Residual thermal strains and stresses in organic matrix composite materials

ABSTRACT

Residual strain/stress may arise in organic matrix composite materials due to the intrinsic heterogeneity of their elementary constituents (polymer matrix and fibrous reinforcements), for instance, during material processing, thermal cycling, for harsh in-service conditions. This article illustrates some method to “measure” residual/internal strains/stresses of thermal origin—at both the microscopic and the mesoscopic levels—by inverse analysis of the matrix shrinkage profiles between fibers in unidirectional composite (at the microscopic scale) and the measure of the deflection (curvature) of 0/90 unsymmetric plates (mesoscopic scale). The analysis is carried out by using multiphysical phenomenological models.     

Boosting Perovskite Solar Cells Performance and Stability through Doping a Poly‐3(hexylthiophene) Hole Transporting Material with Organic Functionalized Carbon Nanostructures

Perovskite solar cells (PSCs) are demonstrating great potential to compete with second generation photovoltaics. Nevertheless, the key issue hindering PSCs full exploitation relies on their stability. Among the strategies devised to overcome this problem, the use of carbon nanostructures (CNSs) as hole transporting materials (HTMs) has given impressive results in terms of solar cells stability to moisture, air oxygen, and heat. Here, the use of a HTM based on a poly(3‐hexylthiophene) (P3HT) matrix doped with organic functionalized single walled carbon nanotubes (SWCNTs) and reduced graphene oxide in PSCs is proposed to achieve higher power conversion efficiencies (η = 11% and 7.3%, respectively) and prolonged shelf‐life stabilities (480 h) in comparison with a benchmark PSC fabricated with a bare P3HT HTM (η = 4.3% at 480 h). Further endurance test, i.e., up to 3240 h, has shown the failure of all the PSCs based on undoped P3HT, while, on the contrary, a η of ≈8.7% is still detected from devices containing 2 wt% SWCNT‐doped P3HT as HTM. The increase in photovoltaic performances and stabilities of the P3HT‐CNS‐based solar cell, with respect to the standard P3HT‐based one, is attributed to the improved interfacial contacts between the doped HTM and the adjacent layers.     

Nanoimprinted,Submicrometric, MOF‐Based 2D Photonic Structures: Toward Easy Selective Vapors Sensing by a Smartphone Camera

In this work, a soft‐lithographic approach to fabricate submicrometer metal organic framework (MOF)‐based 2D photonic structures is described. Nanometric zeolitic imidazole framework material ZIF‐8 (zinc) is chosen as the sensible MOF material because of its chemical stability and its vapor selective adsorption properties. Two different systems are fabricated: nanopatterned colloidal ZIF‐8 homo‐ and ZIF‐8/TiO₂ heterostructures. Several features (stripes, squares, etc.) with dimensions of 200 nm are replicated on different substrates such as silicon, flexible plastics, and even aluminum cans, over relatively large surfaces (up to 1 cm²). In addition, the use of these photonic MOF‐heterostructures as very low‐cost sensing platforms compatible with smartphone technology is demonstrated. This method relies on the evaluation of the change in diffraction efficiency of the photonic MOF‐patterns, induced by the MOF refractive index variation, which is simply detected by a charge coupled device (CCD) camera, as those integrated in smartphones, without need for complex optical instrumentations for transduction data processing. Performances of the sensors are first evaluated using isopropyl alcohol adsorption/desorption cycling as a model case. In addition, a “real” environmental issue is tackled. Selective detection of styrene in presence of interfering water is demonstrated at concentrations below the human permissible exposure limit. In situ ellispometric analyses are also carried out in order to confirm the sensor performances and to propose a mechanism for styrene uptake into the nanoMOFs.     

Metal Organic Framework Crystals in Mixed‐Matrix Membranes: Impact of the Filler Morphology on the Gas Separation Performance

Mixed‐matrix membranes comprising NH₂‐MIL‐53(Al) and Matrimid or 6FDA‐DAM have been investigated. The metal organic framework (MOF) loading has been varied between 5 and 20 wt%, while NH₂‐MIL‐53(Al) with three different morphologies, nanoparticles, nanorods, and microneedles has been dispersed in Matrimid. The synthesized membranes have been tested in the separation of CO₂ from CH₄ in an equimolar mixture. At 3 bar and 298 K for 8 wt% MOF loading, incorporation of NH₂‐MIL‐53(Al) nanoparticles leads to the largest improvement compared to nanorods and microneedles. The incorporation of the best performing filler, i.e., NH₂‐MIL‐53(Al) nanoparticles, into the highly permeable 6FDA‐DAM has a larger effect, and the CO₂ permeability increases up to 85% with slightly lower selectivities for 20 wt% MOF loading. Specifically, these membranes have a permeability of 660 Barrer with a CO₂/CH₄ separation factor of 28, leading to a performance very close to the Robeson limit of 2008. Furthermore, a new non‐destructive technique based on Raman spectroscopy mapping is introduced to assess the homogeneity of the filler dispersion in the polymer matrix. The MOF contribution can be calculated by modeling the spectra. The determined homogeneity of the MOF filler distribution in the polymer is confirmed by focused ion beam scanning electron microscopy analysis.     

