Carbon nitrides have attracted growing attention as the metal-free semiconductor photocatalysts with various advantages, but still suffering from the limited efficiency due to a quick recombination of photogenerated carriers and a scarcity of reactive sites. Here, we developed a templated synthetic method to construct Pd-doped carbon nitride Schottky junctions using a two-dimensional (2D) supramolecular polymer and well-dispersed palladium acetate as the precursors. After the self-assembling, heating, and calcination processes, the Pd(0) atoms and their nanoparticles (Pd(0)NPs) are inserted or doped in the porous graphitic carbon nitride (g-C3N4) nanosheets to produce g-C3N4/Pdx heterojunctions. It is revealed that compositions, microstructure, and photocatalytic H2 evolution rates of the g-C3N4/Pdx heterojunctions can be regulated by the amount of palladium acetate added in the template of 2D polymers. The most efficient g-C3N4/Pd1.2 Schottky junction gives a H2 evolution rate of 468 mu mol g-1 h-1; nearly 40 times higher as compared to that of the corresponding g-C3N4 nanosheets. Investigations on the structure and mechanism reveal that the porous design and Schottky junctions enhance significantly the light utilization and build-in electric field between Pd(0)NPs and g-C3N4 nanosheets, thus resulting in an enhanced separation and transfer efficiency of the photogenerated charge carriers.

Photocatalytic hydrogen evolution with the use of semiconductors as the light-harvesting units is an attractive route for the clean and renewable energy development. Here, we report interfacial self-assembly of Pd(II)directed multiporphyrin arrays sensitized oxidized graphitic carbon nitride (O-g-C3N4) nanocomposites and their Langmuir-Blodgett (LB) films. The nanocomposites and LB films can act as both the light-harvesting unit and catalyst for the hydrogen evolution under irradiation. Monolayer behaviors and spectroscopic features indicate that EDTA and polyacrylic acid (PAA) in the subphases can stabilize the monolayer stability and facilitate the LB film deposition, attributed to the hydrogen bonding between EDTA/PAA and tetraaminoporphyrin (TAPP). The multiporphyrin arrays-sensitized O-g-C3N4@(Pd-TAPP)3 nanocomposites display improved hydrogen evolution efficiency, because of the expanded light absorption region as well as enhanced separation and transport efficiency of the photoinduced charge carriers. Particularly, when the LB films of O-g-C3N4@(PdTAPP)3-EDTA or -PAA are used as the light-harvesting unit and catalyst, the hydrogen evolution rate is about 5-10 times higher than that of the solid powders of similar nanocomposites. Mechanism investigation suggest that EDTA and PAA can not only improve the monolayers and LB films' stability, but also act as the bridged species between the carbon nitride, multiporphyrin arrays and electron donors, hence enhanced charged transfer and hydrogen evolution efficiency.

Abstract We propose a scheme to tailor emission spectra through the engineering of the local density of states by using core-shell nanostructures. A random forest algorithm is used to train a forward model for spectrum prediction and an inverse model for the construction of core-shell nanostructures. From the simulation results, it can be seen that we can predict the spectra very well and achieve good effects for tailoring the emission spectra with core-shell nanostructures based on the established models, eliminating the time-consuming and laborious design process with manual intervention.

Real-time sweat monitoring is vital for athletes in order to reflect their physical conditions, quantify their exercise loads, and evaluate their training results. Therefore, a multi-modal sweat sensing system with a patch-relay-host topology was developed, which consisted of a wireless sensor patch, a wireless data relay, and a host controller. The wireless sensor patch can monitor the lactate, glucose, K+, and Na+ concentrations in real-time. The data is forwarded via a wireless data relay through Near Field Communication (NFC) and Bluetooth Low Energy (BLE) technology and it is finally available on the host controller. Meanwhile, existing enzyme sensors in sweat-based wearable sports monitoring systems have limited sensitivities. To improve their sensitivities, this paper proposes a dual enzyme sensing optimization strategy and demonstrates Laser-Induced Graphene (LIG)-based sweat sensors decorated with Single-Walled Carbon Nanotubes (SWCNT). Manufacturing an entire LIG array takes less than one minute and costs about 0.11 yuan in materials, making it suitable for mass production. The in vitro test result showed sensitivities of 0.53 μA/mM and 3.9 μA/mM for lactate and glucose sensing, and 32.5 mV/decade and 33.2 mV/decade for K+ and Na+ sensing, respectively. To demonstrate the ability to characterize personal physical fitness, an ex vivo sweat analysis test was also performed. Overall, the high-sensitivity lactate enzyme sensor based on SWCNT/LIG can meet the requirements of sweat-based wearable sports monitoring systems.

