Modelling of metal-organic frameworks as tunable adsorbents for separations

Metal-organic frameworks (MOFs) are an interesting class of nanoporous materials synthesized in a “building-block” approach from inorganic nodes and organic linkers. By selecting appropriate building blocks, the structural and chemical properties of the resulting materials can be finely tuned, and this makes MOFs promising materials for applications such as chemical separations, gas storage, sensing, drug delivery, and catalysis. This talk will focus on efforts to design or screen MOFs for adsorption separations. Because of the predictability of MOF synthetic routes and the nearly infinite number of possible structures, molecular modeling is an attractive tool for screening new MOFs before they are synthesized. Large databases of existing and proposed MOFs now exist and can be screened to find the top candidates for a given separation using atomistic Monte Carlo simulations. The resulting data can also provide insight into the molecular-level details that lead to observed macroscopic properties, which can, in turn, be used to design improved candidates. While molecular modeling can predict adsorption properties such as the selectivity and working capacity, process-level modeling can also play a key role in evaluating materials, and we will discuss how the interplay of molecular-level and process-leveling modeling can be used along with experiment to discover, develop, and ultimately design new MOFs for desired separation applications

Progress toward the computational discovery of new metal–organic framework adsorbents for energy applications

Metal–organic frameworks (MOFs) are a class of nanoporous material precisely synthesized from molecular building blocks. MOFs could have a critical role in many energy technologies, including carbon capture, separations and storage of energy carriers. Molecular simulations can improve our molecular-level understanding of adsorption in MOFs, and it is now possible to use realistic models for these complicated materials and predict their adsorption properties in quantitative agreement with experiments. Here we review the predictive design and discovery of MOF adsorbents for the separation and storage of energy-relevant molecules, with a view to understanding whether we can reliably discover novel MOFs computationally prior to laboratory synthesis and characterization. We highlight in silico approaches that have discovered new adsorbents that were subsequently confirmed by experiments, and we discuss the roles of high-throughput computational screening and machine learning. We conclude that these tools are already accelerating the discovery of new applications for existing MOFs, and there are now several examples of new MOFs discovered by computational modelling

The effect of framework flexibility on diffusion of small molecules in the metal-organic framework IRMOF-1

Many efforts have been made to model adsorption and diffusion processes in metalorganic frameworks (MOFs) in the past several years. In most of these studies, the framework has been kept rigid. In this study, we examine the effect of using a flexible framework model on the self-diffusion coefficients and activation energies calculated for several short n-alkanes and benzene in IRMOF-1 from molecular dynamics simulations. We find only minor differences between flexible and rigid framework results. The selfdiffusion coefficients calculated in the flexible framework are 20-50% larger than the ones calculated in the rigid framework, and the activation energies differ by only 10-20%

High-Throughput Screening of Porous Crystalline Materials for Hydrogen Storage Capacity near Room Temperature

The hydrogen storage capabilities of 18,383 porous crystalline structures possessing various degrees of Mg functionalization and diverse physical properties were assessed through combined grand canonical Monte Carlo (GCMC) and quantum mechanical approaches. GCMC simulations were performed for pressures of 2 and 100 bar at a temperature of 243 K. Absolute uptake at 100 bar and deliverable capacity between 100 bar and 2 bar were calculated. Maximum absolute and deliverable gravimetric capacities were 9.35 wt% and 9.12 wt % respectively. Volumetrically, absolute and deliverable capacities were 51 g/L and 30 g/L respectively. In addition, the results reveal relationships between hydrogen uptake and the physical properties of the materials. We show that the introduction of an optimum amount of Mg alkoxide to increase the isosteric heat of adsorption is a promising strategy to improve hydrogen uptake and delivery near ambient temperature.This research was supported by the U.S. Department of Energy (DE-FG02-08EF15967). This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grand No. DGE-0824162 (Y. J. C.). D.F.-J. acknowledges the Royal Society (UK) for a University Research Fellowship. We gratefully acknowledge Northwestern University’s Quest cluster and the National Energy Research Scientific Computing Center’s Carver Cluster for computer resources.This is the accepted manuscript. The final version is available from ACS at http://pubs.acs.org/doi/abs/10.1021/jp4122326

Machine learning using host/guest energy histograms to predict adsorption in metal–organic frameworks: Application to short alkanes and Xe/Kr mixtures

A machine learning (ML) methodology that uses a histogram of interaction energies has been applied to predict gas adsorption in metal–organic frameworks (MOFs) using results from atomistic grand canonical Monte Carlo (GCMC) simulations as training and test data. In this work, the method is first extended to binary mixtures of spherical species, in particular, Xe and Kr. In addition, it is shown that single-component adsorption of ethane and propane can be predicted in good agreement with GCMC simulation using a histogram of the adsorption energies felt by a methyl probe in conjunction with the random forest ML method. The results for propane can be improved by including a small number of MOF textural properties as descriptors. We also discuss the most significant features, which provides physical insight into the most beneficial adsorption energy sites for a given application

Computer-aided discovery of a metal-organic framework with superior oxygen uptake.

