Evaluating different classes of porous materials for carbon capture

Carbon Capture and Sequestration (CCS) is one of the promising ways to significantly reduce the CO2 emission from power plants. In particular, amongst several separation strategies, adsorption by nano-porous materials is regarded as a potential means to efficiently capture CO2 at the place of its origin in a post-combustion process. The search for promising materials in such a process not only requires the screening of a multitude of materials but also the development of an adequate evaluation metric. Several evaluation criteria have been introduced in the literature concentrating on a single adsorption or material property at a time. Parasitic energy is a new approach for material evaluation to address the energy load imposed on a power plant while applying CCS. In this work, we evaluate over 60 different materials with respect to their parasitic energy, including experimentally realized and hypothetical materials such as metal-organic frameworks (MOFs), zeolitic imidazolate frameworks (ZIFs), porous polymer networks (PPNs), and zeolites. The results are compared to other proposed evaluation criteria and performance differences are studied regarding the regeneration modes, (i.e. Pressure-Swing (PSA) and Temperature-Swing Adsorption (TSA)) as well as the flue gas composition.

Systematic Tuning and Multifunctionalization of Covalent Organic Polymers for Enhanced Carbon Capture

Johanna Maria Huck, Rocio Mercado, Berend Smit, Hui Wang

Porous covalent polymers are attracting increasing interest in the fields of gas adsorption, gas separation, and catalysis due to their fertile synthetic polymer chemistry, large internal surface areas, and ultrahigh hydrothermal stabilities. While precisely manipulating the porosities of porous organic materials for targeted applications remains challenging, we show how a large degree of diversity can be achieved in covalent organic polymers by incorporating multiple functionalities into a single framework, as is done for crystalline porous materials. Here, we synthesized 17 novel porous covalent organic polymers (COPs) with finely tuned porosities, a wide range of Brunauer Emmett Teller (BET) specific surface areas of 430-3624 m(2) g(-1), and a broad range of pore volumes of 0.24-3.50 cm(3) g(-1), all achieved by tailoring the length and geometry of building blocks. Furthermore, we are the first to successfully incorporate more than three distinct functional groups into one phase for porous organic materials, which has been previously demonstrated in crystalline metal organic frameworks (MOFs). COPs decorated with multiple functional groups in one phase can lead to enhanced properties that are not simply linear combinations of the pure component properties. For instance, in the dibromobenzene-lined frameworks, the bi- and multifunctionalized COPs exhibit selectivities for carbon dioxide over nitrogen twice as large as any of the singly functionalized COPs. These multifunctionalized frameworks also exhibit a lower parasitic energy cost for carbon capture at typical flue gas conditions than any of the singly functionalized frameworks. Despite the significant improvement, these frameworks do not yet outperform the current state-of-art technology for carbon capture. Nonetheless, the tuning strategy presented here opens up avenues for the design of novel catalysts, the synthesis of functional sensors from these materials, and the improvement in the performance of existing covalent organic polymers by multifunctionalization.

American Chemical Society2015

Ab Initio Derived Force Fields for Predicting CO2 Adsorption and Accessibility of Metal Sites in the Metal-Organic Frameworks M-MOF-74 (M = Mn, Co, Ni, Cu)

Peng Bai, Wendy Lee Queen

Metal-organic frameworks (MOFs) are versatile nanoporous materials that have gained significant interest as low heat capacity, high selectivity sorbents for CO2 capture applications. Large-scale atomistic simulations for identifying high-performance MOFs are possible, but are limited to systems for which existing molecular mechanics force fields describe the interactions between the guest and framework atoms with sufficient accuracy. However, standard force fields are not applicable to cases involving coordinatively unsaturated metal centers that can strongly bind specific sorbate molecules. It has been previously shown that improved force fields can be derived from quantum mechanical calculations. In this work, we derived force fields for an isostructural series of MOFs, M-MOF-74, where M = Mn, Co, Ni, and Cu, from first principles. Monte Carlo calculations in the Gibbs ensemble were used to calculate the CO2 adsorption isotherms in order to assess the quality of the derived force field parameters and to determine a generally applicable procedure for obtaining a reliable force field for a targeted MOF and adsorbate system. The computed CO2 adsorption isotherms for the different M-MOF-74 members agree with experimental measurements at low loading and show that Ni-MOF-74 possesses the highest affinity toward CO2 and Cu-MOF-74 the weakest. In addition, we explored the source of open metal site and pore inaccessibility in these materials and quantified its impact on adsorption, especially the discrepancies often observed between experiments and simulations at high loadings.

Amer Chemical Soc2015

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

Systematic Tuning and Multifunctionalization of Covalent Organic Polymers for Enhanced Carbon Capture

Johanna Maria Huck, Rocio Mercado, Berend Smit, Hui Wang

American Chemical Society2015