Soft Electronics for Health Monitoring Assisted by Machine Learning

Due to the development of the novel materials,the past two decades have witnessed the rapid advances of soft electronics.The soft electronics have huge potential in the physical sign monitoring and health care.One of the important advantages of soft electronics is forming good interface with skin,which can increase the user scale and improve the signal quality.Therefore,it is easy to build the specific dataset,which is important to improve the performance of machine learning algorithm.At the same time,with the assistance of machine learning algorithm,the soft electronics have become more and more intelligent to realize real-time analysis and diagnosis.The soft electronics and machining learning algorithms complement each other very well.It is indubitable that the soft electronics will bring us to a healthier and more intelligent world in the near future.Therefore,in this review,we will give a careful introduction about the new soft material,physiological signal detected by soft devices,and the soft devices assisted by machine learning algorithm.Some soft materials will be discussed such as two-dimensional material,carbon nanotube,nanowire,nanomesh,and hydrogel.Then,soft sensors will be discussed according to the physiological signal types(pulse,respiration,human motion,intraocular pressure,phonation,etc.).After that,the soft electronics assisted by various algorithms will be reviewed,including some classical algorithms and powerful neural network algorithms.Especially,the soft device assisted by neural network will be introduced carefully.Finally,the outlook,challenge,and conclusion of soft system powered by machine learning algorithm will be discussed.

A Better Zn-Ion Storage Device:Recent Progress for Zn-Ion Hybrid Supercapacitors

As a new generation of Zn-ion storage systems,Zn-ion hybrid supercapacitors(ZHSCs)garner tremendous interests recently from researchers due to the perfect integration of batteries and supercapacitors.ZHSCs have excellent integration of high energy density and power density,which seamlessly bridges the gap between batteries and supercapacitors,becoming one of the most viable future options for large-scale equipment and portable electronic devices.However,the currently reported two configurations of ZHSCs and corresponding energy storage mechanisms still lack systematic analyses.Herein,this review will be prudently organized from the perspectives of design strategies,electrode configurations,energy storage mechanisms,recent advances in electrode materials,electrolyte behaviors and further applications(micro or flexible devices)of ZHSCs.The synthesis processes and electrochemical properties of well-designed Zn anodes,capacitor-type electrodes and novel Zn-ion battery-type cathodes are comprehensively discussed.Finally,a brief summary and outlook for the further development of ZHSCs are presented as well.This review will provide timely access for researchers to the recent works regarding ZHSCs.

Black phosphorus junctions and their electrical and optoelectronic applications

Black phosphorus(BP),an emerging two-dimensional material,is considered a promising candidate for next-generation electronic and optoelectronic devices due to in-plane anisotropy,high mobility,and direct bandgap.However,BP devices face challenges due to their limited stability,photo-response speed,and detection range.To enhance BP with powerful electrical and optical performance,the BP heterostructures can be created.In this review,the state-of-the-art heterostructures and their electrical and optoelectronic applications based on black phosphorus are discussed.Five parts introduce the performance of BP-based devices,including black phosphorus sandwich structure by hBN with better stability and higher mobility,black phosphorus homojunction by dual-gate structure for optical applications,black phosphorus heterojunction with other 2D materials for faster photo-detection,black phosphorus heterojunction integration with 3 D bulk material,and BP via Asdoping tunable bandgap enabling photo-detection up to 8.2μm.Finally,we discuss the challenges and prospects for BP electrical and optical devices and applications.

Magnetoresistive behavior and magnetization reversal of NiFe/Cu/CoFe/IrMn spin valve GMRs in nanoscale

The magnetoresistance behavior and the magnetization reversal mode of NiFe/Cu/CoFe/IrMn spin valve giant magnetoresistance （SV-GMR） in nanoscale were investigated experimentally and theoretically by nanosized magnetic simulation methods. Based on the Landau-Lifshitz-Gilbert equation, a model with a special gridding was proposed to calculate the giant magnetoresistance ratio （MR） and investigate the magnetization reversal mode. The relationship between MR and the external magnetic field was obtained and analyzed. Studies into the variation of the magnetization distribution reveal that the magnetization reversal mode, that is, the jump variation mode for NiFe/Cu/CoFe/IrMn, depends greatly on the antiferromagnetic coupling behavior between the pinned layer and the antiferromagnetic layer. It is also found that the switching field is almost linear with the exchange coefficient.

