Correlative Optoelectronic Measurements for Optimisation of Semiconductor Nanolasers

Abstract

Nanowires have emerged as essential building blocks for miniaturised devices due to their unique properties. These nanowires show promise in diverse applications, including lasers, LEDs, photodetectors, solar cells, etc. Achieving optimal operation of nanowire-based devices is critical, and reducing the variability between nanowires in mass production is essential. Although variation between nanowires leads to variation in performance, this variation is an important resource for revealing the fundamental physics of nanowires and gaining insight into material properties. This PhD thesis is dedicated to exploiting variation between nanowires to study carrier dynamics in a sub-picosecond time frame. This study aims to reveal hidden correlations between optoelectronic parameters, thus offering insight into the underlying physics and properties of nanowires. A large scale of nanowires was studied using automated high-throughput spectroscopy. Low-power and power-dependent photoluminescence measurements were acquired at room temperature. These measurements entail photoluminescence spectra and optical images for each nanowire. Fitting each photoluminescence spectrum provides profound insight into the material, electrical, and optical characteristics of the nanowires. In this work, for the first time, a Bayesian approach is presented and integrated with high-throughput spectroscopy. The Bayesian approach relies on prior knowledge and observed data to obtain updated predictions of the parameters. This novel approach allows for obtaining unknown optoelectronic parameters in high-dimensional space and reveals hidden correlations between controllable parameters (e.g., diameter) and functional parameters (e.g., lasing threshold). Using this approach, the dynamics of charge carriers within these nanowires are studied, revealing a remarkably short carrier lifetime, estimated to be 1.1 ps. High-throughput spectroscopy and the Bayesian approach together form a unified framework to investigate the inherent variation between nanowires and exploit that to uncover hidden correlations between parameters. This work serves to enhance the understanding of nanowires through simple experimentation methods.

Date of Award	1 Aug 2024
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Mark Dickinson (Supervisor) & Patrick Parkinson (Supervisor)