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Tuning Nanoparticles and Mesoporous Materials Using Simulated Acoustic Vibrations

Thompson, Martin (2024) Tuning Nanoparticles and Mesoporous Materials Using Simulated Acoustic Vibrations. Master of Science by Research (MScRes) thesis, University of Kent,. (doi:10.22024/UniKent/01.02.104634) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:104634)

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Language: English

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Official URL:
https://doi.org/10.22024/UniKent/01.02.104634

Abstract

Nanoparticles and mesoporous materials are commonly used in chemistry for catalysis, nano-medicine and photo-catalysis. These structures, specifically CeO2 and TiO2 excel at donating oxy-gen atoms, which is why they're commonly used in catalysis. Monitoring the rate at which these particles vibrate is quite difficult, although it can be seen and tested via simulation. Simulating en-ergy via irradiation allows the particle to vibrate, which emits a frequency, similar to how we hear sound. This frequency can be thought of as an acoustic wave, where one atom in the nanoparticle hits another creating a wave of energy giving off differing frequencies. These frequencies can then be used to describe the nanoparticle or mesoporous material via Fourier transform, the Fourier plot that has the most peaks shows more imperfections in the particle, which can be used to tune the particles or check to see if there are crystallographic defects which can then be changed or poten-tially modified. Smaller nanoparticles were seen to have a higher frequency; this shows it is easier to remove oxygen from smaller nanoparticles due to overall interactions between atoms, which could be due to weaker overall bonding, the displacement of bonds, coordination and surface bonding along the planes.

Item Type: Thesis (Master of Science by Research (MScRes))
Thesis advisor: Mountjoy, Gavin
DOI/Identification number: 10.22024/UniKent/01.02.104634
Uncontrolled keywords: Acoustics Nanosculpting Chemistry Deformity Catalysis Nanoparticles DLPoly Dynamics Computational
Subjects: Q Science > QD Chemistry
Divisions: Divisions > Division of Natural Sciences > Chemistry and Forensics
Funders: University of Kent (https://ror.org/00xkeyj56)
SWORD Depositor: System Moodle
Depositing User: System Moodle
Date Deposited: 16 Jan 2024 16:10 UTC
Last Modified: 17 Jan 2024 12:21 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/104634 (The current URI for this page, for reference purposes)

University of Kent Author Information

Thompson, Martin.

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