Abstract: Palladium-catalyzed hydrodechlorination is a
promising alternative for the treatment of environmentally relevant
water bodies, such as groundwater, contaminated with chlorinated
organic compounds (COCs). In the aqueous phase
hydrodechlorination of COCs, Pd-based catalysts were found to have
a very high catalytic activity. However, the full utilization of the
catalyst-s potential is impeded by the sensitivity of the catalyst to
poisoning and deactivation induced by reduced sulfur compounds
(e.g. sulfides). Several regenerants have been tested before to recover
the performance of sulfide-fouled Pd catalyst. But these only
delivered partial success with respect to re-establishment of the
catalyst activity. In this study, the deactivation behaviour of
Pd/Al2O3 in the presence of sulfide was investigated. Subsequent to
total deactivation the catalyst was regenerated in the aqueous phase
using potassium permanganate. Under neutral pH condition,
oxidative regeneration with permanganate delivered a slow recovery
of catalyst activity. However, changing the pH of the bulk solution to
acidic resulted in the complete recovery of catalyst activity within a
regeneration time of about half an hour. These findings suggest the
superiority of permanganate as regenerant in re-activating Pd/Al2O3
by oxidizing Pd-bound sulfide.
Abstract: In this study, the effect of nanofluids on the pool film
boiling was experimentally investigated at saturated condition under
atmospheric pressure. For this purpose, four different water-based
nanofluids (Al2O3, SiO2, TiO2 and CuO) with 0.1% particle volume
fraction were prepared. To investigate the boiling heat transfer, a
cylindrical rod with high temperature was used. The rod heated up to
high temperatures was immersed into nanofluids. The center
temperature of rod during the cooling process was recorded by using
a K-type thermocouple. The quenching curves showed that the pool
boiling heat transfer was strongly dependent on the nanoparticle
materials. During the repetitive quenching tests, the cooling time
decreased and thus, the film boiling vanished. Consequently, the
primary reason of this was the change of the surface characteristics
due to the nanoparticles deposition on the rod-s surface.
Abstract: Hydrogen is an important chemical in many industries
and it is expected to become one of the major fuels for energy
generation in the future. Unfortunately, hydrogen does not exist in its
elemental form in nature and therefore has to be produced from
hydrocarbons, hydrogen-containing compounds or water.
Above its critical point (374.8oC and 22.1MPa), water has lower
density and viscosity, and a higher heat capacity than those of
ambient water. Mass transfer in supercritical water (SCW) is
enhanced due to its increased diffusivity and transport ability. The
reduced dielectric constant makes supercritical water a better solvent
for organic compounds and gases. Hence, due to the aforementioned
desirable properties, there is a growing interest toward studies
regarding the gasification of organic matter containing biomass or
model biomass solutions in supercritical water.
In this study, hydrogen and biofuel production by the catalytic
gasification of 2-Propanol in supercritical conditions of water was
investigated. Pt/Al2O3and Ni/Al2O3were the catalysts used in the
gasification reactions. All of the experiments were performed under a
constant pressure of 25MPa. The effects of five reaction temperatures
(400, 450, 500, 550 and 600°C) and five reaction times (10, 15, 20,
25 and 30 s) on the gasification yield and flammable component
content were investigated.
Abstract: Hydrogen is regarded to play an important role in
future energy systems because it can be produced from abundant
resources and its combustion only generates water. The disposal of
waste tyres is a major problem in environmental management
throughout the world. The use of waste materials as a source of
hydrogen is particularly of interest in that it would also solve a waste
treatment problem. There is much interest in the use of alternative
feedstocks for the production of hydrogen since more than 95% of
current production is from fossil fuels. The pyrolysis of waste tyres
for the production of liquid fuels, activated carbons and gases has
been extensively researched. However, combining pyrolysis with
gasification is a novel process that can gasify the gaseous products
from pyrolysis. In this paper, an experimental investigation into the
production of hydrogen and other gases from the bench scale
pyrolysis-gasification of tyres has been investigated. Experiments
were carried using a two stage system consisting of pyrolysis of the
waste tyres followed by catalytic steam gasification of the evolved
gases and vapours in a second reactor. Experiments were conducted
at a pyrolysis temperature of 500 °C using Ni/Al2O3 as a catalyst. The
results showed that there was a dramatic increase in gas yield and the
potential H2 production when the gasification temperature was
increased from 600 to 900 oC. Overall, the process showed that high
yields of hydrogen can be produced from waste tyres.
