Voltage-Controlled Conversion from CDS to MDS in an Azobenzene-Based Organic Memristor for Information Storage and Logic Operations

Memristor-Based Bionic Tactile Devices: Opening the Door for Next-Generation Artificial Intelligence

Bioinspired tactile devices can effectively mimic and reproduce the functions of the human tactile system, presenting significant potential in the field of next-generation wearable electronics. In particular, memristor-based bionic tactile devices have attracted considerable attention due to their exceptional characteristics of high flexibility, low power consumption, and adaptability. These devices provide advanced wearability and high-precision tactile sensing capabilities, thus emerging as an important research area within bioinspired electronics. This paper delves into the integration of memristors with other sensing and controlling systems and offers a comprehensive analysis of the recent research advancements in memristor-based bionic tactile devices. These advancements incorporate artificial nociceptors and flexible electronic skin (e-skin) into the category of bio-inspired sensors equipped with capabilities for sensing, processing, and responding to stimuli, which are expected to catalyze revolutionary changes in human-computer interaction. Finally, this review discusses the challenges faced by memristor-based bionic tactile devices in terms of material selection, structural design, and sensor signal processing for the development of artificial intelligence. Additionally, it also outlines future research directions and application prospects of these devices, while proposing feasible solutions to address the identified challenges.

Transmission Mechanism and Logical Operation of Graphene-Doped Poly(vinyl alcohol) Composite-Based Memristor

Memristors are considered the best candidates for nonvolatile memory and advanced computing technologies, and polymer and two-dimensional (2D) materials have been developed as functional layer materials in memristors with high-performance resistive switching characteristics. In this work, a polymer memristor with a graphene (Gr)-doped poly(vinyl alcohol) (PVA) composite acting as the functional layer was prepared. The memristor device exhibited superior performance with good retention and a comparatively large ON/OFF ratio at room temperature. Additionally, excellent logic operations were achieved. These satisfactory properties can be attributed to trap-induced carrier trapping and detrapping. In addition, the device exhibited stable bipolar resistive switching behavior over a moderate temperature range. This work provides insight into the transmission mechanism of polymer-based memristors and the reasons why they become unstable at high temperatures, demonstrating the potential applications of PVA-Gr-based polymer memristors as logic circuit units in integrated chips and artificial intelligence.

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.

Memristor-based neural networks: a bridge from device to artificial intelligence

Since the beginning of the 21st century, there is no doubt that the importance of artificial intelligence has been highlighted in many fields, among which the memristor-based artificial neural network technology is expected to break through the limitation of von Neumann so as to realize the replication of the human brain by enabling strong parallel computing ability and efficient data processing and become an important way towards the next generation of artificial intelligence. A new type of nanodevice, namely memristor, which is based on the variability of its resistance value, not only has very important applications in nonvolatile information storage, but also presents obsessive progressiveness in highly integrated circuits, making it one of the most promising circuit components in the post-Moore era. In particular, memristors can effectively simulate neural synapses and build neural networks; thus, they can be applied for the preparation of various artificial intelligence systems. This study reviews the research progress of memristors in artificial neural networks in detail and highlights the structural advantages and frontier applications of neural networks based on memristors. Finally, some urgent problems and challenges in current research are summarized and corresponding solutions and future development trends are put forward.

Tailoring the Resistive Switching WORM Memory Behavior of Functionalized Bis(triphenylamine)

To better understand the structure-property relationship and the significance of the donor-acceptor (D-A) system in resistive memory devices, a series of new organic small molecules with A-π-D-π-A- and D-π-D-π-D-based architecture comprising a bis(triphenylamine) core unit and ethynyl-linked electron donor/acceptor arms were designed and synthesized. The devices with A-π-D-π-A structures exhibited write-once-read-many memory behavior with a good retention time of 1000 s while those based on D-π-D-π-D molecules presented only conductor property. The compound with nitrophenyl substitution resulted in a higher ON/OFF current ratio of 10⁴, and the fluorophenyl substitution exhibited the lowest threshold voltage of -1.19 V. Solubility of the compounds in common organic solvents suggests that they are promising candidates for economic solution-processable techniques. Density functional theory calculations were used to envision the frontier molecular orbitals and to support the proposed resistive switching mechanisms. It is inferred that the presence of donor/acceptor substituents has a significant impact on the highest occupied molecular orbital-lowest unoccupied molecular orbital energy levels of the molecules, which affects their memory-switching behavior and thus suggests that a D-A architecture is ideal for memory device resistance switching characteristics.

In-Depth Physical Mechanism Analysis and Wearable Applications of HfOx-Based Flexible Memristors

Since memristors as an emerging nonlinear electronic component have been considered the most promising candidate for integrating nonvolatile memory and advanced computing technology, the in-depth reveal of the memristive mechanism and the realization of hardware fabrication have facilitated their wide applications in next-generation artificial intelligence. Flexible memristors have shown great promising prospects in wearable electronics and artificial electronic skin (e-skin), but in-depth research on the physical mechanism is still lacking. Here, a flexible memristive device with a Ag/HfO_x/Ti/PET crossbar structure was fabricated, and a remarkable analog switching characteristic similar to synaptic behavior was observed. Through detailed data fitting and in-depth physical mechanism analysis, it is confirmed that the analog switching characteristics of the device are mainly caused by carrier tunneling. Furthermore, the memristive properties of the Ag/HfO_x/Ag/PET device can be attributed to the conductive filaments formed by the redox reaction of the active metal Ag. Finally, the interfacial barrier is extracted by the Arrhenius diagram and the energy band diagram, which is drawn to clearly demonstrate the conduction mechanism of charge trapping in the device. Therefore, the HfO_x-based flexible memristor with analog switching behavior and stable memory performance lays the foundation for cutting-edge applications in wearable electronics and smart e-skin.