Process Optimization and Modeling of Microwave Roasting of Bastnasite Concentrate Using Response Surface Methodology

Abstract

The investigation of the dielectric properties of bastnasite concentrate has critical directing centrality for the microwave roasting process of bastnasite concentrate. The dielectric properties are correlated with information such as thermogravimetry–differential scanning calorimetry and temperature rise curves. This combination permits a targeted study of the mechanism of the microwave roasting process, providing new evidence about the unique conditions of this microwave roasting process. This work also explores the response surface methodology based on a central composite design to optimize the microwave non-oxidative roasting process. Single-factor tests were conducted to determine the suitable range of factors such as the content of activated carbon, holding time, and roasting temperature. The interactions between parameters were investigated through the analysis of variance method. It was indicated that the models are available to navigate the design space. Also, the optimal roasting temperature, content of activated carbon, and holding time were 1100 °C, 20%, and 21.5 min, respectively. Under these conditions, the decomposition rate of bastnasite concentrate (hereinafter to be referred as DRBC) and the oxidation rate of cerium (hereinafter to be referred as ORC) was 99.8% and less than 0.3%, respectively. The new non-oxidizing roasting method significantly shortens the roasting time, reduces the energy consumption, and has great significance for industrial applications.

Ionic Liquid and Tween-80 Mixture as an Effective Dispersant for Oil Spills: Toxicity, Biodegradability, and Optimization

“…Hence, it is important to use a comprehensive optimization method that effectively links the dispersion effectiveness with different environmental variables. In this regard, response surface methodology (RSM) is a well-established statistical technique widely used to optimize several processes. , However, very few studies have used RSM optimization for the dispersion of oil under different environmental conditions. It is highly desirable to optimize the dispersion process to improve its effectiveness and design a model that efficiently determines the influence of different environmental variables on the performance of newly developed formulations.…”