Graphene Oxide: Graphene Quantum Dot Nanocomposite for Better Memristic Switching Behaviors

Carbon Nanodots Memristor: An Emerging Candidate toward Artificial Biosynapse and Human Sensory Perception System

In the era of big data and artificial intelligence (AI), advanced data storage and processing technologies are in urgent demand. The innovative neuromorphic algorithm and hardware based on memristor devices hold a promise to break the von Neumann bottleneck. In recent years, carbon nanodots (CDs) have emerged as a new class of nano-carbon materials, which have attracted widespread attention in the applications of chemical sensors, bioimaging, and memristors. The focus of this review is to summarize the main advances of CDs-based memristors, and their state-of-the-art applications in artificial synapses, neuromorphic computing, and human sensory perception systems. The first step is to systematically introduce the synthetic methods of CDs and their derivatives, providing instructive guidance to prepare high-quality CDs with desired properties. Then, the structure-property relationship and resistive switching mechanism of CDs-based memristors are discussed in depth. The current challenges and prospects of memristor-based artificial synapses and neuromorphic computing are also presented. Moreover, this review outlines some promising application scenarios of CDs-based memristors, including neuromorphic sensors and vision, low-energy quantum computation, and human-machine collaboration.

High sensitivity and wide response range artificial synapse based on polyimide with embedded graphene quantum dots

Artificial electronic synapses are commonly used to simulate biological synapses to realize various learning functions, regarded as one of the key technologies in the next generation of neurological computation. This work used a simple spin coating technique to fabricate polyimide (PI):graphene quantum dots(GQDs) memristor structure. As a result, the devices exhibit remarkably stable exponentially decaying postsynaptic suppression current over time, as interpreted in the spike-timing-dependent plasticity phenomenon. Furthermore, with the increase of the applied electrical signal over time, the conductance of the electrical synapse gradually changes, and the electronic synapse also shows plasticity dependence on the amplitude and frequency of the pulse applied. In particular, the devices with the structure of Ag/PI:GQDs/ITO prepared in this study can produce a stable response to the stimulation of electrical signals between millivolt to volt, showing not only high sensitivity but also a wide range of "feelings", which makes the electronic synapses take a step forwards to emulate biological synapses. Meanwhile, the electronic conduction mechanisms of the device are also studied and expounded in detail. The findings in this work lay a foundation for developing brain-like neuromorphic modeling in artificial intelligence.

Functionalization of nitrogen-doped graphene quantum dot: A sustainable carbon-based catalyst for the production of cyclic carbonate from epoxide and CO2

A series of organic compounds were successfully immobilized on an N-doped graphene quantum dot (N-GQD) to prepare a multifunctional organocatalyst for coupling reaction between CO₂ and propylene oxide (PO). The simultaneous presence of halide ions in conjunction with acidic- and basic-functional groups on the surface of the nanoparticles makes them highly active for the production of propylene carbonate (PC). The effects of variables such as catalyst loading, reaction temperature, and structure of substituents are discussed. The proposed catalysts were characterized by different techniques, including Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy/energy dispersive X-ray microanalysis (FESEM/EDX), thermogravimetric analysis (TGA), elemental analysis, atomic force microscopy (AFM), and ultraviolet-visible (UV-Vis) spectroscopy. Under optimal reaction conditions, 3-bromopropionic acid (BPA) immobilized on N-GQD showed a remarkable activity, affording the highest yield of 98% at 140°C and 10⁶ Pa without any co-catalyst or solvent. These new metal-free catalysts have the advantage of easy separation and reuse several times. Based on the experimental data, a plausible reaction mechanism is suggested, where the hydrogen bonding donors and halogen ion can activate the epoxide, and amine functional groups play a vital role in CO₂ adsorption.

Synaptic Characteristics from Homogeneous Resistive Switching in Pt/Al2O3/TiN Stack

In this work, we propose three types of resistive switching behaviors by controlling operation conditions. We confirmed well-known filamentary switching in Al₂O₃-based resistive switching memory using the conventional device working operation with a forming process. Here, filamentary switching can be classified into two types depending on the compliance current. On top of that, the homogeneous switching is obtained by using a negative differential resistance effect before the forming or setting process in a negative bias. The variations of the low-resistance and high-resistance states in the homogeneous switching are comparable to the filamentary switching cases. However, the drift characteristics of the low-resistance and high-resistance states in the homogeneous switching are unstable with time. Therefore, the short-term plasticity effects, such as the current decay in repeated pulses and paired pulses facilitation, are demonstrated when using the resistance drift characteristics. Finally, the conductance can be increased and decreased by 50 consecutive potentiation pulses and 50 consecutive depression pulses, respectively. The linear conductance update in homogeneous switching is achieved compared to the filamentary switching, which ensures the high pattern-recognition accuracy.