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Please find a list of funded projects for the CDT in Computational Methods for Materials Science below.

Click on the title to see a description of each project.

Applying and developing computer simulation methods to better understand environmental ice formation - Prof Angelos Michaelides

Ice formation is one of the most common phase transitions on Earth. It is relevant to an enormous variety of phenomena such as weathering, cloud formation, airline safety, and energy. However, despite having been studied since antiquity, our molecular level understanding of ice formation is very poor. In particular, almost all ice formation in nature is aided by impurities or the surfaces of foreign materials, yet how surfaces act to facilitate ice formation (heterogeneous ice nucleation) is unclear. Given the ubiquity of ice nucleation, this is arguably one of the biggest unsolved problems in the physical sciences.

This PhD project will focus on applying and developing computer simulation approaches to better understand ice formation on solid substrates. The overall aim is to establish what makes a material good or bad at nucleating ice. The results from this project will not only shed light on an important everyday process but may also help to improve climate models and develop improved cloud seeding materials, or inhibitor coatings for industrial purposes (or maybe even better tasting ice cream!).

This project will be supervised by Prof Angelos Michaelides (Cambridge Chemistry Department)

For more information on Prof Michaelides’ research team see: https://www.ch.cam.ac.uk/group/michaelides/

Machine learning for the environment – towards improved understanding of confined water and desalination - Prof Angelos Michaelides

There is plenty of water on earth but unfortunately most of it is salty and undrinkable. Membranes for purifying and desalinating water exist but there is enormous scope to improve their performance if a clearer understanding of how water interacts with and flows across the surfaces of membrane materials. This project will involve the development and application of state of the art computer simulation approaches to obtain fundamental understanding of water when confined within the pores of membrane materThe techniques developed and applied will involve a combination of ab initio electronic structure methods and machine learning potentials. Some of the key questions we will seek to answer are: What is the structure of water when confined within the nanometre-scale pores of typical carbon-based membranes? How rapidly can water diffuse across the surfaces of membranes materials? What are the physiochemical factors that optimise water flow versus salt rejection? And more…

This project will be supervised by Prof Angelos Michaelides (Cambridge Chemistry Department)

For more information on Prof Michaelides’ research team see: https://www.ch.cam.ac.uk/group/michaelides/