Sucrose Crystallization: Modeling and Evaluation of Production Responses to Typical Process Fluctuations

Castro, Bruno José Chiaramonte de; Marciniuk, Melécio; Giulietti, Marco; Bernardo, André

doi:10.1590/0104-6632.20190363s20180240

Cited by 15 publications

(6 citation statements)

References 23 publications

(34 reference statements)

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“…There is no agreement in literatures about sucrose's theoretical ideal habit and, depending on the operating conditions, namely the presence of impurities, the growth kinetics of the different faces will vary which results in the diversification of crystal shapes. 11,12 The procedures developed using sucrose "as model material" is then utilized to understand the impact of solvent on the particle properties of the API.…”

Section: Model Sample Selection-sucrosementioning

confidence: 99%

Quantitative Microscopy: Particle Size/Shape Characterization, Addressing Common Errors Using ‘Analytics Continuum’ Approach

Saravanan

Muthudoss

Khullar

et al. 2021

Journal of Pharmaceutical Sciences

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Particle size/shape characterization of active pharmaceutical ingredient (API) is integral to successful product development. It is more of a correlative property than a decision-making measure. Though microscopy is the only technique that provides a direct measure of particle properties, it is neglected for reasons like non-repeatability and non-reproducibility which is often attributed to a) fundamental error, b) segregation error, c) human error, d) sample randomness, e) sample representativeness etc. Using the "Sucrose" as model sample, we propose "analytics continuum" approach that integrates optical microscope PSD measurements complimented by NIR spectroscopy-based trending analysis as a prescreening tool to demonstrate sample randomness and representativeness. Furthermore, plethora of statistical tests are utilized to infer population statistics. Subsequently, an attribute-based control chart and bootstrap-based confidence interval was developed to monitor product performance. A flowchart to serve as an elementary guideline is developed, which is then extended to handle more complex situations involving API crystallized from two different solvent systems. The results show that the developed methodology can be utilized as a quantitative procedure to assess the suitability of API/excipients from different batches or from alternate vendors and can significantly help in understanding the differences between material even on a minor scale.

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Section: Model Sample Selection-sucrosementioning

confidence: 99%

Quantitative Microscopy: Particle Size/Shape Characterization, Addressing Common Errors Using ‘Analytics Continuum’ Approach

Saravanan

Muthudoss

Khullar

et al. 2021

Journal of Pharmaceutical Sciences

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“…Коэффициенты модели (23) равны: a 0 = 0,18822524; a 1 = 1,4168116; a 2 = 0,61027645; a 3 = 0,62882917; a 4 = 0,32209431; a 5 = 0,29126081; a 6 = 0,29813377; a 7 = 0,21398706; a 8 = 0,015677561; a 9 = 7,5; a 10 = 0,62516922; a 11 = 0,66918776; a 12 = 0,37433054; a 13 = 2,0826152. Формулы ( 23)-( 26) служат для пересчета скорости роста свободного монокристалла (формулы (13)-( 22)) в удельную скорость роста стесненного коллектива кристаллов, средний размер которых [42,43].…”

Section:  unclassified

“…Таким образом, создана обобщенная вероятностная математическая модель ( 13)-( 26) для описания удельной скорости роста кристаллов при массовой кристаллизации сахарозы, которая может быть использована при имитационном моделировании процесса, его исследовании и для оптимального управления в промышленном производстве. Идентификация модели может быть реализована подстройкой коэффициента 0 a в формуле (23).…”

Section:  unclassified

“…В работе B. J. C. de Castro и др. с использованием ПО EMSO разработана феноменологическая модель, позволяющая определять концентрацию кристаллов в утфеле, чистоту мелассы и утфеля, а также распределение кристаллов по размерам [23]. Отмечается, что стоимость ПО EMSO составляет значительную часть производственных затрат.…”

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Specific Mass Growth Rate of Sugar Crystals: Probabilistic Modeling

