Search Results
Blending In Situ Polyurethane-Urea with Different Kinds of Rubber: Performance and Compatibility Aspects
Specific physical and reactive compatibilization strategies are applied to enhance the interfacial adhesion and mechanical properties of heterogeneous polymer blends. Another pertinent challenge is the need of energy-intensive blending methods to blend high-tech polymers such as the blending of a pre-made hard polyurethane (-urea) with rubbers. We developed and investigated a reactive blending method to prepare the outstanding blends based on polyurethane-urea and rubbers at a low blending temperature and without any interfacial compatibilizing agent. In this study, the polyurethane-urea (PUU) was synthesized via the methylene diphenyl diisocyanate end-capped prepolymer and m-phenylene diamine based precursor route during blending at 100 °C with polar (carboxylated nitrile rubber (XNBR) and chloroprene rubber (CR)) and non-polar (natural rubber (NR), styrene butadiene rubber (sSBR), and ethylene propylene butadiene rubber (EPDM)) rubbers. We found that the in situ PUU reinforces the tensile response at low strain region and the dynamic-mechanical response up to 150 °C in the case of all used rubbers. Scanning electron microscopy reveals a stronger rubber/PUU interface, which promotes an effective stress transfer between the blend phases. Furthermore, energy filtered transmission electron microscopy (EFTEM) based elemental carbon map identifies an interphase region along the interface between the nitrile rubber and in situ PUU phases of this exemplary blend type.
A coaxial dielectric barrier discharge reactor for treatment of winter wheat seeds
Non-thermal atmospheric pressure plasmas have been recently explored for their potential usage in agricultural applications as an interesting alternative solution for a potential increase in food production with a minor impact on the ecosystem. However, the adjustment and optimization of plasma sources for agricultural applications in general is an important study that is commonly overlooked. Thus, in the present work, a dielectric barrier discharge (DBD) reactor with coaxial geometry designed for the direct treatment of seeds is presented and investigated. To ensure reproducible and homogeneous treatment results, the reactor mechanically shakes the seeds during treatment, and ambient air is admixed while the discharge runs. The DBD, operating with argon and helium, produces two different chemically active states of the system for seed modification. The temperature evolution was monitored to guarantee a safe manipulation of seeds, whereas a physiological temperature was assured by controlling the exposure time. Both treatments led to a remarkable increase in wettability and acceleration in germination. The present study showed faster germination acceleration (60% faster after 24 h) and a lower water contact angle (WCA) (82% reduction) for winter wheat seeds by using the described argon discharge (with air impurities). Furthermore, the treatment can be easily optimized by adjusting the electrical parameters. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
CHASE-PL—Future Hydrology Data Set: Projections of Water Balance and Streamflow for the Vistula and Odra Basins, Poland
There is considerable concern that the water resources of Central and Eastern Europe region can be adversely affected by climate change. Projections of future water balance and streamflow conditions can be obtained by forcing hydrological models with the output from climate models. In this study, we employed the SWAT hydrological model driven with an ensemble of nine bias-corrected EURO-CORDEX climate simulations to generate future hydrological projections for the Vistula and Odra basins in two future horizons (2024–2050 and 2074–2100) under two Representative Concentration Pathways (RCPs). The data set consists of three parts: (1) model inputs; (2) raw model outputs; (3) aggregated model outputs. The first one allows the users to reproduce the outputs or to create the new ones. The second one contains the simulated time series of 10 variables simulated by SWAT: precipitation, snow melt, potential evapotranspiration, actual evapotranspiration, soil water content, percolation, surface runoff, baseflow, water yield and streamflow. The third one consists of the multi-model ensemble statistics of the relative changes in mean seasonal and annual variables developed in a GIS format. The data set should be of interest of climate impact scientists, water managers and water-sector policy makers. In any case, it should be noted that projections included in this data set are associated with high uncertainties explained in this data descriptor paper.
