Graphene-based RRAM devices for neural computing

Transient N-GQDs/PVA nanocomposite thin film for memristor application

In recent years quantum dot (QDs) based resistive switching devices(memristors) have gained a lot of attention. Here we report the resistive switching behavior of nitrogen-doped graphene quantum dots/Polyvinyl alcohol (N-GQDs/PVA) degradable nanocomposite thin film with different weight percentages (wt.%) of N-GQDs. The memristor device was fabricated by a simple spin coating technique. It was found that 1 wt% N-GQDs/PVA device shows a prominent resistive switching phenomenon with good cyclic stability, high on/off ratio of ~102and retention time of ∼104s. From a detailed experimental study of band structure, we conclude that memristive behavior originates from the space charge controlled conduction (SCLC) mechanism. Further transient property of built memristive device was studied. Within three minutes of being submerged in distilled water, the fabricated memory device was destroyed. This phenomenon facilitates the usage of fabricated memristor devices to develop memory devices for military and security purposes.

Neuromorphic Photonics Circuits: Contemporary Review

Neuromorphic photonics is a cutting-edge fusion of neuroscience-inspired computing and photonics technology to overcome the constraints of conventional computing architectures. Its significance lies in the potential to transform information processing by mimicking the parallelism and efficiency of the human brain. Using optics and photonics principles, neuromorphic devices can execute intricate computations swiftly and with impressive energy efficiency. This innovation holds promise for advancing artificial intelligence and machine learning while addressing the limitations of traditional silicon-based computing. Neuromorphic photonics could herald a new era of computing that is more potent and draws inspiration from cognitive processes, leading to advancements in robotics, pattern recognition, and advanced data processing. This paper reviews the recent developments in neuromorphic photonic integrated circuits, applications, and current challenges.