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Full-Text Articles in Engineering
Modeling Solvent Extraction Of Lignin From Hardwoods, Su Pan
Modeling Solvent Extraction Of Lignin From Hardwoods, Su Pan
McKelvey School of Engineering Theses & Dissertations
This study interprets the observed behavior of solvent extraction of lignin from hardwoods by adapting the framework of the FLASHCHAIN theory (Niksa and Kerstein, 1991; Niksa, 2017). A constitution submodel specifies distributions of molecular weight and reactive sites for native lignin. The model simulates delignification as depolymerization of lignin macromolecules into fragments small enough to be soluble. This process competes with intrachain condensation that consumes labile bridges without forming new fragments, and with recombination that forms larger chains and inhibits further depolymerization. After the soluble fragments are transported from the particle into the bulk solvent, all chemistry continues as long …
Advanced Materials For Air Pollutants Removal In A Combustion System, Sungyoon Jung
Advanced Materials For Air Pollutants Removal In A Combustion System, Sungyoon Jung
McKelvey School of Engineering Theses & Dissertations
Air pollutants directly or indirectly impact human health and the environment. Large quantities of CO2, volatile organic compounds (VOCs), and particulate matter are emitted from combustion systems, and cause climate change, smog formation, and pose serious health risks. The increasing demand for the remediation of air pollutants at the source has drawn much attention to the use of advanced materials due to their high reactivities and special properties. In order to achieve the successful application of advanced materials for the remediation of problematic emissions, three aspects, (1) synthesis method, (2) characterization of materials’ structural properties, and (3) evaluation of materials’ …
Applying Bayesian Machine Learning Methods To Theoretical Surface Science, Shane Carr
Applying Bayesian Machine Learning Methods To Theoretical Surface Science, Shane Carr
McKelvey School of Engineering Theses & Dissertations
Machine learning is a rapidly evolving field in computer science with increasingly many applications to other domains. In this thesis, I present a Bayesian machine learning approach to solving a problem in theoretical surface science: calculating the preferred active site on a catalyst surface for a given adsorbate molecule. I formulate the problem as a low-dimensional objective function. I show how the objective function can be approximated into a certain confidence interval using just one iteration of the self-consistent field (SCF) loop in density functional theory (DFT). I then use Bayesian optimization to perform a global search for the solution. …