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Materials Science and Engineering

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Clemson University

Theses/Dissertations

Microstructure

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Investigating The Effects Of Sic Abrasive Particles On Friction Element Welding, Gaurav Awate May 2022

Investigating The Effects Of Sic Abrasive Particles On Friction Element Welding, Gaurav Awate

All Theses

The growing demands on reducing the harmful emissions from automobiles have forced automakers to reduce the weight of the vehicle. The increasing demands on improving the fuel economy also has challenged automotive manufacturers to make the vehicle as lightweight as possible. However, the challenge is also to ensure that the vehicle meets safety standards. For the vehicle to meet these standards, it needs to be of adequate strength as well. Automotive manufacturers have adopted a strategy of using multi-material construction to achieve the target. But with multi-material construction comes the requirement of advanced joining techniques that are capable of joining …


Deep Learning-Guided Prediction Of Material’S Microstructures And Applications To Advanced Manufacturing, Jianan Tang Dec 2021

Deep Learning-Guided Prediction Of Material’S Microstructures And Applications To Advanced Manufacturing, Jianan Tang

All Dissertations

Material microstructure prediction based on processing conditions is very useful in advanced manufacturing. Trial-and-error experiments are very time-consuming to exhaust numerous combinations of processing parameters and characterize the resulting microstructures. To accelerate process development and optimization, researchers have explored microstructure prediction methods, including physical-based modeling and feature-based machine learning. Nevertheless, they both have limitations. Physical-based modeling consumes too much computational power. And in feature-based machine learning, low-dimensional microstructural features are manually extracted to represent high-dimensional microstructures, which leads to information loss.

In this dissertation, a deep learning-guided microstructure prediction framework is established. It uses a conditional generative adversarial network (CGAN) …


Microstructure Modification Of Cu0.2ag2.8sbsete2 Through, Sloan Lindsey Aug 2010

Microstructure Modification Of Cu0.2ag2.8sbsete2 Through, Sloan Lindsey

All Theses

Cu0.2Ag2.8SbSeTe2 is new potential thermoelectric compound that exhibits very low thermal conductivity and a region of glass-like thermal conductivity. The compound phase segregates into AgSbTe2 and Ag2Te phases with Se and Cu acting as isoelectronic dopants. Backscatter SEM imaging is used to study the resulting microstructure. Normally cast samples exhibit cracks forming near the interfaces of the two phases. In this work we show that the cracks are caused by a low temperature monoclinic to cubic phase transition that occurs in the Ag2Te phase. We demonstrate that through rapid quenching we can control the size and shape of the phase …