Resistance Drift Convergence and Inversion in Amorphous Phase Change Materials

Phase change materials (PCMs) are key to the development of artificial intelligence technologies such as high-density memories and neuromorphic computing, thanks their ability for multi-level data storage through stepwise resistive encoding. Individual resistance levels realized by adjusting crystalline amorphous volume fraction memory cell. However, phase exhibits a drift in over time that has so far hindered commercial implementation schemes. In this study, underlying physical process with goal modeling is elucidated will help minimize potentially overcome PCM devices. Clear evidence provided dominated glass dynamics. Resistivity convergence inversion chalcogenide Ge15Te85 Ge3Sb6Te5 experimentally demonstrated these changes successfully predicted dynamics model. This new insight into provides tools advanced