Experimental and modeling studies for intensification of mercaptans extraction from LSRN using a microfluidic system

Mirani, Mohammad Reza; Fazlali, Alireza; Rahimi, Masoud

doi:10.1007/s11814-021-0749-9

Cited by 3 publications

(1 citation statement)

References 33 publications

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“…The authors have declared no conflict of interest. Extraction of mercaptan from naphtha Extraction percentage modeling by ANN 0.9862 [31] Lanthanum extraction from acidic nitrate Extraction percentage prediction by ANN 0.999 [32] Extraction of phenol compounds Modeling of the extraction process by ANFIS 0.997 [33] Extraction of mercaptan from naphtha Extraction percentage prediction by RSM 0.9798 [31] Calcium extraction from the aqueous phase Extraction yield modeling by RSM 0.9830 [34] Copper extraction from an aqueous solution Extraction percentage modeling by RSM 0.985 [35]…”

Section: Comparison With Other Studiesmentioning

confidence: 99%

Experimental Study and Artificial Intelligence Modeling of Dye Removal in Microfluidic Systems

Hosseini

Rahimi²

2023

Chem Eng & Technol

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A modeling approach was utilized to achieve efficient operational conditions for Alizarin removal from synthetic wastewater in a T‐type micromixer. Besides experimental work, the neuro‐fuzzy system and artificial neural network techniques were utilized for this purpose. Input parameters were the pH, the initial Alizarin concentration in the feed, the extractant volume percentage in the organic phase, and the fluid flow rate. Based on the obtained results, both models have high precision. However, the accuracy of the neural network for estimating the extraction percentage is higher compared to that of the neuro‐fuzzy model. The optimal values of the operating parameters were determined by the genetic algorithm technique and the extraction percentage value was obtained as about 99.4 %.

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Section: Comparison With Other Studiesmentioning

confidence: 99%

Experimental Study and Artificial Intelligence Modeling of Dye Removal in Microfluidic Systems

Hosseini

Rahimi²

2023

Chem Eng & Technol

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Lagrangian-based simulation method using constrained Stokesian dynamics for particulate flows in microchannel

Lee,

Jin,

Kim

et al. 2024

J. Fluid Mech.

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A simulation method has been developed to efficiently evaluate the motion of colloidal particles in a low-Reynolds-number confined microchannel flow using a Lagrangian-based approach. In this method, the background velocity within the channel, in the absence of suspended particles, is obtained from a fluid dynamics solver and is used to update the velocity at the particle centres using the Stokesian dynamics (SD) method, which incorporates multi-body hydrodynamic interactions. As a result, instead of computing the momentum of both the fluid and particles throughout the entire computational domain, the microscopic balance equation is solved only at the particle centres, increasing the computational efficiency. To accommodate complex boundary conditions within the SD framework, imaginary particles are placed on the channel walls, allowing the mobility relation to be reformulated to apply velocity constraints to immobilized wall particles. By employing this constrained SD approach, global mobility interactions that need to be computed at each time step are limited to the interior particles, resulting in a significant reduction in computational cost. The efficiency of this study is demonstrated through case studies on particulate flows in contraction and cross-flow microchannels. By using colloidal particles that incorporate Brownian motion and inter-particle attraction, observations through the entire stages of fouling dynamics are possible, from particle inflow to channel blockage. The fouling patterns observed in the simulations are consistent with experiments conducted under the same flow conditions. This study provides an efficient approach for analysing the effect of hydrodynamic interactions on particle dynamics in microfluidics and materials processing fields while allowing for predictions about structural changes over long-time scales, including complex phenomena such as clogging.

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Mercaptan adsorption for desulfurization using a batch microprocess

Mohammadi

Azizzadeh

Raji

2023

Separation Science and Technology

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Experimental and modeling studies for intensification of mercaptans extraction from LSRN using a microfluidic system

Cited by 3 publications

References 33 publications

Experimental Study and Artificial Intelligence Modeling of Dye Removal in Microfluidic Systems

Experimental Study and Artificial Intelligence Modeling of Dye Removal in Microfluidic Systems

Lagrangian-based simulation method using constrained Stokesian dynamics for particulate flows in microchannel

Mercaptan adsorption for desulfurization using a batch microprocess

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