Multilevel screening of computation-ready, experimental metal-organic frameworks for natural gas purification

Zhi Li, Berend Smit, Yi Zhang
WILEY, 2021
Article

In this study, traditional Monte Carlo simulation and density functional theory-based structural optimization methods were combined to screen computation-ready experimental metal-organic framework (MOF) database for the application of natural gas purification. Our results show that about half of the good performing computation-ready experimental MOF structures displayed various degrees of deformation (even collapse) after the structure optimization. This phenomenon attributed to the strong attraction of unsaturated metals which attract nearby organic components. For some materials with deformation, unsaturated metals form new bonds with the adjacent organic linkers creating distortions that would be unrealistic in the experimental materials. For the remaining relatively stable materials whose structural characteristics did not change too much, we further studied the adsorption performance of their optimized structures. Finally, 12 good-performing MOF materials with high stability were found which could greatly improve the possibility for constructing robust MOFs that could hold open metal sites by experiments.

À propos de ce résultat

Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.

Concepts associés

Chargement

Publications associées

Chargement

Zhi Li, Berend Smit, Yi Zhang
WILEY, 2021
Article

Résumé

Official source

https://infoscience.epfl.ch/record/286487?ln=fr

À propos de ce résultat

Concepts associés (11)

Concepts associés

Chargement

Publications associées (66)

Publications associées

Chargement

Phénomène

Un phénomène est la manière dont une chose, un fait du monde physique (objet, action…), psychique (émotion, pensée…) ou social (produit d'interactions sociales) se manifeste à la sensibilité d'un êtr

Structure

A structure is an arrangement and organization of interrelated elements in a material object or system, or the object or system so organized. Material structures include man-made objects such as buil

Matériau

vignette|Grandes classes de matériaux. Les matériaux minéraux sont des roches, des céramiques ou des verres. Les matériaux métalliques sont des métaux ou des alliages. Un matériau est toute matière ut

Geometric landscapes for material discovery within energy–structure–function maps

Seyedmohamad Moosavi, Berend Smit, Henglu Xu

Porous molecular crystals are an emerging class of porous materials formed by crystallisation of molecules with weak intermolecular interactions, which distinguishes them from extended nanoporous materials like metal–organic frameworks (MOFs). To aid discovery of porous molecular crystals for desired applications, energy–structure–function (ESF) maps were developed that combine a priori prediction of both the crystal structure and its functional properties. However, it is a challenge to represent the high-dimensional structural and functional landscapes of an ESF map and to identify energetically favourable and functionally interesting polymorphs among the 1000s to 10 000s of structures typically on a single ESF map. Here, we introduce geometric landscapes, a representation for ESF maps based on geometric similarity, quantified by persistent homology. We show that this representation allows the exploration of complex ESF maps, automatically pinpointing interesting crystalline phases available to the molecule. Furthermore, we show that geometric landscapes can serve as an accountable descriptor for porous materials to predict their performance for gas adsorption applications. A machine learning model trained using this geometric similarity could reach a remarkable accuracy in predicting the materials' performance for methane storage applications.

2020

Chargement

Modeling Methane Adsorption in Interpenetrating Porous Polymer Networks

Cory Matthew Simon, Berend Smit

Porous polymer networks (PPNs) are a class of porous materials of particular interest in a variety of energy-related applications because of their stability, high surface areas, and gas uptake capacities. Computationally derived structures for five recently synthesized PPN frameworks, PPN-2, -3, -4, -5, and -6, were generated for various topologies, optimized using semiempirical electronic structure methods, and evaluated using classical grand-canonical Monte Carlo simulations. We show that a key factor in modeling the methane uptake performance of these materials is whether, and how, these material frameworks interpenetrate and demonstrate a computational approach for predicting the presence, degree, and nature of interpenetration in PPNs that enables the reproduction of experimental adsorption data. © 2013 American Chemical Society.

2013

Chargement

Diversifying Databases of Metal Organic Frameworks for High-Throughput Computational Screening

Kevin Maik Jablonka, Sauradeep Majumdar, Seyedmohamad Moosavi, Daniele Ongari, Berend Smit

By combining metal nodes and organic linkers, an infinite number of metal organic frameworks (MOFs) can be designed in silico. Therefore, when making new databases of such hypothetical MOFs, we need to ensure that they not only contribute toward the growth of the count of structures but also add different chemistries to the existing databases. In this study, we designed a database of similar to 20,000 hypothetical MOFs, which are diverse in terms of their chemical design space-metal nodes, organic linkers, functional groups, and pore geometries. Using machine learning techniques, we visualized and quantified the diversity of these structures. We find that on adding the structures of our database, the overall diversity metrics of hypothetical databases improve, especially in terms of the chemistry of metal nodes. We then assessed the usefulness of diverse structures by evaluating their performance, using grand-canonical Monte Carlo simulations, in two important environmental applications-post-combustion carbon capture and hydrogen storage. We find that many of these structures perform better than widely used benchmark materials such as Zeolite-13X (for post-combustion carbon capture) and MOF-5 (for hydrogen storage). All the structures developed in this study, and their properties, are provided on the Materials Cloud to encourage further use of these materials for other applications.

AMER CHEMICAL SOC2021

Chargement