We measured the switching time statistics for a TiO(2) memristor and found that they followed a lognormal distribution, which is a potentially serious problem for computer memory and data storage applications. We examined the underlying physical phenomena that determine the switching statistics and proposed a simple analytical model for the distribution based on the drift/diffusion equation and previously measured nonlinear drift behavior. We designed a closed-loop switching protocol that dramatically narrows the time distribution, which can significantly improve memory circuit performance and reliability.
In nanoscale memristive switching devices, the statistical distribution of resistance values and other relevant parameters for device operation often exhibits a lognormal distribution, causing large fluctuations of memristive analog state variables after each switching event, which may be problematic for digital nonvolatile memory applications. The state variable w in such devices has been proposed to be the length of an undoped semiconductor region along the thickness of the thin film that acts as a tunnel barrier for electronic transport across it. The dynamical behavior of w is governed by the drift diffusion of ionized dopants such as oxygen vacancies. Making an analogy to scanning tunneling microscopes (STM), a closed-loop write scheme using current feedback is proposed to switch the memristive devices in a controlled manner. An integrated closed-loop current driver circuit for switching a bipolar memristive device is designed and simulated. The estimated upper limit of the feedback loop bandwidth is in the order of 100 MHz. We applied a SPICE model built upon the TiO 2 memristive switching dynamics to simulate the single-device write operation and found the closed-loop write scheme caused a narrowing of the statistical distribution of the state variable w.
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