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A novel nonaqueous solution, triethylenetetramine (TETA) blended with polyethylene glycol (PEG200), was developed for CO2 absorption, with which a phase-changing phenomenon was observed after the absorption. A reaction mechanism for TETA–PEG200 solution and CO2 was proposed based on 13C NMR analysis. It was found that PEG200 not only acts as a solvent that contributes to biphasic separation but also gets involved in the reactions, leading to an increased CO2 absorption capacity. Results show that 1 M TETA–PEG200 solution exhibits a high CO2 capacity of 1.63 mol/mol TETA, which is comparable to a TETA–water solution. The capacity is only slightly affected when the temperature rises up to 60 °C. Moreover, the solution demonstrates good thermostability similar to typical functionalized ionic liquids (ILs) while presenting much lower viscosity than the ILs. For regeneration processes, microwave heating was identified to be a more effective method than classic heating. The solution shows a regeneration efficiency as high as 96% after four absorption–desorption cycles.

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Innovation network has been viewed as one of the most important means in improving technological capabilities for decades. Based on literature review, this paper presents a conceptual model on the relationships between the construction of innovation networks and the development of technological capabilities of industrial clusters in China. Applying this model we conduct a case study on reviewing history path of Zhejiang Haining leather industrial cluster. Conclusions can be drawn as follows: firstly, industrial clusters in China take on specific paradigm for technology acquisition by constructing external innovation networks; secondly, assimilation of acquired external technology resources and their translation into technological capabilities of clustered firms need support from internal innovation networks of industrial clusters; thirdly, quasi-external network, as a nexus between external and internal innovation networks of industrial clusters supported by collective learning, helps promote the effective development of technological capabilities of industrial clusters in China.