Tailoring transient-amorphous states: Towards fast and power-efficient phase-change memory and neuromorphic computing

Current efforts to overcome such limitations are focused on employing material-optimization, or scaling, approaches, such as the development of nanowire-based, or nanostructured, PCM devices. However, the improvement of performance with these methods is rapidly becoming impossible due to physical and lithographic constraints. Applying multiple electrical-excitation pulses in a well-programmed manner not only enables the development of a fast, low-power and efficient (parallel-writing) form of PCM, but also provides an opportunity even for achieving biology-like neuromorphic functionalities, which can benefit from a dynamic control of TA-states. The TA-states can be represented by their cluster-size distribution that form the basis of kinetic theory of nucleation, and the shortening of the ACT time upon a stimulus pulse may be described by their evolution. On the microscopic scale, the TA-states may be described by their degree of medium-range order in the disordered-network structure that fluctuates locally and temporally upon excitations