Prediction model, experimental optimization, and verification for yield of high-pressure crystallization: a case study of citric acid. Issue 1 (2nd January 2020)

• Record Type: Journal Article
• Authors: Huang, Dechun; Zhu, Zhonglin; Wang, Qiming; Qin, Beichen; Dai, Lin; Jiang, Feng; Liu, Wei; Qian, Hongliang
• Is Part Of: Separation science and technology. Volume 55:Issue 1(2020)
• Page Start: 135
• Page End: 143
• Publication Date: 2020-01-02
• Subjects: Prediction model -- yield -- supercritical fluid antisolvent crystallization -- citric acid -- experimental optimization; Separation (Technology) -- Periodicals; 660.284205
• DOI: 10.1080/01496395.2018.1561717
• Languages: English
• ISSNs: 0149-6395

Abstract

ABSTRACT: Yield is one of the most important quality indexes for the crystal produced by high-pressure crystallization such as supercritical antisolvent (SAS) crystallization. In this study, a prediction model of yield of the SAS crystallization was proposed in the first place. Then, an experiment that prepares the citric acid particle crystallization was conducted through SAS batch device. With the help of a uniform design method, the maximum yield (0.86) was obtained under the combination of process parameters (the initial concentration of solution 0.35 g/mL, the operating temperature of 33°C, the operating pressure of 12.5 MPa, and the holding time of 3.5 h), the regression equation between yield of crystallization and four factors was obtained, and the effects of each factor on the yield are as follows: initial solution concentration > operating pressure > operating temperature > holding time. Finally, the prediction model was verified by an experiment, and the results show that the average relative error between the values calculated by prediction model and the experimental ones is 9.77%.