Uncovering structure–function relationships is central to the discovery of new functional materials. Conventionally, this knowledge built up from iterations of synthesis, followed by property measurements and structural characterisation. The use of parallel and automated synthesis can address the speed of experiments, and computation can help us understand the structural origin of properties and even predict which experiments might prove most fruitful. But structural analysis is the crucial link that ties experimental synthesis, measurement and computational prediction together.
In the discovery of functional crystals, powder X-ray diffraction (PXRD) is a key experimental method that has proved invaluable for screening the outcome of automated crystallisation screens  and for identifying the experimental realisation of computationally predicted crystal forms. The PXRD experiment is simple and non-destructive, and is highly suited to in situ measurements; an indispensable feature for characterising functional materials. The data contains a rich source of structural information, yet the ab initio determination of structures from PXRD remains far from routine. In the context of materials discovery, characterisation of new crystalline materials can quickly become a bottleneck in the process.
This project will address the use of PXRD for determining the structures of new functional organic materials by combining experimental diffraction methods with computational materials modelling. The use of accurate methods, such density functional theory, for optimising crystal structures on desktop workstations is becoming increasingly feasible. Therefore we propose to combine population-based direct space methods for structure solution from PXRD  with accurate energy optimisations to provide an integrated efficient approach to determining complex molecular crystal structures from laboratory PXRD. This hybrid method will allow us to tackle structures where the experimental diffraction alone is insufficient to fully determine the structure, including for poorly crystalline materials – particularly relevant for classes such as 2-D covalent organic frameworks – or cases where not even the unit cell can be determined.
We also will make extensive use of information available from existing computational and experimental structural datasets. For example, one key application of this method will be using structures from ab initio crystal structure prediction, in cases where there is no direct match to experiment, as starting points for structure solution. We will also use the vast repository of information contained within the Cambridge Structural Database (CSD) to formulate models, based on structural analogues, expected conformations and intermolecular interactions, in combination with topology-based analysis of the structures.
Candidates should have a degree in in chemistry, physics, materials science or similar.
Please apply by completing the online postgraduate research application form here: https://www.liverpool.ac.uk/study/postgraduate-taught/applying/online/
Please ensure you quote the following reference on your application: Development of structure determination methods combining experimental, computational, and data-driven approaches for a high-throughput materials discovery framework. (Reference Chong LRC114)
The award is primarily available to students resident in the UK/EU and will pay full tuition fees and a maintenance grant for 3.5 years (£14,553 pa in 2017/18). Non-EU nationals are not eligible for this position and applications from non-EU candidates will not be considered unless you have your own funding.
Please note that this is a PhD Graduate Teaching Assistantships (GTA) and as such will have teaching commitments and contractual obligations to teaching associated with it.
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