2018年第79回応用物理学会秋季学術講演会

講演情報

一般セッション(口頭講演)

4 JSAP-OSA Joint Symposia 2018 » 4.2 Photonics Devices, Photonic Integrated Circuit and Silicon Phonics

[21p-211B-1~9] 4.2 Photonics Devices, Photonic Integrated Circuit and Silicon Phonics

2018年9月21日(金) 13:15 〜 16:15 211B (211-2)

太田 泰友(東大)、西山 伸彦(東工大)

15:15 〜 15:30

[21p-211B-6] Object Orientated Monte-Carlo Model Incorporating Quantum Dot Size Anisotropy Effects in State-of-the-art Quantum Dot Lasers

〇(D)Iain Butler1,2、Wei Li3、Sorush Sobhani1、Nasser Babazadeh1、Ian Ross3、Kenichi Nishi4、Keizo Takemasa4、Mitsuru Sugawara4、David Childs1、Richard Hogg1 (1.Univ. of Glasgow、2.Queen's Univ. Belfast、3.Univ. of Sheffield、4.QD Laser Inc.)

キーワード:quantum dots, modeling, laser

Stranski-Krastanov self-assembled quantum dots (QDs) are now available in commercial devices with wide-ranging applications such as optical communication and sensing. The prediction of temperature insensitive laser operation has been a key interest, and due to development in epitaxial process for high quality GaAs based InAs QD materials, this is now possible. The control of inhomogeneous broadening, while simultaneously achieving high QD densities are vital to the commercial success of such QD based devices.
Using high angle annular dark field scanning transmission electron microscopy (HAADF-STEM) imaging, micro-structural analysis of the active region of QD lasers is made possible. A size distribution anisotropy was observed for the QD ensemble through the measurement of orthogonal intensity line profiles across the HAADF STEM images.
A computationally efficient 3D model was developed to successfully link the size distribution to observed opto-electric properties. Here we describe the development of the Monte-Carlo model, which describes the shape of the ensemble gain of QD laser material based on the measured QD ensemble.
We shall discuss the results and implications of this model based on image data from TEM analysis of a real ensemble, rather than a Gaussian approximation. We discuss the sensitivity of QD based device performance on the observed QD size distribution anisotropy.