Design of projected phase-change memory mushroom cells for low-resistance drift

Abstract

Abstract: Projected phase-change memory (PCM) devices have been proposed as a solution to the challenge of resistance drift, an issue where PCM cell resistance increases as a function of time. Here, we theoretically and experimentally study the performance of projected mushroom PCM cells. Using circuit models, we show that the effective drift coefficient of projected PCM cells is proportional to the fraction of the current flowing through the drifting material. To further characterize device operation, we utilize a finite element model and find that tuning the projection liner sheet resistance enables a dynamic range, the ratio of the RESET resistance to the SET resistance, of 14 with a thin 2-nm projection liner. Additionally, we show that increasing the doping level provides a useful tuning knob to increase SET and RESET resistance without sacrificing dynamic range or drift performance. We fabricate projected PCM mushroom cells on 300-mm wafers to calibrate the model parameters and find that experimental trends are consistent with these theoretical predictions. Impact statement: Resistance drift presents a significant challenge in leveraging phase-change memory (PCM) for neuromorphic computing applications. Projected PCM devices offer an alternative design to significantly reduce resistance drift by bypassing the high-drift amorphous PCM material with a lower resistance parallel resistor during the read operation. Although projected PCM bridge cells have been successfully demonstrated, they can be challenging to fabricate reliably on a wafer scale due to inherent etch damage and variability near the active region. Here, we study the performance of the projected PCM mushroom cell, a design that offers a more manufacturable route to fabricate the large arrays of cells needed for analog artificial intelligence hardware. Using finite element method simulations and equivalent circuit models, we highlight the tradeoff between minimizing drift and achieving large dynamic range when increasing the liner sheet resistance. We show that thinner liners enable the largest dynamic range and that the PCM doping can be used to tune the cell SET and RESET resistances. Using this insight, we fabricate projected PCM mushroom cells on 300-mm wafers at the IBM Research AI Hardware Center and confirm these theoretical predictions. Our work, therefore, demonstrates the manufacturability of projected PCM cells for analog computing. Graphical abstract: [Figure not available: see fulltext.]