Breathable Electronic Skins for Daily Physiological Signal Monitoring

With the aging of society and the increase in people’s concern for personal health,long-term physiological signal monitoring in daily life is in demand.In recent years,electronic skin(e-skin)for daily health monitoring applications has achieved rapid development due to its advantages in high-quality physiological signals monitoring and suitability for system integrations.Among them,the breathable e-skin has developed rapidly in recent years because it adapts to the long-term and high-comfort wear requirements of monitoring physiological signals in daily life.In this review,the recent achievements of breathable e-skins for daily physiological monitoring are systematically introduced and discussed.By dividing them into breathable e-skin electrodes,breathable e-skin sensors,and breathable e-skin systems,we sort out their design ideas,manufacturing processes,performances,and applications and show their advantages in long-term physiological signal monitoring in daily life.In addition,the development directions and challenges of the breathable e-skin are discussed and prospected.

Framework for TCAD augmented machine learning on multi-I-V characteristics using convolutional neural network and multiprocessing

In a world where data is increasingly important for making breakthroughs,microelectronics is a field where data is sparse and hard to acquire.Only a few entities have the infrastructure that is required to automate the fabrication and testing of semiconductor devices.This infrastructure is crucial for generating sufficient data for the use of new information technologies.This situation generates a cleavage between most of the researchers and the industry.To address this issue,this paper will introduce a widely applicable approach for creating custom datasets using simulation tools and parallel computing.The multi-I-V curves that we obtained were processed simultaneously using convolutional neural networks,which gave us the ability to predict a full set of device characteristics with a single inference.We prove the potential of this approach through two concrete examples of useful deep learning models that were trained using the generated data.We believe that this work can act as a bridge between the state-of-the-art of data-driven methods and more classical semiconductor research,such as device engineering,yield engineering or process monitoring.Moreover,this research gives the opportunity to anybody to start experimenting with deep neural networks and machine learning in the field of microelectronics,without the need for expensive experimentation infrastructure.

Observation of stabilized negative capacitance effect in hafnium-based ferroic films

A negative capacitance(NC)effect has been proposed as a critical pathway to overcome the‘Boltzmann tyranny’of electrons,achieve the steep slope operation of transistors and reduce the power dissipation of current semiconductor devices.In particular,the ferroic property in hafnium-based films with fluorite structure provides an opportunity for the application of the NC effect in electronic devices.However,to date,only a transient NC effect has been confirmed in hafnium-based ferroic materials,which is usually accompanied by hysteresis and is detrimental to low-power transistor operations.The stabilized NC effect enables hysteresis-free and low-power transistors but is difficult to observe and demonstrate in hafnium-based films.This difficulty is closely related to the polycrystalline and multi-phase structure of hafnium-based films fabricated by atomic layer deposition or chemical solution deposition.Here,we prepare epitaxial ferroelectric Hf_(0.5)Zr_(0.5)O_(2) and antiferroelectric ZrO_(2) films with single-phase structure and observe the capacitance enhancement effect of Hf_(0.5)Zr_(0.5)O_(2)/Al_(2)O_(3) and ZrO_(2)/Al_(2)O_(3) capacitors compared to that of the isolated Al_(2)O_(3) capacitor,verifying the stabilized NC effect.The capacitance of Hf_(0.5)Zr_(0.5)O_(2) and ZrO_(2) is evaluated as−17.41 and−27.64 pF,respectively.The observation of the stabilized NC effect in hafnium-based films sheds light on NC studies and paves the way for low-power transistors.

Operation of silicon-germanium heterojunction bipolar transistors with different structures at deep cryogenic temperature

In this work, the device performances of discrete and integrated SiGe heterojunction bipolar transistors(HBTs) with different device structures from 300 to 4.8 K were investigated. The turn-on voltages of baseemitter and base-collector junctions increased non-linearly with temperature cooled to 4.8 K. Energy bandgap engineering was taken into account for the analytical model of the turn-on voltage versus temperature. Incomplete ionization occurred in the base-collector junction because of the low doping concentration. The trap-assisted tunneling current in the forward base current was clearly observed below20 K. The ideality factor and saturation current were shown to be temperature dependence. The ideality factor was much larger than 2 below 40 K, indicating that the current is not only contributed by drift, diffusion and recombination, but also by tunneling. The peak current gain of the discrete SiGe HBTs achieved the maximum value of 3,388 at 80 K, while that of the integrated was 546 at 140 K. The transconductance in logarithm was linearly dependent on reciprocal temperature above 50 K, but flattened below 50 K.Early effect was evidently observed below 77 K in the fixed base current output characteristics of the discrete SiGe HBTs, and it was not obvious for the integrated SiGe HBTs.

