Two polypyridyl ruthenium complexes, bis[4-(N,N'-diphenylamino)phenyl-2,2':6',2 `'-terpyridine]ruthenium(II) (1) and bis[4'-(4-\2-[-(N,N'-diphenylamino)phenyl]ethylene\phenyl)-2, 2':6',2 `'-terpyridine]uthenium(II) (2), have been synthesized. They possess an extended conjugation and strongly coupled electronic states. The features of these compounds were carefully studied from several respects. Steady-state spectroscopy showed that the two compounds had strong excitation dependent emission behaviors caused by mixing features of different electronic states. Femtosecond fluorescence upconversion spectroscopy was also used to investigate the fluorescence dynamics of the compounds. An ultrafast relaxation time of similar to 100 fs of the (MLCT)-M-1 (metal-to-ligand charge-transfer) states, which may originate from an ultrafast intersystem crossing to form (MLCT)-M-3 states, was found in both samples. However, thermal populated states and vibration associated excited state interactions were suggested for 1 with excitation at wavelengths below 400 nm, whereas vibrational energy redistribution with a time scale of few picoseconds was observed in the extended conjugated system of 2. These compounds will have potential application in both artificial photosynthesis systems and photovoltaic devices.
This work intends to get a better understanding of cluster formation in supersonic nozzles of different geometries. The throat diameters d are within 0.26mm ≤ d ≤ 0.62mm, the half-opening-angle α within 4.2° ≤ α ≤ 11.3°, and the length L of the conical section is 17.5 mm (eight nozzles) or 12 mm (two nozzles). Thus the so-called “equivalent sonic-nozzle diameter deq” for these conical nozzle geometries, defined by deq = 0.74d/tan α (for monatomic gases), is in the range of 1.59mm ≤ deq ≤ 5.21mm. Source temperature for the clustering experiments was T0 = 298K, and the backing pressure P0 was between 0.5 and 30 bars. The (average) cluster sizes observed for these conical nozzles deviate from the predictions of the simple stream-tube-model. These deviations are accounted for by introducing the so-called “effective equivalent sonic-nozzle diameter deq∗,” defined as the product of the equivalent sonic-nozzle diameter deq and a new parameter δ, deq∗ = δdeq. The parameter δ serves to modify the equivalent diameters deq of the conical nozzles, which are applied in the idealized cases where the gas flows are suggested to be formed through free jet expansion. Then, δ represents the deviation of the performance in cluster formation of the practical conical nozzles from those predicted based on the idealized picture. The experimental results show that the values of δ can be described by an empirical formula, depending on the gas backing pressure P0 and the parameter deq of the conical nozzles. The degradation of the performance of the present conical nozzles was found with the increase in P0 and the larger deq. It was revealed that δ is inversely proportional to a fractional power ( ∼ 0.5–0.6) of the molecular density nmol in the gas flows under the present experimental conditions. The boundary layers effects are considered to be mainly responsible for the restriction of the performance of the conical nozzles in cluster formation.
A multivariate statistical approach integrating the absolute principal components score (APCS) and multivariate linear regression (APCS-MLR), along with structural equation modeling (SEM), was used to model the influence of water chemistry variables on chlorophyll a (Chl a) in Lake Qilu, a severely polluted lake in southwestern China. Water quality was surveyed monthly from 2000 to 2005. APCS-MLR was used to identify key water chemistry variables, mine data for SEM, and predict Chl a. Seven principal components (PCs) were determined as eigenvalues > 1, which explained 68.67% of the original variance. Four PCs were selected to predict Chl a using APCS-MLR. The results showed a good fit between the observed data and modeled values. with R(2) = 0.80. For SEM, Chl a and eight variables were used: NH(4)-N (ammonia-nitrogen), total phosphorus (TP), Secchi disc depth (SD), cyanide (CN), arsenic (As), cadmium (Cd), fluoride (F), and temperature (T). A conceptual model was established to describe the relationships among the water chemistry variables and Chl a. Four latent variables were also introduced: physical factors, nutrients, toxic substances, and phytoplankton. In general, the SEM demonstrated good agreement between the sample covariance matrix of observed variables and the model-implied covariance matrix. Among the water chemistry factors, T and TP had the greatest positive influence on Chl a, whereas SD had the largest negative influence. These results will help researchers and decision-makers to better understand the influence of water chemistry on phytoplankton and to manage eutrophication adaptively in Lake Qilu. (C) 2009 Elsevier B.V. All rights reserved.