Xue-Feng Wang

A Graphene-Based Resistive Pressure Sensor with Record-High Sensitivity in a Wide Pressure Range

Pressure sensors are a key component in electronic skin (e-skin) sensing systems. Most reported resistive pressure sensors have a high sensitivity at low pressures (<5 kPa) to enable ultra-sensitive detection. However, the sensitivity drops significantly at high pressures (>5 kPa), which is inadequate for practical applications. For example, actions like a gentle touch and object manipulation have pressures below 10 kPa, and 10–100 kPa, respectively. Maintaining a high sensitivity in a wide pressure range is in great demand. Here, a flexible, wide range and ultra-sensitive resistive pressure sensor with a foam-like structure based on laser-scribed graphene (LSG) is demonstrated. Benefitting from the large spacing between graphene layers and the unique v-shaped microstructure of the LSG, the sensitivity of the pressure sensor is as high as 0.96 kPa−1 in a wide pressure range (0 ~ 50 kPa). Considering both sensitivity and pressure sensing range, the pressure sensor developed in this work is the best among all reported pressure sensors to date. A model of the LSG pressure sensor is also established, which agrees well with the experimental results. This work indicates that laser scribed flexible graphene pressure sensors could be widely used for artificial e-skin, medical-sensing, bio-sensing and many other areas.

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.

Flexible CNT-array double helices Strain Sensor with high stretchability for Motion Capture

Motion capture is attracting more and more attention due to its potential wide applications in various fields. However, traditional methods for motion capture still have weakness such as high cost and space consuming. Based on these considerations, a flexible, highly stretchable strain sensor with high gauge factor for motion capture is fabricated with carbon nanotube (CNT) array double helices as the main building block. Ascribed to the unique flexible double helical CNT-array matrix, the strain sensor is able to measure strain up to 410%, with low hysteresis. Moreover, a demonstration of using this strain sensor for capture hand motion and to control a mechanical hand in real time is also achieved. A model based on finite difference method is also made to help understand the mechanism of the strain sensors. Our work demonstrates that strain sensors can measure very large strain while maintaining high sensitivity, and the motion capture based on this strain sensor is expected to be less expensive, more convenient and accessible.

In Situ Tuning of Switching Window in a Gate-Controlled Bilayer Graphene-Electrode Resistive Memory Device

A resistive random access memory (RRAM) device with a tunable switching window is demonstrated for the first time. The SET voltage can be continuously tuned from 0.27 to 4.5 V by electrical gating from -10 to +35 V. The gate-controlled bilayer graphene-electrode RRAM can function as 1D1R and potentially increase the RRAM density.

Extremely Low Operating Current Resistive Memory Based on Exfoliated 2D Perovskite Single Crystals for Neuromorphic Computing

Extremely low energy consumption neuromorphic computing is required to achieve massively parallel information processing on par with the human brain. To achieve this goal, resistive memories based on materials with ionic transport and extremely low operating current are required. Extremely low operating current allows for low power operation by minimizing the program, erase, and read currents. However, materials currently used in resistive memories, such as defective HfOx, AlOx, TaOx, etc., cannot suppress electronic transport (i.e., leakage current) while allowing good ionic transport. Here, we show that 2D Ruddlesden-Popper phase hybrid lead bromide perovskite single crystals are promising materials for low operating current nanodevice applications because of their mixed electronic and ionic transport and ease of fabrication. Ionic transport in the exfoliated 2D perovskite layer is evident via the migration of bromide ions. Filaments with a diameter of approximately 20 nm are visualized, and resistive memories with extremely low program current down to 10 pA are achieved, a value at least 1 order of magnitude lower than conventional materials. The ionic migration and diffusion as an artificial synapse is realized in the 2D layered perovskites at the pA level, which can enable extremely low energy neuromorphic computing.

Fabrication techniques and applications of flexible graphene-based electronic devices

In recent years, flexible electronic devices have become a hot topic of scientific research. These flexible devices are the basis of flexible circuits, flexible batteries, flexible displays and electronic skins. Graphene-based materials are very promising for flexible electronic devices, due to their high mobility, high elasticity, a tunable band gap, quantum electronic transport and high mechanical strength. In this article, we review the recent progress of the fabrication process and the applications of graphene-based electronic devices, including thermal acoustic devices, thermal rectifiers, graphene-based nanogenerators, pressure sensors and graphene-based light-emitting diodes. In summary, although there are still a lot of challenges needing to be solved, graphene-based materials are very promising for various flexible device applications in the future.

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.

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.