Flexible Parylene C-Based RRAM Array for Neuromorphic Applications

Research progress in architecture and application of RRAM with computing-in-memory

“…In addition, RRAM, made of flexible materials for particular application scenarios, is also a hot topic. Kim et al 30 used PPXC as a resistive switching layer and substrate to fabricate RRAM flexible across-arrays, as shown in Fig. 5(e).…”

Reliable Memristive Synapses Based on Parylene-MoOx Nanocomposites for Neuromorphic Applications

“…The primary objective was to verify the suitability of the studied memristors for emulating synaptic weights in NCSs. Additionally, we addressed the issue of determining the optimal number of resistive states for memristors (i.e., the weight precision) to solve the classification task successfully. ,, …”

“…The primary objective was to verify the suitability of the studied memristors for emulating synaptic weights in NCSs. Additionally, we addressed the issue of determining the optimal number of resistive states for memristors (i.e., the weight precision) to solve the classification task 38,64,65 Two general algorithms exist for setting a memristor's resistive state in NCSs: during or after the training process (on-chip or off-chip training). 38,64,65 The most common approach for achieving the desired resistive state involves applying a specific number of identical voltage pulses (potentiation/depression curves).…”

“…Memristors based on polymer-based organic RS layers, such as polyaniline and poly­(methylsilsesquioxane), have received much attention due to their unique optical properties, flexibility, biocompatibility, and low-cost fabrication. , Poly- p -xylylene (PPX, or parylene) is a promising organic material for memristors because of its cheap and simple production, transparency, and ability to be fabricated on flexible substrates. − Previously, we demonstrated that PPX-based memristors show RS with high plasticity (at least 16 stable states). , However, the RS process was unstable, and we observed poor reproducibility of switching voltages, both cycle-to-cycle (C2C) and device-to-device (D2D).…”

Combination of Organic‐Based Reservoir Computing and Spiking Neuromorphic Systems for a Robust and Efficient Pattern Classification

“…[41] PPX-based OMDs work through the electrochemical metallization mechanism (i.e., ion migration), demonstrate fairly good memristive characteristics, and can be organized in crossbar arrays, which allow them to be used as building blocks of hardware SNSs. [42][43][44][45][46][47] Thus, we propose an RC system with a PANI-based reservoir layer and a PPX-based SNS readout layer modeled in software but based on experimental results. Furthermore in this work, we tested the effectiveness of different approaches (FNS vs. SNS), highlighting the role and impact of the device variations in the total performance of the RC system.…”