Chemical modifications of porous materials almost always result in loss of structural integrity, porosity, solubility, or stability. Previous attempts, so far, have not allowed any promising trend to unravel, perhaps because of the complexity of porous network frameworks. But the soluble porous polymers, the polymers of intrinsic microporosity, provide an excellent platform to develop a universal strategy for effective modification of functional groups for current demands in advanced applications. Here, we report complete transformation of PIM-1 nitriles into four previously inaccessible functional groups – ketones, alcohols, imines, and hydrazones – in a single step using volatile reagents and through a counter-intuitive non-solvent approach that enables surface area preservation. The modifications are simple, scalable, reproducible, and give record surface areas for modified PIM-1s despite at times having to pass up to two consecutive post-synthetic transformations. This unconventional dual-mode strategy offers valuable directions for chemical modification of porous materials.
The development of carbon-based reverse osmosis membranes for water desalination is hindered by challenges in achieving a high pore density and controlling the pore size.
2020 was a year when international trade activities are not favourable. However, Vietnam still ranked in the group of countries with the highest growth in the world. And prominent in that economic picture is Vietnam’s export activities. Therefore, it is really urgent to find suitable solutions to help export continuously maintain its role as the key engine of growth in the context of increasingly complex disease developments. To assess the impact of the epidemic and some macro factors on export activities, this study used regression models for panel data with latent variables to measure main factors: supply, demand, motivation, and barriers to Vietnam’s export activities in the period 2012-2020 through exploratory factor analysis method. The obtained results have shown the effectiveness of combining the factor analysis method in estimating regression models by the ordinary least square (OLS) method, especially in the context of big data, along with the rapid increase in the dimension of the observed variables.
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