Process-Induced ReRAM Performance Improvement of Atomic Layer Deposited HfO2 for Analog In-Memory Computing Applications

Abstract

Neuromorphic computing represents a potential paradigm shift from conventional von Neumann computing architecture and shows promise for achieving massive parallelism and power efficiency for such data-centric tasks as image recognition and language processing. Based on the concept of synaptic plasticity, human-like machine learning can be potentially realized by use of arrays of electronic synapses that function in an analogous manner to biological neurons. One of the key features of this type of computing is the ability to control synaptic weights in an analog-like fashion for use in both inference and training applications.A number of existing device technologies in non-volatile memory systems exhibit attractive characteristics for such synaptic devices.[1,2] In particular, resistive switching devices (resistive random-access memory or ReRAM) can change and store their conductance value (G) in response to electrical stimuli making them potentially enabling for deep learning applications involving synaptic weights. For ReRAM devices, HfO2-based thin films can be utilized for filamentary oxide ReRAM and are an attractive option due to their fab-friendly processing and current implementation in high-volume manufacturing.In this study, we evaluated atomic layer deposition (ALD) for the growth of HfO2 for integration in both front-end-of-line (FEOL) and back-end-of-line (BEOL) compatible test structures on 300 mm wafers in order to optimize electrical performance for use as synaptic device elements in neuromorphic architectures. The effect of oxidant in the ALD process was evaluated and it was shown that H2O outperformed O3 in terms of better uniformity and lower forming voltage. By utilizing a hydrogen-based plasma either after the deposition or inserted as an intermediate step during deposition we were able to further decrease forming voltage for a fixed dielectric thickness. Reducing deposition temperature to 200°C in conjunction with the hydrogen-based plasma treatment offered an additional tuning knob to further reduce forming voltage. Stable high-resistance switching (> 100 kΩ) with analog behavior in scaled BEOL devices was also obtained using this optimized HfO2-based ReRAM. Additionally, a tight distribution of forming voltage was obtained ensuring that 99.9999% devices in a 14 nm ReRAM module can be formed below the targeted voltage.References Kuzum et al., Nanotechnology, 24, 382001 (2013)W. Burr et al., Advanced in Physics:X, 2, 89 (2016)