  Conductive bridge random access memory devices such as Cu/SiO2/W are
promising candidates for applications in neuromorphic computing due to their
fast, low-voltage switching, multiple-conductance states, scalability, low
off-current, and full compatibility with advanced Si CMOS technologies. The
conductance states, which can be quantized, originate from the formation of a
Cu filament in the SiO2 electrolyte due to cation-migration-based
electrochemical processes. A major challenge related to the filamentary nature
is the strong variability of the voltage required to switch the device to its
conducting state. Here, based on a statistical analysis of more than hundred
fifty Cu/SiO2/W devices, we point to the key role of the activation energy
distribution for copper ion diffusion in the amorphous SiO2. The cycle-to-cycle
variability is modeled well when considering the theoretical energy landscape
for Cu diffusion paths to grow the filament. Perspectives of this work point to
developing strategies to narrow the distribution of activation energies in
amorphous SiO2.
