Cyclometalated iridium(III) complexes with 5-acetyl-2-phenypyridine derived ligands for red phosphorescent OLEDs

A series of new iridium complexes with 5-acetyl-2-phenylpyridine derivatives as ligands was developed. The complexes exhibited high EL performance when applied to OLEDs. These materials showed red emission with a peak at 575–636 nm. In particular, one of the devices in this study showed a maximum luminous efficiency, maximum power efficiency, external quantum efficiency and CIE coordinates of 29.0 cd/A, 6.13 lm/W, 8.86% at 20 mA/cm² and (0.57, 0.43) at 10 V, respectively. In addition, a deep red OLED with CIE coordinates of (0.67, 0.32) at 10 V exhibited a maximum luminous efficiency, maximum power efficiency and external quantum efficiency of 5.61 cd/A, 1.02 lm/W and 5.35% at 20 mA/cm², respectively.     

Nonlinear finite element method models for ultimate strength analysis of steel stiffened-plate structures under combined biaxial compression and lateral pressure actions—Part II: Stiffened panels

The present paper (Part II) is a sequel to the previous paper (Part I) [Paik JK, Seo JK. Nonlinear finite element method models for ultimate strength analysis of steel stiffened-plate structures under combined biaxial compression and lateral pressure actions—Part I: Plate elements. Thin-Walled Struct 2008, this issue, doi:10.1016/j.tws.2008.08.005.] on the application of nonlinear finite element methods for ultimate strength analysis of steel stiffened-plate structures under combined biaxial compression and lateral pressure actions. In contrast to Part I dealing with plate elements, the present paper (Part II) treats stiffened panels surrounded by strong support members such as longitudinal girders and transverse frames. In similar to Part I, some important factors of influence such as structural dimensions, initial imperfections, loading types and computational techniques in association with ultimate limit states are studied. Some useful insights in terms of nonlinear finite element method modeling are developed using ANSYS code together with the ALPS/ULSAP semi-analytical method, the latter being for the purpose of a comparison.     

The effect of blade angle on the flow and pressure distributions in the vicinity of the diffuser blades of a room air conditioner

Many studies on air-conditioning systems are more focused on the individual thermal comfort rather than the thermal efficiency, due to an increase in health concerns. There are several factors influencing the thermal comfort, such as temperature, humidity, convection and air movement, etc. Numerical analyses were performed to investigate the effect of blade angle on the flow characteristics in the vicinity of diffuser blades of a room air conditioner (RAC), with three different blade discharge angles of 45.1°, 58.6° and 116°. We used the commercial code FLUENT to calculate the two-dimensional steady thermal flow fields with different impeller rotational velocities. The angular velocities were located within the range from 900 rpm to 1200 rpm. Turbulence closure was achieved using a standard k-ɛ model. A moving reference frame (MRF) approach was adopted to simulate the flow field generated by the impeller in an RAC. The results were graphically depicted with various geometrical configurations and operating conditions. This paper was presented at the 7th JSME-KSME Thermal and Fluids Engineering Conference, Sapporo, Japan, October 2008. Youn-Jea Kim received his B.S. degree in Mechanical Engineering from Sungkyunkwan University, Korea, in 1982. He then received his M.S. and Ph.D. degrees from the State University of New York at Buffalo in 1987 and 1990, respectively. Dr. Kim is currently a Professor at the School of Mechanical Engineering at Sungkyunkwan University in Korea. Dr. Kim’s research interests include gas dynamics, MEMS, and fluid-machineries, etc.     

Effect of Nanoencapsulated Vitamin B1 Derivative on Inhibition of Both Mycelial Growth and Spore Germination of Fusarium oxysporum f. sp. raphani

Nanoencapsulation of thiamine dilauryl sulfate (TDS), a vitamin B1 derivative, was proved to effectively inhibit the spore germination of Fusarium oxysporum f. sp. raphani (F. oxysporum), as well as mycelial growth. The average diameter of nanoparticles was measured as 136 nm by being encapsulated with an edible encapsulant, lecithin, whose encapsulation efficiency was about 55% in containing 200 ppm of TDS concentration: the 100 ppm TDS nanoparticle solution showed a mycelial growth inhibition rate of 59%. These results were about similar or even better than the cases of treating 100 ppm of dazomet, a positive antifungal control (64%). Moreover, kinetic analysis of inhibiting spore germination were estimated as 6.6% reduction of spore germination rates after 24 h treatment, which were 3.3% similar to the case of treating 100 ppm of a positive control (dazomet) for the same treatment time. It was also found that TDS itself could work as an antifungal agent by inhibiting both mycelial growth and spore germination, even though its efficacy was lower than those of nanoparticles. Nanoparticles especially played a more efficient role in limiting the spore germination, due to their easy penetration into hard cell membranes and long resident time on the surface of the spore shell walls. In this work, it was first demonstrated that the nanoparticle of TDS not a harmful chemical can control the growth of F. oxysporum by using a lower dosage than commercial herbicides, as well as the inhibiting mechanism of the TDS. However, field trials of the TDS nanoparticles encapsulated with lecithin should be further studied to be effectively used for field applications.     

Multivariable stream data classification using motifs and their temporal relations

Multivariable stream data is becoming increasingly common as diverse types of sensor devices and networks are deployed. Building accurate classification models for such data has attracted a lot of attention from the research community. Most of the previous works, however, relied on features extracted from individual streams, and did not take into account the dependency relations among the features within and across the streams. In this work, we propose new classification models that exploit temporal relations among features. We showed that consideration of such dependencies does significantly improve the classification accuracy. Another benefit of employing temporal relations is the improved interpretability of the resulting classification models, as the set of temporal relations can be easily translated to a rule using a sequence of inter-dependent events characterizing the class. We evaluated the proposed scheme using different classification models including the Naive Bayesian, TFIDF, and vector distance models. We showed that the proposed model can be a useful addition to the set of existing stream classification algorithms.