Oxygen-induced high diffusion rate of magnesium dopants in GaN/AlGaN based UV LED heterostructures

文献信息

发布日期 2018-05-01

DOI 10.1039/C8CP01470A

影响因子 3.676

作者

Paweł Piotr Michałowski, Sebastian Złotnik, Jakub Sitek, Krzysztof Rosiński, Mariusz Rudziński

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摘要

Further development of GaN/AlGaN based optoelectronic devices requires optimization of the p-type material growth process. In particular, uncontrolled diffusion of Mg dopants may decrease the performance of a device. Thus it is meaningful to study the behavior of Mg and the origins of its diffusion in detail. In this work we have employed secondary ion mass spectrometry to study the diffusion of magnesium in GaN/AlGaN structures. We show that magnesium has a strong tendency to form Mg–H complexes which immobilize Mg atoms and restrain their diffusion. However, these complexes are not present in samples post-growth annealed in an oxygen atmosphere or Al-rich AlGaN structures which naturally have a high oxygen concentration. In these samples, more Mg atoms are free to diffuse and thus the average diffusion length is considerably larger than for a sample annealed in an inert atmosphere.

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来源期刊

Physical Chemistry Chemical Physics

CiteScore: 5.5

自引率: 10.3%

年发文量: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.