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The poor conductivity and deficient active sites of transition metal oxides lead to low energy density of supercapacitors, which limits their wide application. In this work, double transition metal oxide heterojunctions with oxygen vacancy (Vo-ZnO/CoO) nanowires are prepared by effective hydrothermal and thermal treatments. The formation of the heterojunction results in the redistribution of interface charge between ZnO and CoO, generating an internal electric field to accelerate the electron transport. Meanwhile, oxygen vacancies can enhance the redox reaction activity to further improve the electrochemical kinetics of the electrode material. Therefore, the prepared Vo-ZnO/CoO can provide a superior specific capacity of 845 C g−1 (1 A g−1). An asymmetric supercapacitor with the Vo-ZnO/CoO as positive electrode shows a higher energy density of 51.6 Wh kg−1 when the power density reaches 799.9 W kg−1. This work proposes a synergistic combination of defect and heterojunction engineering to improve the electrochemical properties of materials, providing an important guidance for material design in energy-storage field.

In this paper, a computationally efficient multifidelity local search algorithm for aerodynamic design optimization is presented. In this paper’s approach, direct optimization of a computationally ...

Background: Distant metastasis is the major cause of treatment failure in locally advanced rectal cancer (LARC). Adjuvant chemotherapy (AC) is usually used for distant control. However, only certain subgroups of patients could benefit from AC. Our aim was to develop a radiomics model for the prediction of survival and chemotherapeutic benefits using pretreatment multiparameter MR images and clinicopathological features in patients with LARC. Methods: 186 consecutive patients with LARC underwent feature extraction from the whole tumor on T2-weighted (T2w), contrast enhanced T1-weighted (cT1w), and ADC images. Feature selection was based on feature stability and the Boruta algorithm. Radiomics signatures for predicting DFS (disease-free survival) were then generated using the selected features. Combining clinical risk factors, a radiomics nomogram was constructed using Cox proportional hazards regression model. The predictive performance was evaluated by Harrell's concordance indices (C-index) and time-independent receiver operating characteristic (ROC) analysis. Results: Four features were selected to construct the radiomics signature, which was significantly associated with DFS (P < 0.001). The radiomics nomogram, incorporating radiomics signature and two clinicopathological variables (pN and tumor differentiation), exhibited better prediction performance for DFS than the clinicopathological model, with C-index of 0.780 (95%CI, 0.718-0.843) and 0.803 (95%CI, 0.717-0.889) in the training and validation cohorts, respectively. The radiomics nomogram-defined high-risk group had a shorter DFS, DMFS, and OS than those in the low-risk group (all P Conclusion: This study demonstrated that the newly developed pretreatment multiparameter MRI-based radiomics model could serve as a powerful predictor of prognosis, and may act as a potential indicator for guiding AC in patients with LARC.

For structures with both random and fuzzy uncertainty, this paper presents a novel method for determining the membership function in fuzzy reliability with the Automatic Updating Extreme Response Surface (AUERS) method. In the proposed method, fuzzy variables are initially converted into a value domain under the given cut level and the extreme point in the domain where the reliability reaches its extreme value is considered. Second, the Particle Swarm Optimization (PSO) algorithm is used to determine the extreme point according to the extreme responses for different sets of random sample inputs. A kriging response surface is subsequently constructed between the random variables and the corresponding extreme points. An automatic updating strategy is then introduced based on the Relative Mean Square Predicted Error (RMSPE) before performing every iteration of reliability analysis. By adding new sample points, the approximate quality of the kriging response surface is improved. Finally, reliability analysis is used to determine the reliability bound under the given cut level. The proposed method assures the accuracy and computation efficiency of the mixed uncertainty reliability analysis results while it prevents the solution from becoming trapped in a local optimum, which occurs in classical optimization methods. Two example analyses are used to demonstrate the validity and advantages of the proposed method.

Excessive or burst production of reactive oxygen species (ROS) brings oxidative stress that leads to various vital diseases such as cancers, Parkinson’s disease and Ischemia-reperfusion damage, etc. However, traditional biological analysis of ROS based on separate procedure of capturing, labelling, and spectrometrically detecting is complicated and time-consuming, the accuracy of which was severely affected by the short lifespan (microseconds to milliseconds) of ROS, and thus, a fast and effective approach that allows for a real-time detection is highly desired. In this work, we have developed a printable CeO2 − x-CNTs-nanocomposite-based paste and fabricated an integrated flexible ROS sensor (IFRS) by directly printing the paste on a flexible polyethylene terephthalate (PET) substrate as both working electrode and sensing material. This IFRS device demonstrated the fast and real-time response to the hydrogen dioxide in lab as well as to total ROS in sweat of an adult, showing excellent current response to hydrogen oxide in the wide range of 0.01 to 10 mM with a limit of detection (LOD) reaching 1.85 µM. The superior sensitivity of the device to hydrogen oxide was found to be 136.59 \(\text{μA∙}{\text{mM}}^{\text{-1}}\text{∙}{\text{cm}}^{\text{-2}}\), 1.5 to 10 times higher than previously reported sensors. This IFRS device distinguished the instant ROS in the sweat of adult men in vitro, with amperometric response increased 8 times after half an hour strenuous exercise, exhibiting good selectivity and excellent stability together with confirmed high biosafety. Overall, our designed IFRS provides an applicable and translational feasibility toward the simple, rapid and real-time detection of ROS in the near future.

Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued developments in deep learning. We review the applications of ML in ASO to date and provide a perspective on the state-of-the-art and future directions. We first introduce conventional ASO and current challenges. Next, we introduce ML fundamentals and detail ML algorithms that have been successful in ASO. Then, we review ML applications to ASO addressing three aspects: compact geometric design space, fast aerodynamic analysis, and efficient optimization architecture. In addition to providing a comprehensive summary of the research, we comment on the practicality and effectiveness of the developed methods. We show how cutting-edge ML approaches can benefit ASO and address challenging demands, such as interactive design optimization. Practical large-scale design optimizations remain a challenge because of the high cost of ML training. Further research on coupling ML model construction with prior experience and knowledge, such as physics-informed ML, is recommended to solve large-scale ASO problems., 103 pages, 47 figures, published by Progress in Aerospace Sciences

We propose a scalable framework for the learning of high-dimensional parametric maps via adaptively constructed residual network (ResNet) maps between reduced bases of the inputs and outputs. When just few training data are available, it is beneficial to have a compact parametrization in order to ameliorate the ill-posedness of the neural network training problem. By linearly restricting high-dimensional maps to informed reduced bases of the inputs, one can compress high-dimensional maps in a constructive way that can be used to detect appropriate basis ranks, equipped with rigorous error estimates. A scalable neural network learning framework is thus to learn the nonlinear compressed reduced basis mapping. Unlike the reduced basis construction, however, neural network constructions are not guaranteed to reduce errors by adding representation power, making it difficult to achieve good practical performance. Inspired by recent approximation theory that connects ResNets to sequential minimizing flows, we present an adaptive ResNet construction algorithm. This algorithm allows for depth-wise enrichment of the neural network approximation, in a manner that can achieve good practical performance by first training a shallow network and then adapting. We prove universal approximation of the associated neural network class for $L^2_\nu$ functions on compact sets. Our overall framework allows for constructive means to detect appropriate breadth and depth, and related compact parametrizations of neural networks, significantly reducing the need for architectural hyperparameter tuning. Numerical experiments for parametric PDE problems and a 3D CFD wing design optimization parametric map demonstrate that the proposed methodology can achieve remarkably high accuracy for limited training data, and outperformed other neural network strategies we compared against.

A fast and simple method using co-grinding with Fe powder followed by heat treatment is developed to regulate surface oxygen vacancy content of ZnO nanoparticles. The moderately increased surface oxygen vacancy is conducive to shortening the adsorption and desorption times of NO2 molecules, arising from the enhanced O2 adsorption. Therefore, the response and recovery speeds of ZnO nanoparticle-based sensor under UV irradiation were significantly promoted. Our findings not only offer a feasible strategy to modulate surface oxygen vacancy content of nanostructured oxides, but also provide a novel approach to improve the response and recovery speeds of light-activated NO2 sensor.

Biofouling has been a long-last problem in a variety of marine systems which causes energy waste and device damage. In this study, we present a self-activated anti-biofouling system enabled by electrical double layer disturbance, which could effectively suppress the initial formation of conditioning layers and subsequent microbe attachment. The small and low-frequency alternating electrical fields were produced by a triboelectric nanogenerator under water wave impacts. Systematic analyses confirmed that the anti-biofouling efficacy was directly related to the strength of the electric field and was effective in both fresh lake and sea water environments. An on-site demonstration was implemented at a calm lake shore for three weeks. The water wave-driven anti-biofouling exhibited excellent surface protection, which was significantly superior to several commercial anti-biofouling coatings. This development brings a novel, effective and eco-friendly solution for protecting a broad range of surfaces against biofouling.

Aerodynamic inverse design is proposed using multifidelity models and the manifold mapping (MM) technique. Aerodynamic inverse design aims at achieving a target performance characteristic, such as a pressure coefficient distribution of an airfoil or local lift distribution of a wing. Due to the high computational cost of accurate aerodynamic models and the large number of design variables, the overall cost of inverse design can be prohibitive. The MM-based optimization algorithm leverages the speed of the low-fidelity model to accelerate the optimization process, but refers back to the high-fidelity model to ensure an accurate solution. In this work, the MM technique is applied to the characteristic distribution under consideration in each application. In particular, the pressure coefficient distribution is modeled with the MM technique in the case of airfoil inverse design, and the sectional lift distribution in the case of wing design. The proposed method is tested and evaluated on six airfoil inverse design cases and one rectangular wing inverse design case. In the two-dimensional cases, parameterized with eight design variables, direct aerodynamic inverse design using pattern search required 700 to 1200 high-fidelity model evaluations, which took 300 to 700 hours in total. The MM-based design algorithm required less than 20 high-fidelity simulations and 1000 to 2000 low-fidelity evaluations, which took 30 to 90 hours. In the three-dimensional case, parameterized with three design variables, direct aerodynamic inverse design took around 50 hours, whereas the MM-based design needed around six hours.

