With the prospect of a smart society in the foreseeable future, humans are experiencing an increased link to electronics in the digital world, which can benefit our life and productivity drastically. In recent decades, advances in the Human Machine Interface (HMI) have improved from tactile sensors, such as touchpads and joysticks, to now include the accurate detection of dexterous body movements in more diversified and sophisticated devices. Advancements in highly adaptive machine learning techniques, neural interfaces, and neuromorphic sensing have generated the potential for an economic and feasible solution for next-generation applications such as wearable HMIs with intimate and multi-directional sensing capabilities. This review offers a general knowledge of HMI technologies beginning with tactile sensors and their piezoresistive, capacitive, piezoelectric, and triboelectric sensing mechanisms. A further discussion is given on how machine learning, neural interfaces, and neuromorphic electronics can be used to enhance next-generation HMIs in an upcoming 5 G infrastructure and advancements in the internet of things and artificial intelligence of things in the near future. The efficient interactions with kinetic and physiological signals from human body through the fusion of tactile sensor and neural electronics will bring a revolution to both the advanced manipulation and medical rehabilitation.

Technologies toward next generation human machine interfaces: From machine learning enhanced tactile sensing to neuromorphic sensory systems

Skin is the largest organ, with the functionalities of protection, regulation, and sensation. The emulation of human skin via flexible and stretchable electronics gives rise to electronic skin (e-skin), which has realized artificial sensation and other functions that cannot be achieved by conventional electronics. To date, tremendous progress has been made in data acquisition and transmission for e-skin systems, while the implementation of perception within systems, that is, sensory data processing, is still in its infancy. Integrating the perception functionality into a flexible and stretchable sensing system, namely artificial skin perception, is critical to endow current e-skin systems with higher intelligence. Here, recent progress in the design and fabrication of artificial skin perception devices and systems is summarized, and challenges and prospects are discussed. The strategies for implementing artificial skin perception utilize either conventional silicon-based circuits or novel flexible computing devices such as memristive devices and synaptic transistors, which enable artificial skin to surpass human skin, with a distributed, low-latency, and energy-efficient information-processing ability. In future, artificial skin perception would be a new enabling technology to construct next-generation intelligent electronic devices and systems for advanced applications, such as robotic surgery, rehabilitation, and prosthetics.

Artificial Skin Perception.

When external pressure drives an electrolyte solution in a capillary tube with a charged inner surface, we obtain a streaming potential/current. This effect is also manifested when water flows through the microchannels of a tree, which is driven by capillary pressure and natural evaporation. Thus, by making use of natural evaporation, we took advantage of the anisotropic three-dimensional wood structures to fabricate nanogenerators drawing electricity from the streaming potential/current. As a result, direct current can be harvested continuously, simply through a piece of wood. A 300 mV open-circuit voltage and a 10 μA short-circuit current (ISC) were recorded from a single device, which surpassed the ISC values of most previous works by an order. By connecting five wood nanogenerators in series, a calculator can be completely functional, as a demonstration for practical application.

Harvesting Electricity from Water Evaporation through Microchannels of Natural Wood.

The concept of the memristor, a resistor with memory, was proposed by Chua in 1971 as the fourth basic element of electric circuitry. Despite a significant amount of effort devoted to the understanding of memristor theory, our understanding of the nonpinched current–voltage (I–V) hysteresis loop in memristors remains incomplete. Here we propose a physical model of a memristor, with a capacitor connected in parallel, which explains how the nonpinched I–V hysteresis behavior originates from the capacitive-coupled memristive effect. Our model replicates eight types of characteristic nonlinear I–V behavior, which explains all observed nonpinched I–V curves seen in experiments. Furthermore, a reversible transition from a nonpinched I–V hysteresis loop to an ideal pinched I–V hysteresis loop is found, which explains the experimental data obtained in C15H11O6-based devices when subjected to an external stimulus (e.g., voltage, moisture, or temperature). Our results provide the vital physics models and materials ...

A Unified Capacitive-Coupled Memristive Model for the Nonpinched Current-Voltage Hysteresis Loop.

Recent advances in organic-based materials for resistive memory applications

Resistive switching memory integrated with amorphous carbon-based nanogenerators for self-powered device

Ultra-flexible egg albumen paper with a permittivity of 15–21, which is an improvement of nearly 300% compared with native egg albumen, is synthesized. Wearable protein-based memristor arrays exhibit excellent memory behavior and memory logic gate functionality under dual photoelectric control.

Artificial and wearable albumen protein memristor arrays with integrated memory logic gate functionality

Capacitive effect: An original of the resistive switching memory

Memristors possess great application prospects in terabit nonvolatile storage devices, memory-in-logic algorithmic chips and bio-inspired artificial neural network systems. However, "what is the origin state of the memristor?" has remained an unanswered question for half a century. While many applications rely on the memristor, its origin state is becoming a fundamental issue. Herein, we reveal a new state, the pure capacitance state (PCS), which occurs before the memristor is triggered, and the origin state of the memristor can be verified in the memory cells through controlling the ambience parameters. Discovery of the PCS, a missing earlier stage of the memristor, completes the whole evolution map of the memristor from the very beginning to the final developed state.

Zhijun Ren

Papers

Resistive switching memory integrated with amorphous carbon-based nanogenerators for self-powered device

Artificial and wearable albumen protein memristor arrays with integrated memory logic gate functionality

Capacitive effect: An original of the resistive switching memory

Evolution map of the memristor: from pure capacitive state to resistive switching state.