Interlayer engineering for enhanced ferroelectric tunnel junction operations in HfOx-based metal-ferroelectric-insulator-semiconductor stack.

Ferroelectric tunnel junction (FTJ) has been considered as a promising candidate for next-generation memory devices due to its non-destructive and low power operations. In this article, we demonstrate the interlayer (IL) engineering in the FTJs to boost device performances. Through the analysis on the material and electrical characteristics of the fabricated FTJs with engineered IL stacks, it is clearly found that the insertion of an Al2O3layer between the SiO2insulator and the pure-HfOxFE improves the read disturbance (2Vc = 2.2 V increased), the endurance characteristics (tenfold improvement), and the cell-to-cell TER variation simultaneously without the degradation of the ferroelectricity (less than 5%) and the polarization switching speeds through grain size modulation. Based on these investigations, the guidelines of IL engineering for low power ferroelectric devices were provided to obtain stable and fast memory operations.

A novel physical unclonable function (PUF) using 16 × 16 pure-HfOxferroelectric tunnel junction array for security applications.

As the computing paradigm has shifted toward edge computing, improving the security of edge devices is attracting significant attention. However, because edge devices have limited resources in terms of power and area, it is difficult to apply a conventional cryptography system to protect them. On the other hand, as a simple security application, a physical unclonable function (PUF) can be implemented without power and area problems because it provides a security key by utilizing process variations without additional external circuits. Ferroelectric tunnel junctions (FTJs) are 2-terminal devices that store information by changing the resistance of a ferroelectric material, where the resistance is determined by the polarization states of the ferroelectric domains. Because polycrystalline ferroelectric materials have a multi-domain nature, domain variation can also be used as a randomness source to induce cell-to-cell variations along with process variations. In this paper, we demonstrate PUF operations of a low-power, small area 16 × 16 hafnium oxide (pure-HfOx)-based FTJ array using certain metrics. It is clear that the proposed array consisting of scaled FTJs has adequate randomness for security applications such that the array-level PUF operations are robust against model-based machine learning attacks.

Analysis of Hot Carrier Injection According to Gate Length.

In this paper, we analyze hot carrier injection (HCI) in an asymmetric dual gate structure with a charge storage layer. In a floating gate device, holes injected by HCI can move freely in the valence band, since the channel potential is constant. In case of charge trapping layer, however, holes are trapped only in the drain side where impact ionization occurs. Therefore, only small threshold voltage shift occurs because channel formation is enhanced only in the drain side. When the gate length is under 100 nm, trapped holes in the drain side start to control the whole channel. Thus, we expect that HCI into the charge trapping layer can be used as a non-volatile memory (NVM) mechanism in short channel devices.

Comprehensive and accurate analysis of the working principle in ferroelectric tunnel junctions using low-frequency noise spectroscopy.

Recently, ferroelectric tunnel junctions (FTJs) have gained extensive attention as possible candidates for emerging memory and synaptic devices for neuromorphic computing. However, the working principles of FTJs remain controversial despite the importance of understanding them. In this study, we demonstrate a comprehensive and accurate analysis of the working principles of a metal-ferroelectric-dielectric-semiconductor stacked FTJ using low-frequency noise (LFN) spectroscopy. In contrast to resistive random access memory, the 1/f noise of the FTJ in the low-resistance state (LRS) is approximately two orders of magnitude larger than that in the high-resistance state (HRS), indicating that the conduction mechanism in each state differs significantly. Furthermore, the factors determining the conduction of the FTJ in each state are revealed through a systematic investigation under various conditions, such as varying the electrical bias, temperature, and bias stress. In addition, we propose an efficient method to decrease the LFN of the FTJ in both the LRS and HRS using high-pressure forming gas annealing.

Low-Latency Spiking Neural Networks Using Pre-Charged Membrane Potential and Delayed Evaluation.

