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Photoluminescence studies of lnGaN/GaN multi-quantum wells

机译:lnGaN / GaN多量子阱的光致发光研究

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We report measurements of photoluminescence, photoluminescence excitation spectroscopy and photoluminescence time decay on three MOVPE-grown InGaN/GaN multiple quantum well structures with 13/100 In in the wells and well widths L_z = 1.25, 2.5 and 5.0 nm. The PL spectra are dominated by single emission peaks, together with phonon sidebands spaced by a GaN LO phonon energy (92 meV). The peak energies are red-shifted with respect to energies calculated for exciton recombination in square quantum wells and the wide well sample also shows a significant Stokes shift between emission and absorption. Recombination lifetimes measured at 6 K are energy dependent, increasing as the photon energy is scanned downwards through the emission line. They also depend strongly on well width. On the low energy side of the 5 nm well emission line we measure lifetimes as long as 100 ns. Raising the temperature from 6 to 300 K results in a strong reduction of emission intensity for all samples and reduction of the lifetimes, though by a much smaller factor. The peak positions shift slightly to lower energy but by far less than the shift in the band edge. We consider three different theoretical models in an attempt to interpret this data, an exponential tail state model, a model of localization due to In/Ga segregation within the wells and the quantum confined Stark effect model. The QCSE model appears able to explain most of the data reasonably well, though there is evidence to suggest that, in addition, some degree of localization occurs.
机译:我们报告了在三个MOVPE生长的InGaN / GaN多量子阱结构中的光致发光,光致发光激发光谱和光致发光时间衰减的测量,这些结构在阱中具有13/100 In,阱宽度L_z = 1.25、2.5和5.0 nm。 PL谱由单个发射峰以及由GaN LO声子能量(92 meV)隔开的声子边带控制。相对于在方形量子阱中为激子复合计算出的能量,峰值能量发生了红移,宽阱样品在发射和吸收之间也显示出明显的斯托克斯位移。在6 K下测量的重组寿命取决于能量,随着光子能量通过发射线向下扫描而增加。它们还强烈依赖于井宽。在5 nm阱发射线的低能侧,我们测量的寿命长达100 ns。将温度从6 K升高到300 K会导致所有样品的发射强度大大降低,并且寿命缩短,但幅度要小得多。峰值位置会稍微移动以降低能量,但远小于频带边缘的移动。为了解释该数据,我们考虑了三种不同的理论模型,即指数尾态模型,由于孔内In / Ga偏析引起的局部化模型以及量子受限Stark效应模型。 QCSE模型似乎能够合理地解释大多数数据,尽管有证据表明,此外还会发生一定程度的本地化。

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