We propose a scheme to modify spontaneous emission spectra with split rings. We consider the heterogeneous environment around the dipole and the dipole as a whole to comprehensively explore the impact of the parameters of the system on the partial local density of state. And we achieve the customization of spontaneous emission spectra by engineering the partial local density of state with the co-design of split rings and dipoles for different applications. The finite-difference time-domain numerical results show that our approach is in line with theoretical expectations.

Modulation mode recognition of radio signal is a committed step between signal detection and signal demodulation. At present, quite a lot studies have fully proved that deep learning algorithms can effectively identify the modulation pattern of radio signals. However, the sudden decline of recognition accuracy under the condition of low signal-to-noise ratio needs to be continuously studied and solved. Inspired by the excellent performance of recurrent neural network in signal recognition, this article optimizes and improves the existing system methods, realizes the noise reduction processing of low signal-to-noise ratio signals, and further solves the problem of low recognition accuracy. Through a large number of experimental tests using RML public dataset, the effectiveness of this paper is verified. The results show that the accuracy of modulation pattern recognition of low signal-to-noise ratio signals reaches an average of 27.2%. At last, the paper analyzes the existing problems and optimization points, and looks forward to the further research of relevant contents in the future.

We propose a method to use deep learning to achieve transmittance prediction and inverse design of microring resonator channel dropping filters. We transform the transmittance prediction and inverse design into model training problems, which learn and approximate the intrinsic interactions from the geometric parameter space to transmittance space and the transmittance space to geometric parameter space. The test loss and mean square error for the transmittance prediction case are 3.94888×10−2 and 4.68901×10−3, respectively; the test loss and mean square error for the inverse design case are 7.27015×10−3 and 4.0029×10−4, respectively. The numerical results suggest that the models developed by deep learning can make an efficient prediction of the transmittance and achieve excellent performance of the inverse design for microring resonator channel dropping filters, validating the effectiveness and feasibility of the approach we propose. With generalization ability within the given design space, the well-trained models can produce fast and accurate results without the need for time-consuming numerical calculations or case-by-case design.

In recent years, the application of traceability systems in the food and drug industry has developed rapidly, but it is rarely used for wind turbines. From the aspects of low information transparency and information islands in the supply chain process for wind turbines, a reliable traceability system is essential. However, the existing traceability systems are not suitable to be directly applied to wind turbines. Consequently, according to the characteristics of the wind power industry, a semi-centralized traceability architecture based on Internet of Things technology was proposed. Furthermore, a traceability platform was constructed by analyzing the information collected in each stage related to various user needs of wind turbines, and various applications, including manufacturing management and spare parts management, were developed. Compared with the existing systems, the proposed platform was wind-turbine-oriented, effectively improved traceability efficiency and enterprises’ information security, and extended the length of the traceability chain by integrating the after-sales information. The traceability of key components of wind turbines during their life cycle provides a useful reference for further improving the parts quality management system of the wind power industry.

Life cycle assessment (LCA) is conducive to the change in the wind power industry management model and is beneficial to the green design of products. Nowadays, none of the LCA systems are for wind turbines and the concept of Internet of Things (IoT) in LCA is quite a new idea. In this paper, a four-layer LCA platform of wind turbines based on IoT architecture is designed and discussed. In the data transmission layer, intelligent sensing of wind turbines can be achieved and their status and location can be monitored. In the data transmission layer, the LCA platform can be effectively integrated with enterprise information systems through the object name service (ONS) and directory service (DS). In the platform layer, a model based on IMPACT 2002+ is developed, and four management modules are designed. In the application layer, different from other systems, energy payback time (EPBT) is selected as an important evaluation index for wind turbines. Compared with the existing LCA systems, the proposed system is specifically for wind turbines and can collect data in real-time, leading to improved accuracy and response time.

