Epitaxy and thickness scaling of ferroelectric AlScN : towards next-generation memory and computing devices

Information technology including the recent advance of artificial intelligence demands a huge amount of electrical power. Next-generation devices based on the ferroelectric effect could potentially lower this demand. The field-driven switching of the polarization by the application of an electric field promises lowest energy consumption as well as it allows for various device concepts. Such devices are suitable for detaching from the classical Von-Neumann architecture by merging memory and computation (in-memory) and thus lowering the latency gap between those. Additionally, they allow for addressing neuromorphic architectures by emulating the functionality of synapses and neurons found in the human brain on device level. However, after the discovery of ferroelectricity ≈ 100 years ago, ferroelectric random access memory (FeRAM) is up to now the only commercial available memory product which is based on the ferroelectric switching. This is mainly due to the poor Complementary Metal Oxide Semiconductor (CMOS)-compatibility of classical ferroelectric materials such as the perovskites and the related integration and scalability issues. This situation changed after the discovery of ferroelectricity in the CMOS-compatible fluorite-type structures in 2013, which resulted in the demonstration of various types of highly scaled ferroelectricity-based memory and computation devices which are close to commercialization. This was followed by the discovery of ferroelectricity in CMOS-compatible wurtzite-type AlScN in 2019, on which this doctoral thesis is building up. The structure and chemistry of the fluorite- and wurtzite-type ferroelectrics and their respective electrical response differs fundamentally, thus potential advantages and disadvantages in terms of device applications can be expected. The goal of this doctoral thesis is to gain a fundamental understanding of the switching phenomena in AlScN and to identify suitable applications.

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