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Modeling of adsorption in UiO-66 and MOF-based gas sensor arrays

Wei, Xin (2021) Modeling of adsorption in UiO-66 and MOF-based gas sensor arrays. Master's Thesis, University of Pittsburgh. (Unpublished)

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Metal-Organic Frameworks (MOFs) have attracted significant interest for adsorption due to their high degree of tailorability and large specific surface areas. The combination of tailorability and well-defined crystalline pores makes MOFs very promising candidates for highly selective adsorption.
In this study, we explored the properties and applications of MOFs in three areas. Firstly, we studied how adsorption correlates with the number and types of defects. Molecular-level modeling of adsorption and diffusion in MOFs almost always relies on models of MOFs that are defect-free (pristine). However, all real MOFs have defects, which affect adsorption by changing the environment of pores within the MOFs. A fundamental understanding of how defects impact adsorption is important for identifying the limits of the performance of real materials, developing improved design rules for new improved materials, and predicting and maximizing utilization of the material. We initially consider UiO-66 with different levels of missing linker defects. The structures of the generated defective MOFs were optimized using periodic density functional theory with the CP2K simulation package. Adsorption isotherms were generated by carrying out grand canonical Monte Carlo (GCMC) simulations in RASPA. We also investigated the effect of different adsorbate-adsorbent charge schemes by comparing isotherms with no framework charges and atomic charges calculated using DDEC6 and EQEQ methods.
Secondly, we generated new forcefields using the QuickFF formalism for both pristine UiO-66 and 17% defective UiO-66 to facilitate simulation of flexible structures. Bulk modulus calculations, relaxation, and NVT simulations were used to test the validity of the newly developed potentials.
Thirdly, we studied one use of MOFs for developing an electronic nose, a device intended to identify the composition of complex gas mixtures. We modified and improved the previously developed algorithm by applying Henry’s law coefficients and moving CO2 from the trace gas category to background gas. Applying Henry’s law coefficient enables the prediction without performing GCMC simulations of every specific composition combination. Treating CO2 as a background gas enlarged the library of MOFs we can use in the electronic nose by freeing it from the restrictions of Henry’s coefficient of CO2.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Wei, Xinxiw144@pitt.eduxiw144
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairJohnson,
Committee CoChairChris,
Committee MemberJohn,
Date: 13 June 2021
Date Type: Publication
Defense Date: 26 March 2021
Approval Date: 13 June 2021
Submission Date: 5 April 2021
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 50
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Chemical Engineering
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: Metal-Organic Frameworks; adsorption; MOF-based gas sensor arrays
Date Deposited: 13 Jun 2021 17:39
Last Modified: 13 Jun 2021 17:39

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