Bi2O2Se-Based Memristor-Aided Logic

Bi2O2Se-based CBRAM integrated artificial synapse

Integrating two-dimensional (2D) semiconducting materials into memristor structures has paved the way for emerging 2D materials to be employed in a vast field of memory applications. Bismuth oxyselenide (Bi2O2Se), a 2D material with high electron mobility, has attracted significant research interest owing to its great potential in various fields of advanced applications. Here, we explore the out-of-plane intrinsic switching behavior of few-layered Bi2O2Se via a cross point device for application in conductive bridge random access memory (CBRAM) and artificial synapses for neuromorphic computing. Via state-of-the-art methods, CVD-grown Bi2O2Se nanoplate is applied as a switching material (SM) in an Al/Cu/Bi2O2Se/Pd CBRAM structure. The device exhibits ∼90 consecutive DC cycles with a tight distribution of the SET/RESET voltages under a compliance current (CC) of 1 mA, a retention of over 10 ks, and multilevel switching characteristics showing four distinct states at Vread values of 0.1, 0.2, 0.25, and 0.3 V. Moreover, an artificial synapse is realized with potentiation and depression by modulating the conductance. The switching mechanism is explained via Cu migration through Bi2O2Se based on HRTEM analysis. The present structure shows potential for future integrated memory applications.

Bi2O2Se-Based Bimode Noise Generator for the Application of Generative Adversarial Networks

In the emerging technology, the generative aversive networks (GANs), randomness, and unpredictability of inputting noises are the keys to the uniqueness, diversity, robustness, and security of the generated images. Compared with deterministic software-based noise generation, hardware-based noise generation introduces physical entropy sources, such as electronic and photonic noises, to add unpredictability. In this study, bimode Bi2O2Se-based noise generators have been demonstrated for the application of GANs. Harnessing its ultrahigh carrier mobility, excellent air stability, marvelous optoelectronic performance, as well as the unique surface resistive switching effect and defect locations in the energy diagram, Bi2O2Se provides a good material platform to easily integrate with multiple device architectures for generating noises in different physical sources. The noise of the black current mode in a photodetector architecture and the random telegraph noise in a memristor mode were measured, characterized, compared, and analyzed. A method of Markov chain equipped with K-means clustering was carried out to calculate the discrete noise states and the transition probability matrix between them. To evaluate the generated properties of the GANs based on the hardware noise source, the inception score and Fréchet inception distance were evaluated.

Type-II Bi2O2Se/MoTe2 van der Waals Heterostructure Photodetectors with High Gate-Modulation Photovoltaic Performance

In recent years, two-dimensional (2D) nonlayered Bi₂O₂Se-based electronics and optoelectronics have drawn enormous attention owing to their high electron mobility, facile synthetic process, stability to the atmosphere, and moderate narrow band gaps. However, 2D Bi₂O₂Se-based photodetectors typically present large dark current, relatively slow response speed, and persistent photoconductivity effect, limiting further improvement in fast-response imaging sensors and low-consumption broadband detection. Herein, a Bi₂O₂Se/2H-MoTe₂ van der Waals (vdWs) heterostructure obtained from the chemical vapor deposition (CVD) approach and vertical stacking is reported. The proposed type-II staggered band alignment desirable for suppression of dark current and separation of photoinduced carriers is confirmed by density functional theory (DFT) calculations, accompanied by strong interlayer coupling and efficient built-in potential at the junction. Consequently, a stable visible (405 nm) to near-infrared (1310 nm) response capability, a self-driven prominent responsivity (R) of 1.24 A·W^-1, and a high specific detectivity (D*) of 3.73 × 10¹¹ Jones under 405 nm are achieved. In particular, R, D*, fill factor, and photoelectrical conversion efficiency (PCE) can be enhanced to 4.96 A·W^-1, 3.84 × 10¹² Jones, 0.52, and 7.21% at V_g = -60 V through a large band offset originated from the n⁺-p junction. It is suggested that the present vdWs heterostructure is a promising candidate for logical integrated circuits, image sensors, and low-power consumption detection.

