Preparation of Flexible Wavelength-Selective Metasurface for Infrared Radiation Regulation.

Perpetual advancements in modern detection techniques have augmented the requirement of infrared camouflage; however, its development is impeded by multiband compatible regulation and curved application targets. Here, a flexible wavelength-selective metasurface based on two metal-dielectric-metal resonators is experimentally demonstrated for infrared radiation regulation with thermal management utilizing magnetic polariton. Low emissivity in atmosphere windows (infrared stealth) and high emissivity in the wavelength of 5-8 µm nonatmospheric window (radiative cooling) are simultaneously achieved. In comparison with conventional hard substrates, it is for the first time the composite wavelength-length metasurface is successfully prepared directly on a flexible polyimide film via applying polyimide double-sided tapes and S1805/LOR5A bilayer stack lift-off technology. Not only does this method successfully overcome the debonding problem of photoresist on the flexible substrate, but it also solves the bulging problem of the substrate as well as the limitation of high temperature. Besides, the temperature and infrared radiation distributions of flexible wavelength-selective metasurfaces with different curvatures are first investigated. The compared results reveal that the metasurface with larger curvature has a better infrared camouflage performance. Furthermore, the cycle stability of the flexible metasurface is tested, and the results show that the infrared radiation regulation is stable after 30 cycles with essentially no change. This study provides a guideline for preparing flexible composite metasurfaces and avoids the trouble of replacing the metal/dielectric material of the initial structure with a flexible material to improve the structure for application to curved surfaces, thus broadening implications in enhancing the effective bonding of metasurfaces to target surfaces.

Effects of Cathode GDL Gradient Porosity Distribution along the Flow Channel Direction on Gas-Liquid Transport and Performance of PEMFC.

The gas diffusion layer (GDL) is an important component of proton exchange membrane fuel cells (PEMFCs), and its porosity distribution has considerable effects on the transport properties and durability of PEMFCs. A 3-D two-phase flow computation fluid dynamics model was developed in this study, to numerically investigate the effects of three different porosity distributions in a cathode GDL: gradient-increasing (Case 1), gradient-decreasing (Case 3), and uniform constant (Case 2), on the gas-liquid transport and performance of PEMFCs; the novelty lies in the porosity gradient being along the channel direction, and the physical properties of the GDL related to porosity were modified accordingly. The results showed that at a high current density (2400 mA·cm-2), the GDL of Case 1 had a gas velocity of up to 0.5 cm·s-1 along the channel direction. The liquid water in the membrane electrode assembly could be easily removed because of the larger gas velocity and capillary pressure, resulting in a higher oxygen concentration in the GDL and the catalyst layer. Therefore, the cell performance increased. The voltage in Case 1 increased by 8% and 71% compared to Cases 2 and 3, respectively. In addition, this could ameliorate the distribution uniformity of the dissolved water and the current density in the membrane along the channel direction, which was beneficial for the durability of the PEMFC. The distribution of the GDL porosity at lower current densities had a less significant effect on the cell performance. The findings of this study may provide significant guidance for the design and optimization of the GDL in PEMFCs.

Pore-Scale Modeling of Microporous Layer for Proton Exchange Membrane Fuel Cell: Effective Transport Properties.

A microporous layer (MPL) is a transition layer with a porous material structure, located between the gas diffusion layer (GDL) and catalyst layer (CL) in a proton exchange membrane fuel cell (PEMFC). It not only significantly improves electron transfer and heat conduction in membrane electrode assembly, but also effectively manages liquid water transport to enhance the fuel cell performance. The MPL is usually coated on one side of the GDL. The fragile nature of MPL makes it challenging to characterize the effective transport properties using experimental methods. In this study, a stochastic numerical method is implemented to reconstruct the three-dimensional microstructure of an MPL consisting of carbon particles and PTFE. The reliability of the MPL reconstructed model is validated using experimental data. The relationship between the effective transport properties and the compression strain is obtained using the Pore Scale Model (PSM), while the relationship between the liquid water saturation and capillary pressure is solved by Lattice Boltzmann Method (LBM). The effective transport properties in the MPL are then imported into the two-phase flow fuel cell model. It is found that the effective transport parameters in MPL obtained by PSM and LBM can improve the accuracy of the model calculation. This study provides an effective method to reconstruct the microstructure of MPL that can generate precise MPL transport parameters for utilization in various PEMFC performance prediction models.

Study on Self-Humidification in PEMFC with Crossed Flow Channels and an Ultra-Thin Membrane.

In this study, a 3D model of a proton exchange membrane fuel cell (PEMFC) with crossed channels and an ultra-thin membrane is developed to investigate the feasibility of self-humidification; experiments utilizing a PEMFC stack with identical configurations are conducted to validate the simulation results and further investigate the effects of various operating conditions (OCs) on self-humidification. The results indicate that the crossed flow channel leads to enhanced uniformity of water distribution, resulting in improved cell performance under low/no humidification conditions. External humidifiers for the anode can be removed since the performance difference is negligible (≤3%) between RHa = 0% and 100%. Self-humidification can be achieved in the stack at 90 °C or below with an appropriate back pressure among 100-200 kPa. As the current density increases, there is a gradual convergence and crossing of the voltage at low RH with that at high RH, and the crossover points are observed at 60-80 °C with suitable pressure when successful self-humidification is achieved. Below the current density of the point, the stack's performance is inferior at lower RH due to membrane unsaturation, and conversely, the performance is inferior at higher RH due to flooding; this current density decreases with higher pressure and lower temperature.