Aerodynamic optimization based on computational fluid dynamics (CFD) is a powerful design approach because it significantly reduces the design time compared with the human manual design. However, CFD-based optimization can still take hours to converge because it requires repeatedly running computationally expensive flow simulations. To further shorten the design optimization time, we propose a fast, interactive design framework that allows us to complete an airfoil aerodynamic optimization within a few seconds. This framework is made efficient through a B-spline-based generative adversarial network model for shape parameterization, which filters out unrealistic airfoils for a reduced design space that contains all relevant airfoil shapes. Moreover, we use a combination of multilayer perceptron, recurrent neural networks, and mixture of experts for surrogate modeling to enable both scalar (drag and lift) and vector (pressure distribution) response predictions for a wide range of Mach numbers (0.3 to 0.7) and Reynolds numbers (104 to 1010). To verify our proposed framework, we compare the optimization results with the ones computed by direct CFD-based optimization for subsonic and transonic conditions. The results show that the optimal designs and the aerodynamic quantities (lift, drag, and pressure distribution) obtained by our proposed framework agree well with the ones computed by direct CFD-based optimizations and evaluations. The proposed framework is being integrated into a web-based interactive aerodynamic design framework that allows users to predict drag, lift, moment, pressure distribution, and optimal airfoil shapes for a wide range of flow conditions within seconds.

Fast and accurate airfoil design under uncertainty using non-intrusive polynomial chaos (NIPC) expansions and utility functions is proposed. The NIPC expansions provide a means to efficiently and accurately compute statistical information for a given set of input variables with associated probability distribution. Utility functions provide a way to rigorously formulate the design problem. In this work, these two methods are integrated for the design of airfoil shapes under uncertainty. The proposed approach is illustrated on a numerical example of lift-constrained airfoil drag minimization in transonic viscous flow using the Mach number as an uncertain variable. The results show that compared with the standard problem formulation the proposed approach yields more robust designs. In other words, the designs obtained by the proposed approach are less sensitive to variations in the uncertain variables than those obtained with the standard problem formulation.

This work presents the investigation of reduced graphene oxide (RGO) as a new type of stationary phase for gas chromatographic separation on a microcolumn which is fabricated on a silicon wafer by the application of microelectromechanical system (MEMS) techniques. A ZnO film synthesized by a sol–gel method is utilized as a supporting material between RGO and the column wall for inwall roughening to form a stable RGO stationary phase and increase gas-stationary phase interaction. The RGO/ZnO grafted on the column wall was characterized by SEM and FT-IR spectra. The experimental results demonstrate that good separations for mixtures of a wide range of organic compounds including alkanes and esters are achieved by the microcolumn coated with bilayer film. And the maximum column efficiency of 11 363 theoretical plates per meter for n-dodecane is obtained, which is higher than any previously reported values for chromatography columns coated with graphene and their analogs to the best of our knowledge. However, the RGO stationary phase shows obvious peak tailings for polar alcohols, which mainly originate from its specific π–π stacking interaction as well as the hydrophobic effect between analytes and the π-electron on the high surface area of reduced graphene oxide. This work greatly favors RGO coated chip columns for gas chromatographic separation in achieving micro-total analytical systems.

In this paper, we discuss a computationally efficient approach to expedite design optimization of broadband hybrid couplers occupying a minimized substrate area. Structure size reduction is achieved here by decomposing an original coupler circuit into low- and high-impedance components and replacing them with electrically equivalent slow-wave lines with reduced physical dimensions. The main challenge is reliable design of computationally demanding low-impedance slow-wave structures that feature a quasi-periodic circuit topology for wideband operation. Our goal is to determine an adequate number of recurrent unit elements as well as to adjust their designable parameters so that the coupler footprint area is minimal. The proposed method involves using surrogate-based optimization with a reconfigurable co-simulation coarse model as the key component enabling design process acceleration. The latter model is composed in Keysight ADS circuit simulator from multiple EM-evaluated data blocks of the slow-wave unit element and theory-based feeding line models. The embedded optimization algorithm is a trust-region-based gradient search with coarse model Jacobian estimation. We exploit a penalty function approach to ensure that the electrical conditions for the slow-wave lines are accordingly satisfied, apart from explicitly minimizing the area of the coupler. The effectiveness of the proposed technique is demonstrated through a design example of two-section 3-dB branch-line coupler. For the given example, we obtain nine circuit design solutions that correspond to the compact couplers whose multi-element slow-wave lines are composed of unit cells ranging from two to ten.

A deterministic technique for fast surrogate-assisted multi-objective design optimization of antennas in highly-dimensional parameters spaces has been discussed. In this two-stage approach, the initial approximation of the Pareto set representing the best compromise between conflicting objectives is obtained using a bisection algorithm which finds new Pareto-optimal designs by dividing the line segments interconnecting previously found optimal points, and executing poll-type search that involves Pareto ranking. The initial Pareto front is generated at the level of the coarsely-discretized EM model of the antenna. In the second stage of the algorithm, the high-fidelity Pareto designs are obtained through optimization of corrected local-approximation models. The considered optimization method is verified using a 17-variable uniplanar antenna operating in ultra-wideband frequency range. The method is compared to three state-of-the-art surrogate-assisted multi-objective optimization algorithms.

An reduced graphene oxide (RGO) resistive gas sensor was prepared to detect ammonia at room temperature, the result indicated that the desorption of gas (NH 3 ) molecules from a graphene-based sensor was difficult, which lead to a baseline drift. The responses of different concentrations were compared and studied. It was found that both the response rate and its acceleration were affected by the gas concentration. An Intermolecular Forces Based Model was established to explain the adsorption and desorption dynamic response curves. A new method was proposed based on this model. The first and second derivative extrema (FSDE) of the response curve can be attained quickly to calibrate the gas concentrations. The experiment results demonstrated that this new method could eliminate the baseline drift and was capable of increasing the efficiency of gas calibration significantly.

