

12,13 After that, FeFETs using various ferroelectric materials have been manufactured, and this has shown better low power driving and faster read/write speed than DRAM, static RAM (SRAM), and flash memory. discovered the ferroelectricity of Rochelle salt in 1920, Moll and Tarui first proposed the concept of the FeFET using triglycine sulfate (TGS) in 1963. It plays a critical role in neuromorphic computing.


10 Furthermore, a multi-level current flows between the source and the drain ( I sd), and a synaptic weight (SW) can be formed by controlling the gate voltage pulse of the FeFET.

8,9 This 1T structure allows the circuit to achieve higher density in a situation where the limit of integration degree is reached. 6,7 The 1T structure using the FeFET, which can serve as both a switch and memory, was first proposed in 1995, as illustrated in Fig. FeFETs that exhibit the characteristics of nonvolatile memory (NVM) and synaptic devices are an essential element for implementing high-integration circuits and neuromorphic computing. 3–5 In response to these demands, ferroelectric field effect transistors (FeFETs) have received attention for next-generation FET devices because of fast operation speed, low power requirements, and non-destructive read capability as a memory device. 1,2 Accordingly, attempts have been made to break away from the existing von Neumann computer architecture, where the storage space and the computational processing space are separated. Due to this trend, there is a need for a device that has both the fast operating speed of the dynamic random access memory (DRAM) and the nonvolatile characteristics of the NAND flash memory. The demand for machine learning and deep learning has increased as artificial intelligence (AI) technology is used throughout society. Finally, the limitations of these devices’ current performance and the potential of these materials are presented. FeFETs, ferroelectric semiconductor field effect transistors, and metal–ferroelectric–insulator–semiconductor structures to which those materials can be applied are introduced, and their exotic performances are investigated. FeFETs using Pb(Zr xTi 1−x)O 3, polyvinylidene fluoride, HZO, and two-dimensional materials are emphasized. In this article, the basic principles of the FeFET and the design strategies for state-of-the-art FeFETs will be discussed. Since the discovery of hafnium–zirconium oxide (HZO) with high ferroelectricity (even at a thickness of several nanometers) that can be fabricated by a complementary metal–oxide–semiconductor-compatible process, FeFETs have emerged as devices with great potential. Ferroelectric field effect transistors (FeFETs) have attracted attention as next-generation devices as they can serve as a synaptic device for neuromorphic implementation and a one-transistor (1T) for achieving high integration.
