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University of Cambridge

Development of Densified Metal-Organic Framework Monoliths for Gas Adsorption and Separation Applications

Abstract

dc:description.abstract

Metal-organic frameworks (MOFs) have garnered significant interest as promising functional materials with superior gas adsorption and separation performance due to their highly tuneable nature, which enables control over structures and physicochemical properties such as BET area, pore volume, and surface chemistry. However, despite their potential, the practical deployment of these materials in real-world applications has been hindered by their powdery morphology. In recent years, the Adsorption & Advanced Materials Laboratory (AAML) at the University of Cambridge has made significant progress in this regard by developing MOF monoliths (<sub>mono</sub>MOFs) that possess high bulk densities and tuneable porosity. These breakthroughs have enabled record-breaking performance in volumetric CH<sub>4</sub> and H<sub>2</sub> storage applications. The fundamental aim of this thesis is to expand the realm of synthesis techniques utilised for the formation of monolithic MOFs, while concurrently exploring the possible applications of the resultant MOF monoliths. Moreover, this thesis endeavours to investigate the association between synthesis processes, properties, and functionalities of MOF monoliths with respect to gas adsorption and separation applications. To achieve this goal, the self-shaping approach for MOF monolith formation was initially applied to a variety of materials, including homochiral CMOM-3S, mesoporous ZIF-90, and Hf-UiO-66 family MOFs. The synthesis protocols employed in this study demonstrate that highly dense MOF monoliths can be produced using large nanoparticles and that MOF gels are not the sole pathway to monolith formation. Rather, slurries and colloidal suspensions have also been shown to be effective in producing dense MOF monoliths. Following a comprehensive study of MOF monolith synthesis, the knowledge acquired was applied to develop efficient monolithic MOFs for targeted applications of interest. Specifically, using a solvent-determined synthesis approach, UTSA-16-Zn, a promising MOF for carbon capture and separation, has been synthesised as dense monoliths for the first time. The synthesis conditions were systematically optimised to attain optimal porosity properties and bulk densities. The resulting UTSA-16-Zn monoliths exhibit outstanding performance in carbon capture and separation applications, demonstrating high volumetric adsorption capacities and selectivity. Additionally, Al-soc-MOF, a benchmark MOF for CH<sub>4</sub> storage and separation, was also investigated. A modulation approach was employed to shape it into monoliths with varying porosity and bulk densities. The impact of modulators on the performance of Al-soc-MOF monoliths was evaluated, revealing exceptional C3/C1 separation and CH<sub>4</sub> storage performance. Overall, this thesis provides invaluable insights into the synthesis, shaping, and application of MOFs monoliths. The findings reported herein shed light on the unique properties and potential of MOF monoliths as a possible solution for tackling pressing environmental challenges.

Degree

thesis:*
Name dc:type.qualificationname
Doctor of Philosophy (PhD)
Level dc:type.qualificationlevel
Doctoral
Grantor dc:publisher.institution
University of Cambridge
Year dc:date.issued
2023

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Yang, Yue
Advisor dc:contributor.advisor
  • Fairen-Jimenez, David

Subjects

dc:subject × 5

Rights

dc:rights
Language dc:language
eng

Identifiers

dc:identifier.*
DOI dc:identifier.doi
https://doi.org/10.17863/CAM.101618
OAI identifier oai:identifier
oai:www.repository.cam.ac.uk:1810/357356

Chain of custody

source
Harvested from
Cambridge University
Base URL
api.repository.cam.ac.uk/server/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Yang, Yue. Development of Densified Metal-Organic Framework Monoliths for Gas Adsorption and Separation Applications. Doctoral thesis, University of Cambridge, 2023. https://doi.org/10.17863/CAM.101618