Арапов

Kuritsyn

Petrov

et al. 2021

Food Processing: Techniques and Technology

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Introduction. The present research featured industrial sugar crystallization. The article introduces a generalized mathematical model of specific growth rate of sugar crystals depending on temperature, solids, and the purity of solution, as well as on the concentration and average size of crystals. The model includes the probabilistic component of growth rate of monocrystals and the reduced adjustment of the constrained crystal growth depending on the abovementioned as-pects. Study objects and methods. The research focused on mass crystallization of sucrose, including the growth rate of monocrystals and the number of crystals in the fill mass. The obtained experimental data were processed using nonlinear programming. Results and discussion. 421 experiments made it possible to develop a probabilistic mathematical model of specific mass growth rate of sugar monocrystals and its dependence on the solution temperature, purity, and solids content. Model error: ± 11.3%. The model covers the temperature range, concentration of solids, and purity of the solution. The proximity of crystals was calculated according to the dependence of the growth rate on their concentration and the average size (error: ± 1.3%). The adjustment range: concentration of crystals = 5–60%, average size = 0.25–1.50 mm. Conclusion. The present generalized mathematical model of crystallization considered the temperature, as well as the purity and solids content in the fill mass, the concentration of sucrose crystals and their average size. The research compared the effect of linear size and concentration of sugar monocrystals on the calculated and experimental sizes of specific mass growth rate and the dimensionless adjustment of growth rate. The calculated sizes proved to be close to the ex-perimental data, which showed adequacy to the developed crystallization model. The research results can be used to optimize the process of mass sugar crystallization.

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“…С другой стороны, особенность литературных источников, с очевидностью, указывает на ускорение перехода научного сообщества в области сахарного производства к использованию в исследованиях углубленного научного анализа, основанного на проведении опытов с использованием новейших образцов в области экспериментального оборудования [10][11][12][13][14][15][16][17][18][19][20]. Это связано с тем, что на практике в растворах, в том числе, и сахарсодержащих, явление кристаллообразования часто протекает в условиях, при которых, увеличивая свой размер, кристалл по габитусу отклоняется от своей классической формы в чистом растворе, т. е. становится дефектообразным.…”

Section: Introductionunclassified

Simulation of the growth of sucrose crystals in a sugar-containing solution

Семенов

Slavyanskiy

Gribkova

et al. 2021

Vestn. Voronež. gos. univ. inž. tehnol.

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Crystallization is one of the most important steps in the technological flow of commodity sugar. By its nature, it develops in a fairly wide temperature range, conditions of varying concentration of the solution, its peptization and other mass-exchange process of formation and growth of sugar crystals in a sugar solution by diffusion transfer in it sucrose molecules. To this it is necessary to add such complicating physical and mathematical formalization phenomena, affecting crystallization, such as the shape of the crystal, purity, viscous properties and surface tension of the solution, the presence of non-sugars, etc. Therefore, among the factors that determine the whole process, the factors usually take place, keeping among them only priority and most important from the point of view of the study. The article, unlike known analogues, provides justification and quantitative analysis of the kinetics of the sucrose crystallization process, taking into account the features of the crystal shape and diffusion properties of the solution. From the point of view of classical diffusion theory, the phenomenon of crystallization is interpreted as molecular with infinite rate of perilation from the source of diffusion transfer in the solution of sucrose molecules, so that the concentration in the sugar-containing liquid system is also supposed to change instantly at each point. However, since in the real world this effect is not observed, in order to resolve this contradiction, introduce the concepts of the indignant and unperturbed, separated by the diffusion front of the concentration of the regions of these phase states. Using the kinematic characteristics of the front, determine the time of the crystallization process in general in both phases. This allows us to calculate the processing period of the solution with greater accuracy than the results obtained on the basis of classical theory.

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Sucrose Crystallization: Modeling and Evaluation of Production Responses to Typical Process Fluctuations

Cited by 15 publications

References 23 publications

Quantitative Microscopy: Particle Size/Shape Characterization, Addressing Common Errors Using ‘Analytics Continuum’ Approach

Quantitative Microscopy: Particle Size/Shape Characterization, Addressing Common Errors Using ‘Analytics Continuum’ Approach

Specific Mass Growth Rate of Sugar Crystals: Probabilistic Modeling

Simulation of the growth of sucrose crystals in a sugar-containing solution

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