Defect-Engineered Mn-Doped ZnO Memristors for Hardware-Aware Neuromorphic Image Classification https://sscs.ieee.org/wp-content/themes/movedo/images/empty/thumbnail.jpg 150 150 https://secure.gravatar.com/avatar/8fcdccb598784519a6037b6f80b02dee03caa773fc8d223c13bfce179d70f915?s=96&d=mm&r=g
Abstract:
The practical deployment of neuromorphic hardware requires active materials with precisely controlled defect dynamics to govern charge transport and synaptic plasticity. While pristine ZnO offers a structurally favorable switching platform, the stochastic distribution of native defects often results in poor switching uniformity and compromised retention. In this study, we utilize …