Engineering Science and Materials Commons^™

The Study Of Corrosion On Additive-Manufactured Metals., Braydan Daniels

Electronic Theses and Dissertations

The purpose of this study was to investigate and compare the corrosion mechanisms between wrought and additive-manufactured (3D-printed) copper and stainless steel. The experimental procedure consisted of measuring the open circuit potential, electrochemical impedance spectroscopy, linear sweep voltammetry, Tafel analysis, surface topology, and scanning electron microscopy for each metal within salt water, tap water, sulfuric acid, and synthetic body fluid (excluding copper in synthetic body fluid).

Overall, printed stainless steel was more corrosion-resistant than wrought stainless steel in tap water and synthetic body fluid based on OCP, LSV, and surface topology results. Additionally, printed copper was more corrosion-resistant than wrought …

Metal Thin Film Stiffness Extraction Technique For Surface Acoustic Wave Filters, Travis R. Weismeyer

Electronic Theses and Dissertations

Accurate knowledge of the surface acoustic wave (SAW) properties propagating at the surface of a piezoelectric substrate with thin films, electrodes or temperature compensated films, is critical in SAW filter design to meet the target frequency response, power durability and performance prior to device fabrication. While reliable material constants exist for substrates such as LiNbO3 used in SAW filters, the absolute elastic constants associated with operational thin films used for electrodes or temperature compensation do not exist. Although the bulk values of the constituent materials are known, the composite film/substrate properties are difficult to predict since they depend strongly on …

Data Driven Discovery Of Materials Properties., Fadoua Khmaissia

Electronic Theses and Dissertations

The high pace of nowadays industrial evolution is creating an urgent need to design new cost efficient materials that can satisfy both current and future demands. However, with the increase of structural and functional complexity of materials, the ability to rationally design new materials with a precise set of properties has become increasingly challenging. This basic observation has triggered the idea of applying machine learning techniques in the field, which was further encouraged by the launch of the Materials Genome Initiative (MGI) by the US government since 2011. In this work, we present a novel approach to apply machine learning …