Nanoscale resistive memory with intrinsic diode characteristics and long endurance

Abstract

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The future of electronics based on memristive systems

“…A class of memristors used in memory applications is also often called resistive random access memory (RRAM) 4,5 . Fundamental device studies have shown that the device can be scaled to sub-10 nm feature sizes 6 and retain memory states for years 7 , while offering desirable device properties such as subnanosecond switching speed 8,9 , long write-erase endurance 10 and low programming energy (for example, nanoamperes 11 ). It should be noted that while many of the above favourable properties have been realized repeatedly, a single material system that combines them all simultaneously remains an open challenge.…”

Threshold switching behavior of Ag-Si based selector device and hydrogen doping effect on its characteristics

“…2 One way to suppress the sneak current is to use RRAMs with self-rectification property as one resistor (1R) configuration since the rectifying characteristics can significantly reduce the leakage current flowing through a reverse-biased RRAM cell, and various types of rectifying RRAM devices have been demonstrated. [3][4][5] An alternative method is to connect a nonlinear circuit element such as a selector device to each RRAM cell as one selector and one resistor 1S-1R configuration. Several selector devices such as tunneling didoes, 6 bidirectional varistors, 7 mixed-ionic-electronic-conduction (MIEC), 8 Ovonic threshold switching (OTS) 9 and metal-insulator transition (MIT) have been proposed.…”

Demonstration and modeling of multi-bit resistance random access memory

“…1 RRAM can also exhibit >2 resistance states that may promise multi-bit storage. [2][3][4][5][6][7][8] In principle, if each single cell can display 2 N distinguished states, then for the same storage capacity the required die area will scale with 1/N. Stated alternatively, for the same die area, each 2 N -state layer of a 2D memory has the same storage capacity of N 2-state layers of a 3D memory.…”