We present an approach to modify emission spectra of amplifiers by local density of states engineering with structured waveguides. More specifically, an inverse design algorithm is adopted to obtain the geometric parameters of the proposed structure that meets the local density of states target. The finite-difference time-domain numerical results indicate that the 3 dB bandwidth and the figure of merit on flatness in the structure we propose grow by over 22% and 32%, respectively, compared with the values of the typical reference baseline.

Photoinduced space-charges in organic optoelectronic devices, which are usually caused by poor mobility and charge injection imbalance, always limit the device performance. Here we demonstrate that photoinduced space-charge layers, accumulated at organic semiconductor-insulator interfaces, can also play a role for photocurrent generation. Photocurrent transients from organic devices, with insulator-semiconductor interfaces, were systematically studied by using the double-layer model with an equivalent circuit. Results indicated that the electric fields in photoinduced space-charge layers can be utilized for charge generation and can even induce a photovoltage reversal. Such an operational process of light harvesting would be promising for photoelectric conversion in organic devices.

Most viscosity sensors, which are important in the health, automotive and food production industries, are currently based on mechanical or optical approaches. They are not compatible with emerging flexible and wearable electronics consisting of various lightweight integrated sensors with more compact architecture and lower cost. Here we demonstrate an organic device for sensing the viscosity of nonelectrolyte aqueous solutions which can work at low viscosities (0.9-10 mPa.s). The photoconductivity of devices involving semiconductor/water interfaces was found to obey Walden's rule, suggesting that viscosity could be measured by electrical means. This may be a promising approach for the design of viscosity sensors for portable and wearable applications.

The spectral optimization for maximizing limited luminous efficacy (LLE) of correlated color temperature (CCT) tunable white light-emitting diodes (LEDs) with two, three and four color perovskite quantum dots (QDs) excited by a blue chip was investigated under the constraint of designated ultrahigh color rendering index (CRI) and color quality scale (CQS). The results show that high quality white lights with CRIs of 96-97, CQSs of 95-96, and LLEs of 243-225 lm/W at CCTs of 2700 K to 6500 K could be realized by the QDs-converted white LEDs (QD-WLEDs) using a blue chip and different combinations of perovskite quantum dots. The luminous efficacies of QD-WLEDs are expected to reach 114 to 122 lm/W at CCTs of 2700 K to 6500 K, if the radiant efficiency of a blue chip is 60% and the real PLQY values of perovskite QDs are 75%. These results demonstrate that perovskite QD-based LEDs are expected to be promising in next generation display and lighting technologies. (C) 2017 Optical Society of America

A mobile-based high sensitivity absorptiometer is presented to detect organophosphorus (OP) compounds for Internet-of-Things based food safety tracking. This instrument consists of a customized sensor front-end chip, LED-based light source, low power wireless link, and coin battery, along with a sample holder packaged in a recycled format. The sensor front-end integrates optical sensor, capacitive transimpedance amplifier, and a folded-reference pulse width modulator in a single chip fabricated in a 0.18  μ m 1-poly 5-metal CMOS process and has input optical power dynamic range of 71 dB, sensitivity of 3.6 nW/cm 2 (0.77 pA), and power consumption of 14.5  μ W. Enabled by this high sensitivity sensor front-end chip, the proposed absorptiometer has a small size of 96 cm 3 , with features including on-field detection and wireless communication with a mobile. OP compound detection experiments of the handheld system demonstrate a limit of detection (LOD) of 0.4  μ mol/L, comparable to that of a commercial spectrophotometer. Meanwhile, an android-based application (APP) is presented which makes the absorptiometer access to the Internet-of-Things (IoT).

Inverse gas chromatography (IGC) was employed in evaluating the catalytic surface of meso-microporous KIT-6 impregnated Ni (0.5-2.0 wt%) in methane dry reforming reaction. The free energy of adsorption did not changed significantly for the sample modified with highly dispersed Ni species (0.5 we). At higher Ni loadings, higher free energy of adsorption and enthalpy of adsorption of the probes were observed, together with high dispersive interaction and specific interaction of aromatics. The results indicated that during the impregnation, Ni species preferably penetrated into the microporous region to form Ni particles and became 'unaccessible'. This feature was used to understand the dependence of activity on Ni loading for the gas phase catalytic methane reforming with carbon dioxide on Ni/KIT-6. The lower TOF at low metal loadings was attributed to Ni particles located in the micropores which result in diffusional constraint of reactants and products. (C) 2016 Elsevier Inc. All rights reserved.

