Abstract: In the present study, an ecofriendly biocomposite namely calcium alginate immobilized Ammi Visnaga (Khella) extraction waste (SWAV/CA) was prepared by electrostatic extrusion method and used on the cadmium biosorption from aqueous phase with and without the assistance of ultrasound in batch conditions. The influence of low frequency ultrasound (37 and 80 KHz) on the cadmium biosorption kinetics was studied. The obtained results show that the ultrasonic irradiation significantly enhances and improves the efficiency of the cadmium removal. The Pseudo first order, Pseudo-second-order, Intraparticle diffusion, and Elovich models were evaluated using the non-linear curve fitting analysis method. Modeling of kinetic results shows that biosorption process is best described by the pseudo-second order and Elovich, in both the absence and presence of ultrasound.
Abstract: Strong anion exchange resins with QN+OH-, have the
potential to be developed and employed as heterogeneous catalyst for
transesterification, as they are chemically stable to leaching of the
functional group. Nine different SIERs (SIER1-9) with QN+OH-were
prepared by suspension polymerization of vinylbenzyl chloridedivinylbenzene
(VBC-DVB) copolymers in the presence of n-heptane
(pore-forming agent). The amine group was successfully grafted into
the polymeric resin beads through functionalization with
trimethylamine. These SIERs are then used as a catalyst for the
transesterification of triacetin with methanol. A set of differential
equations that represents the Langmuir-Hinshelwood-Hougen-
Watson (LHHW) and Eley-Rideal (ER) models for the
transesterification reaction were developed. These kinetic models of
LHHW and ER were fitted to the experimental data. Overall, the
synthesized ion exchange resin-catalyzed reaction were welldescribed
by the Eley-Rideal model compared to LHHW models,
with sum of square error (SSE) of 0.742 and 0.996, respectively.
Abstract: The study is devoted to define the optimal conditions
for the nitriding of pure iron at atmospheric pressure by using NH3-
Ar-C3H8 gas mixtures. After studying the mechanisms of phase
formation and mass transfer at the gas-solid interface, a mathematical
model is developed in order to predict the nitrogen transfer rate in the
solid, the ε-carbonitride layer growth rate and the nitrogen and
carbon concentration profiles. In order to validate the model and to
show its possibilities, it is compared with thermogravimetric
experiments, analyses and metallurgical observations (X-ray
diffraction, optical microscopy and electron microprobe analysis).
Results obtained allow us to demonstrate the sound correlation
between the experimental results and the theoretical predictions.
Abstract: Poly-β-hydroxybutyrate (PHB) is one of the most
famous biopolymers that has various applications in production of
biodegradable carriers. The most important strategy for enhancing
efficiency in production process and reducing the price of PHB, is the
accurate expression of kinetic model of products formation and
parameters that are effective on it, such as Dry Cell Weight (DCW)
and substrate consumption. Considering the high capabilities of
artificial neural networks in modeling and simulation of non-linear
systems such as biological and chemical industries that mainly are
multivariable systems, kinetic modeling of microbial production of
PHB that is a complex and non-linear biological process, the three
layers perceptron neural network model was used in this study.
Artificial neural network educates itself and finds the hidden laws
behind the data with mapping based on experimental data, of dry cell
weight, substrate concentration as input and PHB concentration as
output. For training the network, a series of experimental data for
PHB production from Hydrogenophaga Pseudoflava by glucose
carbon source was used. After training the network, two other
experimental data sets that have not intervened in the network
education, including dry cell concentration and substrate
concentration were applied as inputs to the network, and PHB
concentration was predicted by the network. Comparison of predicted
data by network and experimental data, indicated a high precision
predicted for both fructose and whey carbon sources. Also in present
study for better understanding of the ability of neural network in
modeling of biological processes, microbial production kinetic of
PHB by Leudeking-Piret experimental equation was modeled. The
Observed result indicated an accurate prediction of PHB
concentration by artificial neural network higher than Leudeking-
Piret model.
