Error compensated MOF-based ReRAM array for encrypted logical operations

Abstract

Metal–organic frameworks (MOFs) form a unique platform for operation with data using ReRAM technology. Here we report on a large-scale fabrication of a MOF-based ReRAM array with 6 × 6 cells, demonstrating 50% variation in their electronic parameters. Despite this inhomogeneity, such a “non-ideal” ReRAM array is used for recording binary information followed by deep learning processes to achieve 95% accuracy of reading. Next, the same ReRAM array is used to record numbers (from 0 to 15) followed by the operation of addition. For the correct performance of such an analogue algorithm, we determine a set of unique coefficients for each ReRAM cell, allowing us to use this set as an encrypted key to get access to logical operations. The obtained results, thereby, demonstrate the possibility of “non-ideal” MOF-based ReRAM for low error reading of information coupled with encrypted logical operations.