The accelerated use of Artificial Neural Networks (ANNs) in Chemical and Process Engineering has drawn the attention of scientific and industrial communities, mainly due to the Big Data boom related to the analysis and interpretation of large data volumes required by Industry 4.0. ANNs are well-known nonlinear regression algorithms in the Machine Learning field for classification and prediction and are based on the human brain behavior, which learns tasks from experience through interconnected neurons. This empirical method can widely replace traditional complex phenomenological models based on nonlinear conservation equations, leading to a smaller computational effort – a very peculiar feature for its use in process optimization and control. Thereby, this chapter aims to exhibit several ANN modeling applications to different Chemical and Process Engineering areas, such as thermodynamics, kinetics and catalysis, process analysis and optimization, process safety and control, among others. This review study shows the increasing use of ANNs in the area, helping to understand and to explore process data aspects for future research.
Resumo Catalisador monolítico comercial de níquel foi selecionado com o objetivo de se determinar o regime cinético da reação de oxidação parcial do metano (OPM). As estruturas cristalinas deste catalisador foram identificadas por DRX. A composição química superficial e o estado químico dos elementos presentes na superfície da amostra foram determinados por EDX. A técnica de microscopia (MEV) com emissão de campo foi utilizada neste trabalho com as finalidades de análise morfológica do catalisador antes de sua utilização nas reações de oxidação parcial. Análises de TG-DTA foram realizadas com o objetivo de se estudar o comportamento térmico do catalisador. A área superficial e a área metálica foram determinadas por BET e Quimissorção, respectivamente. A temperatura de redução do catalisador foi determinada através de TPR. Foi utilizada uma unidade experimental para realização de testes catalíticos. Antes das reações, os catalisadores pulverizados na faixa granulométrica < 0,150 mm foram submetidos a uma etapa de redução para ativar os sítios de níquel metálico. As análises dos produtos de saída do reator e das cargas reagentes foram realizadas por cromatografia gasosa, utilizando-se um Cromatógrafo VARIAN CP3800. Foi determinado o regime cinético na OPM utilizando as massas de catalisador 65, 80 e 95 mg. Palavras-chave: Regime Cinético; Catalisadores; Níquel; Alumina; Oxidação Parcial. KINETIC REGIME OF AN NI/AL2O3 CATALYST IN PARTIAL METHANE OXIDATION REACTIONS Abstract Commercial monolithic nickel catalyst was selected with the objective of determining the kinetic regime of the partial oxidation reaction of methane (OPM). The crystalline structures of this catalyst were identified by XRD. The surface chemical composition and the chemical state of the elements present on the sample surface were determined by EDX. The microscopy technique (SEM) with field emission was used in this work with the purpose of morphological analysis of the catalyst before its use in partial oxidation reactions. TG-DTA analyzes were performed with the objective of studying the thermal behavior of the catalyst. The surface area and the metallic area were determined by BET and Chimimetry, respectively. The catalyst reduction temperature was determined by TPR. An experimental unit was used to carry out catalytic tests. Before the reactions, the pulverized catalysts in the granulometric range <0.150 mm were subjected to a reduction step to activate the metallic nickel sites. Analyzes of the reactor output products and the reagent loads were performed by gas chromatography using a VARIAN CP3800 Chromatograph. The kinetic regime at OPM was determined using the catalyst masses 65, 80 and 95 mg.
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