10×10nm2 Hf/HfOx crossbar resistive RAM with excellent performance, reliability and low-energy operation

By B. Govoreanu, G. Kar, Y. Y. Chen, V. Paraschiv, S. Kubicek, A. Fantini, I. Radu, L. Goux, S. Clima, R. Degraeve and 11 more. International Electron Devices Meeting, 2011

684 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/ac420aad10d7081ecedb50f42793c01d71e48ec0

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In Electrical and Electronic Engineering

Citations in the corpus

In-memory computing with resistive switching devices (2018, background): “Resistive switching devices, such as RRAM, offer several advantages in digital computing, such as the direct access by interconnect lines, the capability to electrically reconfigure the device, and nanoscale miniaturization [40].”
Memristive technologies for data storage, computation, encryption, and radio-frequency communication (2022, background): “Even though transistors can be very small, the real lateral size of the smallest transistors (in the 5-nm node) is actually ~20 nm (24), which is larger than the minimum size of state-of-the-artmemristiveMIMnanocellswith acceptable performance: 10 nm (6).”
On the Switching Parameter Variation of Metal Oxide RRAM—Part II: Model Corroboration and Device Design Strategy (2012, background): “Even for a 10-nm HfOx RRAM device [25], the HRS variation is still remarkable.”
Endurance/Retention Trade-off on $\hbox{HfO}_{2}/\hbox{Metal}$ Cap 1T1R Bipolar RRAM (2013, methodology): “scaled non-volatile memories replacement beyond the 16 nm node [1]–[4].”
Stochastic Memristive Devices for Computing and Neuromorphic Applications (2013, background): “Devices based on resistive switching (memristive devices or memristors (2-6) have been identified as a major contender in applications ranging from nonvolatile memory storage, logic, to neuromorphic systems due to their scalability (7), low power operation (8), and large connectivity offered in a cr”
A Physics-Based Compact Model of Metal-Oxide-Based RRAM DC and AC Operations (2013, background): “Extensive researches have been conducted to understand the resistive switching mechanisms and improve the performance of RRAM [5]–[8].”
Neuro-Inspired Computing With Emerging Nonvolatile Memorys (2018, background): “10 nm without sacrificing their endurance, retention, and tuning accuracy, with some of the properties (such as the on/off conductance ratio) being actually improved [102].”