Design of bypass-simulated moving bed chromatography for reduced purity requirements

Maruyama, Rafael Teruo; Karnal, Preetika; Sainio, Tuomo; Rajendran, Arvind

doi:10.1016/j.ces.2019.05.003

Cited by 18 publications

(9 citation statements)

References 18 publications

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“…Results reported in earlier literature 39,40 have shown through numerical analyses that when the purity requirements are relaxed, the (m 2 , m 3 ) point moves in the corresponding plane similarly in both the linear and the nonlinear cases. On the basis of this analogy, the findings reported for the linear isotherm can be extended to nonlinear isotherm cases, for which the m j values need to be obtained numerically by running the full SMB model simulations.…”

Section: Effect Of Additional Design Parametersmentioning

confidence: 66%

Optimizing the Yield of a Pure Enantiomer by Integrating Chiral SMB Chromatography and Racemization. Part 2: Theory

Breveglieri

Otgonbayar

Mazzotti

2021

Ind. Eng. Chem. Res.

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We address the purification of the target enantiomer of a chiral compound from its racemic mixture, through simulated moving bed (SMB) chromatography either as a standalone or combined with the recycle and racemization of the undesired enantiomer. We carry out a comparative assessment of the two processes with focus on the role of the racemization kinetics, on the effect of the selectivity of the chiral stationary phase, and of the upstream symmetric synthesis of the racemate. The analysis is general thanks to the methods adopted for the optimal design of the integrated process (with racemization) and for the sizing of the SMB unit, as well as for the use of the four generalized Langmuir adsorption isotherms. In this way, we determine quantitative criteria that show that the standalone SMB process outperforms the integrated process when the performance of the racemization catalyst or the chiral stationary phase is poor and the racemic feed is inexpensive.

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Section: Effect Of Additional Design Parametersmentioning

confidence: 66%

Optimizing the Yield of a Pure Enantiomer by Integrating Chiral SMB Chromatography and Racemization. Part 2: Theory

Breveglieri

Otgonbayar

Mazzotti

2021

Ind. Eng. Chem. Res.

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“…where θ is the new parameter population, θ PSO is a matrix of PSO parameters, x is a vector of 3 × 10 4 random variables following a Gaussian distribution, f(x) is a Gaussian probability density function at point x, and V y is a square matrix of PSO population variance, as given by (15) (16) where is the average value of parameter p i and p i PSO is the parameter p i generated by PSO. This new population is then plotted considering combinations between the parameters in order to show the coverage region fully populated in 2D and 3D, the latter when considering the objective function value.…”

Section: Uncertainty Evaluationmentioning

confidence: 99%

“…5 However, a rigorous identification of the AIE has seldom been done. Maruyama et al (2019) compared linear and nonlinear isotherms in a bypass SMB applying numerical simulations based on the equilibrium theory of chromatography, and Subraveti et al (2023) presented the capabilities of machine learning to describe the AIE in adsorption-emulated chromatographic columns, but not in an SMB unit. 16,17 Different authors, such as Rajendran simulator in order to describe the adsorption phenomenon instead of choosing a particular isotherm equation.…”

Section: Introductionmentioning

confidence: 99%

Strategies for Simulated Moving Bed Model Parameter Estimation Based on Minimal System Minimal Knowledge: Adsorption Isotherm Equation Screening and Estimability Analysis

Santos,

Rebello,

Prudente

et al. 2023

Ind. Eng. Chem. Res.

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The simulated moving bed (SMB) is a widely recognized technique for the resolution of several high-value-added compounds, and its mathematical modeling plays a crucial role in predicting its behavior. However, modeling can be challenging as it needs parameter estimation and topology definition, especially for such complex systems. SMB modeling might incorporate different adsorption isotherm equations (AIEs), which might better represent the behavior of a certain mixture to be separated. This work proposes two methodologies for SMB modeling and AIE selection relying on minimal system knowledge that can provide a representative model by a global parameter estimation instead of the traditional "Step by Step" approach. The first methodology proposes an architecture for global parameter estimation that encompasses the screening of the most suitable AIE in the lower level and the definition of the minimum number of experiments necessary for model identification in the upper level. In the second methodology, an extended generic isotherm, a combination of AIE, is formulated; and an estimability analysis is carried out to determine the estimable parameters. Both methodologies apply Latin Hypercube Sampling (LHS) for the design of experiments and emulation of a real unit by incorporating noise in the experimental data under a Gaussian error distribution. Moreover, uncertainty evaluation and data reconciliation are performed to enhance the robustness, reliability, and precision of the proposed approaches. The methodologies are validated by considering experimental data from the literature, apart from the LHS-generated samples, and are subject to cross-validations. Finally, the two methodologies are compared, with the first methodology demonstrating a superior performance for the case study. This work contributes to the advancement of SMB modeling, providing valuable tools for parameter estimation and AIE selection.

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“…Combined with crystallization operation, the purity was further improved to 97.8%, and the yield reached 95%. In 17 , Maruyama et al proposed a new method called bypass simulation moving bed. It provides additional freedom and opportunities to improve productivity.…”

Section: Literature Reviewsmentioning

confidence: 99%

Applicant hierarchical fuzzy controller for concentration control of simulated moving bed

Xie

Tang

2021

Sci Rep

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Simulated moving bed (SMB) is a kind of continuous process which can increase the efficiency of adsorbents in the adsorbent bed. It contains several sectors of flow rate, the switching time of valves and many other possible influencing variables, moreover, these parameters are highly sensitive, so it is very difficult to achieve precise prediction and control. Model predictive control and PID controller are often used in industrial system. Model predictive control needs a lot of accurate industry experience data, and PID controller depends on the selection of control parameters. Therefore, SMB needs an intelligent controller to bypass those complex mechanisms and parameter adjustment processes. This paper we propose the hierarchical fuzzy controller fuzzy controller which is applied to the SMB system to observe the final concentration. Compared with the PID and MPC controller, it is found that the hierarchical fuzzy controller can control good without knowing the system parameters too accurately.

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Design of bypass-simulated moving bed chromatography for reduced purity requirements

Cited by 18 publications

References 18 publications

Optimizing the Yield of a Pure Enantiomer by Integrating Chiral SMB Chromatography and Racemization. Part 2: Theory

Optimizing the Yield of a Pure Enantiomer by Integrating Chiral SMB Chromatography and Racemization. Part 2: Theory

Strategies for Simulated Moving Bed Model Parameter Estimation Based on Minimal System Minimal Knowledge: Adsorption Isotherm Equation Screening and Estimability Analysis

Applicant hierarchical fuzzy controller for concentration control of simulated moving bed

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