Polyvinylidene fluoride (PVDF) films possess multifunctional ability for piezo/pyro/ferroelectronic applications. One critical challenge of the traditional techniques is the complicated fabrication process for obtaining the poled films. In this work, the PVDF film is facilely prepared by the solution cast on hydrophilically treated substrates. The obtained PVDF films exhibit fairly good pyroelectricity comparable to those fabricated by thermal poling, indicating the film is self-polarized. This result is attributed to the hydrogen-bonding-induced orderly arrangement of the first sub-nanolayer at the bottom, which serves as a “seed layer” and triggered alignment of the rest of the film in a layer-by-layer approach. Additionally, to suppress the piezoelectric noise, a pyroelectric sensor with a novel bilayer structure is developed using the as-prepared PVDF film. Compared with the conventional monolayer sensor, the signal-to-noise ratio of the bilayer one is drastically improved to 38 dB from 18 dB. The above results provide great possibilities for achieving a high-performance wearable pyroelectric sensor with reduced cost and simple procedures. Electronic supplementary material The online version of this article (10.1186/s11671-019-2906-1) contains supplementary material, which is available to authorized users.

Introduction Human respiration is rich in physiological and pathological information as biomarker for health assessment and illness prediction. Respiratory diagnosis method carries various advantages, such as continuity, non-invasiveness, comfort and user-friendly [6]. Typically, ammonia (NH3) in exhaled breath can be served as biomarker for some diseases like end-stage renal disease (ESRD), ulcers caused by Helicobacter pylori or bacterial in oral cavity [12-15]. NH3 concentration in healthy people’ exhaled breath is about 0.425-1.8 ppm (mean 0.96 ppm), while the one in ESRD patients’ breathing ranges from 0.82 to14.7 ppm (mean 4.88 ppm) [12]. Even though various traditional sensors have been applied to monitor human physiological information like heartbeat or respiration, some limitations, such as bulky structure, poor portability and requirement of external power sources remarkably restricted their widespread application in smart mobile medical electronics [16]. Therefore, a self-powered ammonia sensor that can harvest energy from human body is desperately needed. In addition, it is underexplored but will be a novel and superior solution if a wearable sensor that could simultaneously chemically detect the inhalation and measure the breath rate for respiration analysis without a power supply. Device fabrication The as-developed triboelectric self-powered respiration sensor (TSRS) is composed of Ce-doped ZnO, Polydimethylsiloxane (PDMS), Au foils and PET films, as revealed in Fig. 1a. Ce-doped ZnO plays dual roles of gas sensing material and triboelectrification layer (Fig. 1b). PDMS functions as the triboelectric layer and Au foils were coated on the back of both triboelectric layers as electrodes. To improve the flexibility and air tightness, the whole device was packed with soft silica gel films. The patterned PDMS film exhibits good transparency and flexibility, as shown in Fig. 1c and 1d. Figure 1e sketches the fabrication flow of the TSRS. Driven by the continuous expansion and contraction of the chest during respiration (Fig. 1g), the deformation of TSRS inflated can be converted into electric signals and human exhaled gas can flow into the TSRS through a soft tube with the breathing process, enabling the real-time spontaneous monitoring of both respiratory behaviors and exhaled gas. Method To explore the sensing behavior of as-prepared TSRS toward NH3 from 0.1 to 10 ppm, including the trace level region (region Ⅰ, 0.1 to 1 ppm) and micro level region (region Ⅱ, 2 to 10 ppm), the NH3-sensing response-concentration fitting curves are plotted in Fig. 2a for five samples. It is found that without moisture atmosphere, the TSRS exhibits an opposite sensing behavior and the response declines with increasing ammonia concentration in both region Ⅰ (Fig. 2e) and region Ⅱ (Fig. 2f). A steeper slope is observed under humid NH3 atmosphere in comparison with the dry NH3 atmosphere, indicating that the existence of water molecular will raise the sensing performance. As a consequence, the moisture-resistant feature of the as-developed TSRS favours NH3 detection in human exhaled gas. Figure 2g elucidates dynamic response profile of TSRS when exposed to 0.01 ppm NH3 with 97.5%RH, which indicates that the TSRS is sensitive to NH3 as low as 0.01 ppm and the response time is nearly 155 s. Results and Conclusions Attached on the human chest, the as-prepared TSRS delivers a stable output voltage signal within 5 min normal breathing (Fig. 3a). The wearable sensor can be applied to distinguish different types of breathing behaviors and human respiratory states after physical exercise. Figure 3b presents the real-time output recording of diverse breathing behaviors, including normal breathing, deep breathing, shallow breathing and rapid breathing. Human respiration rate and depth can be clearly recognized in terms of frequency and amplitude of the output voltage signals. The deep breathing pattern has a bigger peak-to-peak amplitude and wider interval than normal breathing pattern due to the larger and slower change in chest circumference. In addition, the physiological process of human body after exercise can also be accurately reflected by breathing intensity and frequence. The breathing amplitude after 100 squats is more intense than that after 50 squats, as displayed in Fig. 3c. Meanwhile, the injection of exhaled NH3 gas into the TSRS apparently enlarges the amplitude of the output voltage (Fig. 3d), revealing the capability of simultaneously detecting breathing behaviors and exhaled gases. References [1] M. Righettoni, A. Amann, S.E. Pratsinis, Breath analysis by nanostructured metal oxides as chemo-resistive gas sensors, Materials Today. 18 (2015) 163–171. doi:10.1016/j.mattod.2014.08.017 [2] P. Le Maout, J.L. Wojkiewicz, N. Redon, C. Lahuec, F. Seguin, L. Dupont, , Polyaniline nanocomposites based sensor array for breath ammonia analysis. Portable e-nose approach to non-invasive diagnosis of chronic kidney disease, Sens. Actuators, B Chem. 274 (2018) 616 –626. doi:10.1016/j.snb.2018.07.178 [3] S. Wang, H. Tai, B. Liu, Z. Duan, Z. Yuan, H. Pan, Y. Su, G. Xie, X. Du, Y. Jiang, A Facile Respiration-Driven Triboelectric Nanogenerator for Multifunctional Respiratory Monitoring, Nano Energy. 58 (2019) 312–321. doi:10.1016/j.nanoen.2019.01.042 [4] Y. Jung, H.G. Moon, C. Lim, K. Choi, H.S. Song, S. Bae, S.M. Kim, M. Seo, T. Lee, S. Lee, H.H. Park, S.C. Jun, C.Y. Kang, C. Kim, Humidity-Tolerant Single-Stranded DNA-Functionalized Graphene Probe for Medical Applications of Exhaled Breath Analysis, Advanced Functional Materials. 27 (2017) 1–9. doi:10.1002/adfm.201700068 Figure 1

