State Key Laboratory of ASIC and System

In-home healthcare services based on the Internet-of-Things (IoT) have great business potential; however, a comprehensive platform is still missing. In this paper, an intelligent home-based platform, the iHome Health-IoT, is proposed and implemented. In particular, the platform involves an open-platform-based intelligent medicine box (iMedBox) with enhanced connectivity and interchangeability for the integration of devices and services; intelligent pharmaceutical packaging (iMedPack) with communication capability enabled by passive radio-frequency identification (RFID) and actuation capability enabled by functional materials; and a flexible and wearable bio-medical sensor device (Bio-Patch) enabled by the state-of-the-art inkjet printing technology and system-on-chip. The proposed platform seamlessly fuses IoT devices (e.g., wearable sensors and intelligent medicine packages) with in-home healthcare services (e.g., telemedicine) for an improved user experience and service efficiency. The feasibility of the implemented iHome Health-IoT platform has been proven in field trials.

Abstract Highly sensitive gas sensors with remarkably low detection limits are attractive for diverse practical application fields including real-time environmental monitoring, exhaled breath diagnosis, and food freshness analysis. Among various chemiresistive sensing materials, noble metal-decorated semiconducting metal oxides (SMOs) have currently aroused extensive attention by virtue of the unique electronic and catalytic properties of noble metals. This review highlights the research progress on the designs and applications of different noble metal-decorated SMOs with diverse nanostructures (e.g., nanoparticles, nanowires, nanorods, nanosheets, nanoflowers, and microspheres) for high-performance gas sensors with higher response, faster response/recovery speed, lower operating temperature, and ultra-low detection limits. The key topics include Pt, Pd, Au, other noble metals (e.g., Ag, Ru, and Rh . ), and bimetals-decorated SMOs containing ZnO, SnO 2 , WO 3 , other SMOs (e.g., In 2 O 3 , Fe 2 O 3 , and CuO), and heterostructured SMOs. In addition to conventional devices, the innovative applications like photo-assisted room temperature gas sensors and mechanically flexible smart wearable devices are also discussed. Moreover, the relevant mechanisms for the sensing performance improvement caused by noble metal decoration, including the electronic sensitization effect and the chemical sensitization effect, have also been summarized in detail. Finally, major challenges and future perspectives towards noble metal-decorated SMOs-based chemiresistive gas sensors are proposed.

2D materials have attracted tremendous attention due to their unique physical and chemical properties since the discovery of graphene. Despite these intrinsic properties, various modification methods have been applied to 2D materials that yield even more exciting results in terms of tunable properties and device performance. Among all modification methods, intercalation of 2D materials has emerged as a particularly powerful tool: it provides the highest possible doping level and is capable of (ir)reversibly changing the phase of the material. Intercalated 2D materials exhibit extraordinary electrical transport as well as optical, thermal, magnetic, and catalytic properties, which are advantageous for optoelectronics, superconductors, thermoelectronics, catalysis and energy storage applications. The recent progress on host 2D materials, various intercalation species, and intercalation methods, as well as tunable properties and potential applications enabled by intercalation, are comprehensively reviewed.

Atomically thin 2D layered transition metal dichalcogenides (TMDs) have been extensively studied in recent years because of their appealing electrical and optical properties. Here, the fabrication of ReS 2 field‐effect transistors is reported via the encapsulation of ReS 2 nanosheets in a high‐ κ Al 2 O 3 dielectric environment. Low‐temperature transport measurements allow to observe a direct metal‐to‐insulator transition originating from strong electron–electron interactions. Remarkably, the photodetectors based on ReS 2 exhibit gate‐tunable photoresponsivity up to 16.14 A W −1 and external quantum efficiency reaching 3168%, showing a competitive device performance to those reported in graphene, MoSe 2 , GaS, and GaSe‐based photodetectors. This study unambiguously distinguishes ReS 2 as a new candidate for future applications in electronics and optoelectronics.

With the rapid development of the Internet of Things, there is a great demand for portable gas sensors. Metal oxide semiconductors (MOS) are one of the most traditional and well-studied gas sensing materials and have been widely used to prepare various commercial gas sensors. However, it is limited by high operating temperature. The current research works are directed towards fabricating high-performance flexible room-temperature (FRT) gas sensors, which are effective in simplifying the structure of MOS-based sensors, reducing power consumption, and expanding the application of portable devices. This article presents the recent research progress of MOS-based FRT gas sensors in terms of sensing mechanism, performance, flexibility characteristics, and applications. This review comprehensively summarizes and discusses five types of MOS-based FRT gas sensors, including pristine MOS, noble metal nanoparticles modified MOS, organic polymers modified MOS, carbon-based materials (carbon nanotubes and graphene derivatives) modified MOS, and two-dimensional transition metal dichalcogenides materials modified MOS. The effect of light-illuminated to improve gas sensing performance is further discussed. Furthermore, the applications and future perspectives of FRT gas sensors are also discussed.

