We have synthesized a Eu2+-activated Sr2SiO4yellow phosphor and
investigated an attempt to develop white LEDs by combining it with a GaN blue LED
chip. Two distinct emission bands from the GaN-based LED and the Sr2SiO4:Eu phosphor are clearly observed at 400 nm and at around 550 nm, respectively. These two emission bands combine to give a spectrum that appears white to the naked eye. Our results show that GaN (400 nm chip)-based Sr2SiO4:Eu exhibits a better luminous efficiency than that of the industrially available product InGaN (460 nm chip)-based YAG:Ce.
Recently, mechanical shock failures of a flat display unit such as TFT-LCD device have been an important concern of designers. In order to achieve the mechanical shock requirement, it is necessary to perform the detailed FE analyses which could be very expensive either by the lengthy computation or by the complicated geometry modeling. The objective of this study is to propose a simplified analysis methodology to simulate impact behavior of thin glass plates. The static problem
equivalent to the impact one is found from the concept of solid mechanics to estimate the maximum deflection and stress under impact loading. To show the plausibility of the proposed approach, it is applied to the idealized problem which is a two dimensional beam subjected to impact loading. Based on explicit FE analyses using the LS-DYNA FE program, it was shown that the impact problem can
be solved by the equivalent static analysis which is much easier to solve in practice. Therefore, the proposed approach provides significant advantages in design optimization of a TFT-LCD device against shock failure, and enables the designer to avoid ad hoc modeling of the transient dynamics so that product design cycle could be shortened.
Availability of defect test algorithm that recognizes exact and standardized defect information in order to fundamentally resolve generated defects in industrial sites by giving artificial intelligence to SAT(Scanning Acoustic Tomograph), which previously depended on operator’s decision, to find various defect information in a semiconductor package, to decide defect pattern, to reduce personal errors and then to standardize the test process was verified. In order to apply the algorithm to the lately emerging Neural Network theory, various weights were used to derive results for performance advancement plans of the defect test algorithm that promises excellent field applicability.
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