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Computational discovery of electronic materials with structural prediction

Rubinstein, Ethan A.; (2022) Computational discovery of electronic materials with structural prediction. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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Abstract

This thesis examines structure-property relationships with a focus on two promising chemical areas for conductive applications, copper chalcogenides and lone pair containing materials. At the intersection of these two chemical spaces a structural prediction method is used to examine the Cu-Sn(II)-O ternary space for which no stoichiometric ternary is known. The predicted structures are found to have very high thermodynamic instability to competing phases, and relationships between structure and stability are examined. The same method was used to successfully predict the known structures of SnO and Cu2PbO2. The electronic and optical properties are investigated with ab-initio DFT for a pair of novel earth abundant mixed B-site cation delafossites. The properties of two recently discovered lone pair containing quaternary barium bismuth oxides are investigated and compared with collaborating experimental characterisation. The CuM(2/3)Sb(1/3)O2 (M = Zn/Mg) delafossites are both found to have high valence band effective masses and weak absorption of visible light, moving them away from potential application as photoconversion and p-type conductive materials. M(II) and Sb(V) s state incorporation to the conduction band is found to result in improved conduction band dispersion. Substitution of Nb and Ta into perovskite BaBiO3 is shown to successfully modulate band gaps and produce dispersive valence bands. Ba2BiTaO6 is indicated as a promising transparent conductor due to it's 3.1 eV band gap and high potential p-type mobilities.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Computational discovery of electronic materials with structural prediction
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Copyright © The Author 2022. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author's request.
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Chemistry
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10157941
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