Abstract: In this study, the conversion of n-pentane to aromatics is investigated on HZSM-5 zeolites modified by Ga ion-exchange and silylation using tetraethyl orthosilicate (TEOS) via chemical liquid deposition (CLD). The effect of SiO2/Al2O3 ratios of HZSM-5 was also studied. Parameters in preparing catalysts i.e. TEOS loading and cycles of deposition were varied to obtain the optimal condition for enhancing p-xylene selectivity. The highest p-xylene selectivity 99.7% was achieved when the amount of TEOS was 20 vol.%.The catalysts were characterized by TPD, TPO, XRF, and BET. Results show that the conversion of n-pentane was influenced remarkably by the SiO2/Al2O3 ratios of HZSM-5. The highest p-xylene selectivity 99.7% was achieved when the amount of TEOS was 20 vol.%. And cycles of deposition greatly improves HZSM-5 shape-selectivity.
Abstract: The effect of Alumina nanoparticle size on thermophysical
properties, heat transfer performance and pressure loss characteristics of
Aviation Turbine Fuel (ATF)-Al2O3 nanofluids is studied experimentally for
the proposed application of regenerative cooling of semi-cryogenic rocket
engine thrust chambers. Al2O3 particles with mean diameters of 50 nm or 150
nm are dispersed in ATF. At 500C and 0.3% particle volume concentration,
the bigger particles show increases of 17% in thermal conductivity and 55% in
viscosity, whereas the smaller particles show corresponding increases of 21%
and 22% for thermal conductivity and viscosity respectively. Contrary to these
results, experiments to study the heat transfer performance and pressure loss
characteristics show that at the same pumping power, the maximum
enhancement in heat transfer coefficient at 500C and 0.3% concentration is
approximately 47% using bigger particles, whereas it is only 36% using
smaller particles.
Abstract: In order to investigate a PROX microreactor
performance, two-dimensional modeling of the reacting flow
between two parallel plates is performed through a finite volume
method using an improved SIMPLE algorithm. A three-step surface
kinetics including hydrogen oxidation, carbon monoxide oxidation
and water-gas shift reaction is applied for a Pt-Fe/γ-Al2O3 catalyst
and operating temperatures of about 100ºC. Flow pattern, pressure
field, temperature distribution, and mole fractions of species are
found in the whole domain for all cases. Also, the required reactive
length for removing carbon monoxide from about 2% to less than 10
ppm is found. Furthermore, effects of hydraulic diameter, wall
temperature, and inlet mole fraction of air and water are investigated
by considering carbon monoxide selectivity and conversion. It is
found that air and water addition may improve the performance of
the microreactor in carbon monoxide removal in such operating
conditions; this is in agreement with the pervious published results.
Abstract: An accurate and proficient artificial neural network
(ANN) based genetic algorithm (GA) is developed for predicting of
nanofluids viscosity. A genetic algorithm (GA) is used to optimize
the neural network parameters for minimizing the error between the
predictive viscosity and the experimental one. The experimental
viscosity in two nanofluids Al2O3-H2O and CuO-H2O from 278.15
to 343.15 K and volume fraction up to 15% were used from
literature. The result of this study reveals that GA-NN model is
outperform to the conventional neural nets in predicting the viscosity
of nanofluids with mean absolute relative error of 1.22% and 1.77%
for Al2O3-H2O and CuO-H2O, respectively. Furthermore, the results
of this work have also been compared with others models. The
findings of this work demonstrate that the GA-NN model is an
effective method for prediction viscosity of nanofluids and have
better accuracy and simplicity compared with the others models.