First principle study of structural, electronic, spontaneous polarization, and elastic properties of yttrium (≤0.25) doped aluminum nitride

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Authors: Mahin Muntasir, Razia Khan Sharme, Md. Solayman, Md Rasidul Islam, Md Masud Rana, Mukti M. Rana
Cited by: 0
References: 48

Abstract

Yttrium aluminum nitride (YAlN) is a wide-bandgap semiconductor that attracts interest for its notable advantages, including a large band gap, excellent thermal stability, and strong piezoelectric properties, making it suitable for applications in RF filters, power electronics, and UV optoelectronics. In this study, we used first-principles calculations based on density functional theory (DFT) to investigate the effects of varying yttrium doping concentrations (0.05, 0.15, and 0.25) on the wurtzite structure of aluminum nitride. Our exploration focuses on a diverse array of properties, including structural, electronic, elastic, and spontaneous polarization. The enthalpy of the structure was calculated and found to be negative for all the structures, confirming its thermodynamic stability. Remarkably, the stability of the wurtzite phase of YxAl1-xN persisted even at high yttrium concentrations, specifically at x ≤ 0.25. Intriguingly, we observed a decrease in the calculated band gap as the yttrium concentration increased, highlighting the tunable band-gap properties that are essential across several domains, such as photovoltaics, optoelectronics, and sensor technologies. Additionally, we investigated the elastic properties of YxAl1-xN, including Young’s modulus, bulk modulus, shear modulus, Pugh’s ratio, and Poisson’s ratio, providing valuable insights into the material's mechanical behavior. All data show that the elastic constants decrease with increasing Y, while C13 increases, due to changes in bond angles. To assess ferroelectricity in YxAl1-xN (x = 0.05-0.25), we conducted examinations of spontaneous polarization, revealing an increase in spontaneous polarization with increasing yttrium content in the wurtzite structure.

Fields of Study & Subjects

GaN-based semiconductor devices and materials Acoustic Wave Resonator Technologies Machine Learning in Materials Science

Publication details

Journal / source
Physics and simulation of optoelectronic devices. Conference
Pages
32–32
Publication date
5 March 2026
Language
EN