Large-scale approaches to optimizing room temperature nanowire lasers

Abstract

Over the past 20 years, semiconductor nanowires have attracted substantial research interest for the development of nano-photonic devices. Particularly, nanowires are promising for the fabrication of smaller and more power-efficient lasers, and have a wide range of applications in telecommunications, information processing, machine learning, medicine, defence and consumer electronics. Room-temperature lasing has been demonstrated across different material systems in III-N, and II-VI semiconductor nanowires, and more recently in III-V alloys such as GaAs and InP. III-V semiconductors are the most widely used for optoelectronic devices and thus the fabrication of nanowire lasers based on these materials has great potential for the development of new technologies. Recently, further efforts to improve cavity design and nanowire growth techniques have resulted in lasers with high gain and lower pump requirements. However, due to the bottom-up growth, device reproducibility is difficult to achieve. For instance, a difference in local growth conditions may cause nanowires to be different thus causing a spread in lasing performance. In this PhD thesis, I present a large scale fully automated imaging and spectroscopic methodology for nanolaser characterisation. With this technique, I demonstrate a quick way to locate, take images and perform low power optical spectroscopy at room temperature on thousands of nanowires dispersed on a low index substrate. With the acquired images and spectral data, it is possible to obtain specific information about each nanowire morphology, composition and emission quality. Moreover, by using power-dependent photoluminescence under pulsed excitation, information, such as lasing threshold, lasing peak energy and spectral range, can be obtained. By combining a large amount of data with robust statistical techniques I am able to carry out correlations between different nanowire parameters and optoelectronic performance. This has important applications in the field of nanolaser design and fabrication. Firstly, it is possible to obtain the yield of functional devices within a nanowire growth, which is a critical figure of merit for industrial applications. Secondly, this methodology has the capability to accurately identify key parameters affecting lasing performance for a given nanowire architecture. This is helpful to improve the fabrication of future nanolasers thus narrowing the spread in device performance and increasing scalability. Additionally, I apply the large scale technique to provide a deep understanding of the physics underlying device emission efficiency, which would otherwise require more complex and time consuming techniques. Lastly, by looking at a large number of nanowires, I am able to find the best-in-class nanolaser, which is important for single device applications in photonic circuits.

Date of Award	1 Aug 2020
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Philip Dawson (Supervisor) & Patrick Parkinson (Supervisor)