Bio-Inspired Multi-Mode Pain-Perceptual System (MMPPS) with Noxious Stimuli Warning, Damage Localization, and Enhanced Damage Protection

Heterogeneous Integration of Memristive and Piezoresistive MDMO-PPV-Based Copolymers in Nociceptive Transmission with Fast and Slow Pain for an Artificial Pain-Perceptual System

Nociceptive pain perception is a remarkable capability of organisms to be aware of environmental changes and avoid injury, which can be accomplished by specialized pain receptors known as nociceptors with 4 vital properties including threshold, no adaptation, relaxation, and sensitization. Bioinspired systems designed using artificial devices are investigated to imitate the efficacy and functionality of nociceptive transmission. Here, an artificial pain-perceptual system (APPS) with a homogeneous material and heterogeneous integration is proposed to emulate the behavior of fast and slow pain in nociceptive transmission. Retention-differentiated poly[2-methoxy-5-(3,7-dimethyoctyoxyl)-1,4-phenylenevinylene] (MDMO-PPV) memristors with film thicknesses of 160 and 80 nm are manufactured and adopted as A-δ and C nerve fibers of nociceptor conduits, respectively. Additionally, a nociceptor mimic, the ruthenium nanoparticles (Ru-NPs)-doped MDMO-PPV piezoresistive pressure sensor, is fabricated with a noxiously stimulated threshold of 150 kPa. Under the application of pricking and dull noxious stimuli, the current flows predominantly through the memristor to mimic the behavior of fast and slow pain, respectively, in nociceptive transmission with postsynaptic potentiation properties, which is analogous to biological pain perception. The proposed APPS can provide potential advancements in establishing the nervous system, thus enabling the successful development of next-generation neurorobotics, neuroprosthetics, and precision medicine.

Neuromorphic Nanoionics for Human-Machine Interaction: From Materials to Applications

Human-machine interaction (HMI) technology has undergone significant advancements in recent years, enabling seamless communication between humans and machines. Its expansion has extended into various emerging domains, including human healthcare, machine perception, and biointerfaces, thereby magnifying the demand for advanced intelligent technologies. Neuromorphic computing, a paradigm rooted in nanoionic devices that emulate the operations and architecture of the human brain, has emerged as a powerful tool for highly efficient information processing. This paper delivers a comprehensive review of recent developments in nanoionic device-based neuromorphic computing technologies and their pivotal role in shaping the next-generation of HMI. Through a detailed examination of fundamental mechanisms and behaviors, the paper explores the ability of nanoionic memristors and ion-gated transistors to emulate the intricate functions of neurons and synapses. Crucial performance metrics, such as reliability, energy efficiency, flexibility, and biocompatibility, are rigorously evaluated. Potential applications, challenges, and opportunities of using the neuromorphic computing technologies in emerging HMI technologies, are discussed and outlooked, shedding light on the fusion of humans with machines.

A Suspended, 3D Morphing Sensory System for Robots to Feel and Protect

Artificial sensory systems with synergistic touch and pain perception hold substantial promise for environment interaction and human-robot communication. However, the realization of biological skin-like functional integration of sensors with sensitive touch and pain perception still remains a challenge. Here, a concept is proposed of suspended electronic skins enabling 3D deformation-mechanical contact interactions for achieving synergetic ultrasensitive touch and adjustable pain perception. The suspended sensory system can sensitively capture tiny touch stimuli as low as 0.02 Pa and actively perceive pain response with reliable 5200 cycles via 3D deformation and mechanical contact mechanism, respectively. Based on the touch-pain effect, a visualized feedback demo with miniaturized sensor arrays on artificial fingers is rationally designed to give a pain perception mapping on sharp surfaces. Furthermore, the capability is shown of the suspended electronic skin serving as a safe human-robot communication interface from active and passive view through a feedback control system, demonstrating potential in bionic electronics and intelligent robotics.

