In the brain-cell microenvironment, diffusion plays an important role: apart from delivering glucose and oxygen from the vascular system to brain cells, it also moves informational substances between cells. The brain is an extremely complex structure of interwoven, intercommunicating cells, but recent theoretical and experimental works showed that the classical laws of diffusion, cast in the framework of porous media theory, can deliver an accurate quantitative description of the way molecules are transported through this tissue. The mathematical modeling and the numerical simulations are successfully applied in the investigation of diffusion processes in tissues, replacing the costly laboratory investigations. Nevertheless, modeling must rely on highly accurate information regarding the main parameters (tortuosity, volume fraction) which characterize the tissue, obtained by structural and functional imaging. The usual techniques to measure the diffusion mechanism in brain tissue are the radiotracer method, the real time iontophoretic method and integrative optical imaging using fluorescence microscopy. A promising technique for obtaining the values for characteristic parameters of the transport equation is the direct optical investigation using optical fibers. The analysis of these parameters also reveals how the local geometry of the brain changes with time or under pathological conditions. This paper presents a set of computations concerning the mass transport inside the brain tissue, for different types of cells. By measuring the time evolution of the concentration profile of an injected substance and using suitable fitting procedures, the main parameters characterizing the tissue can be determined. This type of analysis could be an important tool in understanding the functional mechanisms of effective drug delivery in complex structures such as the brain tissue. It also offers possibilities to realize optical imaging methods for in vitro and in vivo measurements using optical fibers. The model also may help in radiotracer biomarker models for the understanding of the mechanism of action of new chemical entities.
Intermediate Band (IB) solar cell is a concept belonging to the third generation of photovoltaic converters potentially
having an efficiency limit exceeding the one of single gap solar cells. Its performance is based on the existence of an
intermediate band within the conventional gap of a host semiconductor which facilitates two step absorptions of photons
with energy below the band gap. An extension of intermediary band solar cells is the multiband solar cell achieved by
increasing the number of IBs in the host gap. When the number of IBs increases to infinite, the device becomes
equivalent to an infinite serial tandem, which exhibits a conversion efficiency close to the thermodynamic limit. One
proposes a simple but accurate model for a multiband solar cell having an arbitrary number of IBs that may be
implemented via Quantum Dot (QD) technology. The novelty of this approach lies in the computation procedure of the
energy band diagram using the transfer matrix method and the derivation of an effective absorption coefficient for the IB
system. The presented model is suitable as a tool for investigating electro-optical properties of QD multiband cells.
Results of numerical simulations performed for finding maximum conversion efficiency for given architectures are
presented.
Computer modeling has become a necessity in the solar cells design. A computer model allows the study of the physical
behavior of the device offering valuable information on the effects of each parameter on device performance. Dye-sensitized
solar cells (DSSC) have attracted a lot of interest in recent years, in research as well as in industry. In present,
the development has reached a stage where detailed physical models may contribute considerably to the optimization of
these devices. Up to now, there is not a comprehensive model which links material parameters of a DSSC based on TiO2
nanocrystals DSSC to the electrical performance of the whole cell, such as I-V characteristic and spectral response.
Typically, a DSSC consists of two layers, a TiO2 porous structure coated with a suitable light-absorbing charge-transfer
dye wetted with an iodide/triiodide redox electrolyte and a bulk electrolyte layer, sandwiched between two glass
substrates which are coated with transparent conductive oxide (TCO) layers. In this paper we present a model for the
transport processes inside the DSSC based on the classical transport equations in one dimension. The equations are
solved using the monodomain approach, which consists of using a single set of equations, with different values for the
transport coefficients inside the two regions of the computational domain. The transport coefficients for the porous
medium are calculated using homogenization techniques. The model permits the computation of the dye-sensitized solar
cell I-V curves and efficiency. As model application, the influence of the most important material parameters on the cell
performances investigated by numerical simulation is reported.
The computation of the heat transfer equations solution generally implies the use of commercial codes, often expensive.
An important goal of solving heat transfer problem in a given context is to obtain an accurate solution using accessible
tools at a low computational time cost. Because of complexity of the problem, a variety of different approximations are
used and their validity limit must be tested in each case performing comparisons with experimental results.
In this paper we present a simple, rapid and accurate method to compute the temperature evolution during the heating or
cooling of a metal circular cylinder. For moderate temperature values only the conductive transfer can be considered and
the resulted heat transport equation is solved. The initial temperature distribution is described by Dirichlet type boundary
conditions. Taking into account a sufficiently large number of terms in the analytical solution expression so that the
initial boundary condition is fulfilled (in our case N = 500), we obtain a simple yet accurate approximation of the full
transport solutions. The results are consistent with experimental data and in excellent agreement with simulations
performed with much more complex codes for the investigated temperature domain.
The method can be adapted to the temperature measurement inside the engine. Using the specific advantages of the
optical fibers might be a reliable tool for improving the temperature control in the engine and consequently the
performances of the automobile.
In this paper we present the computed dopant field in the neighborhood of the melt/solid interface in the case of Bridgman-Stockbarger semiconductor crystal growth system in microgravity. The computation is made in quasi-steady state approximation for crystal and melt with thermophysical properties similar to those of gallium-doped germanium, using the 'precrystallization-zone' model. In the quasi- steady state approximation the translation of the ampoule is replaced by supplying melt into the ampoule with velocity V1 and removing crystal at the other end of the ampoule at the rate Vs equals V1. The 'precrystallization-zone' is considered to be a thin layer masking the crystal in which exists a periodical microstructure created by the periodical structure of the crystal which governs the arranging of the own atoms into a specific crystalline lattice. In fact, in this layer we have periodically distributed places which are not available for the dopant. Using this approximation and model, we find relevant radial segregation due to the precrystallization-zone. We also find that reducing the diameter of the rod a lower radial segregation appears. Therefore the influence of the precrystallization-zone is relevant even in microgravity and there is no reason to ignore this zone in general.
Conference Committee Involvement (2)
SPIE Eco-Photonics 2011: Sustainable Design, Manufacturing, and Engineering Workforce Education for a Green Future
28 March 2011 | Strasbourg, France
Education for a Sustainable Engineering Workforce for a Green Future
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