The first amorphous silicon solar cell using a p-i-n structure was developed in 1976 by Carlson and Wronski. In the following decades techniques such as hydrogenation and light trapping texturing were used to raise the efficiency of a-Si thin film solar cell from 2.4% to 9.3%. The research focus has since then shifted from single junction to multi junction solar cells. In a single junction solar cell much of the solar spectrum is underutilised. As photon energy that exceeds the bandgap is wasted as heat, and photons with energy below the bandgap can not be absorbed. In a multi junction structure this problem can be solved by tailoring each layer of the solar cell to a specific range of the solar spectrum, thereby increasing the efficiency.

The focus of this project is to study the potential of germanium tin alloy as a low bandgap material for the bottom layer of a multi junction solar cell. This is done by depositing the a-GeSn:H layers through plasma enhanced chemical vapour deposition(PECVD) with germane and tetramethyltin(TMT) as precursor gas, and examining the optical and electrical properties of the samples made under various deposition conditions. This project will also study the effect of carbon inclusion in germanium, due to it being a side effect of using TMT as a precursor gas.

This report details the design and implementation of a subsystem providing a web-based platform for smartwatch data acquisition. A smartwatch application is developed to read out the accelerometer, gyroscope and heart rate sensor on the smartwatch and transmit the sensor data to the platform. A platform is developed to receive the data and store it in a database. Recordings can be downloaded from the platform to use in research of human activity. The platform presents the type of activity the smartwatch user is doing using machine learning models, by integrating the other subsystem. Multiple tests have been performed to analyse and improve the performance of the system. The battery life of the smartwatch has been tested using various settings in the smartwatch application to determine the most power-efficient settings.