Graphene Oxide-Based Memristive Logic-in-Memory Circuit Enabling Normally-Off Computing

Memristive logic-in-memory circuits can provide energy- and cost-efficient computing, which is essential for artificial intelligence-based applications in the coming Internet-of-things era. Although memristive logic-in-memory circuits have been previously reported, the logic architecture requiring additional components and the non-uniform switching of memristor have restricted demonstrations to simple gates. Using a nanoscale graphene oxide (GO) nanosheets-based memristor, we demonstrate the feasibility of a non-volatile logic-in-memory circuit that enables normally-off in-memory computing. The memristor based on GO film with an abundance of unusual functional groups exhibited unipolar resistive switching behavior with reliable endurance and retention characteristics, making it suitable for logic-in-memory circuit application. In a state of low resistance, temperature-dependent resistance and I-V characteristics indicated the presence of a metallic Ni filament. Using memristor-aided logic (MAGIC) architecture, we performed NOT and NOR gates experimentally. Additionally, other logic gates such as AND, NAND, and OR were successfully implemented by combining NOT and NOR universal logic gates in a crossbar array. These findings will pave the way for the development of next-generation computer systems beyond the von Neumann architecture, as well as carbon-based nanoelectronics in the future.

Bi2O2Se-based integrated multifunctional optoelectronics

The prominent light-matter interaction in 2D materials has become a pivotal research area that involves either an archetypal study of inherent mechanisms to explore such interactions or specific applications to assess the efficacy of such novel phenomena. With scientifically controlled light-matter interactions, various applications have been developed. Here, we report four diverse applications on a single structure utilizing the efficient photoresponse of Bi₂O₂Se with precisely tuned multiple optical wavelengths. First, the Bi₂O₂Se-based device performs the function of optoelectronic memory using UV (λ = 365 nm, 1.1 mW cm^-2) for the write-in process with SiO₂ as the charge trapping medium followed by a +1 V bias for read-out. Second, associative learning is mimicked with wavelengths of 525 nm and 635 nm. Third, using similar optical inputs, functions of logic gates "AND", "OR", "NAND", and "NOR" are realized with response current and resistance as outputs. Fourth is the demonstration of a 4 bit binary to the decimal converter using wavelengths of 740 nm (LSB), 595 nm, 490 nm, and 385 nm (MSB) as binary inputs and output response current regarded as equivalent decimal output. Our demonstration is a paradigm for Bi₂O₂Se-based devices to be an integral part of future advanced multifunctional electronic systems.

Bi2O2Se-Based True Random Number Generator for Security Applications

The fast development of the Internet of things (IoT) promises to deliver convenience to human life. However, a huge amount of the data is constantly generated, transmitted, processed, and stored, posing significant security challenges. The currently available security protocols and encryption techniques are mostly based on software algorithms and pseudorandom number generators that are vulnerable to attacks. A true random number generator (TRNG) based on devices using stochastically physical phenomena has been proposed for auditory data encryption and trusted communication. In the current study, a Bi₂O₂Se-based memristive TRNG is demonstrated for security applications. Compared with traditional metal-insulator-metal based memristors, or other two-dimensional material-based memristors, the Bi₂O₂Se layer as electrode with non-van der Waals interface, high carrier mobility, air stability, extreme low thermal conductivity, as well as vertical surface resistive switching shows intrinsic stochasticity and complexity in a memristive true analogue/digital random number generation. Moreover, those analogue/digital random number generation processes are proved to be resilient for machine learning prediction.

Memristor Based on Inorganic and Organic Two-Dimensional Materials: Mechanisms, Performance, and Synaptic Applications

A memristor is a two-terminal device with nonvolatile resistive switching (RS) behaviors. Recently, memristors have been highly desirable for both fundamental research and technological applications because of their great potential in the development of high-density memory technology and neuromorphic computing. Benefiting from the unique two-dimensional (2D) layered structure and outstanding properties, 2D materials have proven to be good candidates for use in gate-tunable, highly reliable, heterojunction-compatible, and low-power memristive devices. More intriguing, stable and reliable nonvolatile RS behaviors can be achieved in multi- and even monolayer 2D materials, which seems unlikely to be achieved in traditional oxides with thicknesses less than a few nanometers because of the leakage currents. Moreover, such two-terminal devices show a series of synaptic functionalities, suggesting applications in simulating a biological synapse in the neural network. In this review article, we summarize the recent progress in memristors based on inorganic and organic 2D materials, from the material synthesis, device structure and fabrication, and physical mechanism to some versatile memristors based on diverse 2D materials with good RS properties and memristor-based synaptic applications. The development prospects and challenges at the current stage are then highlighted, which is expected to inspire further advancements and new insights into the fields of information storage and neuromorphic computing.