Objective To evaluate the effect of multiple intervention measures on perioperative antimicrobial use in pa-tients undergoing typeⅠincision operation in a hospital,and provide basis for rational use of antimicrobial agents. Methods 9 823 patients with type I incision operation in April and October of 2005-2012 were surveyed retrospectively, data of 2005 was as baseline,from 2006 to 2012,multiple measures,including training,examination,supervision,feed-back,and cooperation of relevant departments were conducted,antimicrobial use before and after intervention was com-pared.Results The qualified rate of perioperative antimicrobial use in patients undergoing typeⅠ incision operation in-creased from 14.20% in 2006 to 92.30% in 2012;the rate of combined use of antimicrobial agents was relatively higher (7.00%-9.00%)in 2006-2009,had a downward trend in 2010- 2012,and decreased to 3.20% in 2012.Types of an-timicrobial agents for prophylactic use in typeⅠincision operation in 2006 and 2007 were similar to that of 2005,the main used antimicrobial agents were cephalosporins,penicillin and it’s compounds,and aminoglycosides;the major antimicrobial prophylaxis in 2008-2012 were the first and second generation cephalosporins,penicillin and it’s compounds.Multivariate non-conditional logistic regression analysis showed that age (40 - 59 years old),departments (orthopedics,general surgery,and ophthalmology),and years (2011 and 2012)were the main influencing factors for the qualified use of antimicrobial agents(all P<0.05).Conclusion Implementation of multiple intervention measures can improve the qualified rate of perioperative antimicrobial use in typeⅠ incision operation,reduce types of antimicrobial use and rate of combined antimicrobial use.

In situ growth of ZnO layer on the surface of carbon dots was realized via a two-step method, which resulted in an enhancement of the broad visible emission with a high quantum yield. Influence of the refluxing time, the temperature and the oleylamine/octadecene ratio was investigated to address the key factors on the preparation of the carbon dots. Under the optimal conditions, the carbon dots with an average diameter of 3.4 +/- 0.4 nm and a photoluminescence quantum yield of 29.3% were achieved. Remarkable improvements of photoluminescence were achieved by the hybridization of the ZnO layer, which can eliminate the surface-trap from the C cores and form the new centers of emission. The synergistic effect arising from the C/ZnO hybridized structure obviously broadened the visible emission and enhanced their photoluminescence quantum yield from 29.3% to 47.3%. The as-prepared highly emissive quantum dots exhibited a broad and stable emission with the Commission Internationaled 'E' clairage chromaticity coordinate of (0.23, 0.34), which could offer a promising solution for the future-generation white light emitting diodes. (C) 2015 Elsevier B.V. All rights reserved.

Synthesis of bright white-light emitting Mn and Cu co-doped ZnSe/ZnS core/shell quantum dots (QDs) (Cu,Mn:ZnSe/ZnS) was reported. Water-soluble ZnSe-based QDs with Mn and Cu doping were prepared using a versatile hot-injection method in aqueous solution with a microwave-assisted approach. Influence of the Se/S ratio, stabilizer, refluxing time and the concentration of Cu/Mn dopant ions on the particle size and photoluminescence (PL) were investigated. The as-prepared QDs in the different stages of growth were characterized by X-ray powder diffractometer (XRD), high-resolution transmission electron microscopy (HRTEM), UV-visible (UV-vis) spectrophotometer, and fluorescence spectrophotometer. It is found that these ZnSe-based QDs synthesized under mild conditions exhibit emission in the range of 390-585 nm. The PL quantum yield (QY) of the as-prepared water-soluble ZnSe QDs can be up to 24.3% after the UV-irradiation treatment. The band-gap emission of ZnSe is effectively restrained through Mn and Cu doping. The refluxing time influences the doping of not only Mn, but also Cu, which leads to the best refluxing time of Mn:ZnSe and the red-shift of the emission of Cu:ZnSe d-dots. Co-doping induced white-light emission (WLE) from Cu,Mn:ZnSe/ZnS core/shell QDs were obtained, which can offer the opportunity for future-generation white-light emitting diodes (LEDs). (C) 2015 Elsevier B.V. All rights reserved.