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Modelling Crystal Growth with Natural Tiles

Hill, Adam

[Thesis]. Manchester, UK: The University of Manchester; 2019.

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Abstract

From catalysis to drug activity in the body, controlling crystal size and morphology is key to maximising the effectiveness of a crystalline material in many applications. Computational modelling combined with the relatively new technique of atomic force microscopy allow researchers to probe underlying crystal growth mechanisms like never before. CrystalGrower (CG), a kinetic Monte Carlo crystal growth simulation tool has existed in some form at the Centre for Nanoporous Materials (CNM) for many years, but over the course of this project has been adapted to grow potentially any type of crystal structure. This, combined with a generalised visualisation package, has led to the study of many material types previously inaccessible with the methodology used in CG. Using the general building schemes of natural tiles and Voronoi-Dirichlet polyhedra (VDP), CG simulates the growth of crystal structures based on a destabilisation model. As units of growth (tiles, molecules or ions) lose connections to their neighbours, they become more destabilised relative to bulk crystal species. Thus, their internal energy is increased, causing the units to be thermodynamically less favoured for growth relative to more stable units. By using a model to imitate a thermodynamic driving force, these potential growth (or dissolution) sites can be assigned a probability, allowing systems to be modelled using a kinetic Monte Carlo algorithm. This work focusses on the application of the CG methodology to a variety of crystal structure types (including zeolites, MOFs, molecular crystals and ionic crystals) and studying the simulation results to gain insight into the energetics of crystal growth. Additionally, detailed notes are presented of the underlying theory of the CG methodology along with presentation of the companion visualisation package designed to view the outputs of CG. The CG approach could be beneficial to academic and industrial groups around the world studying the field of crystal growth. We hope for this approach to eventually be used by not only theoretical groups but also experimentally focused groups, where their knowledge of factors controlling crystal growth can be directly related to parameters within CG (e.g. using templates to stabilise or destabilise particular cage structures relative to others).

Additional content not available electronically

DOIs for supplementary CD data are provided for location on MendeleyData. Supplementary movie and image data for Paper 1: 10.17632/3d88dh68kj.1 CGV source code: 10.17632/66k2xwrwk5.1

Bibliographic metadata

Type of resource:
Content type:
Form of thesis:
Type of submission:
Degree type:
Doctor of Philosophy
Degree programme:
PhD Chemistry (42 month)
Publication date:
Location:
Manchester, UK
Total pages:
333
Abstract:
From catalysis to drug activity in the body, controlling crystal size and morphology is key to maximising the effectiveness of a crystalline material in many applications. Computational modelling combined with the relatively new technique of atomic force microscopy allow researchers to probe underlying crystal growth mechanisms like never before. CrystalGrower (CG), a kinetic Monte Carlo crystal growth simulation tool has existed in some form at the Centre for Nanoporous Materials (CNM) for many years, but over the course of this project has been adapted to grow potentially any type of crystal structure. This, combined with a generalised visualisation package, has led to the study of many material types previously inaccessible with the methodology used in CG. Using the general building schemes of natural tiles and Voronoi-Dirichlet polyhedra (VDP), CG simulates the growth of crystal structures based on a destabilisation model. As units of growth (tiles, molecules or ions) lose connections to their neighbours, they become more destabilised relative to bulk crystal species. Thus, their internal energy is increased, causing the units to be thermodynamically less favoured for growth relative to more stable units. By using a model to imitate a thermodynamic driving force, these potential growth (or dissolution) sites can be assigned a probability, allowing systems to be modelled using a kinetic Monte Carlo algorithm. This work focusses on the application of the CG methodology to a variety of crystal structure types (including zeolites, MOFs, molecular crystals and ionic crystals) and studying the simulation results to gain insight into the energetics of crystal growth. Additionally, detailed notes are presented of the underlying theory of the CG methodology along with presentation of the companion visualisation package designed to view the outputs of CG. The CG approach could be beneficial to academic and industrial groups around the world studying the field of crystal growth. We hope for this approach to eventually be used by not only theoretical groups but also experimentally focused groups, where their knowledge of factors controlling crystal growth can be directly related to parameters within CG (e.g. using templates to stabilise or destabilise particular cage structures relative to others).
Additional digital content not deposited electronically:
DOIs for supplementary CD data are provided for location on MendeleyData. Supplementary movie and image data for Paper 1: 10.17632/3d88dh68kj.1 CGV source code: 10.17632/66k2xwrwk5.1
Thesis main supervisor(s):
Thesis co-supervisor(s):
Funder(s):
Language:
en

Institutional metadata

University researcher(s):

Record metadata

Manchester eScholar ID:
uk-ac-man-scw:318408
Created by:
Hill, Adam
Created:
18th February, 2019, 11:33:16
Last modified by:
Hill, Adam
Last modified:
4th December, 2020, 10:14:51

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