Modeling of crystal size distribution in a mixed suspension, mixed product removal crystallizer when growth is size dependent

Mydlarz, J.; Briedis, Daina

doi:10.1016/0956-9618(93)80020-r

Cited by 7 publications

(3 citation statements)

References 25 publications

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“…16,17 Two of these models are retained here and compared: a power-law function model developed by Abegg, Stevens and Larson, called the ASL model, [18][19][20] and an exponential-law function model developed by Mydlarz and Jones in 1993, called the MJ3 model by the authors. [21][22][23] It is called the MJ model in this paper.…”

Section: Theorymentioning

confidence: 99%

Crystallization Kinetics of Calcium Lactate in a Mixed-Suspension-Mixed-Product Removal Crystallizer

Chemaly

Muhr

Fick

1999

Ind. Eng. Chem. Res.

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Continuous crystallization of calcium lactate pentahydrate was investigated in a mixed-suspension-mixed-product removal crystallizer. Wide ranges of the mean residence time, relative supersaturation, and magma density were covered (40−215 min, 0.01−1.12, and 2−65 kg/m3, respectively). Crystal growth was found to be dependent on crystal size. The Abegg, Stevens, and Larson model and the Mydlarz and Jones model were tested for the determination of the kinetics parameters from experimental results. Zero-size and larger size crystal growth rate values were found to be on the order of 10-13 and 10-8 m/s, respectively. A first-order growth kinetics resulted for both large and small crystals. Nucleation rate values were very high (≈1013−1015 no./m3·s). Nucleation kinetics could not be described by a unique power law equation because two different nucleation mechanisms appeared to control crystallization at low and high residence times, respectively.

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Section: Theorymentioning

confidence: 99%

Crystallization Kinetics of Calcium Lactate in a Mixed-Suspension-Mixed-Product Removal Crystallizer

Chemaly

Muhr

Fick

1999

Ind. Eng. Chem. Res.

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“…Application of the proposed exponential-hyperbolic model for growth date estimation Simulated data JONES (1989b, 1993), MYDLARZ and MYDLARZ and BRIEDIS (1993) have shown that use of simulated data of known characteristics is very useful in making an absolute comparison between the alternative methods of CSD analysis. Two sets of such Crystal size, L urn) …”

Section: Msmpr Crystallizer Cumulative Number Oversize Distributionmentioning

confidence: 99%

An Exponential‐Hyperbolic Crystal Growth Rate Model

Mydlarz

1995

Cryst. Res. Technol.

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A new exponential-hyperbolic size-dependent crystal growth rate function G (L) = Gm(eaL -b)/ (eaL -c) is proposed. The model has been examined in detail for the direct determination of size-dependent crystal growth rates from the cumulative number oversize distribution of continuous Mixed-Suspension Mixed-Product Removal (MSMPR) crystallizers using both simulated and realistic data, both for systems that hold and that violate McCabe's AL law, respectively. It is show that direct fitting of cumulative number oversize distribution data using the proposed model gives an improved estimation of effective crystal growth rates over the whole size range during MSMPR crystallization compared with previous models tested.

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“…The development of continuous MSMPRC dates back to half century ago when population and mass balances were solved to model CSD in MSMPRC . Since the 1980s, both modeling and experimental works were carried out in literature to design and control continuous crystallization in MSMPRC to measure crystallization kinetics and/or achieve a target CSD. ,,,− Mashingaidze et al developed a mathematical model for continuous MSMPRC as a dissolver to tailor CSD . Nishio et al designed a small-scale MSMPRC for kinetics measurement .…”

Section: Introductionmentioning

confidence: 99%

Application of Wet Milling-Based Automated Direct Nucleation Control in Continuous Cooling Crystallization Processes

Yang

Song

Zhang

et al. 2016

Ind. Eng. Chem. Res.

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A novel wet milling-based automated direct nucleation control (WMADNC) concept is proposed and implemented in two continuous cooling crystallization processes in this work. In process 1, WMADNC is implemented upstream to provide closed-loop controlled primary nucleation kinetics and produce seed crystals in situ for continuous mixed suspension mixed product removal crystallizer (MSMPRC). In process 2, WMADNC is applied downstream to achieve closed-loop controlled secondary nucleation kinetics and reduce particle size for crystals in the MSMPRC through recycling. For both processes, a focused beam reflectance measurement (FBRM)-based closed-loop control approach is successfully implemented to control the nucleation kinetics inside the wet mill therefore to control the final chord length distribution (CLD). In the proposed WMADNC approach, the process critical quality attributes (CQA) (e.g., particle number or size) can be directly controlled by the automated closed-loop control framework, which on one hand is aligned with the quality-by-design (QbD) concept, and on the other hand also applies the new quality-by-control (QbC) framework in continuous crystallization processes. Although the proposed WMADNC approach was not able to improve startup dynamics, it can provide high quality control of CLD and automated and effective disturbance rejection for continuous cooling crystallization processes.

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Modeling of crystal size distribution in a mixed suspension, mixed product removal crystallizer when growth is size dependent

Cited by 7 publications

References 25 publications

Crystallization Kinetics of Calcium Lactate in a Mixed-Suspension-Mixed-Product Removal Crystallizer

Crystallization Kinetics of Calcium Lactate in a Mixed-Suspension-Mixed-Product Removal Crystallizer

An Exponential‐Hyperbolic Crystal Growth Rate Model

Application of Wet Milling-Based Automated Direct Nucleation Control in Continuous Cooling Crystallization Processes

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