Complete stability of feedback CNNs with dynamic memristors and second‐order cells

The paper considers a feedback cellular neural network (CNN) obtained by interconnecting elementary cells with an ideal capacitor and an ideal flux‐controlled memristor. It is supposed that during the analogue computation of the CNN the memristors behave as dynamic elements, so that each dynamic memristor (DM)‐CNN cell is described by a second‐order differential system in the state variables given by the capacitor voltage and the memristor flux. The proposed networks are called DM‐CNNs, that is CNNs using a dynamic (D) memristor (M). After giving a foundation to the DM‐CNN model, the paper establishes a fundamental result on complete stability, that is convergence of solutions toward equilibrium points, when the DM‐CNN has symmetric interconnections. Because of the presence of dynamic memristors, a DM‐CNN displays peculiar and basically different dynamic properties with respect to standard CNNs. First of all a DM‐CNN computes during the time evolution of the memristor fluxes, instead of the capacitor voltages as for a standard CNN. Furthermore, when a steady state is reached, the memristors keep in memory the result of the computation, that is the limiting values of the fluxes, while all memristor currents and voltages, as well as all currents, voltages, and power in the DM‐CNN vanish. Instead, for standard CNNs, currents, voltages, and power do not drop off when a steady state is reached. Copyright © 2016 John Wiley & Sons, Ltd.     

Sensing Pollution on Online Social Networks: A Transportation Perspective

Transportation policy and planning strategies, as well as Intelligent Transportation Systems (ITS), can all play important roles in decreasing pollution levels and their negative effects. Interestingly, limited effort has been devoted to exploring the potential of social network analysis in such context. Social networks provide direct feedback from people and, hence, potentially valuable information. A post telling how a person feels about pollution at a given time at a given location, could be useful to policy-makers, planners or environmentally-aware ITS designers. This work verifies the feasibility of sensing air pollution from social networks and of integrating such information with real sensors feeds, unveiling how people advertise such phenomenon, acting themselves as smart objects, and how online posts relate to true pollution levels. This work explores a new dimension in pollution sensing for the benefit of environmental and transportation research in future smart cities, confronting over 1,500,000 posts and pollution readings obtained from governmental on-the-field sensors over a one-year span.     

Near- and Far-Field Characterization of Planar mm-Wave Antenna Arrays with Waveguide-to-Microstrip Transition

We present the design and characterization of planar mm-wave patch antenna arrays with waveguide-to-microstrip transition using both near- and far-field methods. The arrays were designed for metrological assessment of error sources in antenna measurement. One antenna was designed for the automotive radar frequency range at 77 GHz, while another was designed for the frequency of 94 GHz, which is used, e.g., for imaging radar applications. In addition to the antennas, a simple transition from rectangular waveguide WR-10 to planar microstrip line on Rogers 3003? substrate has been designed based on probe coupling. For determination of the far-field radiation pattern of the antennas, we compare results from two different measurement methods to simulations. Both a far-field antenna measurement system and a planar near-field scanner with near-to-far-field transformation were used to determine the antenna diagrams. The fabricated antennas achieve a good matching and a good agreement between measured and simulated antenna diagrams. The results also show that the far-field scanner achieves more accurate measurement results with regard to simulations than the near-field scanner. The far-field antenna scanning system is built for metrological assessment and antenna calibration. The antennas are the first which were designed to be tested with the measurement system.     

Kinetic modulation of pulsed chronopotentiometric polymeric membrane ion sensors by polyelectrolyte multilayers

Polymeric membrane ion-selective electrodes are normally interrogated by zero current potentiometry, and their selectivity is understood to be primarily dependent on an extraction/ion-exchange equilibrium between the aqueous sample and polymeric membrane. If concentration gradients in the contacting diffusion layers are insubstantial, the membrane response is thought to be rather independent of kinetic processes such as surface blocking effects. In this work, the surface of calcium-selective polymeric ion-selective electrodes is coated with polyelectrolyte multilayers as evidenced by zeta potential measurements, atomic force microscopy, and electrochemical impedance spectroscopy. Indeed, such multilayers have no effect on their potentiometric response if the membranes are formulated in a traditional manner, containing a lipophilic ion exchanger and a calcium-selective ionophore. However, drastic changes in the potential response are observed if the membranes are operated in a recently introduced kinetic mode using pulsed chronopotentiometry. The results suggest that the assembled nanostructured multilayers drastically alter the kinetics of ion transport to the sensing membrane, making use of the effect that polyelectrolyte multilayers have different permeabilities toward ions with different valences. The results have implications to the design of chemically selective ion sensors since surface-localized kinetic limitations can now be used as an additional dimension to tune the operational ion selectivity.     

An improved method for Organic Bound Tritium (OBT) determination in urine samples

The Organic Bound Tritium (OBT) amount in the body may induce changes in the evaluation of the internal exposure to tritium, due to its different retention time relative to HTO. OBT measurements for urine are not performed routinely, mainly because of the lengthy work needed in preparation of the samples, when using the standard oxygen combustion method. A simpler and more rapid method based on liquid scintillation counting (LSC) was employed, and an evaluation was performed to check its suitability for urine samples. The principle of the proposed method is based on subtracting the LSC counts of the water phase sample (HTO) from the total activity of the urine sample (OBT+HTO). A good correlation was found between the results obtained when applying the proposed direct method and the Gold standard method. The minimum detectable activity when using this method was determined.