Introduction Nitrogen dioxide (NO2) is a ubiquitous hazardous gas species that can cause light pollution, acid rain [1-3], and water pollution [4]. With increasing vehicles ownership and emission, exhaust from automobiles, i.e. nitrogen dioxide (NO2) and its derivatives, imposes huge threaten on the air quality and public health. However, a majority of the gas sensors demand additional energy supply and undoubtedly increase the energy consumption of the whole device, inhibiting the portability and mobility of the device. A bionic alveolus-shaped triboelectric gas sensor (ATGS) has been designed and fabricated for spontaneously NO2 detection at room temperature. Furthermore, a sensing modeling was proposed by combining the thermodynamic analysis and finite element calculation together with phase-field simulation. This work not only provides a facile, low-cost and portable approach for active gas sensing and real-time physiological assessment, but also proposes a theoretical modeling for self-powered gas detection. Device fabrication The configuration of ATGS is based on contact-separate mode Triboelectric Nanogenerator (TENG). A layer of acrylic with the dimension of 40mm×40mm×1mm was tailored by laser etching machine, together with a layer of latex with the dimension of 40mm×40mm×0.2mm was cleaned by ethanol and deionized water. Then copper electrode with a thickness of 200nm was coated on the one side of the tailored acrylic sheet by thermal evaporation, followed by deposition of prepared suspensions as the gas sensitive material via gas spraying. Subsequently, the WO3/copper coated acrylic sheet was etched through laser etching machine to create a central hole with diameter of 4.0 mm. Then, the latex layer was attached to WO3/copper coated acrylic sheet to form the gas test chamber. Epoxy resin was used to seal the edges between latex film and acrylic sheet to ensure the gas tightness. A plastic tube was integrated as the inlet and outlet of the target gas into the sensor. Method The internal combustion engines burning fossil fuels generate and release huge amount of nitrogen dioxide, which is large threat to environment and public health, as shown in Figure 1a. To address the concern, we designed an alveolus-shaped triboelectric gas sensor (ATGS) for both nitrogen dioxide detection and personal breath behavior monitoring, as the configuration shown in Figure 1b. It was vertically laminated with latex, sensitive material, copper electrode and a plastic air conduit serving as the gas conducting channel. Here, latex film is selected as the contacting layer for its good stretchability and strong electron affinity. Figure 1c shows the photograph of the as-fabricated AIMS, where the gas inflation will hold up the latex membrane to form a tent while the deflation will shrink the tent. During this processing, the latex forms a cycle of contact and separation with the bottom substrate material, pumping the electrons to flow back and forth between the copper electrode and the ground. The working principle and finite element calculation of the as-prepared AIMS is elucidated in Fig. 1d and 1f. Results and Conclusions To explore the gas sensing capability of the as-fabricated ATGS, the output voltage versus NO2 gas concentrations from 0 ppm to 100 ppm were investigated. Compared with 0.01 g and 0.1 g alkali treatments, the device with 0.02 g NaOH treatment revealed a much better sensitivity and linearity, as shown in Fig. 2a, where a response of 452.44% was achieved when being exposed to 100 ppm NO2. In addition, as presented in Fig. 2b, a linearity of 0.976 is observed for the AIMS with 0.02 g NaOH treatment, demonstrating its capability of actively detecting nitrogen dioxide in a wide concentration range. The ATGS also demonstrated capability in distinguishing diverse breathing patterns without any power supply (Fig. 2c). In addition, the NO2 response is at least 20 times higher than other gases, implying a good selectivity (Fig. 2d) A phase-field simulation and finite element calculation were implemented to numerically verify the permittivity effect on the electric field and polarization of sensitive film. As shown in Fig. 3k, the polarization increases with increasing relative dielectric constant, while the electric field follows an opposite trend. Given the depolarization field is proportional to the polarization once the device is fixed, the increase of permittivity facilitates the depolarization of the sensitive layer, which is in agreement with the aforementioned theoretical derivation and experimental data. References [1] R. Ehrlich, M.C. Henry, Chronic toxicity of nitrogen dioxide. I. Effect on resistance to bacterial pneumonia, Journal of Occupational Medicine. 12 (1970) 34. doi: 10.1080/00039896.1968.10665342. [2] K. Mukala, J. Pekkanen, P. Tiittanen, S. Alm, R. Salonen, J. Tuomisto, Personally measured weekly exposure to NO2 and respiratory health among preschool children, European Respiratory Journal 13 (1999) 1411-1417. doi:10.1183/09 031936.99.13614189 [3] R.L. Tse, A.A. Bockman, Nitrogen dioxide toxicity report of four cases in firemen, J. Am. Med. Assoc 212 (1970) 1341-1344. doi: 10.1001/jama.212.8.1341. [4] G. Sberveglieri, P. Benussi, G. Coccoli, S. Groppelli, P. Nelli, Reactively sputtered indium tin oxide polycrystalline thin films as NO and NO2 gas sensors, Thin Solid Films 186 (1990) 349–360. doi:10.1016/0040-6090(90)90150-C. Figure 1

