In this Letter, GaN-based green resonant-cavity light-emitting diodes (RCLEDs) with a low-cost aluminum (Al) metal bottom mirror, a dielectric top mirror, and a copper (Cu) supporting plate were fabricated. The green-emitting epitaxial wafer was grown on a patterned sapphire substrate (PSS) to ensure high crystal quality (CQ). Laser lift-off (LLO) of the PSS and electrical plating of a Cu supporting plate were then carried out to realize the vertical device structure. The emission wavelength and full width at half maximum (FWHM) of the main emission peak of the device are ∼518 nm and 14 nm, respectively. Under the current density of 50 A/cm2, a relatively high light output power (LOP) of 11.1 mW can be obtained from the green RCLED. Moreover, when the current injection is 20 mA (8 A/cm2), the corresponding forward bias voltage is as low as ∼2.46 V. The reasons for the low operating voltage and high LOP can be attributed to the improvement of CQ, the release of residual compressive stress of the GaN-based epilayer due to the removal of PSS, and better heat dissipation properties of the Cu supporting plate.

In the process of learning and using Chinese, many learners of Chinese as foreign language(CFL) may have grammar errors due to negative migration of their native languages. This paper introduces our system that can simultaneously diagnose four types of grammatical errors including redundant (R), missing (M), selection (S), disorder (W) in NLPTEA-5 shared task. We proposed a Bidirectional LSTM CRF neural network (BiLSTM-CRF) that combines BiLSTM and CRF without hand-craft features for Chinese Grammatical Error Diagnosis (CGED). Evaluation includes three levels, which are detection level, identification level and position level. At the detection level and identification level, our system got the third recall scores, and achieved good F1 values.

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