Advanced computational modelling of metal organic frameworks and their performance
The performance of metal organic frameworks (MOFs) in applications relevant to modern technological challenges is assessed using selected computational modelling methods. This class of materials has gained significant attention in recent years thanks to its ability to display advanced properties, in...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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2023
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| Online Access: | https://eprints.nottingham.ac.uk/74884/ |
| _version_ | 1848800880491495424 |
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| author | Cooley, Isabel |
| author_facet | Cooley, Isabel |
| author_sort | Cooley, Isabel |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The performance of metal organic frameworks (MOFs) in applications relevant to modern technological challenges is assessed using selected computational modelling methods. This class of materials has gained significant attention in recent years thanks to its ability to display advanced properties, including high surface area and tunability. This work discusses MOFs and the computational techniques which may be used to obtain useful information about them in the context of modern advanced materials and methods.
There are several areas to which MOFs may be applied, and much of the focus of this work is on their use for gas storage and separation. The ability of selected MOFs to perform the difficult separation of xenon and krypton is examined by modelling uptake of the two gases using grand canonical Monte Carlo (GCMC) simulations. Similar simulations are applied in a high-throughput manner to identify MOFs which may be promising for gas separations important to upgrading biogas fuel streams, considering both total gas uptake and appropriate selectivity. The results of these simulations are used to train machine learning models which may be used to make efficient predictions of biogas upgrading ability. Gas uptake in MOFs may be affected by a number of specifics relating to structure and conditions; an important example of this, the effect of residual solvent on uptake, is assessed via a high-throughput GCMC study. The ability to reliably obtain high-quality images of MOF structures and visualise the processes they undergo is highly desirable. Transmission electron microscopy is a route to achieve this, but can be hampered by electron beam damage. Beam damage in selected 2D MOFs is modelled and analysed using ab initio molecular dynamics. Additionally, a classical many-body potential is used to model energetic favourability of metal cluster geometries, and the performance of the potential carefully assessed. A part of the rich context of advanced materials in which MOFs sit, metal clusters are another class of materials for which behaviour under imaging electron radiation is important.
Valuable conclusions may be drawn as a result of the computational modelling applied in this work. Several conclusions are discussed, including identification of MOFs which may be useful for relevant applications, identification of relationships between performance and other MOF properties, discussion of likely pathways for damage to materials, and discussion of the quality of different methods and models for particular applications. |
| first_indexed | 2025-11-14T20:58:35Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-74884 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:58:35Z |
| publishDate | 2023 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-748842025-02-28T12:27:32Z https://eprints.nottingham.ac.uk/74884/ Advanced computational modelling of metal organic frameworks and their performance Cooley, Isabel The performance of metal organic frameworks (MOFs) in applications relevant to modern technological challenges is assessed using selected computational modelling methods. This class of materials has gained significant attention in recent years thanks to its ability to display advanced properties, including high surface area and tunability. This work discusses MOFs and the computational techniques which may be used to obtain useful information about them in the context of modern advanced materials and methods. There are several areas to which MOFs may be applied, and much of the focus of this work is on their use for gas storage and separation. The ability of selected MOFs to perform the difficult separation of xenon and krypton is examined by modelling uptake of the two gases using grand canonical Monte Carlo (GCMC) simulations. Similar simulations are applied in a high-throughput manner to identify MOFs which may be promising for gas separations important to upgrading biogas fuel streams, considering both total gas uptake and appropriate selectivity. The results of these simulations are used to train machine learning models which may be used to make efficient predictions of biogas upgrading ability. Gas uptake in MOFs may be affected by a number of specifics relating to structure and conditions; an important example of this, the effect of residual solvent on uptake, is assessed via a high-throughput GCMC study. The ability to reliably obtain high-quality images of MOF structures and visualise the processes they undergo is highly desirable. Transmission electron microscopy is a route to achieve this, but can be hampered by electron beam damage. Beam damage in selected 2D MOFs is modelled and analysed using ab initio molecular dynamics. Additionally, a classical many-body potential is used to model energetic favourability of metal cluster geometries, and the performance of the potential carefully assessed. A part of the rich context of advanced materials in which MOFs sit, metal clusters are another class of materials for which behaviour under imaging electron radiation is important. Valuable conclusions may be drawn as a result of the computational modelling applied in this work. Several conclusions are discussed, including identification of MOFs which may be useful for relevant applications, identification of relationships between performance and other MOF properties, discussion of likely pathways for damage to materials, and discussion of the quality of different methods and models for particular applications. 2023-12-12 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/74884/1/IsabelCooleyPhDThesis_corrections.pdf Cooley, Isabel (2023) Advanced computational modelling of metal organic frameworks and their performance. PhD thesis, University of Nottingham. Metal organic frameworks; Computational modelling methods; Gas storage and separation; Gas uptake; Simulations |
| spellingShingle | Metal organic frameworks; Computational modelling methods; Gas storage and separation; Gas uptake; Simulations Cooley, Isabel Advanced computational modelling of metal organic frameworks and their performance |
| title | Advanced computational modelling of metal organic frameworks and their performance |
| title_full | Advanced computational modelling of metal organic frameworks and their performance |
| title_fullStr | Advanced computational modelling of metal organic frameworks and their performance |
| title_full_unstemmed | Advanced computational modelling of metal organic frameworks and their performance |
| title_short | Advanced computational modelling of metal organic frameworks and their performance |
| title_sort | advanced computational modelling of metal organic frameworks and their performance |
| topic | Metal organic frameworks; Computational modelling methods; Gas storage and separation; Gas uptake; Simulations |
| url | https://eprints.nottingham.ac.uk/74884/ |