This letter investigates the impact of self-heating on the post-cycling functionality of a scaled hafnium oxide-based ferroelectric field-effect transistor (FeFET). The full recovery of FeFET switching properties and data retention after the cycling endurance failure is reported. This is achieved by damage annealing through localized heating, which is intentionally induced by a large current flow through the drain (source)-body p-n junctions. The results highlight that the local thermal treatments could be exploited to extend the cycling endurance of FeFETs.

Visualization of domain structure evolution under an electrical bias has been carried out in ferroelectric La:HfO2 capacitors by a combination of Piezoresponse Force Microscopy (PFM) and pulse switching techniques to study the nanoscopic mechanism of polarization reversal and the wake-up process. It has been directly shown that the main mechanism behind the transformation of the polarization hysteretic behavior and an increase in the remanent polarization value upon the alternating current cycling is electrically induced domain de-pinning. PFM imaging and local spectroscopy revealed asymmetric switching in the La:HfO2 capacitors due to a significant imprint likely caused by the different boundary conditions at the top and bottom interfaces. Domain switching kinetics can be well-described by the nucleation limited switching model characterized by a broad distribution of the local switching times. It has been found that the domain velocity varies significantly throughout the switching process indicating strong interaction with structural defects.

Inspired by neurobiological systems, Spiking Neural Networks (SNNs) are gaining an increasing interest in the field of bio-inspired machine learning. Neurons, as central processing and short-term memory units of biological neural systems, are thus at the forefront of cutting-edge research approaches. The realization of CMOS circuits replicating neuronal features, namely the integration of action potentials and firing according to the all-or-nothing law, imposes various challenges like large area and power consumption. The non-volatile storage of polarization states and accumulative switching behavior of nanoscale HfO₂ - based Ferroelectric Field-Effect Transistors (FeFETs), promise to circumvent these issues. In this paper, we propose two FeFET-based neuronal circuits emulating the Integrate-and-Fire (I&F) behavior of biological neurons on the basis of SPICE simulations. Additionally, modulating the depolarization of the FeFETs enables the replication of a biology-based concept known as membrane leakage. The presented capacitor-free implementation is crucial for the development of neuromorphic systems that allow more complex features at a given area and power constraint.

The electric-field-driven and reversible polarization switching in ferroelectric materials provides a promising approach for nonvolatile information storage. With the advent of ferroelectricity in hafnium oxide, it has become possible to fabricate ultrathin ferroelectric films suitable for nanoscale electronic devices. Among them, ferroelectric field-effect transistors (FeFETs) emerge as attractive memory elements. While the binary switching between the two logic states, accomplished through a single voltage pulse, is mainly being investigated in FeFETs, additional and unusual switching mechanisms remain largely unexplored. In this work, we report the natural property of ferroelectric hafnium oxide, embedded within a nanoscale FeFET, to accumulate electrical excitation, followed by a sudden and complete switching. The accumulation is attributed to the progressive polarization reversal through localized ferroelectric nucleation. The electrical experiments reveal a strong field and time dependence of the phenomenon. These results not only offer novel insights that could prove critical for memory applications but also might inspire to exploit FeFETs for unconventional computing.

Ferroelectrics are promising for nonvolatile memories. However, the difficulty of fabricating ferroelectric layers and integrating them into complementary metal oxide semiconductor (CMOS) devices has hindered rapid scaling. Hafnium oxide is a standard material available in CMOS processes. Ferroelectricity in Si-doped hafnia was first reported in 2011, and this has revived interest in using ferroelectric memories for various applications. Ferroelectric hafnia with matured atomic layer deposition techniques is compatible with three-dimensional capacitors and can solve the scaling limitations in 1-transistor-1-capacitor (1T-1C) ferroelectric random-access memories (FeRAMs). For ferroelectric field-effect-transistors (FeFETs), the low permittivity and high coercive field Ec of hafnia ferroelectrics are beneficial. The much higher Ec of ferroelectric hafnia, however, makes high endurance a challenge. This article summarizes the current status of ferroelectricity in hafnia and explains how major issues of 1T-1C FeRAMs and FeFETs can be solved using this material system.

Hafnium oxide (HfO₂)-based ferroelectric field-effect transistor (FeFET) is an attractive device for nonvolatile memory. However, when compared to the well-established flash devices, the memory window (MW) of FeFETs reported so far is rather limited, which might be an obstacle to practical applications. In this article, we report on FeFETs fabricated in the 28-nm high-𝑘 metal gate (HKMG) bulk technology with 90 and 80 nm for the channel length and width, respectively, which show a large MW of nearly 3 V. This is achieved by adopting 20-nm-thick HfO₂ films in the gate stack instead of the usually employed 10-nm-thick films. We show that such a thickness increase leads to only a moderate increase of the switching voltages, and to a significantly improved resilience of the memory characteristics upon the parasitic charge trapping. The devices display a good retention at high temperatures and endure more than 10⁵ bipolar cycles, thus supporting this technology for a future generation of FeFET memories.

