Resonant tunneling based graphene quantum dot memristors

Recent advancements in implantable neural links based on organic synaptic transistors

The progress of brain synaptic devices has witnessed an era of rapid and explosive growth. Because of their integrated storage, excellent plasticity and parallel computing, and system information processing abilities, various field effect transistors have been used to replicate the synapses of a human brain. Organic semiconductors are characterized by simplicity of processing, mechanical flexibility, low cost, biocompatibility, and flexibility, making them the most promising materials for implanted brain synaptic bioelectronics. Despite being used in numerous intelligent integrated circuits and implantable neural linkages with multiple terminals, organic synaptic transistors still face many obstacles that must be overcome to advance their development. A comprehensive review would be an excellent tool in this respect. Therefore, the latest advancements in implantable neural links based on organic synaptic transistors are outlined. First, the distinction between conventional and synaptic transistors are highlighted. Next, the existing implanted organic synaptic transistors and their applicability to the brain as a neural link are summarized. Finally, the potential research directions are discussed.

Synthesis, Applications, and Prospects of Graphene Quantum Dots: A Comprehensive Review

Graphene quantum dot (GQD) is one of the youngest superstars of the carbon family. Since its emergence in 2008, GQD has attracted a great deal of attention due to its unique optoelectrical properties. Non-zero bandgap, the ability to accommodate functional groups and dopants, excellent dispersibility, highly tunable properties, and biocompatibility are among the most important characteristics of GQDs. To date, GQDs have displayed significant momentum in numerous fields such as energy devices, catalysis, sensing, photodynamic and photothermal therapy, drug delivery, and bioimaging. As this field is rapidly evolving, there is a strong need to identify the emerging challenges of GQDs in recent advances, mainly because some novel applications and numerous innovations on the ease of synthesis of GQDs are not systematically reviewed in earlier studies. This feature article provides a comparative and balanced discussion of recent advances in synthesis, properties, and applications of GQDs. Besides, current challenges and future prospects of these emerging carbon-based nanomaterials are also highlighted. The outlook provided in this review points out that the future of GQD research is boundless, particularly if upcoming studies focus on the ease of purification and eco-friendly synthesis along with improving the photoluminescence quantum yield and production yield of GQDs.

Ultrasensitive Magnetic Sensors Enabled by Heterogeneous Integration of Graphene Hall Elements and Silicon Processing Circuits

Graphene Hall elements (GHEs) have been demonstrated to be promising magnetic field sensors with excellent sensitivity, linearity, temperature stability, and compatibility with complementary-metal-oxide-semiconductor (CMOS)-integrated circuits (ICs). However, the demonstrated GHEs have still not exhibited a comprehensive advantage in performance over commercial integrated Hall sensors which were implemented in integrated Hall element and CMOS processing ICs. In this work, we develop a technology for the three-dimensional (3D) heterogeneous integration of silicon-based CMOS ICs and GHEs, and the fabricated magnetic field sensors outperform commercial high-end integrated Hall sensors. Specifically, the integrated Hall sensors are implemented in a stacked integration on Si based on a chopper programmable-gain amplifier (CPGA), a chopper-stabilized second-order sigma-delta modulator (CSDM), and graphene-based Hall elements on monochips. GHEs with high sensitivity (up to 1000 A/VT) are fabricated with a compatible process on a smoothened silicon nitride passivation layer of silicon-based CMOS ICs, and the two device layers are connected by an interlayer. The heterogeneous integrated Hall ICs exhibit current and voltage magnetic sensitivities up to 64 000 A/VT and 6.12 V/VT, respectively, which are much higher than those in all other reported nanomaterial-based Hall sensors and even in high-end commercial Hall ICs. Furthermore, the 3D heterogeneous integration technology used here can be extended as a universal technology for integrating nanomaterial-based sensors and Si CMOS ICs.

Stimuli-Enabled Artificial Synapses for Neuromorphic Perception: Progress and Perspectives

Brain-inspired neuromorphic computing is intended to provide effective emulation of the functionality of the human brain via the integration of electronic components. Recent studies of synaptic plasticity, which represents one of the most significant neurochemical bases of learning and memory, have enhanced the general comprehension of how the brain functions and have thereby eased the development of artificial neuromorphic devices. An understanding of the synaptic plasticity induced by various types of stimuli is essential for neuromorphic system construction. The realization of multiple stimuli-enabled synapses will be important for future neuromorphic computing applications. In this Review, state-of-the-art synaptic devices with particular emphasis on their synaptic behaviors under excitation by a variety of external stimuli are summarized, including electric fields, light, magnetic fields, pressure, and temperature. The switching mechanisms of these synaptic devices are discussed in detail, including ion migration, electron/hole transfer, phase transition, redox-based resistive switching, and other mechanisms. This Review aims to provide a comprehensive understanding of the operating mechanisms of artificial synapses and thus provides the principles required for design of multifunctional neuromorphic systems with parallel processing capabilities.

Decade of 2D-materials-based RRAM devices: a review

Two dimensional (2D) materials have offered unique electrical, chemical, mechanical and physical properties over the past decade owing to their ultrathin, flexible, and multilayer structure. These layered materials are being used in numerous electronic devices for various applications, and this review will specifically focus on the resistive random access memories (RRAMs) based on 2D materials and their nanocomposites. This study presents the device structures, conduction mechanisms, resistive switching properties, fabrication technologies, challenges and future aspects of 2D-materials-based RRAMs. Graphene, derivatives of graphene and MoS2 have been the major contributors among 2D materials for the application of RRAMs; however, other members of this family such as hBN, MoSe2, WS2 and WSe2 have also been inspected more recently as the functional materials of nonvolatile RRAM devices. Conduction in these devices is usually dominated by either the penetration of metallic ions or migration of intrinsic species. Most prominent advantages offered by RRAM devices based on 2D materials include fast switching speed (<10 ns), less power losses (10 pJ), lower threshold voltage (<1 V) long retention time (>10 years), high electrical endurance (>108 voltage cycles) and extended mechanical robustness (500 bending cycles). Resistive switching properties of 2D materials have been further enhanced by blending them with metallic nanoparticles, organic polymers and inorganic semiconductors in various forms.

Recent Advances on Graphene Quantum Dots: From Chemistry and Physics to Applications

Graphene quantum dots (GQDs) that are flat 0D nanomaterials have attracted increasing interest because of their exceptional chemicophysical properties and novel applications in energy conversion and storage, electro/photo/chemical catalysis, flexible devices, sensing, display, imaging, and theranostics. The significant advances in the recent years are summarized with comparative and balanced discussion. The differences between GQDs and other nanomaterials, including their nanocarbon cousins, are emphasized, and the unique advantages of GQDs for specific applications are highlighted. The current challenges and outlook of this growing field are also discussed.