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

Broadband Negative Photoconductive Response in Carbon Nanodots

Due to the broadband response and low selectivity of external light, negative photoconductivity (NPC) effect holds great potential applications in photoelectric devices. Herein, different photoresponsive carbon nanodots (CDs) are prepared from diverse precursors and the broadband response from the NPC CDs are utilized to achieve the optoelectronic logic gates and optical imaging for the first time. In detail, the mcu-CDs which are prepared by the microwave-assisted polymerization of citric acid and urea possess the large specific surface area and abundant hydrophilic groups as sites for the adsorption of H2O molecules and thereby present a high conductivity in dark. Meanwhile, the low affinity of mcu-CDs to H2O molecules permits the light-induced desorption of H2O molecules by heat effect and thus endow the mcu-CDs with a low conductivity under illumination. The easy absorption and desorption of H2O molecules contribute to the extraordinary NPC of mcu-CDs. With the broadband NPC response in CDs, the optoelectronic logic gates and flexible optical imaging system are established, achieving the applications of "NOR" or "NAND" logic operations and high-quality optical images. These findings unveil the unique optoelectronic properties of CDs, and have the potential to advance the applications of CDs in optoelectronic devices.

Versatile Cu2ZnSnS4-based synaptic memristor for multi-field-regulated neuromorphic applications

Integrating both electrical and light-modulated multi-type neuromorphic functions in a single synaptic memristive device holds the most potential for realizing next-generation neuromorphic systems, but is still challenging yet achievable. Herein, a simple bi-terminal optoelectronic synaptic memristor is newly proposed based on kesterite Cu2ZnSnS4, exhibiting stable nonvolatile resistive switching with excellent spatial uniformity and unique optoelectronic synaptic behaviors. The device demonstrates not only low switching voltage (-0.39 ± 0.08 V), concentrated Set/Reset voltage distribution (<0.08/0.15 V), and long retention time (>104 s) but also continuously modulable conductance by both electric (different width/interval/amplitude) and light (470-808 nm with different intensity) stimulus. These advantages make the device good electrically and optically simulated synaptic functions, including excitatory and inhibitory, paired-pulsed facilitation, short-/long-term plasticity, spike-timing-dependent plasticity, and "memory-forgetting" behavior. Significantly, decimal arithmetic calculation (addition, subtraction, and commutative law) is realized based on the linear conductance regulation, and high precision pattern recognition (>88%) is well achieved with an artificial neural network constructed by 5 × 5 × 4 memristor array. Predictably, such kesterite-based optoelectronic memristors can greatly open the possibility of realizing multi-functional neuromorphic systems.

Organic iontronic memristors for artificial synapses and bionic neuromorphic computing

To tackle the current crisis of Moore's law, a sophisticated strategy entails the development of multistable memristors, bionic artificial synapses, logic circuits and brain-inspired neuromorphic computing. In comparison with conventional electronic systems, iontronic memristors offer greater potential for the manifestation of artificial intelligence and brain-machine interaction. Organic iontronic memristive materials (OIMs), which possess an organic backbone and exhibit stoichiometric ionic states, have emerged as pivotal contenders for the realization of high-performance bionic iontronic memristors. In this review, a comprehensive analysis of the progress and prospects of OIMs is presented, encompassing their inherent advantages, diverse types, synthesis methodologies, and wide-ranging applications in memristive devices. Predictably, the field of OIMs, as a rapidly developing research subject, presents an exciting opportunity for the development of highly efficient neuro-iontronic systems in areas such as in-sensor computing devices, artificial synapses, and human perception.

Spike rate dependent synaptic characteristics in lamellar, multilayered alpha-MoO3 based two-terminal devices - efficient way to control the synaptic amplification

Brain-inspired computing systems require a rich variety of neuromorphic devices using multi-functional materials operating at room temperature. Artificial synapses which can be operated using optical and electrical stimuli are in high demand. In this regard, layered materials have attracted a lot of attention due to their tunable energy gap and exotic properties. In the current study, we report the growth of layered MoO3 using the chemical vapor deposition (CVD) technique. MoO3 has an energy gap of 3.22 eV and grows with a large aspect ratio, as seen through optical and scanning electron microscopy. We used transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy for complete characterisation. The two-terminal devices using platinum (Pt/MoO3/Pt) exhibit superior memory with the high-resistance state (HRS) and low-resistance state (LRS) differing by a large resistance (∼MΩ). The devices also show excellent synaptic characteristics. Both optical and electrical pulses can be utilised to stimulate the synapse. Consistent learning (potentiation) and forgetting (depression) curves are measured. Transition from long term depression to long term potentiation can be achieved using the spike frequency dependent pulsing scheme. We have found that the amplification of postsynaptic current can be tuned using such frequency dependent spikes. This will help us to design neuromorphic devices with the required synaptic amplification.

