Yu-Xing Li

Flexible, Highly Sensitive, and Wearable Pressure and Strain Sensors with Graphene Porous Network Structure

A mechanical sensor with graphene porous network (GPN) combined with polydimethylsiloxane (PDMS) is demonstrated by the first time. Using the nickel foam as template and chemically etching method, the GPN can be created in the PDMS-nickel foam coated with graphene, which can achieve both pressure and strain sensing properties. Because of the pores in the GPN, the composite as pressure and strain sensor exhibit wide pressure sensing range and highest sensitivity among the graphene foam-based sensors, respectively. In addition, it shows potential applications in monitoring or even recognize the walking states, finger bending degree, and wrist blood pressure.

Graphene Dynamic Synapse with Modulatable Plasticity

The synaptic activities in the nervous system is the basis of memory and learning behaviors, and the concept of biological synapse has also spurred the development of neuromorphic engineering. In recent years, the hardware implementation of the biological synapse has been achieved based on CMOS circuits, resistive switching memory, and field effect transistors with ionic dielectrics. However, the artificial synapse with regulatable plasticity has never been realized of the device level. Here, an artificial dynamic synapse based on twisted bilayer graphene is demonstrated with tunable plasticity. Due to the ambipolar conductance of graphene, both behaviors of the excitatory synapse and the inhibitory synapse could be realized in a single device. Moreover, the synaptic plasticity could also be modulated by tuning the carrier density of graphene. Because the artificial synapse here could be regulated and inverted via changing the bottom gate voltage, the whole process of synapse development could be imitated. Hence, this work would offer a broad new vista for the 2D material electronics and guide the innovation of neuro-electronics fundamentally.

A Pressure Sensing System for Heart Rate Monitoring with Polymer-Based Pressure Sensors and an Anti-Interference Post Processing Circuit

Heart rate measurement is a basic and important issue for either medical diagnosis or daily health monitoring. In this work great efforts have been focused on realizing a portable, comfortable and low cost solution for long-term domestic heart rate monitoring. A tiny but efficient measurement system composed of a polymer-based flexible pressure sensor and an analog anti-interference readout circuit is proposed; manufactured and tested. The proposed polymer-based pressure sensor has a linear response and high sensitivity of 13.4 kPa−1. With the circuit’s outstanding capability in removing interference caused by body movement and the highly sensitive flexible sensor device, comfortable long-term heart rate monitoring becomes more realistic. Comparative tests prove that the proposed system has equivalent capability (accuracy: <3%) in heart rate measurement to the commercial product.

Enhancement of carrier mobility in MoS2 field effect transistors by a SiO2 protective layer

Molybdenum disulfide is a promising channel material for field effect transistors (FETs). In this paper, monolayer MoS2 grown by chemical vapor deposition (CVD) was used to fabricate top-gate FETs through standard optical lithography. During the fabrication process, charged impurities and interface states are introduced, and the photoresist is not removed cleanly, which both limit the carrier mobility and the source-drain current. We apply a SiO2 protective layer, which is deposited on the surface of MoS2, in order to avoid the MoS2 directly contacting with the photoresist and the ambient environment. Therefore, the contact property between the MoS2 and the electrodes is improved, and the Coulomb scattering caused by the charged impurities and the interface states is reduced. Comparing MoS2 FETs with and without a SiO2 protective layer, the SiO2 protective layer is found to enhance the characteristics of the MoS2 FETs, including transfer and output characteristics. A high mobility of ∼42.3 cm2/V s is achi...

Epidermis Microstructure Inspired Graphene Pressure Sensor with Random Distributed Spinosum for High Sensitivity and Large Linearity

Recently, wearable pressure sensors have attracted tremendous attention because of their potential applications in monitoring physiological signals for human healthcare. Sensitivity and linearity are the two most essential parameters for pressure sensors. Although various designed micro/nanostructure morphologies have been introduced, the trade-off between sensitivity and linearity has not been well balanced. Human skin, which contains force receptors in a reticular layer, has a high sensitivity even for large external stimuli. Herein, inspired by the skin epidermis with high-performance force sensing, we have proposed a special surface morphology with spinosum microstructure of random distribution via the combination of an abrasive paper template and reduced graphene oxide. The sensitivity of the graphene pressure sensor with random distribution spinosum (RDS) microstructure is as high as 25.1 kPa-1 in a wide linearity range of 0-2.6 kPa. Our pressure sensor exhibits superior comprehensive properties compared with previous surface-modified pressure sensors. According to simulation and mechanism analyses, the spinosum microstructure and random distribution contribute to the high sensitivity and large linearity range, respectively. In addition, the pressure sensor shows promising potential in detecting human physiological signals, such as heartbeat, respiration, phonation, and human motions of a pushup, arm bending, and walking. The wearable pressure sensor array was further used to detect gait states of supination, neutral, and pronation. The RDS microstructure provides an alternative strategy to improve the performance of pressure sensors and extend their potential applications in monitoring human activities.

