Silicon cell

A concept gaining support is a hybrid approach to making thick crystalline silicon efficient in thin layers. Although conventional crystalline silicon cells have gone from 400—600-p.m thick to 200—300-p.m, thin-film crystalline silicon cells have reached 10% efficiency while being only 10-p.m thick. 

A thin film of tin oxide with a rough texture, produced by MOCVD from tetramethyl tin, (CH3)4Sn, deposited on an amorphous silicon cell provides a light-trapping surface, which enhances the efficiency of the device. 

A typical 100-cm silicon cell produces a maximum current of just under 3 amps at a voltage of around 0.5 volts. Since many PV applications involve charging lead-acid batteries, which have a typical nominal voltage of 12 volts, the solar modules often consist of around 36 individual cells wired in series to ensure that the voltage is usually above 13 volts which is enough to charge a 12 volt battery even on overcast days. 

Cells made from GaAs are more costly than silicon cells, because the production process is not as well developed, and gallium and arsenic are not abundant materials. GaAs cells have been used when very high efficiency is needed regardless of cost such as required in space applications. They were also used in the Sunraycer, a photovoltaic-powered electric car, which won the Pentax World Solar Challenge race for solar-powered vehicles in 1987. It ran the 3000-km from Darwin to Adelaide, Australia at an average day time speed of 66-km per hour. The 1990 race was won by a... 

J. L. Snoep, The silicon cell initiative Working towards a detailed kinetic description at the cellular level. Curr. Opin. Biotechnol. 16, 336 343 (2005). 

GalnP/GaAs/Ge systems have conversion efficiencies approaching 30% [33]. Triple junction amorphous silicon cells, based on the Si Ge H alloy, with efficiencies up to 12% have been reported [34],... 

I Vegetative cells always with cell wall composed of pectic substances and silicon, cell wall invariably bivalved, but never a complexly... 

The most efficient silicon cells produced are based on p — n homojunctions and convert 23.1% of the energy in incident light set to simulate the global air mass (AM) 1.5 spectrum, an artificial reference spectrum used to standardize measurement of PV power, with an intensity of 1000 W/m2... 

Gallium arsenide solar cells advanced in the 1980s for space use because they weighed much less than silicon cells of similar output, since GaAs absorbs sunlight much more strongly than silicon. 

Photovoltaic devices made of selenium have been known since the 19th Century. Pioneering research in semiconductors, which led to the invention of the transistor in 1947, formed the basis of the modem theory of photovoltaic performance. From this research, die silicon solar cell was the first known photovoltaic device that could convert a sufficient amount of the sun s energy to power complex electronic circuits. The conventional silicon cell is a solid-state device in which a junction is formed between single crystals of silicon separately doped with impurity atoms in order to create n (negative) regions and p (positive) regions which respectively are receptors to electrons and to holes (absence of electrons). See also Semiconductors. The first solar cell to be demonstrated occurred at Bell Laboratories (now AT T Bell Laboratories) in Murray Hill, New Jersey in 1954. 

The flexible solar module based on monocrystalline silicon cells with higher efficiency than thin film solar cells was developed in the VIESH. For example, the folding solar module 36/1-6-P depicted at FigurelO supplies 10W, output voltage 16V, and short circuit current, 0.7A under standard conditions of measurements. His dimensions are 395 x 370 x 4 mm and in the folded condition practically 6 times less by surface (135 x 185 x 12 mm). This folding solar module can be used for applications which small consuming equipment. 

The Silicon Cell version of this model is available at http //www.jjj.bio.vu.nl/database/ hynne. 

Silicon Cell Models Construction, Analysis, and Reduction... 

Biosimulation has a dominant role to play in systems biology. In this chapter, we briefly outline two approaches to systems biology and the role that mathematical models has to play in them. Our focus is on kinetic models, and silicon cell models in particular. Silicon cell models are kinetic models that are firmly based on experiment. They allow for a test of our knowledge and identify gaps and the discovery of unanticipated behavior of molecular mechanisms. These models are very complicated to analyze because of the high level of molecular-mechanistic detail included in them. To facilitate their analysis and understanding of their behavior, model reduction is an important tool for the analysis of silicon cell models. We present balanced truncation as one method to perform model reduction and apply it to a silicon cell model of glycolysis in Saccharomyces cerevisiae. 

Model reduction aims at simplifying without losing the essence of the dynamic behavior of a model. Reduction of silicon cells should thereby facilitate the understanding of real cells. Strategies for model reduction, pinpointing molecular organizational properties that are essential for network behavior, are essential to make silicon cell models understandable. 

This chapter addresses how silicon cell models can be used in biosimulation for systems biology. We first describe the process of model building, as well as its purpose and how it fits in systems biology. Then we compare the use of silicon cell models with the use of the less-detailed core models. We briefly discuss various simulation methods used to model phenomena involving diffusion and/or stochas-ticity as well as methods for model analysis. Finally we discuss balanced truncation as a method for model reduction. This method is illustrated by applying it to a silicon cell model of yeast glycolysis. 

The second method relies on the experimental determination of the kinetic parameters using techniques from biophysics or enzymology. Also in this case problems exist (1) the kinetic parameters are often determined under conditions different from the conditions in the cytoplasm (2) an enormous number of experiments need to be done, even for a network of moderate size, to determine all kinetic parameters experimentally. When the second method is used to parameterize a kinetic model then the resulting model is considered a silicon cell model. A number of silicon cell models exist [25-27, 29, 75-77]. 

Many methods have been developed for model analysis for instance, bifurcation and stability analysis [88, 89], parameter sensitivity analysis [90], metabolic control analysis [16, 17, 91] and biochemical systems analysis [18]. One highly important method for model analysis and especially for large models, such as many silicon cell models, is model reduction. Model reduction has a long history in the analysis of biochemical reaction networks and in the analysis of nonlinear dynamics (slow and fast manifolds) [92-104]. In all cases, the aim of model reduction is to derive a simplified model from a larger ancestral model that satisfies a number of criteria. In the following sections we describe a relatively new form of model reduction for biochemical reaction networks, such as metabolic, signaling, or genetic networks. 

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