Spiking neural networks (SNNs) have attracted many researchers' interests due to its biological plausibility and event-driven characteristic. In particular, recently, many studies on high-performance SNNs comparable to the conventional analog-valued neural networks (ANNs) have been reported by converting weights trained from ANNs into SNNs. However, unlike ANNs, SNNs have an inherent latency that is required to reach the best performance because of differences in operations of neuron. In SNNs, not only spatial integration but also temporal integration exists, and the information is encoded by spike trains rather than values in ANNs. Therefore, it takes time to achieve a steady-state of the performance in SNNs. The latency is worse in deep networks and required to be reduced for the practical applications. In this work, we propose a pre-charged membrane potential (PCMP) for the latency reduction in SNN. A variety of neural network applications (e.g., classification, autoencoder using MNIST and CIFAR-10 datasets) are trained and converted to SNNs to demonstrate the effect of the proposed approach. The latency of SNNs is successfully reduced without accuracy loss. In addition, we propose a delayed evaluation method (DE), by which the errors during the initial transient are discarded. The error spikes occurring in the initial transient is removed by DE, resulting in the further latency reduction. DE can be used in combination with PCMP for further latency reduction. Finally, we also show the advantages of the proposed methods in improving the number of spikes required to reach a steady-state of the performance in SNNs for energy-efficient computing.

3D Integrable W/SiNx/n-Si/p-Si 1D1R Unipolar Resistive Random Access Memory Synapse for Suppressing Reverse Leakage in Spiking Neural Network.

In this paper, we pose reverse leakage current issue which occurs when resistive random access memory (RRAM) is used as synapse for spiking neural networks (SNNs). To prevent this problem, 1 diode-1 RRAM (1D1R) synapse is suggested and simulated to examine their current rectifying chracteristics, Furthermore, high density of 1 K 3D 1D1R synapse array structure and its process flow are proposed.

3D AND-Type Stacked Array for Neuromorphic Systems.

NOR/AND flash memory was studied in neuromorphic systems to perform vector-by-matrix multiplication (VMM) by summing the current. Because the size of NOR/AND cells exceeds those of other memristor synaptic devices, we proposed a 3D AND-type stacked array to reduce the cell size. Through a tilted implantation method, the conformal sources and drains of each cell could be formed, with confirmation by a technology computer aided design (TCAD) simulation. In addition, the cell-to-cell variation due to the etch slope could be eliminated by controlling the deposition thickness of the cells. The suggested array can be beneficial in simple program/inhibit schemes given its use of Fowler-Nordheim (FN) tunneling because the drain lines and source lines are parallel. Therefore, the conductance of each synaptic device can be updated at low power level.

Analysis of a Schottky Barrier MOSFET for Synaptic Device Using Hot Carrier Injection.

In this paper, we analyze the hot carrier injection (HCI) in an asymmetric dual-gate structure with a metallic source/drain. We propose a program/erase scheme where HCI occurs on the source side of the body. Owing to the large resistance of the Schottky barrier used, a large electric field is formed around the Schottky barrier. Therefore, impact ionization occurs as the gate voltage is increased and hot carriers are injected into the source side, which is less influenced by the drain voltage. We also analyze the program and erase efficiency by adjusting the Schottky barrier height or by using dopant segregation technique. We expect a small amount of current to flow and great efficiency of the program/erase operations to use as a synaptic device.

Electrical and Thermal Performances of Omega-Shaped-Gate Nanowire Field Effect Transistors for Low Power Operation.

In this paper, we proposed Omega-Shaped-Gate Nanowire Field Effect Transistor (ONWFET) with different gate coverage ratio (GCR). In order to investigate electrical and self-heating characteristics of the proposed devices, on-current, off-current, subthreshold swing (SS), and operating temperature were examined by using 3D TCAD simulator and compared with nanowire MOSFET (NW-MOSFET). As a result, a possibility of reducing off-current and operating temperature was demonstrated by using the ONWFET with 40% GCR. Therefore, the ONWFET can save power consumption and serve as low power application such as battery-powered portable electronic devices.