We propose and experimentally demonstrate a novel full-duplex bi-directional subcarrier multiplexing (SCM)-wavelength division multiplexing (WDM) visible light communication (VLC) system based on commercially available red-green-blue (RGB) light emitting diode (LED) and phosphor-based LED (P-LED) with 575-Mb/s downstream and 225-Mb/s upstream transmission, employing various modulation orders of quadrature amplitude modulation (QAM) orthogonal frequency division multiplexing (OFDM). For the downlink, red and green colors/wavelengths are assigned to carry useful information, while blue chip is just kept lighting to maintain the white color illumination, and for the uplink, the low-cost P-LED is implemented. In this demonstration, pre-equalization and post-equalization are also adopted to compensate the severe frequency response of LEDs. Using this scheme, 4-user downlink and 1-user uplink transmission can be achieved. Furthermore, it can support more users by adjusting the bandwidth of each sub-channel. Bit error rates (BERs) of all links are below pre-forward-error-correction (pre-FEC) threshold of 3.8x 10(-3) after 66-cm free-space delivery. The results show that this scheme has great potential in the practical VLC system.

Abstract With the advent of the era of big data, resistive random access memory (RRAM) has become one of the most promising nanoscale memristor devices (MDs) for storing huge amounts of information. However, the switching voltage of the RRAM MDs shows a very broad distribution due to the random formation of the conductive filaments. Here, self‐assembled lead sulfide (PbS) quantum dots (QDs) are used to improve the uniformity of switching parameters of RRAM, which is very simple comparing with other methods. The resistive switching (RS) properties of the MD with the self‐assembled PbS QDs exhibit better performance than those of MDs with pure‐Ga 2 O 3 and randomly distributed PbS QDs, such as a reduced threshold voltage, uniformly distributed SET and RESET voltages, robust retention, fast response time, and low power consumption. This enhanced performance may be attributed to the ordered arrangement of the PbS QDs in the self‐assembled PbS QDs which can efficiently guide the growth direction for the conducting filaments. Moreover, biosynaptic functions and plasticity, are implemented successfully in the MD with the self‐assembled PbS QDs. This work offers a new method of improving memristor performance, which can significantly expand existing applications and facilitate the development of artificial neural systems.

Parity-time (PT) symmetric systems experience phase transition between PT exact and broken phases at exceptional point. These PT phase transitions contribute significantly to the design of single mode lasers, coherent perfect absorbers, isolators, and diodes. However, such exceptional points are extremely difficult to access in practice because of the dispersive behaviour of most loss and gain materials required in PT symmetric systems. Here we introduce a method to systematically tame these exceptional points and control PT phases. Our experimental demonstration hinges on an active acoustic element that realizes a complex-valued potential and simultaneously controls the multiple interference in the structure. The manipulation of exceptional points offers new routes to broaden applications for PT symmetric physics in acoustics, optics, microwaves and electronics, which are essential for sensing, communication and imaging.

Antiferroelectric thin films are demonstrated as a new class of giant electrocaloric materials that exhibit a negative electrocaloric response of about -5 K near room temperature. The giant negative electrocaloric effect may open up a new paradigm for light, compact, reliable, and high-efficiency refrigeration devices.

Abstract Memristors as electronic artificial synapses have attracted increasing attention in neuromorphic computing. Emulation of both “learning” and “forgetting” processes requires a bidirectional progressive adjustment of memristor conductance, which is a challenge for cutting‐edge artificial intelligence. In this work, a memristor device with a structure of Ag/Zr 0.5 Hf 0.5 O 2 :graphene oxide quantum dots/Ag is presented with the feature of bidirectional progressive conductance tuning. The conductance of proposed memristor is adjusted through voltage pulse number, amplitude, and width. A series of voltage pulses with an amplitude of 0.6 V and a width of 30 ns is enough to modulate conductance. The impacts of pulses with different parameters on conductance modulation are investigated, and the potential relationship between pulse amplitude and energy is revealed. Furthermore, it is proved that the pulse with low energy can realize the almost linear conductance regulation, which is beneficial to improve the accuracy of pattern recognition. The bidirectional progressive conduction modulation mimics various plastic synapses, such as spike‐timing‐dependent plasticity and paired‐pulse facilitation. This progressive conduction tuning mechanism might be attributed to the coexistence of tunneling effect and extrinsic electrochemical metallization effect. This work provides one way for memristor to attain attractive features such as bidirectional tuning, low‐power consumption, and fast speed switching that is in urgent demand for further evolution of neuromorphic chips.

