A selection design of experiment for optimization of process variables for supercritical carbon dioxide using response surface methodology: a review

Abstract

Supercritical carbon dioxide (SC-CO2) which is an alternative and green method for extraction of natural plants. Many parameters in SC-CO2 including pressure, temperature, extraction time, particle size, CO2 flowrate and composition of solvent modifiers were optimized to improve the extraction efficiencies by using a response surface methodology (RSM). RSM is a collection of statistical and mathematical techniques useful for developing, improving, and optimizing processes. To adequately resolve the above-mentioned issues, a design of experiment (DOE) is required. Recently, in providing a better decision support analysis, the necessity for a specific experimental design modelling is based on statistical methodologies via response surface. Hence, objective of this study is to review the previous studies on various innovative designs that have been employed for SC-CO2 extraction using RSM Consequently, the present paper provides an insight into RSM by scrutinizing the design, modelling, predicting, and optimizing SC-CO2 process with an acceptable accuracy for different designs of experimental work with an appropriate model that fits the desired approach of the researchers.