External stimuli or host–guest interactions induce structural changes, producing a gating effect in which an adsorbent suddenly becomes accessible to guest molecules. This effect greatly facilitates gas separation, storage, and molecular detection.
Nitrogen (N2) rejection
from methane (CH4) is the most challenging step in natural
gas processing because
of the close similarity of their physical-chemical properties. For
decades, efforts to find a functioning material that can selectively
discriminate N2 had little outcome. Here, we report a molecular
trapdoor zeolite K-ZSM-25 that has the largest unit cell among all
zeolites, with the ability to capture N2 in favor of CH4 with a selectivity as high as 34. This zeolite was found
to show a temperature-regulated gas adsorption wherein gas molecules’
accessibility to the internal pores of the crystal is determined by
the effect of the gas–cation interaction on the thermal oscillation
of the “door-keeping” cation. N2 and CH4 molecules were differentiated by different admission-trigger
temperatures. A mild working temperature range of 240–300 K
was determined wherein N2 gas molecules were able to access
the internal pores of K-ZSM-25 while CH4 was rejected.
As confirmed by experimental, molecular dynamic, and ab initio density functional theory studies, the outstanding N2/CH4 selectivity is achieved within a specific temperature
range where the thermal oscillation of door-blocking K+ provides enough space only for the relatively smaller molecule (N2) to diffuse into and through the zeolite supercages. Such
temperature-regulated adsorption of the K-ZSM-25 trapdoor zeolite
opens up a new approach for rejecting N2 from CH4 in the gas industry without deploying energy-intensive cryogenic
distillation around 100 K.
Over the last few decades, the optimal
design and operation of energy-intensive
industries such as cryogenic process has gained considerable attention.
Because of their high energy efficiency, compact design, and energy-efficient
heat transfer, mixed refrigerant (MR) systems are used in several
industrial applications. The optimal refrigerant compositionwhich
is difficult to obtainis crucial to the efficiency of MR systems.
In this research, we explore the MR cryogenic process optimization
using 17 different components in the refrigerant stream with normal
boiling points ranging from −268.9 to 36 °C to achieve
the lowest specific energy consumption. Here, we developed a discrete-continuous
genetic algorithm (DCGA) consisting of five steps to resolve the mathematical
difficulties of the many-variable optimization problem. Through conducting
two case studies, we proved that DCGA can locate the optimal solution
in a reasonable amount of time. Compared to the best optimization
practices in the literature, the new approach saved up to 12.5% of
the unit specific energy consumption. In addition to MR systems, DCGA
can also optimize other extreme problems with many independent variables.
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