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TOWARD III-NITRIDE BASED FERROELECTRIC HIGH ELECTRON MOBILITY TRANSISTORS

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Abstract

With growing needs for data-centric applications such as edge intelligence in recent years, the semiconductor industry has been actively looking for new computing hardware that involves high-speed and energy-efficient data processing solutions. Innovation in memory is critical in resolving the speed mismatch between memory and logic present in von Neumann-based computing architectures. Moving toward near-memory or in-memory computing architectures, which enable efficient data transfer between logic cores and memories, embedded non-volatile memories are arising as a strong candidate for dataintensive applications. In this work, ferroelectric field-effect transistors (FeFETs) are investigated as a memory element for such new computing platforms. The recent discovery of a ferroelectric nitride, ScAlN, shed light on the epitaxial nitride-based FeFET solution. Possessing several advantages for FeFET-based memories, ScAlN has the potential to outperform the widely-investigated Hf0.5Zr0.5O2. The MBE-grown ScAlN exhibits ferroelectric properties that are highly desirable for achieving a sufficient memory window at reasonable operating voltages. The high-quality epitaxial interfaces are expected to help mitigate charge trapping issues reported in Hf0.5Zr0.5O2-based FeFETs. This work aims to manifest the advantages of ScAlN for FeFETs compared with other ferroelectric options and to demonstrate experimental efforts toward the III-nitride FeFETs. An Analytical FeFET model is used to simulate and compare the figures of merit of FeFETs based on various ferroelectrics. ScAlN, grown by reactive co-sputtering and MBE, is fabricated into capacitors and field-effect transistors (FETs), and the electrical properties of the devices are investigated. Despite some challenges in the growth and fabrication of the recent generation, ScAlN shows the potential as a high-k dielectric barrier for FETs and is expected to add a ferroelectric functionality to the III-nitride platform.

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143 pages

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2022-08

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Union Local

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Xing, H. Grace

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Jena, Debdeep
Molnar, Alyosha Christopher

Degree Discipline

Electrical and Computer Engineering

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Ph. D., Electrical and Computer Engineering

Degree Level

Doctor of Philosophy

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Government Document

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dissertation or thesis

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