Microstructure Reconstruction and Multiphysics Dynamic Distribution Simulation of the Catalyst Layer in PEMFC.

Due to the complexity of both material composition and the structure of the catalyst layer (CL) used in the proton-exchange membrane fuel cell (PEMFC), conjugated heat and mass transfer as well as electrochemical processes simultaneously occur through the CL. In this study, a microstructure model of CL was first reconstructed using images acquired by Nano-computed tomography (Nano-CT) of a real sample of CL. Then, the multiphysics dynamic distribution (MPDD) simulation, which is inherently a multiscale approach made of a combination of pore-scale and homogeneous models, was conducted on the reconstructed microstructure model to compute the corresponded heat and mass transport, electrochemical reactions, and water phase-change processes. Considering a computational domain with the size of 4 um and cube shape, this model consisting of mass and heat transport as well as electrochemical reactions reached a stable solution within 3 s as the convergence time. In the presence of sufficient oxygen, proton conduction was identified as the dominant factor determining the strength of the electrochemical reaction. Additionally, it was concluded that current density, temperature, and the distribution of water all exhibit similar distribution trends, which decrease from the interface between CL and the proton-exchange membrane to the interface between CL and the gas-diffusion layer. The present study not only provides an in-depth understanding of the mass and heat transport and electrochemical reaction in the CL microstructure, but it also guides the optimal design and fabrication of CL components and structures, such as improving the local structure to reduce the number of dead pores and large agglomerates, etc.

Two-Dimensional Simulation of the Freezing Characteristics in PEMFCs during Cold Start Considering Ice Crystallization Kinetics.

Cold start is one of the major issues that hinders the commercialization of polymer electrolyte membrane fuel cells (PEMFCs). In this study, a 2D transient multi-physics model is developed to simulate the cold start processes in a PEMFC. The phase change between water vapor, liquid water, and ice in the catalyst layers (CLs), micro porous layer (MPLs), and gas diffusion layers (GDLs) is also investigated, particularly the effect of ice crystallization kinetics when supercooled liquid water changes into ice. The factors affecting the different operating conditions and structural features of the membrane electrode assembly (MEA) are investigated. The results show that when the start temperature is -20 °C or higher, ice formation is delayed and the formation rate is decreased, and supercooled liquid water permeates from the CL into the MPL. For an MEA with relatively high hydrophobicity, the water permeation rate is high. These results can enable a PEMFC to start at subzero temperatures. The effect of ice crystallization kinetics is negligible when the fuel cell is started at -30 °C or below.

Second-harmonic generation microscopy for assessment of mesenchymal stem cell-seeded acellular dermal matrix in wound-healing.

Direct intra-skin injection of mesenchymal stem cells (MSCs) and the use of biomaterial scaffolds for grafts are both promising approaches of skin wound repair, however they still cannot generate skin that completely resembles the natural skin structures. In this study, we combined these two approaches by using acellular dermal matrix (ADM) recellularized with MSCs to repair cutaneous wounds in a murine model and two-photon fluorescence (TPF) microscopy and second-harmonic generation (SHG) microscopy to assess the effects of this therapy on wound healing. Bone marrow-derived mesenchymal stem cells (BM-MSCs) were tagged with GFP and seeded into ADM (ADM-MSC) via MSC and ADM co-culture. ADM-MSC, ADM or saline was applied to murine excisional skin wounds and wound-healing was evaluated by histological examination on days 7, 14, 21 and TFP microscopy on days 1, 3, 5 and 21 post-treatment. ADM-MSC promoted healing significantly more than treatment with ADM or saline alone, as it led to substantial neovascularization and complete skin appendage regeneration. Furthermore, the SHG microscopic imaging technique proved to be a useful tool for monitoring changes in the collagen network at the wound site during the healing process and assessing the effects of different therapies.

[Prognostic value of D-dimer in patients with sepsis in emergency department: a prospective study].