GSH modification as a marker for plasma source and biological response comparison to plasma treatment
This study investigated the use of glutathione as a marker to establish a correlation between plasma parameters and the resultant liquid chemistry from two distinct sources to predefined biological outcomes. Two different plasma sources were operated at parameters that resulted in similar biological responses: cell viability, mitochondrial activity, and the cell surface display of calreticulin. Specific glutathione modifications appeared to be associated with biological responses elicited by plasma. These modifications were more pronounced with increased treatment time for the European Cooperation in Science and Technology Reference Microplasma Jet (COST-Jet) and increased frequency for the dielectric barrier discharge and were correlated with more potent biological responses. No correlations were found when cells or glutathione were exposed to exogenously added long-lived species alone. This implied that short-lived species and other plasma components were required for the induction of cellular responses, as well as glutathione modifications. These results showed that comparisons of medical plasma sources could not rely on measurements of long-lived chemical species; rather, modifications of biomolecules (such as glutathione) might be better predictors of cellular responses to plasma exposure. © 2020 by the authors.
Effect of Graphite Nanoplate Morphology on the Dispersion and Physical Properties of Polycarbonate Based Composites
The influence of the morphology of industrial graphite nanoplate (GNP) materials on their dispersion in polycarbonate (PC) is studied. Three GNP morphology types were identified, namely lamellar, fragmented or compact structure. The dispersion evolution of all GNP types in PC is similar with varying melt temperature, screw speed, or mixing time during melt mixing. Increased shear stress reduces the size of GNP primary structures, whereby the GNP aspect ratio decreases. A significant GNP exfoliation to individual or few graphene layers could not be achieved under the selected melt mixing conditions. The resulting GNP macrodispersion depends on the individual GNP morphology, particle sizes and bulk density and is clearly reflected in the composite's electrical, thermal, mechanical, and gas barrier properties. Based on a comparison with carbon nanotubes (CNT) and carbon black (CB), CNT are recommended in regard to electrical conductivity, whereas, for thermal conductive or gas barrier application, GNP is preferred.
Plasma-derived reactive species shape a differentiation profile in human monocytes
Background: Monocyte-derived macrophages are key regulators and producers of reactive oxygen and nitrogen species (ROS/RNS). Pre-clinical and clinical studies suggest that cold physical plasma may be beneficial in the treatment of inflammatory conditions via the release of ROS/RNS. However, it is unknown how plasma treatment affects monocytes and their differentiation profile. Methods: Naïve or phorbol-12-myristate-13-acetate (PMA)-pulsed THP-1 monocytes were exposed to cold physical plasma. The cells were analyzed regarding their metabolic activity as well as flow cytometry (analysis of viability, oxidation, surface marker expression and cytokine secretion) and high content imaging (quantitative analysis of morphology. Results: The plasma treatment affected THP-1 metabolisms, viability, and morphology. Furthermore, a significant modulation CD55, CD69, CD271 surface-expression and increase of inflammatory IL1β, IL6, IL8, and MCP1 secretion was observed upon plasma treatment. Distinct phenotypical changes in THP-1 cells arguing for a differentiation profile were validated in primary monocytes from donor blood. As a functional outcome, plasma-treated monocytes decreased the viability of co-cultured melanoma cells to a greater extent than their non-treated counterparts. Conclusions: Our results suggest plasma-derived ROS/RNS shaped a differentiation profile in human monocytes as evidenced by their increased inflammatory profile (surface marker and cytokines) as well as functional outcome (tumor toxicity). © 2019 by the authors.
