Supercritical Fluid Extraction Applications in the Process Industries

Supercritical fluid extraction (SFE), a separations technique, has recently attracted the attention of the process industries. SFE is based on the observation that a fluid exhibits enhanced solvating ability when compressed at temperatures near its critical temperature to pressures greater than its critical pressure. This extraction process can, under certain circumstances, offer economic advantages comparable to those of conventional separation techniques. Several commercial supercritical processes are currently in operation in the United States and Europe, and new industrial applications are emerging. In this paper, the current and future applications of supercritical fluid technology and the prospects for implementing an SFE operation on an industrial scale are reviewed

Effects of sulfur dioxide entrainer on the solubility of benzoic acid in supercritical carbon dioxide

Chemical Engineerin

Mass transfer and hydraulic characteristics of a supercritical fluid sieve tray extractor

The mass transfer and hydraulic characteristics of a 2.54 cm diameter sieve tray extraction column operating with supercritical and liquid solvents were investigated. Supercritical and liquid carbon dioxide were used to extract alcohols from water at pressures of 81.6 to 102.0 atm and temperatures of 25°C to 40°C. Toluene was employed to separate acetone from water at 25°C and 1 atmosphere in the same apparatus so that conventional and supercritical extraction could be compared. A mechanistic mass transfer model was developed to predict the overall efficiency of a sieve tray column operating with supercritical and liquid solvents. The model was based on liquid extraction theory and predicted efficiencies within ±25% of the experimental values. The input parameters required for the model simulation were the operating, geometric, and physical properties of the system. The investigation included the measurement of mass transfer efficiency, phase equilibria, throughput capacity, column end effects, drop diameter, and operational holdup data. Average experimental overall efficiencies were 48% for the supercritical CO₂/isopropanol/water system, 63% for the supercritical CO₂/ethanol/water system, 46% for the liquid CO₂/ isopropanol/water system, and 14% for the toluene/acetone/water system. These values were adjusted to account for column end effects which represented about 30% of the total mass transfer. Throughput capacities for the supercritical systems in the sieve tray column were over 100% greater than for the toluene/acetone/water system. The present research represents the first step towards the development of an algorithm for the design of extraction columns operating with supercritical solvents, and it demonstrates that supercritical separations can be modeled mechanistically based on liquid extraction principles. Although results from this investigation indicate that supercritical fluid extraction permits high throughput capacities and provides relatively high mass transfer efficiencies compared with conventional extraction, final evaluations must await studies in larger equipment and with a broader range of system propertiesChemical Engineerin

Tracing the Mathematical Modeling Phases of Pre-Service Teachers: A MAD Analysis

Mathematical modeling has been receiving increased focus with researchers identifying its benefits for students, such as using mathematics in real world applications and affecting change in attitudes towards mathematics. Mathematical modeling also provides the opportunity to support equitable learning, promoting cooperation among students from various mathematical backgrounds with the use of low-floor and high-ceiling tasks. With numerous benefits, it is important to also examine how groups of pre-service teachers negotiate the modeling process in order to better support those who look to include modeling activities in their future classrooms. While there have been several theoretical modeling cycles published that describe the various phases, these tend to provide a simplified view of the complex nature of these tasks. To gain insight into this phenomena, we created, taught, and observed two mathematical modeling sessions for pre-service teachers. This work enabled us to explore how pre-service teachers move between phases of the modeling cycle and if these shifts mirror what is being represented in current modeling cycle diagrams. Our analysis focuses on a holistic task that was completed after pre-service teachers had learned about mathematical modeling and had attempted an atomistic task. We used a modified version of the Modeling Activity Diagram (MAD) framework to create a visual representation of group movements through the modeling cycle phases. While our analysis is ongoing, our emerging findings show that pre-service teachers are able to adapt to the complex nature of modeling activities to varying degrees as they work together to build their mathematical models

Supporting Pre-Service Teachers as They Begin Their Mathematical Modeling Journey

A mathematical model “is a representation of a system or scenario that is used to gain qualitative and/or quantitative understanding of some real-world problems and to predict future behavior” (Bliss et al., 2014, p. 3). CCSSM and NJSLSM call for students to be able to engage in the mathematical practice of modeling; however, modeling is not always a main focus in teacher education curricula. To learn how to best support pre-service teachers (PSTs) as they begin to engage with mathematical modeling, we conducted two 75-minute sessions with PSTs where we: provided an introduction, had participants engage in two modeling tasks, and provided additional resources. From these sessions we utilized pre- and post-surveys along with audio recordings of the PSTs working in groups. This poster reports on the design and implementation of these two sessions, the benefits and concerns the PSTs noted while engaging in the sessions, and suggestions for the design of future sessions with PSTs. We found that PSTs had little prior exposure to mathematical modeling, yet were interested in and benefited from engaging collaboratively in the modeling enactments. The PSTs reported concerns about enacting modeling in their future classrooms, which included managing time constraints, supporting students’ mathematical thinking, and overcoming student frustration. Our recommendations for the design of future modeling sessions with PSTs include providing them with more examples of modeling tasks, having them watch implementation of modeling tasks by a practicing teacher with students, and having PSTs find and evaluate modeling tasks