Flame retardancy and mechanical properties of pet‐based composites containing phosphorus and boron‐based additives

Flame retardancy of poly(ethylene terephthalate), PET, was improved using different flame retardant additives such as triphenylphosphate, triphenylphosphine oxide, zinc borate, and boron phosphate (BP). Composites were prepared using a twin screw extruder and subsequently injection molded for characterization purposes. The flame retardancy of the composites was determined by the limiting oxygen index (LOI) test. Smoke emission during fire was also evaluated in terms of percent light transmittance. Thermal stability and tensile properties of PET‐based composites were compared with PET through TGA and tensile test, respectively. The LOI of the flame retardant composites increased from 21% of neat PET, up to 36% with the addition of 5% BP and 5% triphenyl phosphate to the matrix. Regarding the smoke density analysis, BP was determined as an effective smoke suppressant for PET. Enhanced tensile properties were obtained for the flame retardant PET‐based composites with respect to PET. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42016.     

Investigation of a novel & integrated simulation model for hydrogen production from lignocellulosic biomass

Process simulation and modeling works are very important to determine novel design and operation conditions. In this study; hydrogen production from synthesis gas obtained by gasification of lignocellulosic biomass is investigated. The main motivation of this work is to understand how biomass is converted to hydrogen rich synthesis gas and its environmentally friendly impact. Hydrogen market development in several energy production units such as fuel cells is another motivation to realize these kinds of activities. The initial results can help to contribute to the literature and widen our experience on utilization of the CO₂ neutral biomass sources and gasification technology which can develop the design of hydrogen production processes. The raw syngas is obtained via staged gasification of biomass, using bubbling fluidized bed technology with secondary agents; then it is cleaned, its hydrocarbon content is reformed, CO content is shifted (WGS) and finally H₂ content is separated by the PSA (Pressure Swing Adsorption) unit. According to the preliminary results of the ASPEN HYSYS conceptual process simulation model; the composition of hydrogen rich gas (0.62% H₂O, 38.83% H₂, 1.65% CO, 26.13% CO₂, 0.08% CH₄, and 32.69% N₂) has been determined. The first simulation results show that the hydrogen purity of the product gas after PSA unit is 99.999% approximately. The mass lower heating value (LHV_mass) of the product gas before PSA unit is expected to be about 4500 kJ/kg and the overall fuel processor efficiency has been calculated as ～93%.     

Emotion recognition from EEG signals by using multivariate empirical mode decomposition

This paper explores the advanced properties of empirical mode decomposition (EMD) and its multivariate extension (MEMD) for emotion recognition. Since emotion recognition using EEG is a challenging study due to nonstationary behavior of the signals caused by complicated neuronal activity in the brain, sophisticated signal processing methods are required to extract the hidden patterns in the EEG. In addition, multichannel analysis is another issue to be considered when dealing with EEG signals. EMD is a recently proposed iterative method to analyze nonlinear and nonstationary time series. It decomposes a signal into a set of oscillations called intrinsic mode functions (IMFs) without requiring a set of basis functions. In this study, a MEMD-based feature extraction method is proposed to process multichannel EEG signals for emotion recognition. The multichannel IMFs extracted by MEMD are analyzed using various time and frequency domain techniques such as power ratio, power spectral density, entropy, Hjorth parameters and correlation as features of valance and arousal scales of the participants. The proposed method is applied to the DEAP emotional EEG data set, and the results are compared with similar previous studies for benchmarking.     

On modelling of surface tension of CMC-α-Fe2O3 nanoparticles by fuzzy-hybrid approach: A comparison study

Surface tension is one of the most important rheological parameters of nanoliquids. It influences the thermophysical and mass transfer properties of nanostructures. Accurate estimation of the surface tension from operating variables is critical for determining optimal production processes. However, the challenges of producing nanoparticles and measuring their properties introduce experimental errors in the data used for mathematical modelling. Crisp regression approaches provide adequate representation of the data, but they do not provide information about the experimental uncertainty. In this study, a fuzzy-hybrid approach is proposed for mathematical modelling of surface tension of carboxymethyl cellulose/chitosan-α-Fe₂O₃ nanoparticles. Then, the proposed model is compared with a crisp model from a previous study. Error analysis is conducted to validate the constructed fuzzy model. It is observed that the fuzzy-hybrid modelling approach has yielded significantly lower error values (a 60%–90% improvement in all error metrics on average), and thus, it is superior to the crisp approach. This study contributes to the subject of modelling rheological properties. It is shown that the fuzzy-hybrid approach has impressive potential to be utilized for modelling the rheological properties of nanostructures.     

Optimization of nanofiber-caproate/laurate esters synthesis,their characterization,and usage as emulsifier in o/w emulsion

The aim of this study is to optimize the esterification of nanofibers with caproyl/lauroyl chlorides at different substitution degrees' (DS) and to investigate the usage of nanofiber derivatives in model emulsions. First, cellulosic material was obtained and milled into nanofibers using a micro-fluidizer. Then, these nanofibers were esterified with caproyl/lauroyl chlorides in a solvent of DMAc/LiCl with DMAP as an acid scavenger. The esterification of nanofibers with caproyl/lauroyl chlorides was optimized for fatty acid chloride mole and reaction time. Esterification reactions were carried out at 80°C with various molar ratios of acyl chlorides (3–15 moles) versus anhydroglucose unit of nanofibers and for various time durations (30–360 min). The hydrophobic derivatives with DS in the range of 0.34–2.77 were successfully obtained. Using the data obtained as a result of the optimization, nanofiber-fatty acid esters with different DS (0.50–2.75) were produced and characterized. Analyzes showed that the esterification process was successful and as the degree of esterification increased, the crystallinity index and thermal stability of the derivatives decreased. Then, the nanofiber-caproate/laurate esters with different DS were used as emulsifier (0.5 wt%) in an oil-in-water model emulsion containing 25 wt% oil and the emulsions were analyzed. The nanofiber caproate/laurate esters with a DS of 0.50–1.25 were suitable for o/w emulsions, while samples with a DS of 2.00 and above were not found suitable. Emulsions prepared by using nanofiber derivatives with 1.25 DS had higher G′ and G″ and viscosity values and lower droplet sizes than those of other group.