Figure S1. (a) schematic of a homemade setup for pyroelectric and piezoelectric measurement; (b) Measurement setup for finding the exact direction of dipole vectors in PVDF test sample; (c) pyroelectric responses of test and reference samples. Figure S2. D-E curves of PVDF samples at different substrate treatment time. Figure S3. ε′(ε″) of PVDF samples (@1 kHz) as a function of substrate treatment time. Figure S4. SEM images of the surface morphology of the samples: (a) and (b) are untreated samples; (c) and (d) are 8 h-treated samples. Table S1. Material and geometric parameters set values in simulation. Table S2. Loads and boundary conditions for simulation. Figure S5. Dependences of temperature change rates of both layers on pillars’ height at different pillar’s diameters. Figure S6. Dependences of differences between piezoelectric responses of lower and upper layers (Δpiezoelectric) on pillars’ height at different pillar’s diameters. Figure S7. Dependence of piezoelectric response of lower and upper elements on pillars’ position. (DOCX 2935 kb)

Cobalt-iron-codoped ZnO films were synthesized with different precursor sol pHs by a sol–gel method. All the samples possess hexagonal wurtzite structure, with no evidence of secondary phases. The average crystallite size of the samples was in the range of 10–40 nm, accompanying significant differences with the increase of the H + ion level. The Co/Fe ions are indeed substituted at the Zn 2+ site into the ZnO lattice, as shown by XRD and XPS. Strong ultraviolet emission, blue double emission and weak green emission peaks are observed in the photoluminescence spectra of all samples at room temperature. Further studies reveal that the bandgap energy of the ZnO films increases from 3.15 eV (pH = 5) to 3.24 eV (pH = 9). Enhanced room-temperature ferromagnetism is observed for the (Co, Fe)-codoped ZnO films at sol pHs lower than 8. Our work clearly establishes that the origin of room-temperature ferromagnetism in the (Co,Fe)-codoped ZnO films is linked to O vacancies, tunable by the sol pH.

To investigate the feasibility of using Spectral CT imaging with low contrast medium in abdominal CT angiography (CTA).70 consecutive patients (40 men, 42.6 ± 20.4 years; 30 women, 46.7 ± 18.8 years) with suspected abdominal focal lesions were referred to CTA exam. They were randomly assigned into two groups. Group A: 35 patients underwent conventional CT scan of Tube voltage 120 kVp, automatic current modulation with a Noise Index of 12, ASIR 30%, and injected with Iohexol (350 mgI/ml). Group B: 35 patients underwent Spectral CT Imaging, with Tube current of 600 mA, injected with Iodixanol (270 mgI/ml). The optimal mono-energy keV was achieved using the optimal contrast noise ratio in abdominal aorta at the renal artery level relative to the erector spine muscle. Both groups were injected with an injection rate of 3.5 ml/s, and a contrast volume of 1.5 ml/kg body weight. The Hounsfield units (HU) and noise of the bilateral renal arteries and muscle of both groups, as well as the optimal monochromatic image set of Group B were measured. Two radiologists assessed all images with a 5-points scale. CTDIvol and DLP were recorded. Data were analyzed using student t test.The total iodine intake of Group B was 28% lower than that of Group A. The CNR of abdomen artery, celiac trunk, superior mesenteric artery, and renal artery in spectral group (at the best mono-energy of 53.0 keV) were higher than those in conventional CTA group (p 0.001). The subjective image quality score of spectral CTA group was also rated higher than conventional CTA group (p 0.001). CTDIvol, DLP, and effective dose of spectral group were all lower than conventional group, but there were no significant differences (p 0.05).With 28% contrast medium reduction and reduced radiation dose, CT angiography using spectral imaging and lower concentration contrast agent provided better image quality than conventional CTA.

Superhydrophobic surfaces have been shown to produce significant drag reduction in both laminar and turbulent flows by introducing an apparent slip velocity along an air-water interface trapped within the surface roughness. In the experiments presented within this study, we demonstrate the existence of a surface tension gradient associated with the resultant Marangoni flow along an air-water interface that causes the slip velocity and slip length to be significantly reduced. In this study, the slip velocity along a millimeter-sized air-water interface was investigated experimentally. This large-scale air-water interface facilitated a detailed investigation of the interfacial velocity profiles as the flow rate, interfacial curvature and interface geometry were varied. For the air-water interfaces supported above continuous grooves (concentric rings within a torsional shear flow) where no surface tension gradient exists, a slip velocity as high as 30% of the bulk velocity was observed. However, for the air-water interfaces supported above discontinuous grooves (rectangular channels in a Poiseuille flow), the presence of a surface tension gradient reduced the slip velocity and in some cases resulted in an interfacial velocity that was opposite to the main flow direction. The curvature of the air-water interface in the spanwise direction was found to dictate the details of the interfacial flow profile with reverse flow in the center of the interface for concave surfaces and along the outside of the interface for convex surfaces. The deflection of the air-water interface was also found to greatly affect the magnitude of the slip. Numerical simulations imposed with a relatively small surface tension gradient along the air-water interface were able to predict both the reduced slip velocity and back flow along the air-water interface.

