Engineering Commons^™

Improved Contacts And Device Performance In Mos2 Transistors Using 2d Semiconductor Interlayers, Kraig Andrews

Wayne State University Dissertations

The rapid growth of modern electronics industry over the past half-century has been sustained by the continued miniaturization of silicon-based electronics. However, as fundamental limits approach, there is a need to search for viable alternative materials for next-generation electronics in the post-silicon era. Two-dimensional (2D) semiconductors such as transition metal dichalcogenides (TMDs) have attracted much attention due to their atomic thickness, absence of dangling bonds and moderately high carrier mobility. However, achieving low-resistance contacts has been major impediment in developing high-performance field-effect transistors (FETs) based on 2D semiconductors. A substantial Schottky barrier (SB) is often present at the metal/2D-semicondcutor interface, …

Characterization, Modeling, And Thermal Management Of High-Performance Lithium Batteries, Minjun Bae

Wayne State University Theses

Lithium-ion (Li-ion) batteries, as one of the most advanced commercial rechargeable batteries, play a crucial role in modern society as they are extensively used in portable electronic devices. Nevertheless, the limited electrochemical performance and poor thermal management systems of Li-ion batteries have hindered the expansion of their future applications. In search of alternative electrode materials to develop a battery with higher electrochemical performance, lithium (Li) metal has attracted much attention as an ideal alternative anode material due to its high specific capacity and lowest redox potential. However, needle-like Li dendritic growth causes severe safety concerns and thus prohibits practical applications …

Study Of Grain Growth In Single-Phase Polycrystals, Pawan Vedanti

Wayne State University Dissertations

Materials with random microstructure are characterized by additional thermodynamic parameters, entropy and temperature of microstructure. It has been argued that there is one more law of thermodynamics: entropy of microstructure decays in isolated systems. This assertion has been checked experimentally for the process of grain growth which showed that entropy of grain structure decays indeed as expected. The equation of state for microstructure entropy has also been studied. In general, entropy of grain microstructure is expected to be a function of grain structure energy and the average grain size. Our experiments suggest that in fact, the equation of state degenerates …

Ac Conductivity Studies Of Polyethylene-Oxide-Garnet Type Li7la3zr2o12 Hybrid Composite Solid Polymer Electrolyte For Li-Ion Battery, Parisa Bashiri

Wayne State University Dissertations

Solid electrolytes including ceramics and polymers are considered to be the ultimate substitute for organic liquid electrolytes currently used in commercialized lithium ion batteries to address the safety concerns due to Li dendrite growth and internal short circuiting. However, low ionic conductivity due to high grain boundary resistance in ceramics and semi-crystalline nature of polymers has held back the solid electrolytes from being used in Li-ion batteries. Polyethylene oxide (PEO), complexed with a Li-salt, is a well-studied polymer electrolyte showing ionic conductivity properties at room temperature. However, the coexistence of amorphous and crystalline regions at room temperature (< Tm, the melting temperature) has

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Incorporating Cardiac Substructures Into Radiation Therapy For Improved Cardiac Sparing, Eric Daniel Morris

Wayne State University Dissertations

Growing evidence suggests that radiation therapy (RT) doses to the heart and cardiac substructures (CS) are strongly linked to cardiac toxicities, though only the heart is considered clinically. This work aimed to utilize the superior soft-tissue contrast of magnetic resonance (MR) to segment CS, quantify uncertainties in their position, assess their effect on treatment planning and an MR-guided environment.

Automatic substructure segmentation of 12 CS was completed using a novel hybrid MR/computed tomography (CT) atlas method and was improved upon using a 3-dimensional neural network (U-Net) from deep learning. Intra-fraction motion due to respiration was then quantified. The inter-fraction setup …

Process Data Analytics Using Deep Learning Techniques, Majid Moradi Aliabadi

Wayne State University Theses

In chemical manufacturing plants, numerous types of data are accessible, which could be process operational data (historical or real-time), process design and product quality data, economic and environmental (including process safety, waste emission and health impact) data. Effective knowledge extraction from raw data has always been a very challenging task, especially the data needed for a type of study is huge. Other characteristics of process data such as noise, dynamics, and highly correlated process parameters make this more challenging.

In this study, we introduce an attention-based RNN for multi-step-ahead prediction that can have applications in model predictive control, fault diagnosis, …