Current advances in materials science have resulted in the rapid emergence of thousands of functional adsorbent materials in recent years. This clearly creates multiple opportunities for their potential application, but it also creates the following challenge: how does one identify the most promising structures, among the thousands of possibilities, for a particular application? Here, we present a case of computer-aided material discovery, in which we complete the full cycle from computational screening of metal-organic framework materials for oxygen storage, to identification, synthesis and measurement of oxygen adsorption in the top-ranked structure. We introduce an interactive visualization concept to analyze over 1000 unique structure-property plots in five dimensions and delimit the relationships between structural properties and oxygen adsorption performance at different pressures for 2932 already-synthesized structures. We also report a world-record holding material for oxygen storage, UMCM-152, which delivers 22.5% more oxygen than the best known material to date, to the best of our knowledge

Impact of the strength and spatial distribution of adsorption sites on methane deliverable capacity in nanoporous materials

The methane deliverable capacity of adsorbent materials is a critical performance metric that will determine the viability of using adsorbed natural gas (ANG) technology in vehicular applications. ARPA-E recently set a target deliverable capacity of 315 cc(STP)/cc that a viable adsorbent material should achieve to yield a driving range competitive with incumbent fuels. However, recent computational screening of hundreds of thousands of materials suggests that the target is unattainable. In this work, we aim to determine whether the observed limits in deliverable capacity (similar to 200 cc(STP)/cc) are fundamental limits arising from thermodynamic or material design constraints. Our efforts focus on simulating methane adsorption isotherms in a large number of systems, resulting in a broad exploration of different combinations of spatial distributions and energetics of adsorption sites. All systems were classified into five adsorption scenarios with varying degrees of realism in the manner that adsorption sites are created and endowed with energetics. The scenarios range from methane adsorption on discrete idealized lattice sites to adsorption in metal-organic frameworks with coordinatively unsaturated sites (CUS) provided by metalated catechol groups. Our findings strongly suggest that the ARPA-E target is unattainable, although not due to thermodynamic constraints but due to material design constraints. On the other hand, we also find that the currently observed deliverable capacity limits may be moderately surpassed. For instance, incorporation of CUS in IRMOF-10 is predicted to yield a 217 cc(STP)/cc deliverable capacity. The modified material has a similar to 0.85 void fraction and a heat of adsorption of similar to 15 kJ/mol. This suggests that similar, moderate improvements over existing materials could be achieved as long as CUS incorporation still maintains a relatively large void fraction. Nonetheless, we conclude that more significant improvements in deliverable capacity will require changes in the currently proposed operation conditions. (C) 2016 Elsevier Ltd. All rights reserved

Water-stable zirconium-based metal-organic framework material with high-surface area and gas-storage capacities.

We designed, synthesized, and characterized a new Zr-based metal-organic framework material, NU-1100, with a pore volume of 1.53 ccg(-1) and Brunauer-Emmett-Teller (BET) surface area of 4020 m(2) g(-1) ; to our knowledge, currently the highest published for Zr-based MOFs. CH4 /CO2 /H2 adsorption isotherms were obtained over a broad range of pressures and temperatures and are in excellent agreement with the computational predictions. The total hydrogen adsorption at 65 bar and 77 K is 0.092 g g(-1) , which corresponds to 43 g L(-1) . The volumetric and gravimetric methane-storage capacities at 65 bar and 298 K are approximately 180 vSTP /v and 0.27 g g(-1) , respectively.OKF, JTH and RQS thank DOE ARPA-E and the Stanford Global Climate and Energy Project for support of work relevant to methane and CO2, respectively. TY acknowledges support by the U. S. Department of Energy through BES Grant No. DE-FG02-08ER46522. WB acknowledges support from the Foundation for Polish Science through the “Kolumb” Program. DFJ acknowledges the Royal Society (UK) for a University Research Fellowship. This material is based upon work supported by the National Science Foundation (grant CHE-1048773).This is the accepted manuscript. The final version is available as 'Water-Stable Zirconium-Based Metal–Organic Framework Material with High-Surface Area and Gas-Storage Capacities' from Wiley at http://onlinelibrary.wiley.com/doi/10.1002/chem.201402895/abstract