Bio-Inspired Sensory Receptors for Artificial-Intelligence Perception

In the era of artificial intelligence (AI), there is a growing interest in replicating human sensory perception. Selective and sensitive bio-inspired sensory receptors with synaptic plasticity have recently gained significant attention in developing energy-efficient AI perception. Various bio-inspired sensory receptors and their applications in AI perception are reviewed here. The critical challenges for the future development of bio-inspired sensory receptors are outlined, emphasizing the need for innovative solutions to overcome hurdles in sensor design, integration, and scalability. AI perception can revolutionize various fields, including human-machine interaction, autonomous systems, medical diagnostics, environmental monitoring, industrial optimization, and assistive technologies. As advancements in bio-inspired sensing continue to accelerate, the promise of creating more intelligent and adaptive AI systems becomes increasingly attainable, marking a significant step forward in the evolution of human-like sensory perception.

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.

An Artificial LiSiOx Nociceptor with Neural Blockade and Self-Protection Abilities

An artificial nociceptor, as a critical and special bionic receptor, plays a key role in a bioelectronic device that detects stimuli and provides warnings. However, fully exploiting bioelectronic applications remains a major challenge due to the lack of the methods of implementing basic nociceptor functions and nociceptive blockade in a single device. In this work, we developed a Pt/LiSiOx/TiN artificial nociceptor. It had excellent stability under the 104 endurance test with pulse stimuli and exhibited a significant threshold current of 1 mA with 1 V pulse stimuli. Other functions such as relaxation, inadaptation, and sensitization were all realized in a single device. Also, the pain blockade function was first achieved in this nociceptor with over a 25% blocking degree, suggesting a self-protection function. More importantly, an obvious depression was activated by a stimulus over 1.6 V due to the cooperative effects of both lithium ions and oxygen ions in LiSiOx and the dramatic accumulation of Joule heat. The conducting channel ruptured partially under sequential potentiation, thus achieving nociceptive blockade, besides basic functions in one single nociceptor, which was rarely reported. These results provided important guidelines for constructing high-performance memristor-based artificial nociceptors and opened up an alternative approach to the realization of bioelectronic systems for artificial intelligence.

Proximity Sensing Electronic Skin: Principles, Characteristics, and Applications

The research on proximity sensing electronic skin has garnered significant attention. This electronic skin technology enables detection without physical contact and holds vast application prospects in areas such as human-robot collaboration, human-machine interfaces, and remote monitoring. Especially in the context of the spread of infectious diseases like COVID-19, there is a pressing need for non-contact detection to ensure safe and hygienic operations. This article comprehensively reviews the significant advancements in the field of proximity sensing electronic skin technology in recent years. It covers the principles, as well as single-type proximity sensors with characteristics such as a large area, multifunctionality, strain, and self-healing capabilities. Additionally, it delves into the research progress of dual-type proximity sensors. Furthermore, the article places a special emphasis on the widespread applications of flexible proximity sensors in human-robot collaboration, human-machine interfaces, and remote monitoring, highlighting their importance and potential value across various domains. Finally, the paper provides insights into future advancements in flexible proximity sensor technology.

A Biomimetic Nociceptor Using Centrosymmetric Crystals for Machine Intelligence

Pain sensation is a crucial aspect of perception in the body. Force-activated nociceptors encode electrochemical signals and yield multilevel information of pain, thus enabling smart feedback. Inspired by the natural template, multi-dimensional mechano-sensing materials provide promising approaches for biomimetic nociceptors in intelligent terminals. However, the reliance on non-centrosymmetric crystals has narrowed the range of these materials. Here centrosymmetric crystal Cr3+ -doped zinc gallogermanate (ZGGO:Cr) with multi-dimensional mechano-sensing is reported, eliminating the limitation of crystal structure. Under forces, ZGGO:Cr generates electrical signals imitating those of neuronal systems, and produces luminescence for spatial mapping of mechanical stimuli, suggesting a path toward bionic pain perception. On that basis, a wireless biomimetic nociceptor system is developed and a smart pain reflex in a robotic hand and robot-assisted biopsy surgery of rat and dog is achieved.

