High-efficiency Silicon Solar Cells: A Review

Over the past few decades, crystalline silicon solar cells have been extensively studied due to their high efficiency, high reliability, and low cost. In addition, these types of cells lead the industry and account for more than half of the market. For the foreseeable future, Si will still be a critical material for photovoltaic devices in the solar cell industry. In this paper, we discuss key issues, cell concepts, and the status of recent high-efficiency crystalline silicon solar cells.     

Stability of SiN<Subscript>X</Subscript>/SiN<Subscript>X</Subscript> double stack antireflection coating for single crystalline silicon solar cells

Double stack antireflection coatings have significant advantages over single-layer antireflection coatings due to their broad-range coverage of the solar spectrum. A solar cell with 60-nm/20-nm SiN_X:H double stack coatings has 17.8% efficiency, while that with a 80-nm SiN_X:H single coating has 17.2% efficiency. The improvement of the efficiency is due to the effect of better passivation and better antireflection of the double stack antireflection coating. It is important that SiN_X:H films have strong resistance against stress factors since they are used as antireflective coating for solar cells. However, the tolerance of SiN_X:H films to external stresses has never been studied. In this paper, the stability of SiN_X:H films prepared by a plasma-enhanced chemical vapor deposition system is studied. The stability tests are conducted using various forms of stress, such as prolonged thermal cycle, humidity, and UV exposure. The heat and damp test was conducted for 100 h, maintaining humidity at 85% and applying thermal cycles of rapidly changing temperatures from -20°C to 85°C over 5 h. UV exposure was conducted for 50 h using a 180-W UV lamp. This confirmed that the double stack antireflection coating is stable against external stress.     

Fish science research in China: How does it compare with fish research in India?

Fish and aquaculture research in the People's Republic of China over the six years 1994-1999 has been mapped using data from six databases– three abstracting services and three citation indexes. The results are compared with fish science research in India. During the six years China has published 2035 papers (roughly 4.5 –5% of the world output) and India 2454. More than 95% of China's papers are journal articles, compared to 82.8% of Indian papers. About 78% of China's journal paper output has appeared in 143 domestic journals compared to 70% from India in 113 Indian journals. Less than one-eighth of the journal articles published by Chinese researchers are published in journals indexed in SCI, compared to 30% of journal articles by Indian researchers. Less than a dozen papers from each of these countries have appeared in journals of impact factor greater than 3.0. Fish research institutes and fishery colleges are the major contributors of the Chinese research output in this area. In India academic institutions are the leading contributors (61%), followed by central government institutions (>25%). Qingdao, Wuhan, Beijing and Shanghai are the cities and Shandong, Hubei and Fujian are the provinces contributing a large number of papers. As we do not have addresses of all authors in most of the papers, we are unable to estimate the extent of international collaboration. Although China's research output and its citation impact are less than those of India, China's fish production and export earnings are far higher than those of India. Probably China is better at bridging the gap between knowhow (research) and do-how (technology and creation of employment and wealth). China is pretty strong in extension. This revised version was published online in June 2006 with corrections to the Cover Date.     

Internal stress induced metallization of single-walled carbon nanotubes in a nanotube/glass conducting composite

Single-walled carbon nanotubes (SWCNTs) have been incorporated into a (Pb, Zn)-phosphate glass host by a melt-quenching technique. Studies of the optical and electronic properties show that the nanotubes in the composite have suffered conformational deformations and attained a band structure of quasimetallic type, making the composite a good electrical conductor. Possible strains in the nanotubes of the composite such as radial compression, torsion and bending have been considered and their role in modulating the band structures has been analyzed by judging the change in band gap energies (ΔE) of the deformed SWCNTs using an equation which is based on the π-electron tight binding model. The effect of σ*-π* hybridization due to the radial compression in generating the metallicity is also discussed. The carrier transport in the composite above room temperature has been shown to be dominated by fluctuation induced tunneling.     

Microfluorometric detection of catecholamines with multiphoton-excited fluorescence

We demonstrate sensitive spatially resolved detection of physiological chromophores that emit in the ultraviolet (<330 nm). An atypical laser source (a visible wavelength femtosecond optical parametric oscillator), and an unconventional collection geometry (a lensless detector that detects the forward-emitted fluorescence) enable this detection. We report the excitation spectra of the catecholamines dopamine and norepinephrine, together with near-UV emitters serotonin and tryptophan, in the range of 550-595 nm. We estimate the molecular two-photon action cross section of dopamine, norepinephrine, and serotonin to be 1.2 mGM (1 GM, or Goppert Mayor, is equal to 10(-58) m4 s(-1) photon(-1)), 2 mGM, and 43 mGM, respectively, at 560 nm. The sensitivity achieved by this method holds promise for the microscopic imaging of vesicular catecholamines in live cells.     

Integrated Framework for Quantifying and Predicting Weather-Related Highway Construction Delays

Constant exposure to the environment makes highway construction highly dependent on weather. However, highway construction contracts are often unclear about the potential influence of weather-related delays on highway construction project schedules. There is a need to discourage litigation arising from weather-related delays by including in contracts a reasonable number of nonwork days as a consequence of adverse weather and providing an equitable criteria for the course of action when the predictions in the contracts turn out to be inaccurate. To address this need, an integrated framework consisting of the following two key components is proposed: (1) identification of attributes of weather that cause construction delays and (2) generation of synthetic weather sequences using a stochastic weather generator to quantify and provide probabilistic forecasts of weather threshold values. The utility of this framework is demonstrated through its application to construction work on a project in Texas. The use of probabilistic forecast of construction delay attributes provided by a semiparametric weather generator in this research is an example of interdisciplinary study to help address this problem. The result of the research is better decision support for agencies who wish to author contracts that more equitably allow for the influence of weather during construction.     

Adaptive non-local level-set model for despeckling and deblurring of synthetic aperture radar imagery

ABSTRACT

In this article, we modify Mumford–Shah level-set model to handle speckles and blur in synthetic aperture radar (SAR) imagery. The proposed model is formulated using a non-local regularization framework. Hence, the model duly cares about local gradient oscillations (corresponding to the fine details/textures) during the evolution process. It is assumed that the speckle intensity is gamma distributed, while designing a maximum a posteriori estimator of the functional. The parameters of the gamma distribution (i.e. scale and shape) are estimated using a maximum likelihood estimator. The regularization parameter of the model is evaluated adaptively using these (estimated) parameters at each iteration. The split-Bregman iterative scheme is employed to improve the convergence rate of the model. The proposed and the state-of-the-art despeckling models are experimentally verified and compared using a large number of speckled and blurred SAR images. Statistical quantifiers are used to numerically evaluate the performance of various models under consideration.     

Regression Model for Daily Maximum Stream Temperature

An empirical model is developed to predict daily maximum stream temperatures for the summer period. The model is created using a stepwise linear regression procedure to select significant predictors. The predictive model includes a prediction confidence interval to quantify the uncertainty. The methodology is applied to the Truckee River in California and Nevada. The stepwise procedure selects daily maximum air temperature and average daily flow as the variables to predict maximum daily stream temperature at Reno, Nev. The model is shown to work in a predictive mode by validation using three years of historical data. Using the uncertainty quantification, the amount of required additional flow to meet a target stream temperature with a desired level of confidence is determined.