Graphene-based dual-function acoustic transducers for machine learning-assisted human-robot interfaces

Human–robot interface(HRI)electronics are critical for realizing robotic intelligence.Here,we report graphene-based dual-function acoustic transducers for machine learning-assisted human–robot interfaces(GHRI).The GHRI functions both an artificial ear through the triboelectric acoustic sensing mechanism and an artificial mouth through the thermoacoustic sound emission mechanism.The success of the integrated device is also attributed to the multifunctional laser-induced graphene,as either triboelectric materials,electrodes,or thermoacoustic sources.By systematically optimizing the structure parameters,the GHRI achieves high sensitivity(4500 mV Pa^(–1))and operating durability(1000000 cycles and 60 days),capable of recognizing speech identities,emotions,content,and other information in the human speech.With the assistance of machine learning,30 speech categories are trained by a convolutional neural network,and the accuracy reaches 99.66%and 96.63%in training datasets and test datasets.Furthermore,GHRI is used for artificial intelligence communication based on recognized speech features.Our work shows broad prospects for the development of robotic intelligence.

Pulse electrochemical synaptic transistor for supersensitive and ultrafast biosensors

High sensitivity and fast response are the figures of merit for benchmarking commercial sensors.Due to the advantages of intrinsic signal amplification,bionic ability,and mechanical flexibility,electrochemical transistors(ECTs)have recently gained increasing popularity in constructing various sensors.In the current work,we have proposed a pulse-driven synaptic ECT for supersensitive and ultrafast biosensors.By pulsing the presynaptic input(drain bias,VD)and setting the modulation potential(gate bias)near transconductance intersection(VG,i),the synaptic ECT-based pH sensor can achieve a record high sensitivity up to 124 mV pH^(-1)(almost twice the Nernstian limit,59.2 mV pH^(-1))and an ultrafast response time as low as 8.75 ms(7169 times faster than the potentiostatic sensors,62.73 s).The proposed synaptic sensing strategy can effectively eliminate the transconductance fluctuation issue during the calibration process of the pH sensor and significantly reduce power consumption.Besides,the most sensitive working point at VG,i has been elaborately figured out through a series of detailed mathematical derivations,which is of great significance to provide higher sensitivity with quasi-nonfluctuating amplification capability.The proposed electrochemical synaptic transistor paired with an optimized operating gate offers a new paradigm for standardizing and commercializing high-performance biosensors.

Recent Progress and Applications of HfO_(2)-Based Ferroelectric Memory

The discovery of ferroelectricity in hafnium oxide (HfO_(2)) based thin films in 2011 renewed the interest inferroelectrics. These new ferroelectrics possess completely different crystal morphology with conventional perovskiteferroelectrics, and present more robust ferroelectric properties upon aggressive scaling and compatibility withstandard integrated circuit fabrication processes. In this article, we give a brief introduction to the conventionalferroelectric memories, then review the basic properties, recent progress, and memory applications of theseHfO_(2)-based ferroelectrics.

Au-decorated porous structure graphene with enhanced sensing performance for low-concentration NO2 detection

A recent progress in new emerging two-dimensional(2 D)materials has provided promising opportunity for gas sensing in ultra-low detectable concentration.In this work,we have demonstrated a flexible NO2 gas sensor with porous structure graphene on polyethylene terephthalate substrates operating at room temperature.The gas sensor exhibited good performance with response of 1.2%and a fast response time within 30 s after exposure to50×10^-9 NO2 gas.As porous structure of graphene increased the surface area,the sensor showed high sensitivity of ppb level for NO2 detection.Au nanoparticles were decorated on the surface of the porous structure graphene skeleton,resulting in an incensement of response compared with pristine graphene.Au nanoparticles-decorated graphene exhibits not only better sensitivity(1.5-1.6 times larger than pristine graphene)for NO2 gas detection,but also fast response.The sensor was found to be robust and sensitive under the cycling bending test,which could also be ascribed to the merits of graphene.This porous structure graphene-based gas sensor is expected to enable a simple and inexpensive flexible gas sensing platform.

