Machine Learning-Assisted Discovery of Propane-Selective Metal-Organic Frameworks.

Machine learning is gaining momentum in the prediction and discovery of materials for specific applications. Given the abundance of metal-organic frameworks (MOFs), computational screening of the existing MOFs for propane/propylene (C3H8/C3H6) separation could be equally important for developing new MOFs. Herein, we report a machine learning-assisted strategy for screening C3H8-selective MOFs from the CoRE MOF database. Among the four algorithms applied in machine learning, the random forest (RF) algorithm displays the highest degree of accuracy. We experimentally verified the identified top-performing MOF (JNU-90) with its benchmark selectivity and separation performance of directly producing C3H6. Considering its excellent hydrolytic stability, JNU-90 shows great promise in the energy-efficient separation of C3H8/C3H6. This work may accelerate the development of MOFs for challenging separations.

Dehydration-Induced Cluster Consolidation in a Metal-Organic Framework for Sieving Hexane Isomers.

Metal-organic frameworks (MOFs) that exhibit dynamic phase-transition behavior under external stimuli could have great potential in adsorptive separations. Here we report on a zinc-based microporous MOF (JNU-80) and its reversible transformation between two crystalline phases: large pore (JNU-80-LP) and narrow pore (JNU-80-NP). Specifically, JNU-80-LP can undergo a dehydration-induced cluster consolidation under heat treatment, resulting in JNU-80-NP with a reduced channel that allows exclusion of di-branched hexane isomers while high adsorption of linear and mono-branched hexane isomers. We further demonstrate the fabrication of MOF-polymer composite (JNU-80-NP-block) and its application in the purification of di-branched isomers from liquid-phase hexane mixtures (98 % di-branched) at room temperature, affording the di-branched hexane isomers with 99.5 % purity and close to 90 % recovery rate over ten cycles. This work illustrates an interesting dehydration-induced cluster consolidation in MOF structure and the ensuing channel shrinkage for sieving di-branched hexane isomers, which may have important implications for the development of MOFs with dynamic behavior and their potential applications in non-thermal driven separation technologies.

On a product-type operator from weighted Bergman-Orlicz space to some weighted type spaces.

Let [Formula: see text] be the open unit disk, [Formula: see text] an analytic self-map of [Formula: see text] and [Formula: see text] an analytic function on [Formula: see text]. Let D be the differentiation operator and [Formula: see text] the weighted composition operator. The boundedness and compactness of the product-type operator [Formula: see text] from the weighted Bergman-Orlicz space to the Bers type space, weighted Bloch space and weighted Zygmund space on [Formula: see text] are characterized.

An ato-topology metal-organic framework with large C2H2 adsorption and C2H2/CO2 separation capacity.

The efficient separation of C2H2/CO2 is challenging and energy intensive due to their similar molecular shapes and kinetic diameters. Here we report an ato-topology metal-organic framework (JNU-7a) with a specific surface area of 2046 cm2 g-1 and open-metal-site density of 2.05 mmol cm-3, resulting in a large C2H2 adsorption capacity of (176 cm3 g-1) and high C2H2/CO2 adsorption selectivity (6.2).

One-pot synthesis of 2-substituted benzo[b]furans via Pd-tetraphosphine catalyzed coupling of 2-halophenols with alkynes.

A catalyst composed of [Pd(η(3)-C3H5)Cl]2 and N,N,N',N'-tetra(diphenylphosphinomethyl)pyridine-2,6-diamine (L) was found to be effective for one-pot synthesis of 2-substituted benzo[b]furans from 2-halophenols and alkynes. For 2-bromo-3-hydroxypyridine, the catalyst loading could be as low as 1 ppm and the turnover number (TON) was up to 870,000.