The accurate determination of compositional fluctuations is pivotal in understanding their role in the reduction of efficiency in high indium content ${\mathrm{In}}_x{\mathrm{Ga}}_{1–x}\mathrm{N}$ light emitting diodes (LEDs), the origin of which is still poorly understood. Here we have combined electron energy loss spectroscopy (EELS) imaging at subnanometer resolution with multiscale computational models to obtain a statistical distribution of the compositional fluctuations in ${\mathrm{In}}_x{\mathrm{Ga}}_{1–x}\mathrm{N}$ quantum wells (QWs). Employing a multiscale computational model, we show the tendency of intrinsic compositional fluctuation in ${\mathrm{In}}_x{\mathrm{Ga}}_{1–x}\mathrm{N}$ QWs at different indium concentrations and in the presence of strain. We have developed a systematic formalism based on the autonomous detection of compositional fluctuation in observed and simulated EELS maps. We have shown a direct comparison between the computationally predicted and experimentally observed compositional fluctuations. We have found that although a random alloy model captures the distribution of compositional fluctuations in relatively low In ($\sim 18\%$) content ${\mathrm{In}}_x{\mathrm{Ga}}_{1–x}\mathrm{N}$ QWs, there exists a striking deviation from the model in higher In content (≥24%) QWs. Our results highlight a distinct behavior in carrier localization driven by compositional fluctuations in the low and high In content InGaN QWs, which would ultimately affect the performance of LEDs. Furthermore, our robust computational and atomic characterization method can be widely applied to study materials in which nanoscale compositional fluctuations play a significant role in the material performance.

中文翻译：

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揭开InGaN发光二极管中成分波动的起因

准确确定成分波动对于理解其在降低高铟含量效率中的作用至关重要。 ${在}_X{嘎}_{\mathrm{1个}–X}\mathrm{ñ}$发光二极管（LED）的起源仍知之甚少。在这里，我们将亚纳米级分辨率的电子能量损失谱（EELS）成像与多尺度计算模型进行了组合，以获取元素组成波动的统计分布。${在}_X{嘎}_{\mathrm{1个}–X}\mathrm{ñ}$量子阱（QW）。使用多尺度计算模型，我们显示出内在成分波动的趋势${在}_X{嘎}_{\mathrm{1个}–X}\mathrm{ñ}$不同铟浓度和存在应变时的量子阱。我们基于观察和模拟的EELS映射中成分波动的自主检测，开发了系统的形式主义。我们已经显示了在计算预测和实验观察到的成分波动之间的直接比较。我们发现，尽管随机合金模型捕获了相对较低In（（$〜\mathrm{18岁}％$） 内容 ${在}_X{嘎}_{\mathrm{1个}–X}\mathrm{ñ}$QWs，较高的In含量（≥24％）QWs与模型存在显着偏差。我们的研究结果突出表明，低和高In含量的InGaN QW中的成分波动会导致载流子定位发生明显变化，这最终会影响LED的性能。此外，我们强大的计算和原子表征方法可广泛应用于研究其中纳米级成分波动在材料性能中起重要作用的材料。