Nanoscale resistive switching memory devices: a review

In this review the different concepts of nanoscale resistive switching memory devices are described and classified according to their I–V behaviour and the underlying physical switching mechanisms. By means of the most important representative devices, the current state of electrical performance characteristics is illuminated in-depth. Moreover, the ability of resistive switching devices to be integrated into state-of-the-art CMOS circuits under the additional consideration with a suitable selector device for memory array operation is assessed. From this analysis, and by factoring in the maturity of the different concepts, a ranking methodology for application of the nanoscale resistive switching memory devices in the memory landscape is derived. Finally, the suitability of the different device concepts for beyond pure memory applications, such as brain inspired and neuromorphic computational or logic in memory applications that strive to overcome the vanNeumann bottleneck, is discussed

Accumulative Polarization Reversal in Nanoscale Ferroelectric Transistors

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

On the stabilization of ferroelectric negative capacitance in nanoscale devices

Recently, the proposal to use voltage amplification from ferroelectric negative capacitance (NC) to reduce the power dissipation in nanoelectronic devices has attracted significant attention. Homogeneous Landau theory predicts, that by connecting a ferroelectric in series with a dielectric capacitor, a hysteresis-free NC state can be stabilized in the ferroelectric below a critical film thickness. However, there is a strong discrepancy between experimental results and the current theory. Here, we present a comprehensive revision of the theory of NC stabilization with respect to scaling of material and device dimensions based on multi-domain Ginzburg–Landau theory. It is shown that the use of a metal layer in between the ferroelectric and the dielectric will inherently destabilize NC due to domain formation. However, even without this metal layer, domain formation can reduce the critical ferroelectric thickness considerably, limiting not only the range of NC stabilization, but also the maximum amplification attainable. To overcome these obstacles, the downscaling of lateral device dimensions is proposed as a way to prevent domain formation and to enhance the voltage amplification due to NC. These insights will be crucial for future NC device design and scaling towards nanoscale dimensions

Ferroelectric hafnium oxide for ferroelectric random-access memories and ferroelectric field-effect transistors

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

Mimicking biological neurons with a nanoscale ferroelectric transistor

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

Simulation of integrate-and-fire neuron circuits using HfO₂-based ferroelectric field effect transistors

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