The computation-intensive circuit simulation makes the analog circuit sizing challenging for large-scale/complicated analog/RF circuits. A Bayesian optimization approach has been proposed recently for the optimization problems involving the evaluations of black-box functions with high computational cost in either objective functions or constraints. In this paper, we propose a weighted expected improvement-based Bayesian optimization approach for automated analog circuit sizing. Gaussian processes (GP) are used as the online surrogate models for circuit performances. Expected improvement is selected as the acquisition function to balance the exploration and exploitation during the optimization procedure. The expected improvement is weighted by the probability of satisfying the constraints. In this paper, we propose a complete Bayesian optimization framework for the optimization of analog circuits with constraints for the first time. The existing GP model-based optimization methods for analog circuits take the GP models as either offline models or as assistance for the evolutionary algorithms. We also extend the Bayesian optimization algorithm to handle multi-objective optimization problems. Compared with the state-of-the-art approaches listed in this paper, the proposed Bayesian optimization method achieves better optimization results with significantly less number of simulations.

Plasmon-free surface enhanced Raman scattering (SERS) based on the chemical mechanism (CM) is drawing great attention due to its capability for controllable molecular detection. However, in comparison to the conventional noble-metal-based SERS technique driven by plasmonic electromagnetic mechanism (EM), the low sensitivity in the CM-based SERS is the dominant barrier toward its practical applications. Herein, we demonstrate the 1T′ transition metal telluride atomic layers (WTe2 and MoTe2) as ultrasensitive platforms for CM-based SERS. The SERS sensitivities of analyte dyes on 1T′-W(Mo)Te2 reach EM-comparable ones and become even greater when it is integrated with a Bragg reflector. In addition, the dye fluorescence signals are efficiently quenched, making the SERS spectra more distinguishable. As a proof of concept, the SERS signals of analyte Rhodamine 6G (R6G) are detectable even with an ultralow concentration of 40 (400) fM on pristine 1T′-W(Mo)Te2, and the corresponding Raman enhancement factor (EF) reaches 1.8 × 109 (1.6 × 108). The limit concentration of detection and the EF of R6G can be further enhanced into 4 (40) fM and 4.4 × 1010 (6.2 × 109), respectively, when 1T′-W(Mo)Te2 is integrated on the Bragg reflector. The strong interaction between the analyte and 1T′-W(Mo)Te2 and the abundant density of states near the Fermi level of the semimetal 1T′-W(Mo)Te2 in combination gives rise to the promising SERS effects by promoting the charge transfer resonance in the analyte-telluride complex.

Charge-trap memory with high-κ dielectric materials is considered to be a promising candidate for next-generation memory devices. Ultrathin layered two-dimensional (2D) materials like graphene and MoS2 have been receiving much attention because of their fantastic physical properties and potential applications in electronic devices. Here, we report on a dual-gate charge-trap memory device composed of a few-layer MoS2 channel and a three-dimensional (3D) Al2O3/HfO2/Al2O3 charge-trap gate stack. Because of the extraordinary trapping ability of both electrons and holes in HfO2, the MoS2 memory device exhibits an unprecedented memory window exceeding 20 V. Importantly, with a back gate the window size can be effectively tuned from 15.6 to 21 V; the program/erase current ratio can reach up to 10(4), allowing for multibit information storage. Moreover, the device shows a high endurance of hundreds of cycles and a stable retention of ∼ 28% charge loss after 10 years, which is drastically lower than ever reported MoS2 flash memory. The combination of 2D materials with traditional high-κ charge-trap gate stacks opens up an exciting field of nonvolatile memory devices.

Abstract Traditional von Neumann computing architecture with separated computation and storage units has already impeded the data processing performance and energy efficiency, calling for emerging neuromorphic electronic and optical devices and systems which can mimic the human brain to shift this paradigm. Material‐level innovation has become the key component to this revolution of information technology. Chalcogenide phase‐change material (PCM) as a well‐acknowledged data‐storage medium is a promising candidate to tackle this challenge. In this review, the use of PCMs to implement artificial neurons and synapses from both the electronic and optical respects is discussed, and in particular, the structure–property physics and transition dynamics that enable such brain‐inspired and in‐memory computing applications are emphasized. Recent advances on the atomic‐level amorphous and crystalline structures, transition mechanisms, materials optimization and design, neural and synaptic devices, brain‐inspired chips, and computing systems, as well as the future opportunities of PCMs, are summarized and discussed.

This paper presents a fully-printed chipless radio frequency identification sensor tag for short-range item identification and humidity monitoring applications. The tag consists of two planar inductor-capacitor resonators operating wirelessly through inductive coupling. One resonator is used to encode ID data based on frequency spectrum signature, and another one works as a humidity sensor, utilizing a paper substrate as a sensing material. The sensing performances of three paper substrates, including commercial packaging paper, are investigated. The use of paper provides excellent sensitivity and reasonable response time to humidity. The cheap and robust packaging paper, particularly, exhibits the largest sensitivity over the relative humidity range from 20% to 70%, which offers the possibility of directly printing the sensor tag on traditional packages to make the package intelligent at ultralow cost.