Directly integrated mixed-dimensional van der Waals graphene/perovskite heterojunction for fast photodetection

Mixed-dimensional(2D/3D)van der Waals(vdW)heterostructures made with complementary materials hold a lot of promise in the field of optoelectronic devices.Beyond simple mechanical stacking,directly growing the single-crystal perovskite on 2D materials to construct a high-quality vdW heterojunction can better promote carrier transport.In this work,a monolithic integrated graphene/perovskite heterojunction device is fabricated by directly growing a single-crystal hybrid perovskite on monolayer graphene.Due to the strong inter-face coupling,the hybrid device achieves self-powering behavior and exhibits prominent photoresponse properties with a fast response speed of up to 2.05μs.Moreover,the responsivity and detectivity can be boosted to up to 10.41 A W1 and 4.65×10^(12)Jones under the actuation of3 V bias.This technique not only improves the device performance,but also provides an effective guideline for the development of next-generation directly integrated vdW optoelectronic devices.

Ambipolar Transport Compact Models for Two-Dimensional Materials Based Field-Effect Transistors

Three main ambipolar compact models for Two-Dimensional(2D)materials based Field-Effect Transistors(2D-FETs)are reviewed:(1)Landauer model,(2)2D Pao-Sah model,and(3)virtual Source Emission-Diffusion(VSED)model.For the Landauer model,the Gauss quadrature method is applied,and it summarizes all kinds of variants,exhibiting its state-of-art.For the 2D Pao-Sah model,the aspects of its theoretical fundamentals are rederived,and the electrostatic potentials of electrons and holes are clarified.A brief development history is compiled for the VSED model.In summary,the Landauer model is naturally appropriate for the ballistic transport of short channels,and the 2D Pao-Sah model is applicable to long-channel devices.By contrast,the VSED model offers a smooth transition between ultimate cases.These three models cover a fairly completed channel length range,which enables researchers to choose the appropriate compact model for their works.

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 someone＇s 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 thin- film 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.

The Use of Graphene-Based Earphones in Wireless Communication

Graphene-based materials have attracted much attention in recent years. Many researchers have demonstrated prototypes using graphene-based materials, but few specific applications have appeared. Graphene- based acoustic devices have become a popular topic. This paper describes a novel method to fabricate graphene- based earphones by laser scribing. The earphones have been used in wireless communication systems. A wireless communication system was built based on an ARM board. Voice from a mobile phone was transmitted to a graphene-based earphone. The output sound had a similar wave envelope to that of the input; some differences were introduced by the DC bias added to the driving circuit of the graphene-based earphone. The graphene-based earphone was demonstrated to have a great potential in wireless communication.

K_(0.5)Na_(0.5)NbO_3-Based Self-Powered Pressure Sensor

We report a novel self-powered nanocomposite sensor composed of Ko.5Nao.5NbO3 （KNN） nanoparticles （NPs） and multiwalled carbon nanotubes （MW-CNTs）. The KNN NPs and MW-CNTs are dispersed in polydimethylsioxane by mechanical agitation to produce a piezoelectric nanocomposite device. The device exhibits an output voltage of approximately 30 V and output current of approximately 15 μA. Furthermore, the device exhibits potential as a self-powered pressure sensor because the output voltage can be tested to detect the pressure applied to the device and does not require other sources.

Highly Sensitive and Portable Gas Sensing System Based on Reduced Graphene Oxide

Graphene has been widely used in gas-sensing applications due to its large specific surface area and strong adsorption ability. Among different forms of graphene used as gas-sensing materials, reduced graphene oxide is one of the most convenient and economical materials to integrate with Si-based electronics, which is very important to graphene-based gas sensors. In addition, the stacking structure of graphene oxide flakes facilitates absorption and detection of gas molecules. Based on reduced graphene oxide, a highly sensitive and portable gas-sensing system was demonstrated here. Solution-based graphene oxide was cast on a chip like a TF memory card and then reduced thermally. A signal acquisition system was designed to monitor resistance variation as a sign of gas concentration. This miniature graphene-based gas sensor array demonstrates a new path for the use of graphene in gas-detection technologies. And the creation of a sensitive and portable graphene gas sensor also shows great potential in fields such as medicine and environmental science.