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Study On Styrene Epoxidation Catalyst And Computer Aided Process Optimization

Posted on:2020-01-27Degree:MasterType:Thesis
Country:ChinaCandidate:F LvFull Text:PDF
GTID:2381330623960207Subject:Chemical Engineering and Technology
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Ethylene styrene is an important raw material for the bulk and the fine chemical industries.It is widely used in chemical,pharmaceutical,perfumery and other chemical fields.Styrene epoxidation is an important method for the preparation of styrene oxide.So the reaction has been extensively studied.In this paper,there are two levels of research on the epoxidation of styrene.One is the study of the process system with the reaction process conditions as the research object,and the other is the catalytic system research of the catalyst.We used traditional experiments,computer-aided modeling,optimization and other means,with the goal of economy,green,environmental protection and high efficiency of styrene epoxidation,to obtain better process conditions and more efficient new catalysts.The article draws the following conclusions:(1)a novel prediction and optimization method based on improved generalized regression neural network(GRNN),and particle swarm optimization(PSO)algorithm is proposed to optimize the process conditions for styrene epoxidation to achieve higher yields.This model was designed to optimize five input parameters,the output of the improved GRNN was given to the PSO algorithm to optimize the process conditions.The optimal smoothing parameter ?(0.1)of GRNN was chosen from the training sample with a minimum cross-validation error(0.001).Under the appropriate five process conditions(reaction temperature,reaction time,amount of catalyst,amount of solvent,oxidant),the maximum yield reached 95.76%.So the new model of improved GRNN hybrid PSO algorithm is anticipated to accomplish as a useful tool for optimization of process conditions for styrene epoxidation.(2)Lotus-type holes two-dimensional NiO nanosheets were fabricated via hydrothermal method followed by calcinations.Three types of surfactants as the structure-directing agent in an ammonia aqueous solution with calcination,onlyanionic surfactant sodium dodecyl benzene sulfonate(SDBS),non-ionic surfactant polyvinyl pyrrolidone(PVP)can form lotus-type porous NiO nanosheets,cationic surfactant cetyltrimethyl ammonium bromide(CTAB)have no such effect.A series of characterization of the resulting samples revealed that the materials maintained singularly small thickness of only 3-5 nm,lotus root hole diameter 40nm(SDBS),20nm(PVP).The formation mechanism of the lotus-type porous two-dimensional morphology is investigated.The as-synthesized NiO without support delivered efficient catalytic property in styrene epoxidation which significantly reduced reaction time.When the catalyst was reused the conversion and selectivity of styrene oxide still remained high.
Keywords/Search Tags:Styrene epoxidation, Artificial neural networks, Optimization, Surfactants, Nano flake NiO
PDF Full Text Request
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