Development of a Multiscale Strategy and Application to Chemical Vapor Deposition

Achenie, Luke E.K.; Sharifi, Yousef; Lee, D.G.

doi:10.1016/b978-0-444-63683-6.00004-6

Cited by 5 publications

(2 citation statements)

References 44 publications

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“…The optimization problem has been coded in GAMS® 34.2.0 to perform the multi-objective optimization. This tool is the most used to solve multi-objective optimization problems (Achenie et al 2016;Arora, 2017). The Pareto front was constructed through the ε-constraints method.…”

Section: Description Of Response Surface Methodology and Optimization...mentioning

confidence: 99%

Modeling and Optimization of Coagulation-Flocculation Process to Remove High Phosphate Concentration in Wastewater from a Metal-Mechanic Industry

Gómez-Rodríguez,

Gómez-Castro,

Gamiño-Arroyo

et al. 2024

Environ Model Assess

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In this work, the performance of a coagulation-occulation plant to treat wastewater from a metalmechanic industry located in an industrial park of Queretaro city, Mexico is studied. Wastewater samples were obtained from the homogenization tank and treated with the employed industrial reactants through an experimental jar test to obtain statistical data. Then, a response surface methodology with ANOVA analysis was used to model the process, and the ε-constraints methodology was used to optimize the coagulation-occulation process in terms of economic and environmental impact. Optimal operating conditions were found at 400 mg L − 1 of calcium hydroxide dose, 0.723 mL L − 1 of aluminum salts dose, 3.32x10 − 3 mg L − 1 occulant dose and 100 rpm of agitation speed. The results showed an improvement of phosphates removal, but a minimal increment of 1.01% of operational costs regarding to the current operating conditions.

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Section: Description Of Response Surface Methodology and Optimization...mentioning

confidence: 99%

Modeling and Optimization of Coagulation-Flocculation Process to Remove High Phosphate Concentration in Wastewater from a Metal-Mechanic Industry

Gómez-Rodríguez,

Gómez-Castro,

Gamiño-Arroyo

et al. 2024

Environ Model Assess

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“…An example of a reaction following the above mechanism is the conversion of monosilane for the production of high-grade polysilicon . The deposition rate is affected by thermodynamic, kinetic, and mass diffusion factors, any of which may be dominant depending on the operating conditions of the reactor . Those factors are described in the dynamic model for the lab batch reactor, which is obtained by performing material balances: where component j is described by its inlet feed concentration, C j in [mol·m –3 ], its amount of substance in the gas phase, n j g [mol], and its amount of substance in the solid phase on top of the substrate, n j s [mol]; t [s] is the reaction time; Ḟ in [m 3 · s –1 ] and Ḟ out [m 3 ·s –1 ] are, respectively, the inlet and outlet volumetric flow rates of the carrier gas; h m, j [m·s –1 ] is the gas to solid phase mass transfer coefficient of component j ; V [m 3 ] is the gas phase reaction volume; V int [m 3 ] is the solid–gas interface volume; and A [m 2 ] is the glass surface area in contact with the gas.…”

Section: Aacvd Process Modelmentioning

confidence: 99%

Mathematical Modeling for the Design and Scale-Up of a Large Industrial Aerosol-Assisted Chemical Vapor Deposition Process under Uncertainty

Filho

Carmalt

Angeli

et al. 2020

Ind. Eng. Chem. Res.

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Aerosol-assisted chemical vapor deposition (AACVD) can be used to produce coatings and thin films such as transparent conducting oxide (TCO) films, which are used in self-cleaning surfaces, solar cells, and other electronic and optoelectronic applications. A process based on AACVD consists of a number of steps: aerosol generation, aerosol transport, aerosol delivery, and chemical deposition. Predicting the behavior of such a process at an industrial scale is challenging due to a number of factors: the aerosol generation creates droplets of different sizes, losses are incurred in the transport, the delivery must evaporate the solvent to release the precursors, and the reactions on the surface of the deposition target may be complex. This paper describes a full process model, including the prediction of the size distribution of the generated aerosol, the number and size of droplets delivered, the carrier gas temperature profile at the reaction site, the solvent evaporation time, and the rate of film formation. The key modeling challenges addressed include incorporating the impact of uncertainties in parameters such as heat and mass transfer coefficients and reaction rate constants. Preliminary simulations demonstrate a proof of concept for the use of simulation for gaining insights into the feasibility of a process scale-up for an industrial-scale AACVD.

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Investigation of transport processes in a commercial hot wall CVD reactor with multi-substrates for high-quality pyrocarbon deposition

Shinde

Deivendran

Kumar

et al. 2021

Surface and Coatings Technology

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Development of a Multiscale Strategy and Application to Chemical Vapor Deposition

Cited by 5 publications

References 44 publications

Modeling and Optimization of Coagulation-Flocculation Process to Remove High Phosphate Concentration in Wastewater from a Metal-Mechanic Industry

Modeling and Optimization of Coagulation-Flocculation Process to Remove High Phosphate Concentration in Wastewater from a Metal-Mechanic Industry

Mathematical Modeling for the Design and Scale-Up of a Large Industrial Aerosol-Assisted Chemical Vapor Deposition Process under Uncertainty

Investigation of transport processes in a commercial hot wall CVD reactor with multi-substrates for high-quality pyrocarbon deposition

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