Type-printable photodetector arrays for multichannel meta-infrared imaging.

Multichannel meta-imaging, inspired by the parallel-processing capability of neuromorphic computing, offers considerable advancements in resolution enhancement and edge discrimination in imaging systems, extending even into the mid- to far-infrared spectrum. Currently typical multichannel infrared imaging systems consist of separating optical gratings or merging multi-cameras, which require complex circuit design and heavy power consumption, hindering the implementation of advanced human-eye-like imagers. Here, we present printable graphene plasmonic photodetector arrays driven by a ferroelectric superdomain for multichannel meta-infrared imaging with enhanced edge discrimination. The fabricated photodetectors exhibited multiple spectral responses with zero-bias operation by directly rescaling the ferroelectric superdomain instead of reconstructing the separated gratings. We also demonstrated enhanced and faster shape classification (98.1%) and edge detection (98.2%) using our multichannel infrared images compared with single-channel detectors. Our proof-of-concept photodetector arrays simplify multichannel infrared imaging systems and offer potential solutions in efficient edge detection in human-brain-type machine vision.

Tunable mid-infrared photodetector based on graphene plasmons controlled by ferroelectric polarization for micro-spectrometer.

Surface plasmonic detectors have the potential to be key components of miniaturized chip-scale spectrometers. Graphene plasmons, which are highly confined and gate-tunable, are suitable forin situlight detection. However, the tuning of graphene plasmonic photodetectors typically relies on the complex and high operating voltage based on traditional dielectric gating technique, which hinders the goal of miniaturized and low-power consumption spectrometers. In this work, we report a tunable mid-infrared (MIR) photodetector by integrating of patterned graphene with non-volatile ferroelectric polarization. The polarized ferroelectric thin film provides an ultra-high surface electric field, allowing the Fermi energy of the graphene to be manipulated to the desired level, thereby exciting the surface plasmon polaritons effect, which is highly dependent on the free carrier density of the material. By exciting intrinsic graphene plasmons, the light transmittance of graphene is greatly enhanced, which improves the photoelectric conversion efficiency of the device. Additionally, the electric field on the surface of graphene enhanced by the graphene plasmons accelerates the carrier transfer efficiency. Therefore, the responsivity of the device is greatly improved. Our simulations show that the detectors have a tunable resonant spectral response of 9-14µm by reconstructing the ferroelectric domain and exhibit a high responsivity to 5.67 × 105A W-1at room temperature. Furthermore, we also demonstrate the conceptual design of photodetector could be used for MIR micro-spectrometer application.

Chromatic Plasmonic Polarizer-Based Synapse for All-Optical Convolutional Neural Network.

Emerging memory devices have been demonstrated as artificial synapses for neural networks. However, the process of rewriting these synapses is often inefficient, in terms of hardware and energy usage. Herein, we present a novel surface plasmon resonance polarizer-based all-optical synapse for realizing convolutional filters and optical convolutional neural networks. The synaptic device comprises nanoscale crossed gold arrays with varying vertical and horizontal arms that respond strongly to the incident light's polarization angle. The presented synapse in an optical convolutional neural network achieved excellent performance in four different convolutional results for classifying the Modified National Institute of Standards and Technology (MNIST) handwritten digit data set. After training on 1,000 images, the network achieved a classification accuracy of over 98% when tested on a separate set of 10,000 images. This presents a promising approach for designing artificial neural networks with efficient hardware and energy consumption, low cost, and scalable fabrication.

A Suboptimal Optimizing Strategy for Velocity Vector Estimation in Single-Observer Passive Localization.

In a single-observer passive localization system, the velocity and position of the target are estimated simultaneously. However, this can lead to correlated errors and distortion of the estimated value, making independent estimation of the speed and position necessary. In this study, we introduce a novel optimization strategy, suboptimal estimation, for independently estimating the velocity vector in single-observer passive localization. The suboptimal estimation strategy converts the estimation of the velocity vector into a search for the global optimal solution by dynamically weighting multiple optimization criteria from the starting point in the solution space. Simulation verification is conducted using uniform motion and constant acceleration models. The results demonstrate that the proposed method converges faster with higher accuracy and strong robustness.

Reconfigurable, Stretchable Strain Sensor with the Localized Controlling of Substrate Modulus by Two-Phase Liquid Metal Cells.