Top-Gate Electric-Double-Layer IZO-Based Synaptic Transistors for Neuron Networks

In this letter, top-gate electric-double- layer (EDL) indium–zinc-oxide (IZO)-based synaptic transistors were demonstrated. A silicon oxide solid electrolyte film was used as the insulator, which was deposited by the plasma-enhanced chemical vapor deposition method at room temperature. A low operation voltage of 1 V was achieved due to the formation of the EDL layer at the SiO2/IZO interface. In the top-gate synaptic transistors, paired-pulse facilitation and high-frequency filter were mimicked, which are the short-term synaptic behaviors. Standard microfabrication processes were used to pattern, which could be used for large integration in the future.

Interface Engineering with MoS2–Pd Nanoparticles Hybrid Structure for a Low Voltage Resistive Switching Memory

Metal oxide-based resistive random access memory (RRAM) has attracted a lot of attention for its scalability, temperature robustness, and potential to achieve machine learning. However, a thick oxide layer results in relatively high program voltage while a thin one causes large leakage current and a small window. Owing to these fundamental limitations, by optimizing the oxide layer itself a novel interface engineering idea is proposed to reduce the programming voltage, increase the uniformity and on/off ratio. According to this idea, a molybdenum disulfide (MoS2 )-palladium nanoparticles hybrid structure is used to engineer the oxide/electrode interface of hafnium oxide (HfOx )-based RRAM. Through its interface engineering, the set voltage can be greatly lowered (from -3.5 to -0.8 V) with better uniformity under a relatively thick HfOx layer (≈15 nm), and a 30 times improvement of the memory window can be obtained. Moreover, due to the atomic thickness of MoS2 film and high transmittance of ITO, the proposed RRAM exhibits high transparency in visible light. As the proposed interface-engineering RRAM exhibits good transparency, low SET voltage, and a large resistive switching window, it has huge potential in data storage in transparent circuits and wearable electronics with relatively low supply voltage.

Carbon Nanotube Transistor with Short-Term Memory

Short-Term Memory (STM) is a primary capability of the human brain. Humans use STM to remember a small amount of information, like someones phone number, for a short period of time. Usually the duration of STM is less than 1 minute. Synapses, the connections between neurons, are of vital importance to memory in biological brains. For mimicking the memory function of synapses, Carbon Nanotube (CNT) networks based thinfilm transistors with Electric Double Layers (EDL) at the dielectric/channel interface were researched in this work. A response characteristic of pre-synaptic potential pulses on the gate electrode of this CNT synaptic transistor was shown remarkably similar to Excitatory Post-Synaptic Current (EPSC) of biological synapses. Also a multi-level modulatable STM of CNT synaptic transistors was investigated. Post-synaptic current was shown with tunable peak values, on-off ratio, and relaxation time.

Flexible, wearable, and functional graphene-textile composites

In this paper, a flexible, wearable, and functional graphene-textile composite is demonstrated. Laser scribing technology is applied to fabricate a graphene film. The thin layer of polydimethylsiloxane is covered on the surface of the graphene-textile film evenly, which would improve the abrasive resistance of the film, enhance the ability to adapt to environmental changes, and extend the service life, while maintaining the devices excellent flexibility and comfort. The graphene-textile composite can achieve constant temperature heating by controlling the input voltage, detect the human movement, and perceive the human pulse signal. The composite presents great commercial prospects and a large value in the medical, daily wear, and other areas that are closely related to human lives.

Simultaneously Detecting Subtle and Intensive Human Motions Based on a Silver Nanoparticles Bridged Graphene Strain Sensor

There is a growing demand for flexible electronic devices. In particular, strain sensors with high performance have attracted more and more attention, because they can be attached on clothing or human skin for applications in the real-time monitoring of human activities. However, monitoring human-body motions that include both subtle and intensive motions, and many strain sensors cannot meet the diverse demands simultaneously. In this work, a silver nanoparticles (Ag NPs) bridged graphene strain sensor is developed for simultaneously detecting subtle and intensive human motions. Ag NPs serve as many bridges to connect the self-overlapping graphene sheets, which endows the strain sensor with many excellent performances. Because of the high sensitivity, with a large gauge factor (GF) of 475 and a strain range of >14.5%, high durability of the sensor has been achieved. Besides, the excellent consistency and repeatability of the fabrication process is verified. Furthermore, the model for explaining the working mechanism of the strain sensor is proposed. Most importantly, the designed wearable strain sensor can be applied in human motion detection, including large-scale motions and small-scale motions.