Flexible Graphene-Channel Memory Devices: A Review

Abstract

There is an increasing importance of memory technologies in our ever-digitalizing society, which is characterized by the generation and use of a tremendous amount of real-time data. Beyond traditional performance requirements, mechanical flexibility of memory systems becomes therefore critical to enabling emerging applications such as the Internet of things. Graphene, now an established nanomaterial platform, is a promising element for building such high-performance memories with an unconventional form factor because of its exceptional electrical conductivities, outstanding mechanical properties, and processing versatility desirable for hybrid integration. Here, we provide an overview of recently developed flexible memory devices based on graphene and its functionalized counterparts. A defining feature of this review is that it exclusively compares and analyzes the devices that meet the following two criteria: (i) an explicit demonstration of working devices on a flexible substrate is reported; (ii) graphene is employed as an active channel rather than as an electrode. Our primary focus is to systematically classify various types of memories, in view of their materials, structural, and functional characteristics. For this, the shapes and compositions of the conductive channel, the key operational mechanisms underlying the electrical functionalities, and the major characteristics of representative device structures and materials systems are carefully evaluated. Furthermore, the applicability of flexible graphene memories to the neuromorphic computing area is discussed. Finally, we address several remaining issues that need to be solved for future technological advancements.

Biomass‐Derived Nanoporous Graphene Memory Cell

“…Table 1 shows a comparison with the previous reported graphene‐based two‐terminal memory devices, which may reflect different materials‐ and device‐specific mechanisms. [ 38 ] First of all, our devices outperform all the cited devices in terms of the ON/OFF ratio, benefiting from the high porosity and restricted metallic conductivity of NPG. Also note that most reported devices are of a vertical configuration, while our memories were built upon a planar geometry ideal for simple material transfer and device fabrication.…”

“…[ 32 ] Also, NPG Esaki diodes were experimentally demonstrated, [ 33 ] which featured a negative differential resistance. However, we recognized the lack of efforts on applying NPG to memory devices and systems, [ 33–37 ] despite the rapidly increasing impact of nanomaterials‐based memory technologies on both traditional electronics [ 33,38 ] and emerging neuromorphic computing systems. [ 39–41 ]…”

Technology Roadmap for Flexible Sensors

“…The first strategy will benefit fast data communication but requires either heterogeneous integration of rigid memories or flexible memory devices, which are still in the early stages of research. 783,846,847 The second strategy is suitable for long-term, robust storage of large datasets. However, the escalating energy demand of data centers is a pressing issue to address.…”

Carbon Nanomaterials (CNMs) and Enzymes: From Nanozymes to CNM-Enzyme Conjugates and Biodegradation

“…Applications are similar to CNTs, and they include composite reinforcement [ 188 ], wearable [ 189 ] and flexible electronics [ 190 , 191 ], including memory devices [ 192 ] and even stretchable batteries [ 193 ], energy storage [ 194 ] and conversion [ 195 , 196 , 197 , 198 ], environmental remediation [ 199 , 200 ], varying types of catalysis [ 201 , 202 , 203 , 204 ], and innovative uses in the healthcare sector [ 205 ], such as regenerative medicine [ 206 ] and sensing [ 207 , 208 ]. In this case, large-scale, cost-effective production of high-quality G [ 209 , 210 ] and standardization are key for the translation of G properties into commodity products at a global level [ 211 ].…”