Improved light extraction efficiency of AlGaN deep-ultraviolet light emitting diodes combining Ag-nanodots/Al reflective electrode with highly transparent p-type layer.

Enhancement of light extraction efficiency (LEE) of AlGaN-based deep-ultraviolet (DUV) light emitting diodes (LEDs) has been attempted by adopting Ag-nanodots/Al reflective electrodes on a highly transparent complex p-type layer. By thinning the p-GaN to several nm, highly DUV transparent p-type layer is achieved, making it meaningful for the application of reflective electrodes composed of Ag-nanodots and Al film to allow most light emitted upward to be reflected back to the sapphire side. By this approach, the maximum light output power and external quantum efficiency of the DUV-LEDs with optimized Ag nanodots/Al electrodes are severally increased by 52% and 58%, respectively, compared to those with traditional Ni/Au electrodes when the current is below 200 mA.

Greatly enhanced performance of AlGaN-based deep ultraviolet light emitting diodes by introducing a polarization modulated electron blocking layer.

Carrier transport in AlGaN-based deep ultraviolet (DUV) light emitting diodes (LEDs) with the wavelength of 273 nm has been investigated by introducing polarization modulated electron blocking layer (EBL) that adopts an Al composition and thickness graded multiple quantum barriers (MQB) structure. The experimental result shows that the maximum light output power and external quantum efficiency for the proposed structure at the current of 250 mA are 9.6 mW and 1.03% respectively, severally increasing by 405% and 249% compared to traditional one, meanwhile, the efficiency droop at 250 mA is also dramatically reduced from 42.2% to 16.6%. Further simulation analysis indicates that this graded MQB-EBL enhances the potential barrier height for electrons and meanwhile reduces that for holes, hence effectively suppresses the electron leakage, and at the same time significantly improves the hole injection efficiency. As a result, the whole performance of the LED with the proposed MQB-EBL is dramatically improved.

Operating behavior of micro-LEDs on a GaN substrate at ultrahigh injection current densities.

Near-ultraviolet micro-LEDs with different diameters were fabricated on GaN substrates. The electroluminescence and the light output power-current density and current density-voltage relationships were measured. A saturated current density of 358 kA/cm2 was achieved with a 20 µm LED. The ideality factor curves showed steps and peaks when the injection current density was increased from 20 to 150 kA/cm2 and an abnormal efficiency increase. The transport and recombination processes of micro-LEDs at high injection current densities were simulated, and the many-body effect and phase space filling in the integrated quantum drift-diffusion model were considered. Serious current crowding was observed above 100 kA/cm2, even for the 20 µm LED.

Anisotropic dependence of light extraction behavior on propagation path in AlGaN-based deep-ultraviolet light-emitting diodes.

The anisotropic extraction dependence of polarized light on propagation path in AlGaN-based deep-ultraviolet (DUV) light-emitting diodes (LEDs) is investigated by simulations and photoluminescence (PL) measurements. Theoretical calculations based on k⋅p approximation and Monte Carol ray tracing indicate that there are two kinds of polarized sources with different angular distributions in ~280 nm AlGaN-based LEDs, s-polarized (spherical-shaped) and p-polarized (dumbbell-shaped) sources, which have different extraction behaviors. It is found that the total light extraction intensities are improved with decreasing the propagation path, and the lateral surface extraction gradually becomes dominant. Moreover, the extraction intensity of s-polarized light improves more than that of p-polarized light when the propagation path decreases, leading to a greater polarization degree. Polarization-resolved PL measurements show that the polarization degree of extracted light from lateral facet of the AlGaN multiple quantum well sample can be enhanced from 1% to 17% as the average propagation path reduces by 0.6 mm, which is consistent with the simulation results of the anisotropic dependence of light extraction on propagation path. Our results are significant for understanding and modulating the anisotropic extraction behavior of polarized light to realize high efficiency AlGaN-based DUV LEDs.

SELDI-TOF-MS-based serum proteomic screening in combination with CT scan distinguishes renal cell carcinoma from benign renal tumors and healthy persons.

In order to identify the proteomic differences between renal cell carcinoma (RCC) and benign renal tumors, we analyzed 168 serum samples from 65 RCC patients, 34 patients with benign renal tumors, and 69 healthy persons using the IMAC-Cu2+ ProteinChip system by surface enhanced laser desorption/ionization mass spectrometry technology. Two decision trees were generated by Biomarker Pattern software to distinguish between RCC versus healthy and RCC versus patients with benign tumors, respectively. Although the sensitivity and specificity of the RCC vs. healthy decision tree were 97.6% and 95.7%, respectively, it could not be used to distinguish RCC from benign renal tumors. The sensitivity of a blind test process using RCC, benign tumors and healthy persons were 92%. The specificity of the test process was 35.3% for benign tumors and 95.5% for healthy persons. The sensitivity and specificity of the RCC-Benign tumors decision tree were 85.7% and 95.5%, respectively. The blind test process using RCC, benign tumors and healthy persons also showed significant results. The sensitivity was 90.0%. The specificity was 95.7% for healthy persons and 90.0% for benign tumors. Combining these data with the results of CT scanning, the sensitivity can be improved over the use of either CT and decision tree analysis and the specificity may reach 100%. Two peaks with molecular masses of 3887.11 Da and 11079.8 Da were detected that are potentially useful for the diagnosis or screening of RCC. It was found that these two peaks can be used, not only to distinguish the RCC vs. healthy cases, but also to distinguish RCC from benign renal tumors. In combination with CT scanning, the sensitivity and specificity of the diagnosis of renal tumors can be improved. However, the decision tree constructed for RCC and healthy persons may not present good specificity for use in distinguishing malignant from benign renal tumors.