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Computationally Exploring Structure-Property Relationships of Thermal Transport in Metal-Organic Frameworks

Islamov, Meiirbek (2024) Computationally Exploring Structure-Property Relationships of Thermal Transport in Metal-Organic Frameworks. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

Metal-organic frameworks (MOFs) are emerging as a promising class of materials for applications such as gas storage, separation, and catalysis, attributed to their large surface area, tunable pore geometry, and high porosity. However, their thermal transport properties have been relatively underexplored, leaving a gap in our understanding of the relationship between structure and thermal conductivity - knowledge that is crucial for the design of MOFs with specific thermal transport properties. To bridge this gap, we performed the first computational high-throughput screening of over 10,000 hypothetical MOFs using classical molecular dynamics simulations and the Green-Kubo method. Our research also includes an investigation of the impact of both randomly and symmetrically distributed defects on the thermal conductivity of two well-known MOFs, UiO-66 and HKUST-1. The results indicate that while randomly introduced missing linker and missing cluster defects generally reduce thermal conductivity, spatially correlated missing linker defects can actually increase thermal conductivity when carefully incorporated into the parent framework.
Given that approximately 90,000 synthesized and 500,000 predicted MOFs are known, there remains a vast, largely unexplored MOF-thermal conductivity structure-property design space, primarily due to the high computational cost of molecular dynamics simulations. To circumvent this challenge, we trained several graph neural network models to rapidly predict the thermal conductivity tensor of MOFs, thus facilitating the exploration of the MOF design space.
In conclusion, this dissertation provides critical insights into the design of MOFs with tailored thermal properties and underscores the importance of considering structural features and defects in the design of thermally conductive MOFs for a variety of applications.

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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Islamov, Meiirbekmei12@pitt.edumei12
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairWilmer, Christopher E.wilmer@pitt.eduwilmer
Committee MemberJohnson, J. Karlkarlj@pitt.edukarlj
Committee MemberVelankar, Sachinvelankar@pitt.eduvelankar
Committee MemberMcGaughey, Alan J. H.mcgaughey@cmu.edu
Date: 3 June 2024
Date Type: Publication
Defense Date: 25 January 2024
Approval Date: 3 June 2024
Submission Date: 27 January 2024
Access Restriction: 1 year -- Restrict access to University of Pittsburgh for a period of 1 year.
Number of Pages: 149
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Chemical Engineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: metal-organic framework, thermal transport, molecular dynamics, machine learning
Date Deposited: 03 Jun 2024 14:36
Last Modified: 03 Jun 2024 14:36
URI: http://d-scholarship.pitt.edu/id/eprint/45779

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