Toward optimization of a robust low-cost sulfonated-polyethersulfone containing layered double hydroxide for PEM fuel cells

Polyethersulphone (PES) is an aromatic thermoplastic, at low environmental impact, evaluated in this work as a promising candidate for new polymer electrolytes in the PEMFCs technology. A sulfonation procedure has been tuned in order to graft sulfonic acid groups on the polymer chains (sPES) and to make it hydrophilic. Homogeneous membranes with different polymer's sulfonation degrees (SD%) have demonstrated excellent mechanical properties and very low permeability toward methanol (important in the DMFCs), even if low proton conductivity. Nanocomposite sPES membranes were prepared by dispersion of highly hydrophilic lamellar particles such as layered double hydroxide (LDH) in the polymer. Deep investigations performed by a combination of PFG-NMR, EIS, XRD, DMA, and scanning electron microscopy have evidenced the exfoliation of the lamellae in polymer matrix. However, a certain anisotropy was evidenced both in the morphology and molecular diffusion, favored in the longitudinal direction (parallel to surface), while completely inhibited in the cross-section. This finding is most likely induced by the polymer structure, therefore particular attention must be paid to the choice of the filler and preparation of the composites. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47884.     

Charting of geoelectric potential signal dynamics via geometrical techniques and its possible relation to significant earthquakes in Western Greece

An exploratory data analysis (EDA) framework was developed in order to investigate the presence of possible correlations in the long-term geoelectric potential (LTGP) signal, prior to significant seismic events in Western Greece. Experimental data, which had been collected continuously within a 6-year period (1998–2003) at the earthquake signal-acquisition center of the University of Patras Seismological Laboratory (UPSL), were studied. The multidimensional scaling (MDS) technique was used to detect putative clustering tendencies in the ensemble of time-series (TS) segments that could indicate the existence of a possible correlation between the geoelectric signal structure and the impending seismic activity. The end result is a 2-dimensional point diagram with the geometry reflecting important signal characteristics, directly related with the underlying seismic events. In addition, the “appending technique”, a well-suited data analysis methodology was incorporated as a means of relating any other TS segment directly with the pre-computed, via the MDS, point diagram. Using the proposed EDA framework, we examined the presence of similar temporal patterns in the recorded geoelectric TS field, 10 days before the occurrence of the major earthquakes. The presented experimental results indicated clearly the validity of the introduced approach and, further, motivated the use of such advanced visualization schemes for charting precursor trends of significance seismicity.     

Dynamic light scattering and ultrasonic investigations during the cure reaction of an epoxy resin

Brillouin scattering (BS), photon correlation spectroscopy (PCS), and ultrasonic (US) measurements were conducted to study the curing process of diglycidyl ether of bisphenol A with butane-1,4-diol at a curing temperature of 100°C. The experimental techniques probe the primary glass-rubber transition during the curing reaction. The primary relaxation time τ obtained from the BS and US velocity and absorption increases with curing time and hence the BS experiment measures τ at earlier stages of cure than the US experiment. The relaxation times at a different extent of reaction and for different measuring temperatures are consistent with BS, US, PCS, and DSC measurements and conform to a single reduced Vogel–Fulcher–Hesse–Tamann equation. Furthermore, the US experiments show evidence of secondary relaxations in the epoxy system.     

ON THE DYNAMIC PROPERTIES OF THE EXTENSIVE VARIABLE CONTROL STRUCTURES

The purpose of this paper is to investigate the dynamic properties of controller structures synthesized using extensive thermodynamic variables of a process. Several state-space and frequency domain multivariable techniques, including INA, and Modal Interaction Analysis, are used in order to evaluate the dynamic properties of these control structures. These structures show zero steady state interaction and minimal dynamic interaction for all processes examined. Dynamic simulation of several application examples, including distillation columns and a network of two stirred tank heaters in series, shows that the loops in these structures can also be tuned with minimum effort. Comparison of the proposed structures, with the conventional parallel single-input single-output control structures, shows the advantages of the proposed method.     

