Quantitative Judgment Method and Feedback System of Ela Inhomogeneity

Abstract

The invention discloses a quantitative judging method and a feedback system for ELA (excimer laser annealing) heterogeneity. The system mainly comprises a detecting device, a calculating and grading module and a feedback and adjustment module, wherein the detecting device is used for detecting the life of a polysilicon minority carrier; the calculating and grading module is used for collecting detection data, and calculating as well as classifying a statistical result; and the feedback adjustment module is used for collecting a grading result and controlling the automatic adjustment of a laser annealing device. By the adoption of the quantitative judging method and the feedback system, quantitative judgment on heterogeneity of polysilicon (polysilicon mura) can be realized, the detecting and judging result can be further fed back to process equipment through the feedback system, timely adjustment is carried out, the loss of a product is reduced, and the yield of the product is improved.

Description

technical field [0001] The invention relates to flat panel display, low-temperature polysilicon and active matrix organic light emitting diode (AMOLED, ActiveMatrixOrganicLightEmittingDiode) display technology, in particular to a quantitative judgment method and a feedback system for the inhomogeneity of a laser crystallization process (ELA). Background technique [0002] Polysilicon with better mobility and stability is obtained by laser crystallization (ELA), which can be used to make thin-film transistors (TFTs) for driving organic light-emitting diodes (OLEDs). However, due to the instability of the laser energy used and the inhomogeneity of the energy at different positions of the beam, the obtained polysilicon crystallization rate, grain size and internal defect density will be different. These differences are in turn related to the TFT threshold voltage (V th ) and mobility are closely related, and when reflected in OLED displays, uneven luminance (display mura) will...

AI Technical Summary

Problems solved by technology

The equipment detected by this method only scans a certain area and gives the maximum and minimum detection values ​​and standard deviations of the entire area, and draws the detection results of the scanned area intuitively in different colors by drawing, but the degree of mura is judged The quality and quality of the product still need to be judged by people, and the degree of unevenness of the line and the product grade cannot be directly judged by the value

[0005] Moreover, this type of equipment can only detect the polysilicon substrate after completion, and cannot perform real-time detection during the process, let alone adjust the equipment after detecting process problems in real time

Moreover, due to the irreversibility of the laser crystallization process, it is impossible to rework it. If it is inspected after completion, if there is a quality problem, the entire batch of products will often be scrapped, which will suffer a great loss in yield.

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