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Designing efficient search strategies for new material discovery in complex phase and data space

Project Description

As we search for higher-performance materials with a particular function, we need to explore systems that contain more chemical elements, referred to as more complex phase space. This larger search space presents incredible opportunities but owing to the significant effort required to investigate even a single sample in a lab, the sheer number of possible sample compositions available in more complex phase and data space demands effective search algorithms in order to succeed.
This chemical problem can be stated as an optimal simplex exploration/sampling problem, and towards this goal, this project will explore optimization methods and routines to develop optimal search strategies for new materials in high-dimensional search spaces, beginning with a single batch of data points, and expanding towards multi-batch searches incorporating information gained from previous batches. The synthetic methods used to identify each material also contain multiple variables, which also require optimal search.
Specifically, the student will work closely with computer scientists, inorganic chemists, physicists, and material scientists to develop software tools and active learning algorithms to choose experimental compositions in phase space with >5 elements, associated synthesis conditions, and to efficiently determine the compositions of new unknown materials. This will also involve exploring and benchmarking optimization strategies and developing visualization tools that accurately convey the optimization processes to users in terms of composition and experimental condition selection.
Qualifications: Applications are welcomed from students with a 2:1 or higher master’s degree or equivalent in Computer Science, Mathematics, Chemistry, Physics, or Materials Science, particularly those with some of the skills directly relevant to the project outlined above. Successful candidates will have strong math and programming skills.

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Funding Notes

EPSRC eligibility
Please refer to the EPSRC website View Website

The award will pay full tuition fees and a maintenance grant for 3.5 years. The maintenance grant is £15,009 pa for 2019-20, with the possibility of an increase for 2020/21.

GTA eligibility (EU or non-EU students only)
Depending on the successful applicant this studentship would include a commitment to work up to 77 hours per academic year to help with teaching-related activities. The award will pay full home/EU tuition fees and a maintenance grant for 3.5 years. Non-EU applicants may have to contribute to the higher non-EU overseas fee.


Accelerated discovery of two crystal structure types in a complex inorganic phase field. Nature 546, 280-284 (2017);
Perspective: Composition–structure–property mapping in high-throughput experiments: Turning data into knowledge. APL Materials 4, 053211 (2016);

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