Development of an experimentally validated semi-empirical fully-coupled performance model of a PEM electrolysis cell with a 3-D structured porous transport layer

A semi-empirical non-isothermal model incorporating coupled momentum, heat and mass transport phenomena for predicting the performance of a proton exchange membrane (PEM) water electrolysis cell operating without flow channels is presented. Model input parameters such as electro-kinetics properties and mean pore size of the porous transport layer (PTL) were determined by rotating disc electrode and capillary flow porometry, respectively. This is the first report of a semi-empirical fully coupled model which allows one to quantify and investigate the effect of the gas phase and bubble coverage on PEM cell performance up to very high current densities of about 5 A/cm². The mass transport effects are discussed in terms of the operating conditions, design parameters and the microstructure of the PTL. The results show that, the operating temperature and pressure, and the inlet water flowrate and thickness of the PTL are the critical parameters for mitigating mass transport limitation at high current densities. The model presented here can serve as a tool for further development and scale-up effort in the area of PEM water electrolysis, and provide insight during the design stage.     

Performance characteristics of Mo–Ni/Al2O3 catalysts in LPG oxidative steam reforming for hydrogen production

A 1:1 propane–butane mixture was used to study the effect of promoting 15 wt.% Ni/Al₂O₃ (15Ni) catalyst with small amounts of Mo (0.05, 0.1, 0.3, and 0.5 wt.%) for H₂ production during LPG oxidative steam reforming. Stability tests at 450 °C showed that lower Mo loadings (0.1 and 0.05 wt.%) had higher conversions and H₂ production rates than the non-promoted catalyst and a stable performance for the whole 18-h test period. TPO results showed that slightly more Ni sites were available for whisker formation over the Mo catalyst with 0.1 wt.% loading, the types of carbon resulting from cracking were the same on both promoted and non-promoted catalysts. Higher Mo loaded catalysts (0.3 and 0.5 wt.%) showed higher H₂ yields than the non-promoted catalysts, but lower feed-fuel conversions. XRD revealed that the loss in activity was due to oxidation of active Ni species to inactive Ni and Ni–Mo.     

Numerical modeling of CdS/CdTe and CdS/CdTe/ZnTe solar cells as a function of CdTe thickness

CdTe-based solar cells have long been of interest for terrestrial usage because of their high potential conversion efficiency (in the range of 18–24%) with low-cost manufacturability and concern over environmental effects. In order to conserve material and address environmental pollution concerns as well as to reduce carrier recombination loss throughout the absorber layer, efforts have been carried out to decrease the thickness of the CdTe absorption layer to 1 μm. As a result, to date, the experimental part of this study has realized cell efficiencies of 15.3% and 11.5% with 7 and 1.2-μm-thick CdTe layers, grown by close-spaced sublimation (CSS) [N. Amin, T. Isaka, T. Okamoto, A. Yamada, M. Konagai, Jpn. J. Appl. Phys. 38 (8) (1999) 4666; N. Amin, T. Isaka, A. Yamada, M. Konagai, Sol. Energy Matter. Sol. Cells 67 (2001) 195]. Since some problems remain with such thin 1 μm CdTe layers, possible methods to realize higher efficiency have been investigated using novel solar cell structures, with the help of numerical analyses tools. In the theory part of this study, numerical analysis with a 1-D simulation program named NSSP (Numerical Solar Cell Simulation Program) has been used to simulate these structures. We investigated the viability of CdTe thickness reduction to 1 μm together with the insertion of higher band-gap materials (i.e., ZnTe) at the back contacts to reduce carrier recombination loss there. The study shows potential results of the thickness reduction of CdTe absorption layer for a conventional CdS/CdTe/Cu-doped C structure with around 16% efficiency for cells below 3  μm CdTe. Decreases were found in spectral response that suggest from minority carrier recombination loss at the back contact interface. A higher band-gap material like ZnTe has been inserted to produce a back surface field (BSF) to inhibit the minority carrier loss at the back contact. An increase in the efficiency to about 20% has been found for a 1 μm-thin CdTe cell, which can be attributed to the increased BSF effect at the back contact of thinner CdTe-based cells.     

Two-dimensional problem for thermoviscoelastic materials with fractional order heat transfer

Abstract

The model of equations of thermo-viscoelasticity with fractional order heat transfer is constructed. Some fundamental theorems on the linear coupled and generalized theories of thermo-viscoelasticity can be easily obtained as special cases. The medium is assumed initially quiescent. Laplace and Fourier integral transforms are utilized. The method of the matrix exponential which constitutes the basis of the state–space approach of modern control theory is applied to the system of two-dimensional equations. The resulting formulation is applied to a thermal shock half-space problem. The inversion process for Fourier and Laplace transforms is carried out using numerical method based on Fourier series expansions. Numerical results are given and illustrated graphically for the problem considered. Comparisons are made with the results predicted by the coupled theory and generalized theory. The effect of the fractional order parameter on all the considered fields is examined.     

