Fully 2D Materials‐Based Resistive Switching Circuits for Advanced Data Encryption

• Published in: Advanced functional materials Vol. 34; no. 41
• Main Authors: Han, Tingting, Aguirre, Fernando, Zhu, Kaichen, Yuan, Bin, Pazos, Sebastian, Zhang, Nan, Wang, Sui‐Dong, Li, Shaojuan, Lanza, Mario
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc 01-10-2024
• Subjects: 2D materials; crossbar; Electronic circuits; Electronic systems; Encryption; Espionage; hexagonal boron nitride; memristor; Random numbers; Switching circuits; true random number generator; Two dimensional materials
• ISSN: 1616-301X; 1616-3028
• DOI: 10.1002/adfm.202403029

Data encryption is an essential building block in modern electronic systems to prevent spying and hacking. Every day more and more objects produce electronic data, and this needs to be encrypted before being transmitted. Hence, designing devices, circuits, and systems for data encryption that can be integrated in all kinds of objects and that consume low amounts of energy is highly necessary. Here, this work reports the fabrication of flexible and transparent electronic circuits consisting of devices that exhibit threshold‐type resistive switching with a high degree of stochasticity. The cycle‐to‐cycle variability of switching voltages and state currents is significant but confined within a well‐defined range, which is consistent across multiple devices. This allows to design an efficient protocol for true random number generation. The circuits are fabricated with only synthetic 2D materials, can be fabricated in a scalable manner, and can be integrated in any object.
Flexible and transparent fully 2D materials based memristors exhibit reliable threshold resistive switching behavior with a high degree of stochasticity. A true random number generator circuit for advanced data encryption can be developed using the Graphene/hexagonal boron nitride/Graphene devices with high cycle‐to‐cycle variability of switching voltages and state currents as entropy source.