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Full-Text Articles in Physical Sciences and Mathematics
Optimizing Electrospun Ceramic Nanofiber Strength Through Two-Step Sintering, Michael Ross
Optimizing Electrospun Ceramic Nanofiber Strength Through Two-Step Sintering, Michael Ross
Materials Engineering
Two-step sintering (TSS) consists of a high-temperature step and immediate cooling to a sintering temperature for an extended sintering time, where grain growth is suppressed by severe densification during the high-temperature step. TSS is adopted to enhance mechanical properties of electrospun ceramic nanofibers (CNFs), a class of porous ceramics used for environmental remediation, optoelectronics, and filtration. PVP and Ga(NO3)3 nanofiber mesh, provided by Lawrence Livermore National Laboratory, was shaped, oxidized, and two-step sintered to form a nanocrystalline β-Ga2O3 CNF tube using a high-temperature step of 1,000oC. Sintering temperatures and times varied from …
The Martingale Approach To Financial Mathematics, Jordan M. Rowley
The Martingale Approach To Financial Mathematics, Jordan M. Rowley
Master's Theses
In this thesis, we will develop the fundamental properties of financial mathematics, with a focus on establishing meaningful connections between martingale theory, stochastic calculus, and measure-theoretic probability. We first consider a simple binomial model in discrete time, and assume the impossibility of earning a riskless profit, known as arbitrage. Under this no-arbitrage assumption alone, we stumble upon a strange new probability measure Q, according to which every risky asset is expected to grow as though it were a bond. As it turns out, this measure Q also gives the arbitrage-free pricing formula for every asset on our market. 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 …
Daily And Seasonal Variability Of Offshore Wind Power On The Central California Coast And Statewide Demand, Matthew Douglas Kehrli
Daily And Seasonal Variability Of Offshore Wind Power On The Central California Coast And Statewide Demand, Matthew Douglas Kehrli
Physics
No abstract provided.