The feasibility of using Cu(Mg) alloy film as a gate electrode for thin-film transistor (TFT) liquid crystal displays has been investigated. When pure Cu was used as a gate electrode, severe interdiffusion occurred between Cu and the gases SiH4, NH3, and CF4 during plasma-enhanced chemical vapor deposition of a gate dielectric, SiNx, and dry etching of the SiNx. On the other hand, the deposition of a Cu(Mg) alloy film gives rise to the formation of a MgO/Cu bilayer structure with low Cu resistivity, good adhesion to SiO2, higher leakage current density, and excellent passivation capability. A hydrogenated amorphous silicon TFT with a MgO encapsulated Cu gate exhibited a gate voltage swing of 0.91 V/dec. and a threshold voltage of 6.8 V, resulting in a reduction of process steps and better performance.
In this paper, the evaluation method of image sticking was proposed by measuring 2-Dimension of luminance level. We used the 2D-CCD luminance meter and pattern generator for chessboard pattern. The test samples were burned in about 2 hours and the tested data were normalized by data before image sticking test. The normalized value was so sensitive for determining the image sticking level. We proposed a new parameter of ISV(image sticking value) for increasing sensitivity. It was resulted that the image sticking under ISV 1% was difficult to be detected by human eye. And the image sticking over ISV 2% was strongly detected. It was found that this test method is similar to human eye testing result. Therefore, this analysis method helps to determine the objective image sticking level.
We have analyzed the phenomenon of image sticking and studied for the method of quantifying image sticking by the three different analysis methods. The three analysis methods are R_SEMU [1], Color Difference [2] and Luminance Ratio. We usually use a chessboard pattern to test the image sticking of LCD panels. A new method is NVP (Non-uniformity value of panel). NVP removes a non-uniformity luminance of a panel except the image sticking on the reference image and the image tested. The NVP increases the accuracy of the image sticking analysis. We have measured the image sticking after an image sticking test using a 2D CCD camera and then analyzed the data comparing with a reference image using R_SEMU, Color Difference and Luminance Ratio. We investigate which method is the best analysis one for the evaluation of the image sticking. We have developed an analysis software using VBA. This software can select the quantitative level of image sticking.
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