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

Abstract

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 (C 3 H 8 /C 3 H 6 ) separation could be equally important for developing new MOFs. Herein, we report a machine learningassisted strategy for screening C 3 H 8 -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 C 3 H 6 . Considering its excellent hydrolytic stability, JNU-90 shows great promise in the energy-efficient separation of C 3 H 8 /C 3 H 6 . This work may accelerate the development of MOFs for challenging separations.

Recycling Organic Dyes within the Metal–Organic Framework for Photothermal Conversion

“…Metal–organic frameworks (MOFs), as pioneering crystalline porous materials, have garnered increasing attention for their meticulously engineered structures and a broad spectrum of applications. − The exceptionally high and tunable porosities of MOF materials offer a confined environment for delving into the host–guest chemistry, which involves the incorporation or substitution of particular guest molecules. − Typically, the guest molecules within the MOF pores are not free but are often anchored through various supramolecular interactions, such as hydrogen bonds, π–π stackings, electrostatic forces, or direct coordination with the metal sites. , By means of these host–guest interactions, preferential trapping or separation of target guest molecules can be facilely achieved. − More impressively, the complementary physicochemical properties and intimate interaction between host and guest facilitate the straightforward synthesis of sophisticated multifunctional MOF composites, which present combined properties superior to those of the individual components. − …”