Strain modulation based on the heterogeneous design of soft substrates is an effective method to improve the sensitivity of stretchable resistive strain sensors. In this study, a novel design for reconfigurable strain modulation in the soft substrate with two-phase liquid cells is proposed. The modulatory strain distribution induced by the reversible phase transition of the liquid metal provides reconfigurable strain sensing capabilities with multiple combinations of operating range and sensitivity. The effectiveness of our strategy is validated by theoretical simulations and experiments on a hybrid carbonous film-based resistive strain sensor. The strain sensor can be gradually switched between a highly sensitive one and a wide-range one by selectively controlling the phases of liquid metal in the cell array with a external heating source. The relative change of sensitivity and operating range reaches a maximum of 59% and 44%, respectively. This reversible heterogeneous design shows great potential to facilitate the fabrication of strain sensors and might play a promising role in the future applications of stretchable strain sensors.

Hybrid strategy of graphene/carbon nanotube hierarchical networks for highly sensitive, flexible wearable strain sensors.

One-dimensional and two-dimensional materials are widely used to compose the conductive network atop soft substrate to form flexible strain sensors for several wearable electronic applications. However, limited contact area and layer misplacement hinder the rapid development of flexible strain sensors based on 1D or 2D materials. To overcome these drawbacks above, we proposed a hybrid strategy by combining 1D carbon nanotubes (CNTs) and 2D graphene nanoplatelets (GNPs), and the developed strain sensor based on CNT-GNP hierarchical networks showed remarkable sensitivity and tenability. The strain sensor can be stretched in excess of 50% of its original length, showing high sensitivity (gauge factor 197 at 10% strain) and tenability (recoverable after 50% strain) due to the enhanced resistive behavior upon stretching. Moreover, the GNP-CNT hybrid thin film shows highly reproducible response for more than 1000 loading cycles, exhibiting long-term durability, which could be attributed to the GNPs conductive networks significantly strengthened by the hybridization with CNTs. Human activities such as finger bending and throat swallowing were monitored by the GNP-CNT thin film strain sensor, indicating that the stretchable sensor could lead to promising applications in wearable devices for human motion monitoring.

Simulation of tuning graphene plasmonic behaviors by ferroelectric domains for self-driven infrared photodetector applications.

We demonstrate a tunable longwave infrared photodetector with ultra-high sensitivity based on graphene surface plasmon polaritons controlled by ferroelectric domains. The simulated results show that the photodetector shows a tunable absorption peak, modulated by periodically polarized ferroelectric domains at the nanoscale, with an ultra-high responsivity up to 7.62 × 106 A W-1 and a detectivity of ∼6.24 × 1013 Jones (Jones = cm Hz1/2 W-1) in the wavelengths ranging from 5 to 20 µm at room temperature. The potential mechanism for the prominent performances of the proposed photodetector can be attributed to the highly confined graphene surface plasmons excited by the local electrical field across the interface of the graphene and ferroelectric layer resonant to the incident wavelength, which could be easily controlled by the features of the ferroelectric domains. Compared with the silicon-based graphene plasmonic photodetector using a complex process of micro-nano fabrication, the proposed photodetector provides the advantages of a more convenient and controllable technique without the need for patterning graphene, and lower energy consumption due to the non-volatile properties of the ferroelectrics without an additional contact electrode. The tunable spectral response and the ultra-high responsivity make the graphene plasmonic photodetector tuned by the ferroelectric domains promising in practical applications of micro-spectrometers and other light sensing devices.

Graphene-based polarization-sensitive longwave infrared photodetector.

We demonstrated a polarization-sensitive photodetector based on periodically crossed graphene ribbons theoretically. Localized surface plasmon is generated by patterned graphene structure with significantly enhanced incident light absorption. Broadband detection is observed from 10.5 to 16.5 µm. Moreover, the photoresponsivity reaches up to 1.717 A W-1 at the wavelength of 12.58 µm under 0° polarization, and the photoresponsivity is 0.212 A W-1 under 90° polarization. The tunability of photodetectors is achieved by changing the gate voltage to modulate the chemical potential of graphene. The finite difference time domain solutions are used to predict the performance of the photodetector with different polarization angles for longwave infrared (LWIR) light. The polarization-sensitive, tunable and broadband graphene photodetector provides a promising direction for high performance LWIR detection at room temperature.

Study of the adsorption of endocrine disruptor compounds on typical filter materials using a quartz crystal microbalance.

