Abstract: A new and novel approach in medicine is the use of
cold plasma for various applications such as sterilization blood
coagulation and cancer cell treatment. In this paper a pin-to-hole
plasma jet suitable for biological applications is investigated and
characterized and the possibility and feasibility of cancer cell
treatment is evaluated. The characterization includes power
consumption via Lissajous method, thermal behavior of plasma using
Infra-red camera as a novel method, Optical Emission Spectroscopy
(OES) to determine the species that are generated. Treatment of
leukemia cancer cells is also implemented and MTT assay is used to
evaluate viability.
Abstract: Films of pure tin oxide SnO2 and in presence of
antimony atoms (SnO2-Sb) deposited onto glass substrates have
shown a sufficiently high energy gap to be transparent in the visible
region, a high electrical mobility and a carrier concentration which
displays a good electrical conductivity [1]. In this work, the effects of
polycrystalline silicon substrate on the optical properties of pure and
Sb doped tin oxide is investigated.
We used the APCVD (atmospheric pressure chemical vapour
deposition) technique, which is a low-cost and simple technique,
under nitrogen ambient, for growing this material. A series of SnO2
and SnO2-Sb have been deposited onto polycrystalline silicon
substrates with different contents of antimony atoms at the same
conditions of deposition (substrate temperature, flow oxygen,
duration and nitrogen atmosphere of the reactor). The effect of the
substrate in terms of morphology and nonlinear optical properties,
mainly the reflectance, was studied. The reflectance intensity of the
device, compared to the reflectance of tin oxide films deposited
directly on glass substrate, is clearly reduced on the overall
wavelength range. It is obvious that the roughness of the poly-c
silicon plays an important role by improving the reflectance and
hence the optical parameters.
A clear shift in the minimum of the reflectance upon doping level
is observed. This minimum corresponds to strong free carrier
absorption, resulting in different plasma frequency. This effect is
followed by an increase in the reflectance depending of the antimony
doping. Applying the extended Drude theory to the combining
optical and electrical obtained results these effects are discussed.
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: Predicting short term wind speed is essential in order
to prevent systems in-action from the effects of strong winds. It also
helps in using wind energy as an alternative source of energy, mainly
for Electrical power generation. Wind speed prediction has
applications in Military and civilian fields for air traffic control,
rocket launch, ship navigation etc. The wind speed in near future
depends on the values of other meteorological variables, such as
atmospheric pressure, moisture content, humidity, rainfall etc. The
values of these parameters are obtained from a nearest weather
station and are used to train various forms of neural networks. The
trained model of neural networks is validated using a similar set of
data. The model is then used to predict the wind speed, using the
same meteorological information. This paper reports an Artificial
Neural Network model for short term wind speed prediction, which
uses back propagation algorithm.