Overview of compressed sensing: Sensing model, reconstruction algorithm, and its applications
With the development of intelligent networks such as the Internet of Things, network scales are becoming increasingly larger, and network environments increasingly complex, which brings a great challenge to network communication. The issues of energy-saving, transmission efficiency, and security were gradually highlighted. Compressed sensing (CS) helps to simultaneously solve those three problems in the communication of intelligent networks. In CS, fewer samples are required to reconstruct sparse or compressible signals, which breaks the restrict condition of a traditional Nyquist-Shannon sampling theorem. Here, we give an overview of recent CS studies, along the issues of sensing models, reconstruction algorithms, and their applications. First, we introduce several common sensing methods for CS, like sparse dictionary sensing, block-compressed sensing, and chaotic compressed sensing. We also present several state-of-the-art reconstruction algorithms of CS, including the convex optimization, greedy, and Bayesian algorithms. Lastly, we offer recommendation for broad CS applications, such as data compression, image processing, cryptography, and the reconstruction of complex networks. We discuss works related to CS technology and some CS essentials. © 2020 by the authors.
Development of Liquid Diene Rubber Based Highly Deformable Interactive Fiber-Elastomer Composites
The preparation of intelligent structures for multiple smart applications such as soft-ro-botics, artificial limbs, etc., is a rapidly evolving research topic. In the present work, the preparation of a functional fabric, and its integration into a soft elastomeric matrix to develop an adaptive fiber-elastomer composite structure, is presented. Functional fabric, with the implementation of the shape memory effect, was combined with liquid polybutadiene rubber by means of a low-temperature vulcanization process. A detailed investigation on the crosslinking behavior of liquid polybutadiene rubber was performed to develop a rubber formulation that is capable of crosslinking liquid rubber at 75 °C, a temperature that is much lower than the phase transformation temperature of SMA wires (90–110 °C). By utilizing the unique low-temperature crosslinking protocol for liquid polybutadiene rubber, soft intelligent structures containing functional fabric were developed. The adaptive structures were successfully activated by Joule heating. The deformation behavior of the smart structures was experimentally demonstrated by reaching a 120 mm bending distance at an activation voltage of 8 V without an additional load, whereas 90 mm, 70 mm, 65 mm, 57 mm bending distances were achieved with attached weights of 5 g, 10 g, 20 g, 30 g, respectively.
Integrated Energy System Optimization Based on Standardized Matrix Modeling Method
Aiming at the optimization of an integrated energy system, a standardized matrix modeling method and optimization method for an integrated energy system is proposed. Firstly, from the perspective of system engineering, the energy flow between energy conversion devices is used as a state variable to deal with nonlinear problems caused by the introduction of scheduling factors, and a standardized matrix model of the integrated energy system is constructed. Secondly, based on the proposed model, the structural optimization (i.e., energy flow structure and equipment type), design optimization (i.e., equipment capacity and quantity), and operation optimization for the integrated energy system can be achieved. The simulation case studies have shown that the proposed integrated energy system standardized matrix modeling method and optimization method are both simple and efficient, and can be effectively used to decide the system components and their interconnections, and the technical characteristics and daily operating strategy of the system components.
Biomethane Potential Test: Influence of Inoculum and the Digestion System
High precision of measurement of methane potential is important for the economic operation of biogas plants in the future. The biochemical methane potential (BMP) test based on the VDI 4630 protocol is the state-of-the-art method to determine the methane potential in Germany. The coefficient of variation (CV) of methane yield was >10% in several previous inter-laboratory tests. The aim of this work was to investigate the effects of inoculum and the digestion system on the measurement variability. Methane yield and methane percentage of five substrates were investigated in a Hohenheim biogas yield test (D-HBT) by using five inocula, which were used several times in inter- laboratory tests. The same substrates and inocula were also tested in other digestion systems. To control the quality of the inocula, the effect of adding trace elements (TE) and the microbial community was investigated. Adding TE had no influence for the selected, well- supplied inocula and the community composition depended on the source of the inocula. The CV of the specific methane yield was <4.8% by using different inocula in one D-HBT (D-HBT1) and <12.8% by using different digestion systems compared to D-HBT1. Incubation time between 7 and 14 days resulted in a deviation in CV of <4.8%.