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Full-Text Articles in Chemistry
Vertical Ionization Energies From The Average Local Electron Energy Function, Amer Marwan El-Samman
Vertical Ionization Energies From The Average Local Electron Energy Function, Amer Marwan El-Samman
Electronic Thesis and Dissertation Repository
It is a non-intuitive but well-established fact that the first and higher vertical ionization energies (VIE) of any N-electron system are encoded in the system's ground-state electronic wave function. This makes it possible to compute VIEs of any atom or molecule from its ground-state wave function directly, without performing calculations on the (N-1)-electron states. In practice, VIEs can be extracted from the wave function by using the (extended) Koopmans' theorem or by taking the asymptotic limit of certain wave-function-based quantities such as the ratio of kinetic energy density to the electron density. However, when the wave function is expanded in …
Implementation Of Multivariate Artificial Neural Networks Coupled With Genetic Algorithms For The Multi-Objective Property Prediction And Optimization Of Emulsion Polymers, David Chisholm
Master's Theses
Machine learning has been gaining popularity over the past few decades as computers have become more advanced. On a fundamental level, machine learning consists of the use of computerized statistical methods to analyze data and discover trends that may not have been obvious or otherwise observable previously. These trends can then be used to make predictions on new data and explore entirely new design spaces. Methods vary from simple linear regression to highly complex neural networks, but the end goal is similar. The application of these methods to material property prediction and new material discovery has been of high interest …
A Robust And Automated Deconvolution Algorithm Of Peaks In Spectroscopic Data, William Johan Burke Iv
A Robust And Automated Deconvolution Algorithm Of Peaks In Spectroscopic Data, William Johan Burke Iv
Theses and Dissertations
The huge amount of spectroscopic data in use in metabolomic experiments requires an algorithm that can process the data in an autonomous fashion while providing quality of analysis comparable to manual methods. Scientists need an algorithm that effectively deconvolutes spectroscopic peaks automatically and is resilient to the presence of noise in the data. The algorithm must also provide a simple measure of quality of the deconvolution. The deconvolution algorithm presented in this thesis consists of preprocessing steps, noise removal, peak detection, and function fitting. Both a Fourier Transform and Continuous Wavelet Transform (CWT) method of noise removal were investigated. The …