8 April, 2019
Organic solar cells are an emerging technology for low-cost, sustainable energy production. When these absorb light, this triggers electron- transfer from a donor molecule to an acceptor molecule, forming charges. This process occurs within 100 trillionths of a second. Dr Paul Hume will be exploring how the charge-generation process depends on the chemical structure of the acceptor.
Dr Ben Yin’s research focuses on developing membrane technologies for gas separation and water treatment. Specifically, his MacDiarmid Institute project aims at producing high quality natural gas through a customized mixed matrix membrane process to remove impurities such as excess carbon dioxide.
Dr Komal Patil’s research aims to generate new knowledge and expertise in the area of carbon capture using novel porous materials called ‘metal-organic frameworks’ (MOFs). She will develop new MOFs with improved stability and modify the pores of these materials to target the reversible capture of carbon dioxide and other gaseous environmental contaminants such as hydrogen sulfide.
Dr Frederick Wells plans to look at how a liquid superconductor would behave near a magnet. By drying these liquids like paint, he hopes to make a liquid superconductor! Superconductors carry electricity with 100% efficiency. They can also hover above a magnet. But what would a liquid superconductor do near a magnet? Also, by drying these liquids like paint, he hopes to make sturdier superconducting cables to transport huge amounts of electricity.
Dr Krista Steenbergen’s proposed research hopes to advance our fundamental understanding of carbon nanotubes (CNTs) by developing a computational algorithm that enables electronic structure calculations for larger CNTs. A CNT consists of a thin sheet of carbon atoms (graphene) curled into a cylinder. Despite their small size and simple composition, this remarkable nanoscale system holds profound technological promise and power.
Dr Walter Somerville’s research examines how light behaves inside materials. By using computational techniques, the effect of different sample properties on light scattering statistics can be determined. This work has applications in improving the ability to measure properties of varied samples, including milk, paint, clouds, water or biological samples.