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GaN bandgap bias caused by semi-core treatment in pseudopotentials analyzed by the diffusion Monte Carlo method

机译:由扩散蒙特卡罗法分析的假软盘上的半核处理引起的GaN带隙偏差

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This study investigates how the prediction of the gallium nitride (GaN) bandgap is affected by treating semi-core d -electrons as either valence or core states in the pseudopotentials, which correspond to small-core and large-core approximations, respectively. To distinguish the effect of semi-core treatment from another bandgap problem recognized in density functional theory (DFT), that is , the underestimation related to the self-interaction problem, we perform diffusion Monte Carlo (DMC) evaluations under the fixed-node approximation and the optical gap scheme (where the evaluation uses N -electron many-body wavefunctions). A comparison to experimental measurements of bandgap energies indicates that DMC predictions are overestimated, whereas DFT simulations, which are used as a guiding function (DFT → DMC), are typically underestimated. This agrees with the trend reported in previous DMC studies on bandgap estimates. The large-core approximation results in a greater overestimation than the small-core treatment in both DFT and DMC. The bias in the overestimation is ~30% for the DFT → DMC operation. Several possible causes of this bias are considered, such as pd -hybridization, core-polarization, and electronic screening effects. However, although these factors could qualitatively account for the overestimation caused by the large-core treatment, the estimated magnitude of the bias is too small to explain the evaluated difference between small-core and large-core approximations of the bandgap.
机译:该研究研究了如何通过将半核D-endercons视为伪能量中的价值或核心状态,分别对应于小核和大核心近似的比例或核心状态来影响氮化镓(GaN)带隙的预测。为了区分从密度函数理论(DFT)中识别的另一个带隙问题的半核处理的影响,即与自交互问题有关的低估,我们在固定节点近似下执行扩散蒙特卡罗(DMC)评估和光学间隙方案(评估使用N-Electron的许多身体波力)。与带隙能量的实验测量的比较表明DMC预测高估,而使用作为引导功能(DFT→DMC)的DFT模拟通常被低估。这同意以前关于Bandgap估计的DMC研究中报告的趋势。大核近似导致比DFT和DMC中的小核心处理更高的高度估量。高估的偏差为DFT→DMC操作的〜30%。考虑该偏差的几种可能的原因,例如PD-酵母,核心极化和电子筛选效果。然而,尽管这些因素可以定性地解释由大核心处理引起的高估,但偏差的估计大小太小,无法解释带隙的小核和大核心近似之间的评估差异。

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