Adaptive Smooth Simulcast Protocol (ASSP) for Video Applications: Description and Performance Evaluation

In this paper, we present Adaptive Smooth Simulcast Protocol (ASSP) for simulcast transmission of multimedia data over best-effort networks. ASSP is a new multiple-rate protocol that implements a single rate TCP-friendly protocol as the underlying congestion control mechanism for each simulcast stream. The key attributes of ASSP are: (a) TCP-friendly behavior, (b) adaptive per-stream transmission rates, (c) adaptive scalability to large sets of receivers and (d) smooth transmission rates that are suitable for multimedia applications. We evaluate the performance of ASSP under an integrated simulation environment which combines the measurements of both network and video performance metrics. We also compare ASSP against other proposed solutions and the results demonstrate that the performance of ASSP is significantly better than the tested solutions. Finally, ASSP is a practical solution with very low implementation complexity for video transmission over best-effort networks.     

On the efficiency of user identification: a system-based approach

In the Internet era, users’ fundamental privacy and anonymity rights have received significant research and regulatory attention. This is not only a result of the exponential growth of data that users generate when accomplishing their daily task by means of computing devices with advanced capabilities, but also because of inherent data properties that allow them to be linked with a real or soft identity. Service providers exploit these facts for user monitoring and identification, albeit impacting users’ anonymity, based mainly on personal identifiable information or on sensors that generate unique data to provide personalized services. In this paper, we report on the feasibility of user identification using general system features like memory, CPU and network data, as provided by the underlying operating system. We provide a general framework based on supervised machine learning algorithms both for distinguishing users and informing them about their anonymity exposure. We conduct a series of experiments to collect trial datasets for users’ engagement on a shared computing platform. We evaluate various well-known classifiers in terms of their effectiveness in distinguishing users, and we perform a sensitivity analysis of their configuration setup to discover optimal settings under diverse conditions. Furthermore, we examine the bounds of sampling data to eliminate the chances of user identification and thus promote anonymity. Overall results show that under certain configurations users’ anonymity can be preserved, while in other cases users’ identification can be inferred with high accuracy, without relying on personal identifiable information.     

Evaluation of hydrogen producing cultures using pretreated food waste

In order to enhance bio-hydrogen production from food waste, pretreatment methods are widely used. The influence of the initial pH and autoclaving were investigated in batch experiments. Fermentative studies showed that pure cultures like Clostridium beijerinckii could directly utilize raw food waste to produce hydrogen, while other cultures (Clostridium butyricum and Clostridium pasteurianum) could produce hydrogen only after pH adjustment. In this case, the optimal starting pH of the culture was found to be 7. Autoclaving could further enhance hydrogen yields due to increased hydrolysis of food waste. The maximum hydrogen yield was achieved by C. butyricum (38.9 mL-H₂/g-VS_added) after autoclaving food waste with pH adjustment at 7. In addition, the ratio acetic to butyric acid was decreased by autoclaving pretreatment, because butyrate metabolic pathway was favored in the fermentation process. However, suitable pH for bacteria growth and the low ammonia production could be achieved from autoclaving food waste.     

Effect of particle tethering and Scale‐Up on solid–liquid mass transfer in Three‐Phase fluidized beds of light particles

Solid–liquid mass transfer in three‐phase fluidized beds with low‐density particles was studied using a tethered benzoic acid particle dissolution technique. Two columns with air, water and polypropylene cylinders were used for experiments. The solid–liquid mass transfer coefficient was found to increase with column diameter but decrease with tether length. The effect of tethering on solid particle movements was also evaluated using radioactive particle tracking (RPT) technique. RPT showed that tethered particles exhibited slower movements. Statistical analysis suggests that tether lengths 3 times the column radius are sufficient to reduce the effects of tethering.