Boron-Doped Engineering for Carbon Quantum Dots-Based Memristors with Controllable Memristance Stability

Carbon quantum dots-based memristors (CQDMs) have emerged as a rising star in data storage and computing. The key constraint to their commercialization is memristance variability, which mainly arises from the disordered conductive paths. Doping methodology can optimize electron and ion transport to help construct a stable conductive mode. Herein, based on boron (B)-doped engineering strategy, three kinds of comparable quantum dots are synthesized, including carbon quantum dots (CQDs), a series of boron-doped CQDs (BCQDs) with different B contents, and boron quantum dots. The corresponding device performances highlight the superiority of BCQDs-based memristors, exhibiting a ternary flash-type memory behavior with longer retention time and more controllable memristance stability. The comprehensive analysis results, including device performance, functional layer morphology, and material simulated calculation, illustrate that the doped B elements can directionally guide the migration of aluminum ions by enhancing the capture of free electrons, resulting in ordered conductive filaments and stable ternary memory behavior. Finally, the conceptual applications of logic display and logic gate are discussed, indicating a bright prospect for BCQDs-based memristors. This work proves that modest B doping can optimize memristance property, establishing a theoretical foundation and template scheme for developing effective and stable CQDMs.

Bismuth, Nitrogen-Codoped Carbon Dots as a Dual-Read Optical Sensing Platform for Highly Sensitive, Ultrarapid, Ratiometric Detection of Doxorubicin

Doxorubicin (DOX) is a potent anticancer drug, but it has side effects on normal tissues, particularly myocardial cells. Therefore, it is crucial to detect the DOX concentration in body fluids for effective clinical treatment. In this work, N,Bi-codoped CDs (Bi,N-CDs) were synthesized through a one-step hydrothermal method to carbonize the raw materials of 2,4-dinitroaniline and bismuth nitrate. The resulting Bi,N-CDs showed a reduced emission at 490 nm and an enhanced emission at 590 nm in the presence of DOX. The ratio of fluorescence (FL) intensity (F590/F490) was found to be a reliable indicator of DOX concentration, ranging from 0.05 to 30 μM and 40-200 μM, with detection limits (LOD) of 34 and 24 nM, respectively. A ratiometric fluorescence nanoprobe was established for highly selective and sensitive detection of DOX using a specific electrostatic interaction and inner filter effect between Bi,N-CDs and DOX. Meanwhile, Bi,N-CDs exhibited a distinct color change ranging from yellow to orange-red when exposed to DOX, allowing for a colorimetric method to measure DOX levels in the range of 0.05-30 μM, with a detection limit of 169 nM. The probe was triumphantly used to monitor DOX in actual samples via a dual-mode optical sensing strategy. This study contributes to the development of heteroatom-doped CDs and expands their potential applications for detecting biological samples.

Porous crystalline materials for memories and neuromorphic computing systems

Porous crystalline materials usually include metal-organic frameworks (MOFs), covalent organic frameworks (COFs), hydrogen-bonded organic frameworks (HOFs) and zeolites, which exhibit exceptional porosity and structural/composition designability, promoting the increasing attention in memory and neuromorphic computing systems in the last decade. From both the perspective of materials and devices, it is crucial to provide a comprehensive and timely summary of the applications of porous crystalline materials in memory and neuromorphic computing systems to guide future research endeavors. Moreover, the utilization of porous crystalline materials in electronics necessitates a shift from powder synthesis to high-quality film preparation to ensure high device performance. This review highlights the strategies for preparing porous crystalline materials films and discusses their advancements in memory and neuromorphic electronics. It also provides a detailed comparative analysis and presents the existing challenges and future research directions, which can attract the experts from various fields (e.g., materials scientists, chemists, and engineers) with the aim of promoting the applications of porous crystalline materials in memory and neuromorphic computing systems.