence image analysis. The pseudo-1st-order reaction kinetic constants in the only PS, only US, and US/PS processes at 20, 28, and 300 kHz were obtained under 5-10 ℃, 15-20 ℃, 25-30 ℃, 45-50 ℃, 55-60 ℃, and no temperature control conditions. No notable BPA degradation occurred at 5-10 ℃, 15-20 ℃, and 25-30 ℃ in the only PS processes for all frequencies. The highest sonochemical BPA degradation was obtained at 300 kHz, and much lower BPA degradation was observed at 45-50 ℃ and 55-60 ℃ for all frequencies in the only US processes. No notable enhancement of BPA degradation was observed at 5-10 ℃, 15-20 ℃, and 25-30 ℃ in the US/PS processes compared to the only US processes for all frequencies. At 20 kHz and temperatures between 55 and 60 ℃, the highest BPA degradation was obtained, with a synergistic effect of 171 %. However, the enhancement might be due to the instant or local temperature increase, and not due to acoustic cavitation. No notable PS activation by US irradiation was observed in the US/PS processes in this study. The profiles of the generated sulfate ion concentrations in the US/PS processes confirmed this. Some previous studies found high synergistic effects, whereas others have found low or no synergistic effects in US/PS processes.

A brief review on the progress of MXene-based catalysts for electro- and photochemical water splitting for hydrogen generation

The development and generation of affordable and highly efficient energy, particularly hydrogen, are one of the best approaches to address the challenges posed by the depletion of non-renewable energy sources. Hydrogen energy, as a green and ecosystem-friendly source with zero carbon emission, can be generated through various methods, including water splitting (HER/OER) via either photo- or electrocatalytic reactions. To implement these reactions effectively in practical applications, it is highly desirable to develop extremely efficient and cost-effective catalytic materials that are comparable to contemporary catalysts. MXenes, a family of newly discovered 2D transition metal carbides, nitrides, or carbonitrides with surface termination groups, such as -OH, -O, and -F, have emerged as promising materials and substrates for photo- and electrocatalytic applications due to their unique characteristics. These include excellent conductivity provided by the transition metals, hydrophilic nature imparted by the surface termination groups, high mechanical stability, fast electronic transmission and extremely high surface area-to-volume ratios. In this review, we provide detailed insights into the synthesis, properties, and catalytic applications of MXenes. We systematically outline the photo- and electrocatalytic water splitting reactions carried out by various MXene-based heterostructures, supported by experimental data. A thorough deliberation on the structure-activity associations of reported catalysts and a basic understanding of the electrocatalytic applications of MXenes are also included. Furthermore, we offer an insight into the upcoming tasks, challenges, prospects and new research strategies for MXenes in water splitting applications. A noteworthy recognition of the design and optimization of extremely efficient MXene-based catalysts in water splitting applications is therefore offered in this review.

Machine learning model to predict rate constants for sonochemical degradation of organic pollutants

In this study, machine learning (ML) algorithms were employed to predict the pseudo-1st-order reaction rate constants for the sonochemical degradation of aqueous organic pollutants under various conditions. A total of 618 sets of data, including ultrasonic, solution, and pollutant characteristics, were collected from 89 previous studies. Considering the difference between the electrical power (Pele) and calorimetric power (Pcal), the collected data were divided into two groups: data with Pele and data with Pcal. Eight input variables, including frequency, power density, pH, temperature, initial concentration, solubility, vapor pressure, and octanol-water partition coefficient (Kow), and one target variable of the degradation rate constant, were selected for ML. Statistical analysis was conducted, and outliers were determined separately for the two groups. ML models, including random forest (RF), extreme gradient boosting (XGB), and light gradient boosting machine (LGB), were used to predict the pseudo-1st-order reaction rate constants for the removal of aqueous pollutants. The prediction performance of the ML models was evaluated using different metrics, including the root mean squared error (RMSE), mean absolute error (MAE), and R squared (R2). A significantly higher prediction performance was obtained using data without outliers and augmented data. Consequently, all the applied ML models could be used to predict the sonochemical degradation of aqueous pollutants, and the XGB model showed the highest accuracy in predicting the rate constants. In addition, the power density and frequency were the most influential factors among the eight input variables in prediction with the Shapley additive explanation (SHAP) values method. The degradation rate constants of the two pollutants over a wide frequency range (20-1,000 kHz) were predicted using the trained ML model (XGB) and the prediction results were analyzed.

Ultrasonic reactor set-ups and applications: A review

Sonochemistry contributes to green science as it uses less hazardous solvents and methods to carry out a reaction. In this review, different reactor designs are discussed in detail providing the necessary knowledge for implementing various processes. The main characteristics of ultrasonic batch systems are their low cost and enhanced mixing; however, they still have immense drawbacks such as their scalability. Continuous flow reactors offer enhanced production yields as the limited cognition which governs the design of these sonoreactors, renders them unusable in industry. In addition, microstructured sonoreactors show improved heat and mass transfer phenomena due to their small size but suffer though from clogging. The optimisation of various conditions of regulations, such as temperature, frequency of ultrasound, intensity of irradiation, sonication time, pressure amplitude and reactor design, it is also discussed to maximise the production rates and yields of reactions taking place in sonoreactors. The optimisation of operating parameters and the selection of the reactor system must be considered to each application's requirements. A plethora of different applications that ultrasound waves can be implemented are in the biochemical and petrochemical engineering, the chemical synthesis of materials, the crystallisation of organic and inorganic substances, the wastewater treatment, the extraction processes and in medicine. Sonochemistry must overcome challenges that consider the scalability of processes and its embodiment into commercial applications, through extensive studies for understanding the designs and the development of computational tools to implement timesaving and efficient theoretical studies.