Optimization of cooling strategy and seeding by FBRM analysis of batch crystallization

被引：29

作者：

Zhang, Dejiang ^{[1
,2
]}

Liu, Lande ^{[3
]}

Xu, Shijie ^{[1
,2
]}

Du, Shichao ^{[1
,2
]}

Dong, Weibing ^{[1
,2
]}

Gong, Junbo ^{[1
,2
]}

机构：

[1] Tianjin Univ, Sch Chem Engn & Technol, State Key Lab Chem Engn, Tianjin 300072, Peoples R China

[2] Tianjin Univ, Coinnovat Ctr Chem & Chem Engn Tianjin, Tianjin 300072, Peoples R China

[3] Univ Huddersfield, Sch Appl Sci, Huddersfield HD1 3DH, W Yorkshire, England

来源：

JOURNAL OF CRYSTAL GROWTH | 2018年 / 486卷

基金：

中国国家自然科学基金;

关键词：

Batch crystallization; Constant growth rate trajectory; FBRM; Optimized seed policy; Optimization; CRYSTAL SIZE DISTRIBUTION; DIRECT NUCLEATION CONTROL; DESIGN; DISTRIBUTIONS; PERSPECTIVE; ZONE;

D O I：

10.1016/j.jcrysgro.2017.12.046

中图分类号：

O7 [晶体学];

学科分类号：

0702 ; 070205 ; 0703 ; 080501 ;

摘要：

A method is presented for optimizing the cooling strategy and seed loading simultaneously. Focused beam reflectance measurement (FBRM) was used to determine the approximating optimal cooling profile. Using these results in conjunction with constant growth rate assumption, modified Mullin-Nyvlt trajectory could be calculated. This trajectory could suppress secondary nucleation and has the potential to control product's polymorph distribution. Comparing with linear and two step cooling, modified Mullin-Nyvlt trajectory have a larger size distribution and a better morphology. Based on the calculating results, the optimized seed loading policy was also developed. This policy could be useful for guiding the batch crystallization process. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：1 / 9

页数：9

共 50 条

[31] Comparative Study on Adaptive Bayesian Optimization for Batch Cooling Crystallization for Slow and Fast Kinetic Regimes [J].

Pickles, Thomas ;

Mustoe, Chantal ;

Brown, Cameron J. ;

Florence, Alastair J. .

CRYSTAL GROWTH & DESIGN, 2024, 24 (03) :1245-1253

[32] FBRM and PVM investigations of the double feed semi-batch crystallization of 6-aminopenicillanic acid [J].

Su M. ;

Wang L. ;

Sun H. ;

Wang J. .

Frontiers of Chemical Engineering in China, 2009, 3 (3) :282-288

[33] Adjustment of Process Conditions in Seeded Batch Cooling Crystallization [J].

Kardum, Jasna Prlic ;

Hrkovac, Martina ;

Leskovac, Mirela .

CHEMICAL ENGINEERING & TECHNOLOGY, 2013, 36 (08) :1347-1354

[34] A model for the prediction of supersaturation level in batch cooling crystallization [J].

Yang, Guangyu ;

Louhi-Kultanen, Marjatta ;

Sha, Zuoliang ;

Kubota, Noriaki ;

Kallas, Juha .

JOURNAL OF CHEMICAL ENGINEERING OF JAPAN, 2006, 39 (04) :426-436

[35] ANALYSIS OF OPERATING CONDITIONS FOR CANE SUGAR BATCH CRYSTALLIZATION BASED ON MSZW COUPLED WITH MECHANISTIC KINETIC MODELS [J].

Sanchez-Sanchez, K. B. ;

Bolanos-Reynoso, E. ;

Urrea-Garcia, G. R. .

REVISTA MEXICANA DE INGENIERIA QUIMICA, 2017, 16 (03) :1029-1052

[36] Data-Driven Modeling and Dynamic Programming Applied to Batch Cooling Crystallization [J].

Griffin, Daniel J. ;

Grover, Martha A. ;

Kawajiri, Yoshiaki ;

Rousseau, Ronald W. .

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2016, 55 (05) :1361-1372

[37] Mathematical modeling and optimal control strategy development for batch crystallization process [J].

Niu, Lin .

2015 CHINESE AUTOMATION CONGRESS (CAC), 2015, :243-246

[38] Membrane-Assisted Cooling Crystallization for Interfacial Nucleation Induction and Self-Seeding Control [J].

Xiao, Wu ;

He, Zeman ;

Shao, Guanying ;

Li, Peiyu ;

Ruan, Xuehua ;

Yan, Xiaoming ;

Wu, Xuemei ;

Li, Xiangcun ;

He, Gaohong ;

Jiang, Xiaobin .

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2022, 61 (01) :765-776

[39] Process optimization in batch crystallization of sodium fluosilicate [J].

Zhao, RX .

CRYSTAL RESEARCH AND TECHNOLOGY, 2005, 40 (03) :243-247

[40] Stochastic Nucleation for Feedback-Controlled Cooling Crystallization without Seeding [J].

Sugita, Kazuta ;

Unno, Joi ;

Hirasawa, Izumi .

CHEMICAL ENGINEERING & TECHNOLOGY, 2023, 46 (11) :2265-2272

← 1 2 3 4 5 →