Multifunctional Optoelectronic Synapses Based on Arrayed MoS2 Monolayers Emulating Human Association Memory

Optoelectronic synaptic devices integrating light-perception and signal-storage functions hold great potential in neuromorphic computing for visual information processing, as well as complex brain-like learning, memorizing, and reasoning. Herein, the successful growth of MoS₂ monolayer arrays assisted by gold nanorods guided precursor nucleation is demonstrated. Optical, spectral, and morphology characterizations of MoS₂ prove that arrayed flakes are homogeneous monolayers, and they are further fabricated as optoelectronic devices showing featured photocurrent loops and stable optical responses. Typical synaptic behaviors of photo-induced short-term potentiation, long-term potentiation, and paired pulse facilitation are recorded under different light stimulations of 450, 532, and 633 nm lasers at various excitation powers. A visual sensing system consisting of 5 × 6 pixels is constructed to simulate the light-sensing image mapped by forgetting curves in real time. Moreover, the system presents the ability of utilizing associated images to restore vague and incomplete memories, which successfully mimics human intelligent behaviors of association memory and logical reasoning. The work emulates the brain-like artificial intelligence using arrayed 2D semiconductors, which paves an avenue to achieve smart retina and complex brain-like system.

Liquid Metal-Based Electronics for On-Skin Healthcare

Wearable devices are receiving growing interest in modern technologies for realizing multiple on-skin purposes, including flexible display, flexible e-textiles, and, most importantly, flexible epidermal healthcare. A 'BEER' requirement, i.e., biocompatibility, electrical elasticity, and robustness, is first proposed here for all the on-skin healthcare electronics for epidermal applications. This requirement would guide the designing of the next-generation on-skin healthcare electronics. For conventional stretchable electronics, the rigid conductive materials, e.g., gold nanoparticles and silver nanofibers, would suffer from an easy-to-fail interface with elastic substrates due to a Young's modulus mismatch. Liquid metal (LM) with high conductivity and stretchability has emerged as a promising solution for robust stretchable epidermal electronics. In addition, the fundamental physical, chemical, and biocompatible properties of LM are illustrated. Furthermore, the fabrication strategies of LM are outlined for pure LM, LM composites, and LM circuits based on the surface tension control. Five dominant epidermal healthcare applications of LM are illustrated, including electrodes, interconnectors, mechanical sensors, thermal management, and biomedical and sustainable applications. Finally, the key challenges and perspectives of LM are identified for the future research vision.

Liquid Metal Based Nano-Composites for Printable Stretchable Electronics

Liquid metal (LM) has attracted prominent attention for stretchable and elastic electronics applications due to its exceptional fluidity and conductivity at room temperature. Despite progress in this field, a great disparity remains between material fabrication and practical applications on account of the high surface tension and unavoidable oxidation of LM. Here, the composition and nanolization of liquid metal can be envisioned as effective solutions to the processibility-performance dilemma caused by high surface tension. This review aims to summarize the strategies for the fabrication, processing, and application of LM-based nano-composites. The intrinsic mechanism and superiority of the composition method will further extend the capabilities of printable ink. Recent applications of LM-based nano-composites in printing are also provided to guide the large-scale production of stretchable electronics.

A biopolymer-gated ionotronic junctionless oxide transistor array for spatiotemporal pain-perception emulation in nociceptor network

Capable of reflecting the location and intensity of external harmful stimuli, a nociceptor network is of great importance for receiving pain-perception information. However, the hardware-based implementation of a nociceptor network through the use of a transistor array remains a great challenge in the area of brain-inspired neuromorphic applications. Herein, a simple ionotronic junctionless oxide transistor array with pain-perception abilities is successfully realized due to a coplanar-gate proton-coupling effect in sodium alginate biopolymer electrolyte. Several important pain-perception characteristics of nociceptors are emulated, such as a pain threshold, the memory of prior injury, and sensitization behavior due to pathway alterations. In particular, a good graded pain-perception network system has been successfully established through coplanar capacitance and resistance. More importantly, clear polarity reversal of Lorentz-type spatiotemporal pain-perception emulation can be finally realized in our projection-dependent nociceptor network. This work may provide new avenues for bionic medical machines and humanoid robots based on these intriguing pain-perception abilities.