Aspen plus simulation of heavy oil gasification in a fluidized bed gasifier

Gasification is a clean technology to convert fuels to high-quality syngas in presence of a gasifying agent. In this study, an Aspen Plus model of heavy oil gasification was developed to produce the hydrogen rich syngas. Effect of some parameters such as gasification temperature and steam/fuel ratio on the hydrogen yield and was investigated. Results showed that the temperature plays a major role in the process; higher temperatures produce the higher hydrogen content. It was also found that the operation under high steam/fuel ratio can cause a significant increase in the hydrogen yield. The modeling results were compared with the experimental data available in the literature and found to be in good agreement.     

The preparation of an amino acid-based surfactant and its potential application as an EOR agent

Most of the synthetic surfactants investigated with the aim of enhanced chemically oil recovery in the literature have environmental drawbacks. In this work, application of an environmentally-friendly synthetic surfactant as an enhanced oil recovery agent is introduced by measuring interfacial tension of water–kerosene systems and wettability alteration of carbonate pellets. For this purpose, an amino acid-based surfactant was initially synthesized using a new synthetic approach which was subsequently confirmed by spectra of Fourier transform infrared and Proton nuclear magnetic resonance. Results showed a value of critical micelle concentration in the range of 9000–9100 ppm for this surfactant. Results also demonstrated a decrease of 38.53% in water–kerosene system interfacial tension and a 17.76% reduction in oil-wetness of the carbonate pellets.     

Application of LS-SVM strategy to estimate H2S loading capacity in different ionic liquids and alkanolamines

Favorable properties of aqueous solutions are improved with the addition of different materials for separation of hydrogen sulfide (H₂S). Also, equilibrium data and available equations for solubility estimation of this gas are only valid for specific solutions and limited ranges of temperature and pressure. In this regard, a machine learning model based on Support vector machine (SVM) algorithm is proposed and developed with mixtures containing different amines and ionic liquids to predict H₂S solubility over wide ranges of temperature (298–434.5 K), pressure (13–9319 kPa), overall mass concentration (3.82–100%) and mixture's apparent molecular weight (18.39–556.17 g/mol). The accuracy of the performance of this network was evaluated by regression analysis on calculated and experimental data, which had not been used in network training.     

Adaptive response of Listeria monocytogenes to heat and its impact on food safety

Listeria monocytogenes is an important food associated pathogen because of its relatively high heat resistance and ability to multiply in refrigeration temperatures. Its thermotolerance can be increased when its cells are subjected to heat shock. One- to eight-fold increase of D values of L. monocytogenes have been reported, depending on the heat shock duration, the temperature and the heating menstrum. This acquisition of heat tolerance is related to the induction of the synthesis of heat shock proteins (HSPs).The adaptive response of food pathogens has important consequences on the safety of thermally processed foods. It is believed that this is responsible for the frequent occurrence of deviations (tails and shoulders) during heat treatments that are observed in the exponential model of microbial inactivation. These deviations from log-linear kinetic especially encountered under mild heat treatments, mean that prediction of food safety can no longer rely upon D and z values. Adaptive response to heat must be considered when quantifying and modeling microbial inactivation during thermal processing in order to achieve microbiologically safe products without overly conservative heat processes. Therefore a more mechanistic approach is needed for more accurate predictions of thermal inactivation. Prerequisite to this model are thorough studies to understand how L. monocytogenes and other pathogens adapt their cellular physiology to overcome heat and other stresses.     

Prediction of carbon dioxide separation from gas mixtures in petroleum industries using the Levenberg–Marquardt algorithm

In this study, two mathematical models for hydrate formation process to separate carbon dioxide by a combination of two different kinds of organic and surfactant promoters are presented. Promoters such as sodium dodecyl sulfate, sodium dodecyl benzene sulfonate, and dodecyl trimethyl ammonium chloride as surfactant promoters; also, tetrahydrofuran, cyclopentane, 1,3-dioxolane, and 2-methyl tetrahydrofuran as organic promoters have been used in recent years. The results showed that a combination of 3000 ppm of surfactant promoters and 4 wt% organic promoters had the highest separation rate of carbon dioxide and; consequently, the investigated models were based on this optimum condition. As a matter of fact, by using these simulations the hydrate formation behavior was predicted with high accuracy; moreover, conducting consuming experiments is not essential anymore. To sum up, in the present research both Vandermonde matrix model and Levenberg-Marquardt algorithm were applied to predict the hydrate formation behavior; in addition, their results were precisely considered and validated with experimental data.     

On the prediction of solubility of alkane in carbon dioxide using the LSSVM algorithm

The increasing global energy demand and declination of oil reservoir in recent years cause the researchers attention focus on the enhancement of oil recovery approaches. One of the extensive applicable methods for enhancement of oil recovery, which has great efficiency and environmental benefits, is carbon dioxide injection. The CO₂ injection has various effects on the reservoir fluid, which causes enhancement of recovery. One of these effects is extraction of lighter components of crude oil, which straightly depends on solubility of hydrocarbons in carbon dioxide. In order to better understand of this parameter, in this study, Least squares support vector machine (LSSVM) algorithm was developed as a novel predictive tool to estimate solubility of alkane in CO₂ as function of carbon number of alkane, carbon dioxide density, pressure, and temperature. The predicting model outputs were compared with the extracted experimental solubility from literature statistically and graphically. The comparison showed the great ability and high accuracy of developed model in prediction of solubility.