Drinking water containing environmental endocrine disruptor compounds (EDCs) endangers human health, and researching the purification process of drinking water for the effective removal of EDCs is vitally important. Filtering plays a crucial role in the bio-adsorption of EDCs, but the adsorption mechanism that occurs between the EDCs and filters remains unclear. In this study, a quartz crystal microbalance (QCM) was employed to elucidate the adsorption mechanism because QCM is a label-free method that possesses high selectivity, high stability, and high sensitivity. The results indicated that a pseudo-first-order kinetic model best fits the adsorption process of four different EDCs, which included bisphenol A (BPA), estrone (E1), estradiol (E2), and sulfamethoxazole (SMZ), on silica (quartz sand), a typical filter material surface. The order of the amount of individual EDCs absorbed on the silica surface was qE2 > qE1 > qSMZ > qBPA and related to their molecular structure, polarity, and chargeability. As the initial EDC concentration increased, the adsorbed amount of the four EDCs on the silica surface increased; however, the initial concentration had little effect on removal efficiency. The calculated Freundlich exponent (1/n) demonstrated SMZ and BPA showed a greater tendency for adsorption than E1 and E2. The mass response time on the surface of the silica gradually increased as the pH increased (from 5.5 to 8.5), indicating the adsorption rate was inhibited by the increase in pH. The addition of electrolytes shortened the mass response time of EDCs on the QCM chip. The pH and ionic strength produced no significant effects on adsorption because hydrophobicity was the primary contributor to adsorption. This study facilitated a better understanding of the interaction between EDCs and filters in water treatment.

Ultra-sensitive and plasmon-tunable graphene photodetectors for micro-spectrometry.

We demonstrate an ultra-sensitive photodetector based on a graphene/monolayer MoS2 vertical heterostructure working at room temperature. Highly confined plasmon waves are efficiently excited through a periodic array of monolayer graphene ribbons in which plasmon resonance has remarkably large oscillator strength, resulting in a sharp optical absorption peak in the normal-incidence transmission spectrum. A significant amount of electron-hole pairs are produced in graphene ribbons by optical absorption, separated by the built-in electric field across the graphene/MoS2 heterojunction. The responsivity reaches up to 1 × 107 A W-1 at room temperature due to very strong resonance in the heterostructure, yielding a highly sensitive graphene-based photodetector. Additionally, the absorption can be tuned over a wide spectral range (6-16 µm) by varying gate biasing. The ultra-sensitive, spectrally tunable photodetector could be potentially used as a promising candidate for mid-infrared micro-spectrometers.

Ultra-Sensitive Strain Sensor Based on Flexible Poly(vinylidene fluoride) Piezoelectric Film.

A flexible 4 × 4 sensor array with 16 micro-scale capacitive units has been demonstrated based on flexible piezoelectric poly(vinylidene fluoride) (PVDF) film. The piezoelectricity and surface morphology of the PVDF were examined by optical imaging and piezoresponse force microscopy (PFM). The PFM shows phase contrast, indicating clear interface between the PVDF and electrode. The electro-mechanical properties show that the sensor exhibits excellent output response and an ultra-high signal-to-noise ratio. The output voltage and the applied pressure possess linear relationship with a slope of 12 mV/kPa. The hold-and-release output characteristics recover in less than 2.5 µs, demonstrating outstanding electro-mechanical response. Additionally, signal interference between the adjacent arrays has been investigated via theoretical simulation. The results show the interference reduces with decreasing pressure at a rate of 0.028 mV/kPa, highly scalable with electrode size and becoming insignificant for pressure level under 178 kPa.

[Clinical observation on fire needles at bones combined with cupping and Tuina for knee osteoarthritistis].

OBJECTIVE: To explore a better therapy for knee osteoarthritis. METHODS: One hundred cases were randomly divided into a comprehensive group and an acupuncture group, 50 cases in each one. The comprehensive treatment of fire needles at bones combined with cupping and Tuina on local area of affected knee was applied in the comprehensive group. The Ashi points were mainly selected in the fire needles at bones therapy, once every other day. The cupping and Tuina therapy was adopted once a day. The conventional acupuncture was applied in the acupuncture group, in which Dubi (ST 35), Neixiyan (EX-LE 4), Xuehai (SP 10), Liangqiu (ST 34) and so on were selected, once a day. Ten days of treatment were taken as a treatment course in both two groups, and totally 1 to 2 courses was required. The pain score of joint before and after the treatment was observed and efficacy was assessed in two groups. RESULTS: Compared before the treatment, the pain score of joint after the treatment was obviously improved in two groups (both P<0.05), and the score in the comprehensive group was lower than that in the acupuncture group (P<0.05). The clinical cured rate was 38.0% (19/50), which was superior to 20.0% (10/50) in the acupuncture group. CONCLUSION: The comprehensive treatment of fire needles at bones combined with cupping and Tuina, considered as a better therapy for knee osteoarthritis, could improve joint pain, swelling and action function, which is superior to the conventional acupuncture.