BITS Faculty Publications
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Item Optimum conditions of zero-valent iron nanoparticle stabilized foam application for diesel-contaminated soil remediation involving three major soil types(Springer, 2021-08) Chattopadhyay, PradiptaStability of foam, enhanced by nano zero-valent iron (nZVI) and its optimized constituents, may have significant potential for effective treatment of soil contaminated with diesel oil—a major environmental problem. The optimum diesel removal efficiency from distinct types of soil accomplished by the unique application of such foams as well as the optimum conditions of the foaming constituents have not been reported in literature so far. Hence, in this work, the removal of diesel contaminant from different soil types (desert, coastal, clay soil) is optimized, and the optimized results are reported for the first time, using response surface methodology (RSM), for alkylpolyglucoside phosphate (APG-Ph) foam, stabilized by nZVI. The effect of concentrations of APG-Ph (0.02, 0.04, 0.06, 0.08, and 0.1 volume %) and nZVI (2, 3, and 3.5 mg/l) on diesel removal efficacy from soil is studied using Box-Behnken design (BBD) of response surface methodology (RSM). Maximum diesel removal efficiency obtained at a concentration of 0.1 volume % APG-Ph foam with 3.5 mg/l nZVI for desert, coastal, and clay soil is 94.6, 95.3, and 57.5%, respectively. The optimum concentrations of APG-Ph and nZVI are found to be 0.98 volume % and 0.8 mg/l, respectively. Validation of this optimal condition experimentally results in highest removal efficiency of 98.3, 97.2, and 75.9% for desert, coastal, and clay soil respectively. This is in good agreement with the predicted values by RSM (98.67, 97.57, and 76.85%). The maximum diesel removal efficiency predicted at optimal concentration of APG-Ph and nZVI is significantly larger than the results reported in literature in last three years.Item Analyzing milk foam using machine learning for diverse applications(Springer, 2022-08) Chattopadhyay, PradiptaIn the beverages industry, milk foaming is done to enhance the flavor, texture, and visual appeal of milk-based beverages. It is very crucial to study milk foam properties not just to create visually appealing and rich in taste beverages but also to estimate the adulterants present in it. Machine learning is being used in every field nowadays as it can analyze large datasets quickly and help in making data-driven decisions. This paper is a demonstration of how a futuristic apparatus will detect the best type of milk for beverages and identify milk adulteration using machine learning. In the current study, machine learning methods are employed to assess milk foam properties. This study aims to choose the best type of milk for foam-based milk beverages preparations and detect surfactants often used in low concentrations for foaming but act as adulterants at high concentrations. Surfactants alter the foaming properties of milk in different ways depending on their charge and are therefore used in the dairy industry. By using machine learning techniques, the impact of three different surfactants, having distinct ionic properties, on three distinct types of milk have been analyzed. It was found that foaming properties of milk were highly correlated to each other. “Random forest classifier” turned out to be the most effective among all the machine learning models in both the tasks. Heating and addition of sodium dodecyl sulfate (SDS) improved foaming. The findings of this study can be used for deriving valuable insights about the dairy industryItem Remediation of Diesel-contaminated soil using zero-valent nano-nickel and zero-valent nano copper particles-stabilized Tween 80 surfactant foam(Elsevier, 2023-02) Chattopadhyay, PradiptaThis paper uniquely reports the remediation of diesel-contaminated desert soil by aqueous Tween 80 (TW80) surfactant foams stabilized by zero–valent nickel (Ni0) and zero–valent copper (Cu0) nanoparticles (NPs). The sizes of synthesized nanoparticles, ∼21 nm (Cu0), ∼20 nm (Ni0), are determined by XRD and FE-SEM. The impact of these NPs (1 mg, 2 mg concentrations) on foaming characteristics, remediation of diesel-contaminated soils is explored at 2 vol% TW80 surfactant concentration. With 2 mg concentration of Ni0, Cu0 NPs and 2 vol% TW80 surfactant, it is found that 98.73 and 99.38 % diesel contaminants are removed.Item Effects of N-alkanol adsorption on bubble acceleration and local velocities in solutions of the homologous series from ethanol to N-decanol(MDPI, 2023-03) Chattopadhyay, PradiptaThe influence of n-alkanol (C2–C10) water solutions on bubble motion was studied in a wide range of concentrations. Initial bubble acceleration, as well as local, maximal and terminal velocities during motion were studied as a function of motion time. Generally, two types of velocity profiles were observed. For low surface-active alkanols (C2–C4), bubble acceleration and terminal velocities diminished with the increase in solution concentration and adsorption coverage. No maximum velocities were distinguished. The situation is much more complicated for higher surface-active alkanols (C5–C10). In low and medium solution concentrations, bubbles detached from the capillary with acceleration comparable to gravitational acceleration, and profiles of the local velocities showed maxima. The terminal velocity of bubbles decreased with increasing adsorption coverage. The heights and widths of the maximum diminished with increasing solution concentration. Much lower initial acceleration values and no maxima presence were observed in the case of the highest n-alkanol concentrations (C5–C10). Nevertheless, in these solutions, the observed terminal velocities were significantly higher than in the case of bubbles moving in solutions of lower concentration (C2–C4). The observed differences were explained by different states of the adsorption layer in the studied solutions, leading to varying degrees of immobilization of the bubble interface, which generates other hydrodynamic conditions of bubble motion.Item Impact of protein nanoparticles on beer foam(Springer, 2023-06) Roy, Banasri; Chattopadhyay, PradiptaBeer foam adds a visual aesthetic to the beer- a good beer foam layer presents the beer as fresh and tasty and attracts customers. Beer foam also helps in maintaining the flavor of the beer by acting as an airtight blanket preventing the escape of CO2 from the beer. Thus, stable, long-lasting beer foam is preferred in the final product irrespective of consumer preferences. Beer foam stability is impacted by the proteins and protein nanoparticles. This work encompasses the effects that proteins and protein nanoparticles have on foaming in beer. Studies regarding the impact of protein nanoparticles on the quality of beer foam are also discussed.