Highly Linear and Symmetric Synaptic Memtransistors Based on Polarization Switching in Two-Dimensional Ferroelectric Semiconductors

Photo-Assisted Ferroelectric Domain Control for α-In2Se3 Artificial Synapses Inspired by Spontaneous Internal Electric Fields

α-In2Se3 semiconductor crystals realize artificial synapses by tuning in-plane and out-of-plane ferroelectricity with diverse avenues of electrical and optical pulses. While the electrically induced ferroelectricity of α-In2Se3 shows synaptic memory operation, the optically assisted synaptic plasticity in α-In2Se3 has also been preferred for polarization flipping enhancement. Here, the synaptic memory behavior of α-In2Se3 is demonstrated by applying electrical gate voltages under white light. As a result, the induced internal electric field is identified at a polarization flipped conductance channel in α-In2Se3/hexagonal boron nitride (hBN) heterostructure ferroelectric field effect transistors (FeFETs) under white light and discuss the contribution of this built-in electric field on synapse characterization. The biased dipoles in α-In2Se3 toward potentiation polarization direction by an enhanced internal built-in electric field under illumination of white light lead to improvement of linearity for long-term depression curves with proper electric spikes. Consequently, upon applying appropriate electric spikes to α-In2Se3/hBN FeFETs with illuminating white light, the recognition accuracy values significantly through the artificial learning simulation is elevated for discriminating hand-written digit number images.

Artificial Tactile Perception System Based on Spiking Tactile Neurons and Spiking Neural Networks

The artificial tactile perception system of this work utilizes a fully connected spiking neural network (SNN) comprising two layers. Its architecture is streamlined and energy-efficient as it directly integrates spiking tactile neurons with piezoresistive sensors and Pt/NbOx/TiN memristors as input neurons. These spiking tactile neurons possess the ability to perceive and integrate pressure stimuli from multiple sensors and encode the information into rate-coded electrical spikes, closely resembling the behavior of a biological tactile neuron. The system's real-time information processing capability is demonstrated through an artificial perceptual learning system that successfully encodes and decodes the Morse code; the artificial perceptual learning system accurately recognizes and displays 26 English letters. Furthermore, the artificial tactile perception system is evaluated for the recognition of the MNIST data set, achieving a classification accuracy of 85.7% with the supervised spiking-rate-dependent plasticity learning rule. The key advantages of this artificial tactile perception system are its simple structure and high efficiency, which contributes to its practicality for various real-world applications.

Artificial Neuron Devices

Efforts to design devices emulating complex cognitive abilities and response processes of biological systems have long been a coveted goal. Recent advancements in flexible electronics, mirroring human tissue's mechanical properties, hold significant promise. Artificial neuron devices, hinging on flexible artificial synapses, bioinspired sensors, and actuators, are meticulously engineered to mimic the biological systems. However, this field is in its infancy, requiring substantial groundwork to achieve autonomous systems with intelligent feedback, adaptability, and tangible problem-solving capabilities. This review provides a comprehensive overview of recent advancements in artificial neuron devices. It starts with fundamental principles of artificial synaptic devices and explores artificial sensory systems, integrating artificial synapses and bioinspired sensors to replicate all five human senses. A systematic presentation of artificial nervous systems follows, designed to emulate fundamental human nervous system functions. The review also discusses potential applications and outlines existing challenges, offering insights into future prospects. We aim for this review to illuminate the burgeoning field of artificial neuron devices, inspiring further innovation in this captivating area of research.

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.

Reversible Thermally Driven Phase Change of Layered In2Se3 for Integrated Photonics

Two-dimensional In₂Se₃, an unconventional phase-change material, has drawn considerable attention for polymorphic phase transitions and electronic device applications. However, its reversible thermally driven phase transitions and potential use in photonic devices have yet to be explored. In this study, we observe the thermally driven reversible phase transitions between α and β' phases with the assistance of local strain from surface wrinkles and ripples, as well as reversible phase changes within the β phase family. These transitions lead to changes in the refractive index and other optoelectronic properties with minimal optical loss at telecommunication bands, which are crucial in integrated photonic applications such as postfabrication phase trimming. Additionally, multilayer β'-In₂Se₃ working as a transparent microheater proves to be a viable option for efficient thermo-optic modulation. This prototype design for layered In₂Se₃ offers immense potential for integrated photonics and paves the way for multilevel, nonvolatile optical memory applications.

Biomedical application of 2D nanomaterials in neuroscience

Two-dimensional (2D) nanomaterials, such as graphene, black phosphorus and transition metal dichalcogenides, have attracted increasing attention in biology and biomedicine. Their high mechanical stiffness, excellent electrical conductivity, optical transparency, and biocompatibility have led to rapid advances. Neuroscience is a complex field with many challenges, such as nervous system is difficult to repair and regenerate, as well as the early diagnosis and treatment of neurological diseases are also challenged. This review mainly focuses on the application of 2D nanomaterials in neuroscience. Firstly, we introduced various types of 2D nanomaterials. Secondly, due to the repairment and regeneration of nerve is an important problem in the field of neuroscience, we summarized the studies of 2D nanomaterials applied in neural repairment and regeneration based on their unique physicochemical properties and excellent biocompatibility. We also discussed the potential of 2D nanomaterial-based synaptic devices to mimic connections among neurons in the human brain due to their low-power switching capabilities and high mobility of charge carriers. In addition, we also reviewed the potential clinical application of various 2D nanomaterials in diagnosing and treating neurodegenerative diseases, neurological system disorders, as well as glioma. Finally, we discussed the challenge and future directions of 2D nanomaterials in neuroscience.

Controlled Bipolar Doping of One-Dimensional van der Waals Nb2Pd3Se8

Tailoring the electrical properties of one-dimensional (1D) van der Waals (vdW) materials is desirable for their applications toward electronic devices by exploiting their unique characteristics. However, 1D vdW materials have not been extensively investigated for modulation of their electrical properties. Here we control doping levels and types of 1D vdW Nb₂Pd₃Se₈ over a wide energy range by immersion in AuCl₃ or β-nicotinamide adenine dinucleotide (NADH) solutions, respectively. Through spectroscopic analyses and electrical characterizations, we confirm that the charges were effectively transferred to Nb₂Pd₃Se₈, and the dopant concentration was adjusted to the immersion time. Furthermore, we make the axial p-n junction of 1D Nb₂Pd₃Se₈ by a selective area p-doping using the AuCl₃ solution, which exhibits rectifying behavior with an I_forward/I_reverse of 81 and an ideality factor of 1.2. Our findings could pave the way to more practical and functional electronic devices based on 1D vdW materials.