With the development and application of artificial intelligence, there is an appeal to the exploitation of various sensors and memories. As the most important perception of human beings, vision occupies more than 80% of all the received information. Inspired by biological eyes, an artificial retina based on 2D Janus MoSSe was fabricated, which could simulate functions of visual perception with electronic/ion and optical comodulation. Furthermore, inspired by human brain, sensing, memory, and neuromorphic computing functions were integrated on one device for multifunctional intelligent electronics, which was beneficial for scalability and high efficiency. Through the formation of faradic electric double layer (EDL) at the metal-oxide/electrolyte interfaces could realize synaptic weight changes. On the basis of the optoelectronic performances, light adaptation of biological eyes, preprocessing, and recognition of handwritten digits were implemented successfully. This work may provide a strategy for the future integrated sensing-memory-processing device for optoelectronic artificial retina perception application.

Abstract Memory cells have always been an important element of information technology. With emerging technologies like big data and cloud computing, the scale and complexity of data storage has reached an unprecedented peak with a much higher requirement for memory technology. As is well known, better data storage is mostly achieved by miniaturization. However, as the size of the memory device is reduced, a series of problems, such as drain gate‐induced leakage, greatly hinder the performance of memory units. To meet the increasing demands of information technology, novel and high‐performance memory is urgently needed. Fortunately, emerging memory technologies are expected to improve memory performance and drive the information revolution. This review will focus on the progress of several emerging memory technologies, including two‐dimensional material‐based memories, resistance random access memory (RRAM), magnetic random access memory (MRAM), and phase‐change random access memory (PCRAM). Advantages, mechanisms, and applications of these diverse memory technologies will be discussed in this review. image

Atomic layer deposition (ALD) of TiO2 thin films using Ti isopropoxide and tetrakis-dimethyl-amido titanium (TDMAT) as two kinds of Ti precursors and water as another reactant was investigated. TiO2 films with high purity can be grown in a self-limited ALD growth mode by using either Ti isopropoxide or TDMAT as Ti precursors. Different growth behaviors as a function of deposition temperature were observed. A typical growth rate curve-increased growth rate per cycle (GPC) with increasing temperatures was observed for the TiO2 film deposited by Ti isopropoxide and H2O, while surprisingly high GPC was observed at low temperatures for the TiO2 film deposited by TDMAT and H2O. An energetic model was proposed to explain the different growth behaviors with different precursors. Density functional theory (DFT) calculation was made. The GPC in the low temperature region is determined by the reaction energy barrier. From the experimental results and DFT calculation, we found that the intermediate product stability after the ligand exchange is determined by the desorption behavior, which has a huge effect on the width of the ALD process window.

Brain-inspired neuromorphic computing has shown great promise beyond the conventional Boolean logic. Nanoscale electronic synapses, which have stringent demands for integration density, dynamic range, energy consumption, etc., are key computational elements of the brain-inspired neuromorphic system. Ferroelectric tunneling junctions have been shown to be ideal candidates to realize the functions of electronic synapses due to their ultra-low energy consumption and the nature of ferroelectric tunneling. Here, we report a new electronic synapse based on a three-dimensional vertical Hf0.5Zr0.5O2-based ferroelectric tunneling junction that meets the full functions of biological synapses. The fabricated three-dimensional vertical ferroelectric tunneling junction synapse (FTJS) exhibits high integration density and excellent performances, such as analog-like conductance transition under a training scheme, low energy consumption of synaptic weight update (1.8 pJ per spike) and good repeatability (>103 cycles). In addition, the implementation of pattern training in hardware with strong tolerance to input faults and variations is also illustrated in the 3D vertical FTJS array. Furthermore, pattern classification and recognition are achieved, and these results demonstrate that the Hf0.5Zr0.5O2-based FTJS has high potential to be an ideal electronic component for neuromorphic system applications.

Acoustical tweezers based on focalized acoustical vortices hold the promise of precise contactless manipulation of millimeter down to submicrometer particles, microorganisms, and cells with unprecedented combined selectivity and trapping force. Yet, the widespread dissemination of this technology has been hindered by severe limitations of current systems in terms of performance and/or miniaturization and integrability. Here, we unleash the potential of focalized acoustical vortices by developing the first flat, compact, paired single electrode focalized acoustical tweezers. These tweezers rely on spiraling transducers obtained by folding a spherical acoustical vortex on a flat piezoelectric substrate. We demonstrate the ability of these tweezers to grab and displace micrometric objects in a standard microfluidic environment with unique selectivity. The simplicity of this system and its scalability to higher frequencies open tremendous perspectives in microbiology, microrobotics, and microscopy.