Abstract: Functional imaging procedures for the non-invasive assessment of tissue microcirculation are highly requested, but require a mathematical approach describing the trans- and intercapillary passage of tracer particles. Up to now, two theoretical, for the moment different concepts have been established for tracer kinetic modeling of contrast agent transport in tissues: pharmacokinetic compartment models, which are usually written as coupled differential equations, and the indicator dilution theory, which can be generalized in accordance with the theory of lineartime- invariant (LTI) systems by using a convolution approach. Based on mathematical considerations, it can be shown that also in the case of an open two-compartment model well-known from functional imaging, the concentration-time course in tissue is given by a convolution, which allows a separation of the arterial input function from a system function being the impulse response function, summarizing the available information on tissue microcirculation. Due to this reason, it is possible to integrate the open two-compartment model into the system-theoretic concept of indicator dilution theory (IDT) and thus results known from IDT remain valid for the compartment approach. According to the long number of applications of compartmental analysis, even for a more general context similar solutions of the so-called forward problem can already be found in the extensively available appropriate literature of the seventies and early eighties. Nevertheless, to this day, within the field of biomedical imaging – not from the mathematical point of view – there seems to be a trench between both approaches, which the author would like to get over by exemplary analysis of the well-known model.
Abstract: In the following text, we show that by introducing
universal kinetic scheme, the origin of rate retardation and inhibition
period which observed in dithiobenzoate-mediated RAFT
polymerization can be described properly. We develop our model by
utilizing the method of moments, then we apply our model to
different monomer/RAFT agent systems, both homo- and
copolymerization. The modeling results are in an excellent
agreement with experiments and imply the validity of universal
kinetic scheme, not only for dithiobenzoate-mediated systems, but
also for different types of monomer/RAFT agent ones.
Abstract: The purpose of this study was to understand the main
sources of copper (Cu) accumulation in target organs of tilapia
(Oreochromis mossambicus) and to investigate how the organism
mediate the process of Cu accumulation under prolonged conditions.
By measuring both dietary and waterborne Cu accumulation and total
concentrations in tilapia with biokinetic modeling approach, we were
able to clarify the biokinetic coping mechanisms for the long term Cu
accumulation. This study showed that water and food are both the
major source of Cu for the muscle and liver of tilapia. This implied
that control the Cu concentration in these two routes will be correlated
to the Cu bioavailability for tilapia. We found that exposure duration
and level of waterborne Cu drove the Cu accumulation in tilapia. The
ability for Cu biouptake and depuration in organs of tilapia were
actively mediated under prolonged exposure conditions. Generally,
the uptake rate, depuration rate and net bioaccumulation ability in all
selected organs decreased with the increasing level of waterborne Cu
and extension of exposure duration.Muscle tissues accounted for over
50%of the total accumulated Cu and played a key role in buffering the
Cu burden in the initial period of exposure, alternatively, the liver
acted a more important role in the storage of Cu with the extension of
exposures. We concluded that assumption of the constant biokinetic
rates could lead to incorrect predictions with overestimating the
long-term Cu accumulation in ecotoxicological risk assessments.
Abstract: The rate of production of main products of the Fischer-Tropsch reactions over Fe/HZSM5 bifunctional catalyst in a fixed bed reactor is investigated at a broad range of temperature, pressure, space velocity, H2/CO feed molar ratio and CO2, CH4 and water flow rates. Model discrimination and parameter estimation were performed according to the integral method of kinetic analysis. Due to lack of mechanism development for Fisher – Tropsch Synthesis on bifunctional catalysts, 26 different models were tested and the best model is selected. Comprehensive one and two dimensional heterogeneous reactor models are developed to simulate the performance of fixed-bed Fischer – Tropsch reactors. To reduce computational time for optimization purposes, an Artificial Feed Forward Neural Network (AFFNN) has been used to describe intra particle mass and heat transfer diffusion in the catalyst pellet. It is seen that products' reaction rates have direct relation with H2 partial pressure and reverse relation with CO partial pressure. The results show that the hybrid model has good agreement with rigorous mechanistic model, favoring that the hybrid model is about 25-30 times faster.