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Design and Discovery of Adsorbent Materials for Challenging Gas Separation Applications


Project Description

Adsorptive gas separation and purification have long been proposed as lower cost and lower energy-use methods to replace traditional cryogenic distillation or absorptive methods. Interest in adsorptive processes has only increased with the recent proliferation of new adsorbents and increasing energy/environmental concerns. To that end, temperature swing adsorption (TSA) and pressure/vacuum swing adsorption (P/VSA) processes have been applied in several small to large scale industrial separations. With a wide variety of adsorbents and potential operating conditions, adsorptive processes are flexible in their design and operation. However, this flexibility creates complexity in both optimizing process conditions and screening potential adsorbents.

This exciting PhD project aims to design and discover new porous adsorbent materials (e.g. metal-organic frameworks and zeolites) for challenging gas separation applications in industry. To do this, we will employ a wide range of cutting-edge computational techniques from molecular- to process-level simulations as well as machine learning to enhance the speed with which adsorbent materials are developed and deployed in industry.

This is a multidisciplinary project and the successful candidate will benefit from an extensive peer-group of researchers, as well as acquiring skills at the interface between chemical engineering, material and big data science, that are in high demand in both industry and academia.

For more information, please contact Dr Peyman Z. Moghadam, or Dr Solomon Brown, .

Funding Notes

The ideal candidate will have a 1st class degree or equivalent in chemical/materials engineering, chemistry or computer science, experience in cross-disciplinary work, excellent computer skills and a hands-on approach to problem solving. No prior knowledge of simulations is necessary.

If English is not your first language, then you must have International English Language Testing Service (IELTS) average of 6.5 or above with at least 6.0 in each component.

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