journal article·2021-12-29Open access

Incorporating Flexibility Effects into Metal–Organic Framework Adsorption Simulations Using Different Models

Zhenzi Yu, Dylan M. Anstine, Salah Eddine Boulfelfel, Chenkai Gu, Coray M. Colina, David S. Sholl

ACS Applied Materials & Interfaces· Volume 13· Issue 51

Abstract

High-throughput calculations based on molecular simulations to predict the adsorption of molecules inside metal–organic frameworks (MOFs) have become a useful complement to experimental efforts to identify promising adsorbents for chemical separations and storage. For computational convenience, all existing efforts of this kind have relied on simulations in which the MOF is approximated as rigid. In this paper, we use extensive adsorption–relaxation simulations that fully include MOF flexibility effects to explore the validity of the rigid framework approximation. We also examine the accuracy of several approximate methods to incorporate framework flexibility that are more computationally efficient than adsorption–relaxation calculations. We first benchmark various models of MOF flexibility for four MOFs with well-established CO2 experimental consensus isotherms. We then consider a range of adsorption properties, including Henry’s constants, nondilute loadings, and adsorption selectivity, for seven adsorbates in 15 MOFs randomly selected from the CoRE MOF database. Our results indicate that in many MOFs adsorption–relaxation simulations are necessary to make quantitative predictions of adsorption, particularly for adsorption at dilute concentrations, although more standard calculations based on rigid structures can provide useful information. Finally, we investigate whether a correlation exists between the elastic properties of empty MOFs and the importance of including framework flexibility in making accurate predictions of molecular adsorption. Our results did not identify a simple correlation of this type.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Metal-Organic Frameworks: Synthesis and Applications · Enhanced Oil Recovery Techniques · Machine Learning in Materials Science

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30318, United States

Department of Materials Science and Engineering, University of Florida, Gainesville, Florida 32611, United States

George and Josephine Butler Polymer Research Laboratory, University of Florida, Gainesville, Florida 32611, United States

State Key Laboratory of Coal Combustion, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China

School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China

Department of Chemistry, University of Florida, Gainesville, Florida 32603, United States

Transformational Decarbonization Initiative, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37830, United States

Funding

Basic Energy Sciences · China Scholarship Council

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