Nanoporous Dielectric Resistive Memories Using Sequential Infiltration Synthesis

Resistance switching in metal-insulator-metal structures has been extensively studied in recent years for use as synaptic elements for neuromorphic computing and as nonvolatile memory elements. However, high switching power requirements, device variabilities, and considerable trade-offs between low operating voltages, high on/off ratios, and low leakage have limited their utility. In this work, we have addressed these issues by demonstrating the use of ultraporous dielectrics as a pathway for high-performance resistive memory devices. Using a modified atomic layer deposition based technique known as sequential infiltration synthesis, which was developed originally for improving polymer properties such as enhanced etch resistance of electron-beam resists and for the creation of films for filtration and oleophilic applications, we are able to create similar to 15 nm thick ultraporous (pore size similar to 5 nm) oxide dielectrics with up to 73% porosity as the medium for filament formation. We show, using the Ag/Al2O3 system, that the ultraporous films result in ultrahigh on/off ratio (>10(9)) at ultralow switching voltages (similar to +/- 600 mV) that are 10x smaller than those for the bulk case. In addition, the devices demonstrate fast switching, pulsed endurance up to 1 million cycles. and high temperature (125 degrees C) retention up to 10(4) s, making this approach highly promising for large-scale neuromorphic and memory applications. Additionally, this synthesis methodology provides a compatible, inexpensive route that is scalable and compatible with existing semiconductor nanofabrication methods and materials.

Automated summary

This study addresses the issues of high switching power requirements and device variabilities in metal-insulator-metal structures by using ultraporous dielectrics for high-performance resistive memory devices. The ultraporous films exhibit ultrahigh on/off ratio and ultralow switching voltages, making them promising for large-scale neuromorphic and memory applications. The synthesis methodology provides a compatible, inexpensive route that is scalable and compatible with existing semiconductor nanofabrication methods and materials.