Hall, Brendan Lee (2022) Continuous flow optimisation of nanoparticle catalysts. Integrated PhD and Master thesis, University of Leeds.
Abstract
Continuous flow reactors offer a host of advantages over their more traditional batch
counterparts. These include more controlled mixing, enhanced heat transfer and
increased safety when handling hazardous reagents as only a small volume of material
is present within the reactor at any one time. For these reasons, flow reactors are
becoming increasingly popular for the synthesis of nanoparticle catalysts.
Recent advances in reactor technology and automation have transformed how chemical
products are developed and tested. Automated continuous flow reactors have been
coupled with machine learning algorithms in closed feedback loops, allowing vast areas
of multi-dimensional experimental space to be explored quickly and efficiently,
significantly accelerating the identification of optimum synthesis conditions. While
both reducing costs and improving the sustainability of process development.
This work describes the development of a novel two-stage autonomous reactor for the
optimisation of nanoparticle catalysts by direct observation of their performance in a
catalysed chemical reaction. The key advantage of this performance directed system is
that no offline processing or analysis of the nanoparticles is required. Allowing both the
nanoparticle properties and the nanoparticle catalysed reaction conditions to be
optimised in tandem by an automated system with zero human intervention.
Chapter 1 introduces the principles and methods underlying this work with a focus on
nanoparticle catalysts, flow reactor technologies and optimisation algorithms. Chapter
2 describes a self-optimising reactor capable of nanoparticle catalysed reaction
optimisation. Chapter 3 shows the development of a reactor which was able to produce
alloyed nanoparticle catalysts with tuneable composition. Chapter 4 describes a body of
work surrounding the computational modelling of nanoparticle catalysed reactions for
the evaluation of different optimisation algorithms. Chapter 5 concludes this project by
presenting a two-stage reactor which was able to optimise both the physical properties
of the nanoparticles as well as the conditions under which they were used to catalyse a
reaction.
Metadata
Supervisors: | Chamberlain, Thomas and Bourne, Richard |
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Awarding institution: | University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering (Leeds) > School of Chemical and Process Engineering (Leeds) |
Identification Number/EthosID: | uk.bl.ethos.868419 |
Depositing User: | Mr Brendan Hall |
Date Deposited: | 07 Dec 2022 11:25 |
Last Modified: | 11 Jan 2023 15:02 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:19226 |
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