Robotic systems for exploitation of chemistry in random number generation and discovery of iron-oxo clusters

Lee, Edward Calum (2019) Robotic systems for exploitation of chemistry in random number generation and discovery of iron-oxo clusters. PhD thesis, University of Glasgow.

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Incorporation of robotic automation to chemical synthesis and discovery allows a more rapid, efficient and reliable investigation of the chemical space involved, compared to a manual approach, whilst simultaneously allowing the incorporation of inline analytics for automated real-time monitoring and recording of experimental progress. The objective of this thesis was to create a robot capable of liquid handling and inline analytics, and use these capabilities in two regards: firstly, to generate random numbers by observing outcomes of the random processes in compound synthesis and crystallisation, and secondly to discover new large iron-oxo clusters.

This thesis presents the development and results of using robotic automation and analysis in two areas. In the first, a robotic synthesis platform was used to investigate the stochasticity involved in chemical synthesis and crystallisation of polyoxometalates and coordination clusters by using observations of crystallisations to generate random numbers. In the second, a combination of a robotic synthesis platform and traditional bench methods were used to discover large iron oxide clusters.

Chapter one provides an overview of the fields studied in this thesis, beginning with an overview of polyoxometalate chemistry as an archetypal example of large molecular metal oxides. This is followed by current state of the art in large iron-oxide cluster chemistry and synthetic approaches to compound discovery. Chapter one then concludes by discussing current approaches to automation of chemistry.

Chapter two then describes the construction of a platform for automation and visual analysis of inorganic chemical synthesis and crystallisation while chapter three presents the approached used in, and results from this platform in using synthesis and crystallisation of chemical compounds to true generate random numbers.

In chapter four, the discovery and characterisation of new large iron oxide compounds is presented from both automated and traditional bench methods, including the double stranded ring {Fe16}, and the large aggregates of {Fe30}, {Fe34} and {Fe36}.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Keywords: Automation, iron clusters, random numbers.
Subjects: Q Science > QD Chemistry
Colleges/Schools: College of Science and Engineering > School of Chemistry
Funder's Name: European Research Council (ERC)
Supervisor's Name: Cronin, Professor Leroy
Date of Award: 2019
Depositing User: Mr Edward Calum Lee
Unique ID: glathesis:2019-75123
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 01 Nov 2019 09:17
Last Modified: 01 Nov 2022 09:29
Thesis DOI: 10.5525/gla.thesis.75123
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