The CO2 emission content of post-combustion flue gas cannot be ignored in the whole petroleum and natural gas industries chain. Membrane separation technology becomes a potential method of CO2 capture because of its advantages of large flux, energy saving and low cost. Thin-Film Composite (TFC) membrane has attracted extensive attention due to its flexible structure and wide application range. Selecting the suitable layer as the core of the separation membrane is the key to obtain a high-performance TFC membrane which is suitable for practical application environment. In this review, we summarize the development trend of selective layer of TFC membrane for CO2 capture and explore related synthesis methods and different materials. Finally, we highlight the outstanding challenges and opportunities for the future research in this field.
In view of the characteristics of standard quality evaluation index diversification, multi-dimension and the result susceptible to subjective factors, a standard quality evaluation model based on T-S model of fuzzy neural network is established by introducing fuzzy system theory. This model combines the advantages of fuzzy system and neural network, such as good fuzzy knowledge expression ability and adaptive ability. It has the advantages of optimal result approximation, short training time and fast convergence speed. This model was used to evaluate the quality of 7 standards in the field of petroleum engineering. The results show that the fuzzy neural network method could solve the fuzzy data processing problem in standard quality evaluation, and the reliability of the evaluation model could also meet the requirements of standard quality evaluation.
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