Design of materials properties and device performance in memristive systems

Future development of the modern nanoelectronics and its flagships internet of things and artificial intelligence as well as many related applications is largely associated with memristive elements. This technology offers a broad spectrum of functionalities, however, it follows predominantly a phenomenological approach and crucial challenge/limit for further development remains variability and lack of fundamental materials' design strategy. Here we demonstrate the vital importance of materials' purity for determining memristors' functionalities, showing that part per million foreign elements significantly change the performance. By appropriate choice of chemistry and amount of doping material we can selectively enhance desired operation mode. We highlight how dopant dependent structure and charge/potential distribution in the space charge layers and the cell capacitance determine the device kinetics and functions. We evidence for first time experimentally the relation between materials properties and switching/neuromorphic performance, thus providing rules and directions for a rational design of memristive devices.