The oxidation of para‐xylene to terephthalic acid has been commercialised as the AMOCO process(Co/Mn/Br) that uses a homogeneous catalyst of cobalt and manganese together with a corrosive bromide compound as a promot...The oxidation of para‐xylene to terephthalic acid has been commercialised as the AMOCO process(Co/Mn/Br) that uses a homogeneous catalyst of cobalt and manganese together with a corrosive bromide compound as a promoter. This process is conducted in acidic medium at a high tempera‐ture(175–225 °C). Concerns over environmental and safety issues have driven studies to find mild‐er oxidation reactions of para‐xylene. This review discussed past and current progress in the oxida‐tion of para‐xylene process. The discussion concentrates on the approach of green chemistry in‐cluding(1) using heterogeneous catalysts with promising high selectivity and mild reaction condi‐tion,(2) application of carbon dioxide as a co‐oxidant, and(3) application of alternative promoters. The optimisation of para‐xylene oxidation was also outlined.展开更多
In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation fa...In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.展开更多
基金The National Natural Science Foundation of China(No.21276050)the Scientific Research Foundation of Graduate School of Southeast University(No.YBJJ1341)
基金supported by Universiti Malaysia Pahang and the Ministry of Education, Malaysia for Exploratory Research Grant Scheme (ERGS) (RDU 120605) Ministry of Education, Malaysia support for MyPhD funding aid (Nor Aqilah Mohd Fadzil)
文摘The oxidation of para‐xylene to terephthalic acid has been commercialised as the AMOCO process(Co/Mn/Br) that uses a homogeneous catalyst of cobalt and manganese together with a corrosive bromide compound as a promoter. This process is conducted in acidic medium at a high tempera‐ture(175–225 °C). Concerns over environmental and safety issues have driven studies to find mild‐er oxidation reactions of para‐xylene. This review discussed past and current progress in the oxida‐tion of para‐xylene process. The discussion concentrates on the approach of green chemistry in‐cluding(1) using heterogeneous catalysts with promising high selectivity and mild reaction condi‐tion,(2) application of carbon dioxide as a co‐oxidant, and(3) application of alternative promoters. The optimisation of para‐xylene oxidation was also outlined.
基金Supported by the Major State Basic Research Development Program of China (2012CB720500)the National Natural Science Foundation of China (Key Program: U1162202)+1 种基金the National Natural Science Foundation of China (General Program:61174118)Shanghai Leading Academic Discipline Project (B504)
文摘In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained.
