Large magnetization modulation in ZnO-based memory devices with embedded graphene quantum dots

Flexible Threshold-Type Switching Devices with Low Threshold and High Stability Based on Silkworm Hemolymph

In this paper, a floating-gate flexible nonvolatile memory is reported that is composed of natural biological materials, namely, silkworm hemolymph, graphene quantum dots as the floating-gate layer, and polymethyl methacrylate (PMMA) as the insulating layer. The device has a high ON/OFF current ratio (4.76 × 106), a low setting voltage (<−1.75 V), and good durability and retention ability. The device has two storage characteristics, namely, Flash and WORM, which can be effectively and accurately controlled by adjusting the limiting current during device setting. The resistance switching characteristics are the result of the formation and fracture of conductive filaments. The floating-gate flexible bioresistive random access memory prepared in this paper provides a new idea for the development of multifunctional and biocompatible flexible memory.

Dual-Tunable Memristor Based on Carbon Nanotubes and Graphene Quantum Dots

Nanocarbon materials have the advantages of biocompatibility, thermal stability and chemical stability and have shown excellent electrical properties in electronic devices. In this study, Al/MWCNT:GQD/ITO memristors with rewritable nonvolatile properties were prepared based on composites consisting of multiwalled carbon nanotubes (MWCNTs) and graphene quantum dots (GQDs). The switching current ratio of such a device can be tuned in two ways. Due to the ultraviolet light sensitivity of GQDs, when the dielectric material is illuminated by ultraviolet light, the charge capture ability of the GQDs decreases with an increasing duration of illumination, and the switching current ratio of the device also decreases with an increasing illumination duration (10³–10). By exploiting the charge capture characteristics of GQDs, the trap capture level can be increased by increasing the content of GQDs in the dielectric layer. The switching current ratio of the device increases with increasing GQD content (10–10³). The device can be programmed and erased more than 100 times; the programmable switching state can withstand 10⁵ read pulses, and the retention time is more than 10⁴ s. This memristor has a simple structure, low power consumption, and enormous application potential for data storage, artificial intelligence, image processing, artificial neural networks, and other applications.