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Emerging Memory Webinar Abstract

This lecture is intended to provide an expository, physics-based, framework for the estimation of the performance potential and physical scaling limits for emerging memory devices. The approach taken seeks to provide physical insight into those parameters and those physical effects that define device performance and scaling properties.

In the beginning of the lecture a generic physics-based abstraction for memory devices will be introduced and applied to several baseline memory technologies, such as DRAM and flash. Fundamental scaling limits for electron-based memory will be analyzed.

Next, emerging memory devices identified by the International Technology Roadmap for Semiconductors (ITRS) will be discussed. A metric for the evaluation of the performance of memory elements operating with different physical principles is proposed, which is the product of energy, space and read/write time.  This metric choice was partially motivated by the minimum action principle of physics (Action = Energy ×Time) but it also reflects the need for an ever-decreasing cell element volume to support denser reduced-energy memory systems. Using basic physics, the optimal Energy-Space-Time products will be estimated for different classes of memory elements.

Another pertinent question addressed in this lecture is: What is the smallest volume of matter needed for a memory? A memory cell in array can be viewed as being composed of two fundamental components: the ‘storage node’, which is usually characterized by the physics of operation of different memory devices and the ‘selector’, which allows a given memory cell in an array to be addressed for read or write. Both components impact scaling limits for memory. For example, for several advanced concepts of resistance-based memories, the storage node could in principle be scaled down below 10 nm, however the memory cell size might be limited by the select device, which faces difficult scaling challenges.

Recently there have been suggestions from research that the physical limits of semiconductor technology may in fact be overcome by borrowing from synthetic biology principles. For example, it has recently been shown that DNA can be used to achieve storage densities that cannot be approached by any known semiconductor technology. This lecture will examine how one might develop a technology in the semiconductor context that would open up DNA memory to widespread applications.