Neuron is the basic computing unit in brain-inspired neural networks. Although a multitude of excellent artificial neurons realized with conventional transistors have been proposed, they might not be energy and area efficient in large-scale networks. The recent discovery of ferroelectricity in hafnium oxide (HfO₂) and the related switching phenomena at the nanoscale might provide a solution. This study employs the newly reported accumulative polarization reversal in nanoscale HfO₂-based ferroelectric field-effect transistors (FeFETs) to implement two key neuronal dynamics: the integration of action potentials and the subsequent firing according to the biologically plausible all-or-nothing law. We show that by carefully shaping electrical excitations based on the particular nucleation-limited switching kinetics of the ferroelectric layer further neuronal behaviors can be emulated, such as firing activity tuning, arbitrary refractory period and the leaky effect. Finally, we discuss the advantages of an FeFET-based neuron, highlighting its transferability to advanced scaling technologies and the beneficial impact it may have in reducing the complexity of neuromorphic circuits.

Ferroelectric field effect transistor (FeFET) memories based on a new type of ferroelectric material (silicon doped hafnium oxide) were studied within the scope of the present work. Utilisation of silicon doped hafnium oxide (Si:HfO2) thin films instead of conventional perovskite ferroelectrics as a functional layer in FeFETs provides compatibility to the CMOS process as well as improved device scalability. The influence of different process parameters on the properties of Si:HfO2 thin films was analysed in order to gain better insight into the occurrence of ferroelectricity in this system. A subsequent examination of the potential of this material as well as its possible limitations with the respect to the application in non-volatile memories followed. The Si:HfO2-based ferroelectric transistors that were fully integrated into the state-of-the-art high-k metal gate CMOS technology were studied in this work for the first time. The memory performance of these devices scaled down to 28 nm gate length was investigated. Special attention was paid to the charge trapping phenomenon shown to significantly affect the device behaviour.

Ferroelectric field effect transistor (FeFET) memories based on a new type of ferroelectric material (silicon doped hafnium oxide) were studied within the scope of the present work. Utilisation of silicon doped hafnium oxide (Si:HfO2) thin films instead of conventional perovskite ferroelectrics as a functional layer in FeFETs provides compatibility to the CMOS process as well as improved device scalability. The influence of different process parameters on the properties of Si:HfO2 thin films was analysed in order to gain better insight into the occurrence of ferroelectricity in this system. A subsequent examination of the potential of this material as well as its possible limitations with the respect to the application in non-volatile memories followed. The Si:HfO2-based ferroelectric transistors that were fully integrated into the state-of-the-art high-k metal gate CMOS technology were studied in this work for the first time. The memory performance of these devices scaled down to 28 nm gate length was investigated. Special attention was paid to the charge trapping phenomenon shown to significantly affect the device behaviour.:1 Introduction 2 Fundamentals 2.1 Non-volatile semiconductor memories 2.2 Emerging memory concepts 2.3 Ferroelectric memories 3 Characterisation methods 3.1 Memory characterisation tests 3.2 Ferroelectric memory specific characterisation tests 3.3 Trapping characterisation methods 3.4 Microstructural analyses 4 Sample description 4.1 Metal-insulator-metal capacitors 4.2 Ferroelectric field effect transistors 5 Stabilisation of the ferroelectric properties in Si:HfO2 thin films 5.1 Impact of the silicon doping 5.2 Impact of the post-metallisation anneal 5.3 Impact of the film thickness 5.4 Summary 6 Electrical properties of the ferroelectric Si:HfO2 thin films 6.1 Field cycling effect 6.2 Switching kinetics 6.3 Fatigue behaviour 6.4 Summary 7 Ferroelectric field effect transistors based on Si:HfO2 films 7.1 Effect of the silicon doping 7.2 Program and erase operation 7.3 Retention behaviour 7.4 Endurance properties 7.5 Impact of scaling on the device performance 7.6 Summary 8 Trapping effects in Si:HfO2-based FeFETs 8.1 Trapping kinetics of the bulk Si:HfO2 traps 8.2 Detrapping kinetics of the bulk Si:HfO2 traps 8.3 Impact of trapping on the FeFET performance 8.4 Modified approach for erase operation 8.5 Summary 9 Summary and Outlook