In this work, utility theory is introduced to optimum aerodynamic shape design under uncertainty (also called robust aerodynamic design). Specifically, utility theory is used to formulate the objective function of the optimization problem. The advantage of the proposed approach over the commonly used weighted sum method is that it does not require the use of weighting factors or the addition of constraints on the statistical moments. The polynomial chaos expansion metamodel with the least-angle regression and the hyperbolic truncation scheme are used to accelerate the uncertainty propagation and the optimization process. The proposed approach is demonstrated on the optimum airfoil shape design under uncertainty at steady transonic conditions. Two design cases are considered. In both cases the drag coefficient is to be minimized subject to constraints on the lift coefficient and the airfoil thickness at two chordwise locations. The first case treats the Mach number as uncertainty parameter and the second case treats the Mach number and the lift coefficient at target as uncertain. The proposed method is compared with deterministic single-point optimization and multi-point optimization, and the standard robust design formulations. Results show that the proposed approach is capable of obtaining airfoil design of the lowest mean drag coefficient with the smallest standard deviation as compared to the other approaches. In the first case, the proposed approach yields a design with a mean drag coefficient comparable to the standard robust design (around 97.6 drag counts, cts), but with a significantly lower variance (0.6 cts versus 2.5 cts). In the second case, the proposed approach yielded a design with a higher mean drag coefficient than the standard approach (98.4 cts versus 97.6 cts), but with a lower standard deviation (4.1 cts versus 4.8 cts). In both cases, the deterministic approaches yield designs with comparable or lower drag coefficients but with significantly larger standard deviations.

In this paper, micro gas chromatography columns were fabricated through the micro-electro-mechanical system (MEMS) technique. Two types of columns were designed, namely, open-tube and semi-packed columns. By comparing different structures, column efficiency was improved by embedding square posts in the channel to form a semi-packed column. The result showed that column efficiency of the semi-packed column reached 55 366 plates per m. This study was the first to report based on experimentation that MEMS-based columns can reach a plate number this high. The plate number was five times higher than the value previously reported. In addition, a 30 m-long Agilent HP-5 commercial capillary column was used to compare the results with findings obtained using a MEMS-based semi-packed column. The analytes were perfectly separated in both columns. The column efficiency of the HP-5 capillary column was 5490 plates per m, which was 10 times lower than that of the micro-fabricated, semi-packed column.

Two strong hydrogen-bond acidic (HBA) polymers DKAP and PLF, were coated onto 434 MHz surface acoustic wave (SAW) devices for rapid detection of an explosive compound, 2,4-dinitrotoluene (2,4-DNT). Sensitivity and selectivity of the polymer-coated sensors were studied by exposure to 2,4-DNT in the concentration range of 200 ppb to 1 ppm, as well as some common interferences at higher concentrations. The results showed that the DKAP sensor has a 4.6 times higher sensitivity to 2,4-DNT than PLF at the concentration of 1 ppm, while a further comparison indicated that their sensitivities to dimethyl methylphosphonate (DMMP) are essentially identical. The superior sensitive performance of DKAP to nitroaromatics as compared to PLF can be attributed to the dipolarity induced by the aromatic ring segments, which promotes π–π interactions between the explosive vapor and the polymer coating. In addition, the DKAP sensor exhibits a high response of 4.6 kHz to 200 ppb 2,4-DNT, with an extrapolated limit of detection (LOD) of 0.1 ppb, which is comparable to most sensitive polymer-coated sensors previously reported. Furthermore, both adsorption and recovery time of the DKAP sensor is much shorter than other related sensors. Sensor responses to possible common interferences are found to be 11–35 fold lower than to 2,4-DNT. In situ infrared spectroscopy studies were performed to demonstrate the hydrogen bonding between nitroaromatic compounds and the chemoselective polymers.

Ultrasonic testing (UT) is used to detect internal flaws in materials and to characterize material properties. In many applications, computational simulations are an important part of the inspection-design and analysis processes. Having fast surrogate models for UT simulations is key for enabling efficient inverse analysis and model-assisted probability of detection (MAPOD). In many cases, it is impractical to perform the aforementioned tasks in a timely manner using current simulation models directly. Fast surrogate models can make these processes computationally tractable. This paper presents investigations of using surrogate modeling techniques to create fast approximate models of UT simulator responses. In particular, we propose to integrate data-driven methods (here, kriging interpolation with variable-fidelity models to construct an accurate and fast surrogate model. These techniques are investigated using test cases involving UT simulations of solid components immersed in a water bath during the in...

Single-walled carbon nanotube (SWNT) films were prepared on interdigitated electrodes by airbrush technique, and their sensing properties to dimethyl methylphosphonate (DMMP) were studied. The SWNT films were characterized by field-emission scanning electron microscope. The response to different concentrations of DMMP vapors were investigated at room temperature. The results showed that the capacitance of airbrush SWNT sensor decreased rapidly in varying concentrations ranging from 12 to 60 mg/m3 (2.4–12 ppm). The capacitance sensitivity was about 12.5 % when exposed to 12 mg/m3 DMMP vapor. The capacitance sensitivity was higher when the initial capacitance and loss tangent were higher and the SWNT film was denser. It was found that the capacitance sensitivity was nearly 10 times to the resistance sensitivity. The airbrush SWNT sensor exhibited highly and fast capacitance response, good repeatability and selectivity for DMMP vapor.

