Magnetoresistance studies of two-dimensional Fe3GeTe2nano-flake.

The magneto-transport properties of two-dimensional (2D) Fe3GeTe2(FGT) nano-flakes are carefully investigated with the variation of the temperature and the direction of the applied magnetic field (B). Four magnetoresistance (MR) behavior are obtained at different temperatures withBparalleling the flake's surface, because of the competition between the merging of different domains, spin fluctuation, and the spin momentum flipping. Different from the reported negative MR of bulk FGT, 2D FGT shows a positive MR behavior with the increase ofBat a low temperature in a lowBrange, owning to the domination of the spin momentum flipping induced by the weakening of the coupling between different layers with the decrease of the thickness of the FGT flake. The angle-dependence of the FGT MR is also investigated and can be well explained by the competition mentioned above.

Coexistence of Contact Electrification and Dynamic p-n Junction Modulation Effects in Triboelectrification.

The triboelectric effect occurs when two dissimilar materials are in physical contact, attributed to the combination of contact electrification (CE) and electrostatic induction. It has been extensively explored for the development of high-performance triboelectric nanogenerators (TENGs). In this paper, we report on, besides the CE-related charge generation, an additional charge generation phenomenon associated with the modulation of the p-n junction when two semiconductor materials [methylammonium lead iodide (MAPI) and poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS)] are put in contact and separated dynamically. The electrical outputs generated by the CE effect are determined by the surface potential difference between the two friction materials, while the ones induced by the p-n junction modulation are determined by the dynamic variations in the depletion widths of the two semiconductor friction materials. The outputs generated by the CE effect and the p-n junction effect are well separated in time scale; the p-n junction modulation contributes ∼20% of the total charge generated and could be varied by changing the chemical composition of the semiconductors. The results may provide an alternative method for the development of high-performance TENGs by utilizing this additional p-n junction modulation effect.

Electric-Field-Resonance-Based Wireless Triboelectric Nanogenerators and Sensors.

Energy harvesting and energy transmission are the key technologies for self-powered systems; thus, the combination of these two is urgently needed. An innovative electric field resonance (EFR)-based wireless triboelectric nanogenerator (TENG) is proposed herein. By integrating the TENG with a capacitive coupler, the output of the TENG can be transmitted wirelessly from the transmitter to the receiver in the form of an oscillating signal with an energy-transfer efficiency of 67.8% for a 5 cm distance. Theoretical models of the EFR-TENG system are established, showing excellent agreement with the experimental results. It is demonstrated that the flexible EFR-TENG worn on the wrist can drive a digital watch wirelessly or light up at least 40 light-emitting diodes in series. The EFR-TENG is further utilized for spontaneous wireless sensing with a transmission distance up to 2.3 m with high system tolerance, showing the great potential of this novel strategy for energy harvesting and real-time wireless sensing applications.

A high-performance free-standing Zn anode for flexible zinc-ion batteries.

Zinc-ion batteries (ZIBs) have attracted significant attention owing to their high safety, high energy density, and low cost. ZIBs have been studied as a potential energy device for portable and flexible electronics. Here, a highly flexible free-standing Zn anode is fabricated using a simple spin-coating technique, and its application in ZIBs is demonstrated. The free-standing Zn anode precursor is formed by mixing Zn particles with carbon nanotubes and poly(vinylidene fluoride)-co-hexafluoropropylene (PVDF-HFP). The hexafluoropropylene group in PVDF-HFP improves the mechanical properties of the free-standing Zn anode, whereas the carbon nanotubes created percolation conduction in the composite electrode, leading to an increased electrical conductivity of the anode. Owing to the excellent electrical conductivity and high specific surface area of the free-standing Zn anode, ZIBs with high capacity, rate performance, and mechanical flexibility are achieved. The volumetric energy density of the ZIBs reaches 8.22 mW h cm-3 with a battery thickness of 0.4 mm. This work demonstrates that free-standing Zn anodes are promising anodes for flexible ZIBs.

Controllable high-performance memristors based on 2D Fe2GeTe3oxide for biological synapse imitation.

Memristors are an important component of the next-generation artificial neural network, high computing systems, etc. In the past, two-dimensional materials based memristors have achieved a high performance and low power consumption, though one at the cost of the other. Furthermore, their performance can not be modulated frequently once their structures are fixed, which remains the bottleneck in the development. Herein, a series of forming free memristors are fabricated with the same Cu/Fe3GeTe2oxide/Fe3GeTe2/Al structure, yet the On/Off ratio and set voltage is modulated continuously by varying the oxidation time during fabrication. With an optimal oxidation time, a large On/Off ratio (1.58 × 103) and low set voltage (0.74 V) is achieved in a single device. The formation and rapture of Al conductive filaments are found to be responsible for the memristors, and the filaments density and the cross-section area increase with the increase of current compliance, which achieves a higher On/Off ratio. The memristor can imitate basic biological synaptic functions using voltage pulses, demonstrating the potential for low-power consuming neuromorphic computing applications.

Emotion Recognition Based on Skin Potential Signals with a Portable Wireless Device.

Emotion recognition is of great importance for artificial intelligence, robots, and medicine etc. Although many techniques have been developed for emotion recognition, with certain successes, they rely heavily on complicated and expensive equipment. Skin potential (SP) has been recognized to be correlated with human emotions for a long time, but has been largely ignored due to the lack of systematic research. In this paper, we propose a single SP-signal-based method for emotion recognition. Firstly, we developed a portable wireless device to measure the SP signal between the middle finger and left wrist. Then, a video induction experiment was designed to stimulate four kinds of typical emotion (happiness, sadness, anger, fear) in 26 subjects. Based on the device and video induction, we obtained a dataset consisting of 397 emotion samples. We extracted 29 features from each of the emotion samples and used eight well-established algorithms to classify the four emotions based on these features. Experimental results show that the gradient-boosting decision tree (GBDT), logistic regression (LR) and random forest (RF) algorithms achieved the highest accuracy of 75%. The obtained accuracy is similar to, or even better than, that of other methods using multiple physiological signals. Our research demonstrates the feasibility of the SP signal's integration into existing physiological signals for emotion recognition.