Computational Chemistry Methods for Nanoporous Materials

Evans, Jack D.; Fraux, Guillaume; Gaillac, Romain; Kohen, Daniela; Trousselet, Fabien; Vanson, Jean-Mathieu; Coudert, François‐Xavier

doi:10.1021/acs.chemmater.6b02994

Cited by 79 publications

(58 citation statements)

References 120 publications

(165 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…21 In the literature, there are several methodologies investigating the gas storage problem in MOFs. There are accurate ab initio quantum chemical approaches, 22 computational light and fast classical Monte Carlo and molecular dynamics techniques 23 and "multi-scale" methods that try to combine both. 22 All of them address specific MOFs, either synthesized earlier, or designed for a specific application following chemical intuition.…”

Section: Introductionmentioning

confidence: 99%

Chemically intuited, large-scale screening of MOFs by machine learning techniques

et al. 2017

View full text Add to dashboard Cite

A novel computational methodology for large-scale screening of MOFs is applied to gas storage with the use of machine learning technologies. This approach is a promising trade-off between the accuracy of ab initio methods and the speed of classical approaches, strategically combined with chemical intuition. The results demonstrate that the chemical properties of MOFs are indeed predictable (stochastically, not deterministically) using machine learning methods and automated analysis protocols, with the accuracy of predictions increasing with sample size. Our initial results indicate that this methodology is promising to apply not only to gas storage in MOFs but in many other material science projects.npj Computational Materials (2017) 3:40 ; doi:10.1038/s41524-017-0045-8 INTRODUCTION Metal-organic frameworks (MOFs) or porous coordination polymers are a rapidly growing family of hybrid inorganic-organic nanoporous materials, which belong to the category of coordination polymers.1-3 These relatively new materials consist of a threedimensional periodic network, constructed from molecular building blocks, such as metal clusters and organic linkers (Fig. 1). The possible combinations of these numerous building blocks under different topologies result is an almost unlimited number of potential MOFs! Since their discovery 4 MOFs have attracted significant scientific attention due to their extraordinary properties. As "skeleton" materials, they pose very large pores and outstanding apparent surface area. If we were able to unwrap the surface of only one gram of these "very empty" materials, we could cover the area of a football court! These unique characteristics of the MOFs made them excellent candidates for catalysis and gas storage applications.MOFs have shown exceptional performance in gas storage and separation. Both useful and harmful gases can be absorbed in their pores in very large amounts. The storage of hydrogen,

show abstract

Section: Introductionmentioning

confidence: 99%

Chemically intuited, large-scale screening of MOFs by machine learning techniques

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Furthermore, we have highlighted examples where these methods have been used for the a priori design and large scale screening of candidate PMMs. While many of these computational approaches have been employed to investigate porous framework and polymer materials, 60,79 the discrete composition and disconnected pores typical of PMMs has necessitated the development of novel methodologies. Salient examples are the analysis of dynamic pore interconnectivity 76 and the use of transition state theory to inspect the diffusion of large and constrained adsorbates.…”

Section: Discussionmentioning

confidence: 99%

“…Similar to conventional porous materials, such as zeolites and MOFs, 79 adsorption of guests in PMMs is simulated using Monte Carlo methods. 80 This technique was used to demonstrate the applicability of BET analysis for determining surface areas in framework materials.…”

Section: Gas Adsorptionmentioning

confidence: 99%

Application of computational methods to the design and characterisation of porous molecular materials

et al. 2017

Self Cite

View full text Add to dashboard Cite

Composed from discete units, porous molecular materials (PMMs) possess unique properties not observed for conventional, extended, solids, such as solution processibility and permanent porosity in the liquid phase. However, identifying the origin of porosity is not a trivial process, especially for amorphous or liquid phases. Furthermore, the assembly of molecular components is typically governed by a subtle balance of weak intermolecular forces that makes structure prediction challenging. Accordingly, in this review we canvass the crucial role of molecular simulations in the characterisation and design of PMMs. We will outline strategies for modelling porosity in crystalline, amorphous and liquid phases and also describe the state-of-the-art methods used for high-throughput screening of large datasets to identify materials that exhibit novel performance characteristics.

show abstract

“…In this section, we will focus on the theoretical and computational approaches that have been reported in the literature to study the structure, physical and chemical properties of MM-MOFs. Among the vast body of computational studies on MOFs and coordination polymers in general, 74,75 published works on MM-MOFs appear relatively few and far between. We can attribute this to the complexity of the mixed-metal systems, both in terms of the experimental characterization necessary to generate structural models, as well as in the modelling approaches themselves.…”

Section: Computational Techniquesmentioning

confidence: 99%