OBJECTIVE: To investigate the value of the concentration of D-dimer in predicting 28-day mortality of sepsis patients in emergency department in order to determine its prognostic values. METHODS: A prospective study was conducted. A total of 766 sepsis patients treated in the emergency department of Beijing Chaoyang Hospital of the Capital Medical University from October 2009 to July 2010 were enrolled, and admission blood samples were obtained for D-dimer measurement (solid phase immune chromatography). A variety of clinical and laboratory variables were recorded. With 28 days as end point, the D-dimer levels, acute physiology and chronic health evaluation II (APACHEII) score, and simplify acute physiology score II (SAPSII) were compared respectively between survivors and non-survivors. The status of each patient was ascertained, and the association between the concentration of D--dimer and 28-day mortality was assessed. RESULTS: Two hundred and thirty-three patients died during the 28--day observation period among 766 patients. D--dimer concentration (µg/L) among deceased were significantly higher than those of survivors [1220.0 (789.0, 1835.0) vs. 323.0 (158.0, 642.0), P < 0.01]. The level of D-dimer showed positive correlation with APACHEII score and SAPSII [r1=0.643, r2=0.632, both P < 0.01]. D-dimer concentration had an area under the receiver operating characteristic (ROC) curve (AUC) of 0.880 for predicting 28-day mortality, with 95% confidence interval (95%CI) 0.855-0.904, P < 0.001; the optimal D-dimer cut point for predicting 28-day mortality was 663.5 µg/L. D--dimer concentration higher than 663.5 µg/L, APACHEII score higher than 19.5 and SAPSII higher than 39.5 were the independent predictors of 28-day mortality [odds ratio (OR): 17.5, 15.7, 19.6, all P < 0.001]. The 28-day mortality (1.4%, 12.3%, 64.2%), APACHEII score [11 (9, 13), 13 (11, 16), 19 (15, 22)] and SAPSII [24 (18, 29), 31 (24, 36), 40 (33, 49)] showed statistically significant among D--dimer <250.0, 250.0--663.5, >663.5 µg/L three groups (all P < 0.01). CONCLUSIONS: D-dimer concentration is an independent predictor of 28--day mortality in patients with sepsis. D--dimer level shows a high predictive value in patients with sepsis, similar to APACHE II score and SAPSII. It can be helpful in risk stratification in septic patients.

Parameter stability of the functional-structural plant model GREENLAB as affected by variation within populations, among seasons and among growth stages.

BACKGROUND AND AIMS: It is increasingly accepted that crop models, if they are to simulate genotype-specific behaviour accurately, should simulate the morphogenetic process generating plant architecture. A functional-structural plant model, GREENLAB, was previously presented and validated for maize. The model is based on a recursive mathematical process, with parameters whose values cannot be measured directly and need to be optimized statistically. This study aims at evaluating the stability of GREENLAB parameters in response to three types of phenotype variability: (1) among individuals from a common population; (2) among populations subjected to different environments (seasons); and (3) among different development stages of the same plants. METHODS: Five field experiments were conducted in the course of 4 years on irrigated fields near Beijing, China. Detailed observations were conducted throughout the seasons on the dimensions and fresh biomass of all above-ground plant organs for each metamer. Growth stage-specific target files were assembled from the data for GREENLAB parameter optimization. Optimization was conducted for specific developmental stages or the entire growth cycle, for individual plants (replicates), and for different seasons. Parameter stability was evaluated by comparing their CV with that of phenotype observation for the different sources of variability. A reduced data set was developed for easier model parameterization using one season, and validated for the four other seasons. KEY RESULTS AND CONCLUSIONS: The analysis of parameter stability among plants sharing the same environment and among populations grown in different environments indicated that the model explains some of the inter-seasonal variability of phenotype (parameters varied less than the phenotype itself), but not inter-plant variability (parameter and phenotype variability were similar). Parameter variability among developmental stages was small, indicating that parameter values were largely development-stage independent. The authors suggest that the high level of parameter stability observed in GREENLAB can be used to conduct comparisons among genotypes and, ultimately, genetic analyses.

Parameter optimization and field validation of the functional-structural model GREENLAB for maize.

BACKGROUND AND AIMS: There are three reasons for the increasing demand for crop models that build the plant on the basis of architectural principles and organogenetic processes: (1) realistic concepts for developing new crops need to be guided by such models; (2) there is an increasing interest in crop phenotypic plasticity, based on variable architecture and morphology; and (3) engineering of mechanized cropping systems requires information on crop architecture. The functional-structural model GREENLAB was recently presented that simulates resource-dependent plasticity of plant architecture. This study introduces a new methodology for crop parameter optimization against measured data called multi-fitting, validates the calibrated model for maize with independent field data, and describes a technique for 3D visualization of outputs. METHODS: Maize was grown near Beijing during the 2000, 2001 and 2003 (two sowing dates) summer seasons in a block design with four to five replications. Detailed morphological and topological observations were made on the plant architecture throughout the development of the four crops. Data obtained in 2000 was used to establish target files for parameter optimization using the generalized least square method, and parameter accuracy was evaluated by coefficient of variance. In situ plant digitization was used to establish 3D symbol files for organs that were then used to translate model outputs directly into 3D representations for each time step of model execution. KEY RESULTS AND CONCLUSIONS: Multi-fitting against several target files obtained at different growth stages gave better parameter accuracy than single fitting at maturity only, and permitted extracting generic organ expansion kinetics from the static observations. The 2000 model gave excellent predictions of plant architecture and vegetative growth for the other three seasons having different temperature regimes, but predictions of inter-seasonal variability of biomass partitioning during grain filling were less accurate. This was probably due to insufficient consideration of processes governing cob sink size and terminal leaf senescence. Further perspectives for model improvement are discussed.