Low‐Power Self‐Rectifying Memristive Artificial Neural Network for Near Internet‐of‐Things Sensor Computing

Frequent data transfers between Internet‐of‐Things (IoT) sensors and cloud servers consume energy and lead to latency—a bottleneck for ubiquitous computing. To reduce the need for such enormous data transfers, the combined function of IoT sensors and near‐sensor artificial neural networks can process data properly before they are transferred to cloud servers. Herein, energy‐efficient memristor crossbar arrays are demonstrated for image recognition tasks that are potentially adopted for IoT sensors. The adoption of the selector‐free memristor device with a self‐rectifying function allows for simple stacking of metal–dielectric–metal layer, thus significantly simplifying the fabrication process while achieving low‐current operation (