Browsing School of Physics by Sponsor "Irish Research Council (IRC)"
Now showing items 21-40 of 65
-
Implementation of Morse-Witten theory for a polydisperse wet 2D foam simulation
(Taylor & Francis, 2019-06)The Morse–Witten theory provides a formulation for the inter-bubble forces and corresponding deformations in a liquid foam, accurate in the limit of high liquid fraction. Here we show how the theory may be applied in ... -
The in-situ structural characterization of layered double hydroxide materials in catalytic and biological applications
(Trinity College Dublin. School of Physics. Discipline of Physics, 2019)The overall aim of this PhD research is to understand the physical behaviours of layered double hydroxide (LDH) nanomaterials in applied environments. Two aspects of LDH-based applications were studied. Firstly, the thermal ... -
The Jacobi-Legendre framework for Machine Learning in Materials Investigation and Discovery
(Trinity College Dublin. School of Physics. Discipline of Physics, 2024)Machine-learning models have rapidly become fundamental tools in the study of materials properties. In the past few years there has been a surge of interest in the construction of new models and descriptors to accelerate ... -
LOFAR Observations of Shocks in the Solar Corona
(Trinity College Dublin. School of Physics. Discipline of Physics, 2022)The Sun can produce large-scale energetic events such as solar flares and coronal mass ejections, which can excite shock waves that propagate from the low solar atmosphere into interplanetary space. Such shocks can result ... -
Machine Learned Compact Kinetic Models for Combustion
(Trinity College Dublin. School of Physics. Discipline of Physics, 2023)Chemical kinetic models are an essential component in the development and optimisation of combustion devices through their coupling to multi-dimensional simulations such as computational fluid dynamics (CFD). Due to the ... -
Machine learning density functional theory for the Hubbard model
(2019)The solution of complex many-body lattice models can often be found by defining an energy functional of the relevant density of the problem. For instance, in the case of the Hubbard model the spin-resolved site occupation is ... -
Machine Learning for Condensed Matter Physics
(Trinity College Dublin. School of Physics. Discipline of Physics, 2021)This thesis is about the application of machine learning (ML) methods to a variety of problems in condensed matter physics. As condensed matter physics has large computational and experimental datasets readily available - ... -
Machine-learning semilocal density functional theory for many-body lattice models at zero and finite temperature
(2021)We introduce a machine-learning density-functional-theory formalism for the spinless Hubbard model in one dimension at both zero and finite temperature. In the zero-temperature case this establishes a one-to-one ... -
Machine-Learning-Assisted Construction of Ternary Convex Hull Diagrams
(Journal of Chemical Information and Modeling, 2024-01-25)In the search for novel intermetallic ternary alloys, much of the effort goes into performing a large number of ab initio calculations covering a wide range of compositions and structures. These are essential to building ... -
Magnetic Characteristics of Sunspot Groups and their Role in Producing Adverse Space Weather
(Trinity College Dublin. School of Physics. Discipline of Physics, 2019)The energy that powers solar flares is known to come from magnetic energy stored in sunspot groups, but the precise conditions required and processes involved in energy release remain unclear. The likelihood of ... -
Magnetic order and magnetotransport in half-metallic ferrimagnetic MnyRuxGa thin films
(2021)The ruthenium content of half-metallic Mn2RuxGa thin films, with a biaxially strained inverse Heusler structure, controls the ferrimagnetism that determines their magnetic and electronic properties. An extensive study of ... -
A Microscopy Study of PVD Grown Cu: Sample preparation, optimisation and in-situ analysis
(Trinity College Dublin. School of Physics. Discipline of Physics, 2019)A variety of sample preparation techniques have been developed and optimised for PVD grown Cu films and Cu NWs. These techniques include traditional cross-sectional preparation, plan-view preparation, site-specific ... -
Modelling and Monitoring Geomagnetically Induced Currents in Ireland
(Trinity College Dublin. School of Physics. Discipline of Physics, 2018)This thesis is the first detailed study of the effects of geomagnetic storms and geomagnetically induced currents (GICs) on the Irish power network. In order to better monitor geomagnetic storms in Ireland, a network of ... -
Monitoring and Modelling Geomagnetic and Geoelectric Fields in Ireland
(Trinity College Dublin. School of Physics. Discipline of PhysicsTrinity College Dublin, School of Physics, 2024)Geomagnetic storms form in response to the arrival of solar storms at the Earth, which interact with the Earth's magnetic field and can lead to geomagnetic storms. Magnetic field variations generated during geomagnetic ... -
Neutron Imaging of Paramagnetic Ions: Electrosorption by Carbon Aerogels and Macroscopic Magnetic Forces
(2021)The electrosorption of Gd3+ ions from an aqueous 70 mM Gd(NO3)3 solution in monolithic carbon aerogel electrodes was recorded by dynamic neutron imaging. The aerogels have a bimodal pore size distribution consisting of ... -
Optical Transmitters based on High-Order Surface Grating Lasers for Applications in Communication Systems
(Trinity College Dublin. School of Physics. Discipline of Physics, 2021)Optical communication is the forefront of modern communication systems and is unarguably the leading technology for information sharing and transmission of large amounts of data over longer distances with low latency. Since ... -
Optimizing performance of quantum operations with non-Markovian decoherence: the tortoise or the hare?
(2024)The interaction between a quantum system and its environment limits our ability to control it and perform quantum operations on it. We present an efficient method to find optimal controls for quantum systems coupled to ...