Essays about: "ab initio simulation"
Showing result 1 - 5 of 9 essays containing the words ab initio simulation.
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1. Tuning Photovoltaic Properties of Two-dimensional Molybdenum Disulfide by Alloying: An ab initio study
University essay from KTH/MaterialvetenskapAbstract : Addressing the urgent need for innovative energy solutions amidst increasing environmental concerns, the focus on photovoltaic solar cells is intensifying. Currently limited by the Shockley-Queisser limit, conventional silicon-based solar cells offer a maximum power conversion efficiency of 32%. READ MORE
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2. Surface orientation of the formamidinium cation in black formamidinium lead iodide perovskite
University essay from Stockholms universitet/FysikumAbstract : Formamidinium lead iodide perovskite (FAPI) holds promise to be used in high–efficiency solar cells. A comprehensive understanding of the immediate surface properties of this material can provide insights into its interaction with other materials and guide future engineering of its interface with other constituents of the solar cell. READ MORE
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3. Modelling Magnetism of hcp Iron under Earth’s Inner Core Conditions : Based on first-principle DFT calculations and Machine Learning
University essay from Linköpings universitet/Teoretisk FysikAbstract : The structure of Earth’s core remains largely a mystery. The solid inner core is believed to exist in extreme pressure and temperature conditions comparable to 300 GPa and 6000 K and consists mainly of iron, Fe. READ MORE
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4. Accelerating bulk material property prediction using machine learning potentials for molecular dynamics : predicting physical properties of bulk Aluminium and Silicon
University essay from Linköpings universitet/Teoretisk FysikAbstract : In this project machine learning (ML) interatomic potentials are trained and used in molecular dynamics (MD) simulations to predict the physical properties of total energy, mean squared displacement (MSD) and specific heat capacity for systems of bulk Aluminium and Silicon. The interatomic potentials investigated are potentials trained using the ML models kernel ridge regression (KRR) and moment tensor potentials (MTPs). READ MORE
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5. Accelerating longitudinal spinfluctuation theory for iron at high temperature using a machine learning method
University essay from Linköpings universitet/Teoretisk FysikAbstract : In the development of materials, the understanding of their properties is crucial. For magnetic materials, magnetism is an apparent property that needs to be accounted for. There are multiple factors explaining the phenomenon of magnetism, one being the effect of vibrations of the atoms on longitudinal spin fluctuations. READ MORE