Single-walled carbon nanotube (SWNT) films were prepared on silicon/silica substrates by screen-printed technique at a wafer scale, and their sensing properties to dimethyl methylphosphonate (DMMP) were studied. The SWNT networks were characterized by field-emission scanning electron microscope. The resistance responses to different concentrations of DMMP vapors were investigated at room temperature. The results showed that the resistance changes of the screen-printed SWNT films increased rapidly in varying concentrations ranging from 20 to 200 ppm. The sensor exhibited high resistance responses, good reproducibility and excellent long-term stability for DMMP vapor detection. The screen-printed SWNT networks would be potentially extended to large-scale, low cost and simple manufacturing sensor applications.

Supercapacitor have attracted much attention due to its fast power supply, long cycle life, simple principle, etc. Supercapacitors are widely used in consumer electronics. Activated carbon is a typical material for electric double layer capacitor. Here, we study the electrochemical performance of an activated carbon (TF-B520) bulky paper electrode made by vacuum filtration method. Cyclic Voltammetry and Constant Current Charge/Discharge were used to test the electrode capacitance and the rate performance. The results showing that TF-B520 activated carbon balky paper electrodes have the highest capacitance of 120F/g at scan rate 1mV/s and good capacitor behaviour at scan rate below 20mV/s and current density below 250mA/g.

A new material-poly{methyl [3-(2-hydroxyl, 4,6-bistrifluoromethyl)phenyl]propylsiloxane} (PMTFMPS), which was sensitive to toxic organophosphate vapor, was synthesized via O-alkylation, claisen rearrange reaction and hydrosilylation reaction. The polymer was coated on quartz crystal microbalance (QCM) to investigate its gas sensitive properties to nerve agents’ simulant dimethyl methylphosphonate (DMMP) vapor, as well as other interfering vapors. It was found that QCM sensor responded linearly to DMMP vapor with a slope of 27 Hz/ppm in the 10–50 ppm range. The material was much more sensitive to DMMP than to other interfering vapors, thus high selectivity to DMMP was demonstrated. The influence of humidity on the sensor response was also examined. The results showed that the frequency shifts were about 60% when tested in 77% RH wet air than in dry N2. When compared with our previously studied unfluorinated phenol-modified siloxane PMPS, PMTFMPS exhibited sensitivity enhancement of 2.3 times and an increased resistance to humidity variations.

Quartz crystal microbalance (QCM) gas sensors based on polymeric material were fabricated and their gas response characteristics were examined for four simulant gases of chemical agents, which were dimethyl methyl phosphonate (DMMP), N,N-dimethylacetamide (DMA), 1,5-dichloropentane (DCP) and dichloroethane (DCE). For the selection of appropriate coating materials, both principal component analysis (PCA) and hierarchical cluster methods were applied to a data set collected from 15 QCM sensors for 12 analytes. Four appropriate coating materials were selected after optimizing the correlation between the 15 coating materials and the first four principal component (PC) factors. The four chosen polymers were used as sensitive component for a sensor array, and then PCA is adapted to classify four simulant gases. The results show that the QCM sensor array has high sensitivity and selectivity to four chemical agents.

ZnO nanoparticles and graphene oxide (GO) thin film were deposited on gold interdigital electrodes (IDEs) in sequence via simple spraying process, which was further restored to ZnO/reduced graphene oxide (rGO) bilayer thin film by the thermal reduction treatment and employed for ammonia (NH3) detection at room temperature. rGO was identified by UV-vis absorption spectra and X-ray photoelectron spectroscope (XPS) analyses, and the adhesion between ZnO nanoparticles and rGO nanosheets might also be formed. The NH3-sensing performances of pure rGO film and ZnO/rGO bilayer films with different sprayed GO amounts were compared. The results showed that ZnO/rGO film sensors exhibited enhanced response properties, and the optimal GO amount of 1.5 ml was achieved. Furthermore, the optimal ZnO/rGO film sensor showed an excellent reversibility and fast response/recovery rate within the detection range of 10-50 ppm. Meanwhile, the sensor also displayed good repeatability and selectivity to NH3. However, the interference of water molecules on the prepared sensor is non-ignorable; some techniques should be researched to eliminate the effect of moisture in the further work. The remarkably enhanced NH3-sensing characteristics were speculated to be attributed to both the supporting role of ZnO nanoparticles film and accumulation heterojunction at the interface between ZnO and rGO. Thus, the proposed ZnO/rGO bilayer thin film sensor might give a promise for high-performance NH3-sensing applications.

We report a first-principles molecular dynamics study on Li-doped beta-phase manganese phthalocyanine (MnPc). Four electronegative sites next to pyrrole-bridging nitrogen atoms in single MnPc were characterized by analyzing electrostatic potentials. In one-dimensional stacked MnPc, six binding sites were unambiguously located, among which two were newly identified by both static and dynamic simulations. Molecular dynamics simulations were conducted to explore the underlying mechanism governing the diffusive motion of Li dopants. The continuous diffusion of Li atoms among these six binding sites of adjacent MnPc molecules has a distinct cooperative pair-hopping character. The activation energy is significantly lower for pair-hopping than for a single jump. Accepted version