If you're an early career researcher (ECR) looking for a postdoctoral fellowship, and are interested in machine-driven materials discovery and/or synthesis please get in touch as we would love to work with you! More details available on the RAEng website; deadline 19th April.
UK IC Postdoctoral Research Fellowship
A new year, new group members
We're delighted to welcome two new members to the group this year! Ruizhi joins us as a PDRA from Queen Mary, University of London and will be working on developing new ways of describing crystal structures for use in machine learning. Ellie joins us for her final year Chemical Physics project looking at the effect of oxide doping on the electronic properties of niobium oxyfuorides. Welcome to them both!
We're hiring a postdoctoral researcher! If you are interested in combining machine learning with crystallography in order to discover new materials, please apply for our PDRA position funded by the AI3SD network. Closing date 3rd August 2020.
Electronic origin of negative thermal expansion in vanadium oxyphosphate
We have studied the negative thermal expansion (NTE) behaviour of oxyphosphate V2OPO4 over a wide temperature range using X-ray and neutron diffraction, and have discovered that the NTE arises due to an electronic charge ordering transition from a larger-volume charge-ordered phase to a smaller-volume charge-disordered phase as temperature increases. The highly anisotropic thermal expansion is dominated by the difference in size of V2+ and V3+, with NTE most apparent along the directions of face-sharing octahedral chains. This material is unusual in remaining semi-conducting throughout the charge order transition, in contrast to many other electronically-driven NTE materials.
E. Pachoud, J. Cumby, J.Wright, B. Raguž, R. Glaum and J. P. Attfield, Electronic origin of negative thermal expansion in V2OPO4, Chemical Communications, Advance Article, 2020.
Site-selective doping of ordered charge states in magnetite
We report the effect of iron off-stoichiometry in magnetite (Fe3-xO4) on the charge-ordering (Verwey) transition, and the underlying changes in crystal structure. Our detailed analysis reveals that oxidation from Fe2+ to Fe3+ preferentially occurs at one crystallographic site, while the rest of the charge-ordered structure remains intact. This new 'charge order within a charge order' phenomenom is driven by the unusual electronic trimeron distribution around the special site, causing a locally distinct ionisation potential.
E. Pachoud, J. Cumby, G. Perversi, J. P. Wright and J. P. Attfield, Site-selective doping of ordered charge states in magnetite, Nature Communications, 11, 2020, 1671.
Review: Machine learning descriptors to unify molecular and bulk systems
To use machine learning techniques to understand (and predict) structure-property relationships within chemistry, it is first necessary to represent the chemical structure in a computer-readable way. In this perspective review, we outline some of the state-of-the-art methods used to represent structure with applications both for molecular and extended solid systems. We also suggest future areas of focus in the field in order to bridge the divide between machine learning in small molecules and crystalline solids.
K. Rossi and J. Cumby, Representations and descriptors unifying the study of molecular and bulk systems, International Journal of Quantum Chemistry, 120, 2020, e26151.
Co-emergence of magnetic order and structural fluctuations in magnetite
We report high-temperature analysis of the local structure in magnetite, Fe3O4, which reveals that the low-temperature Verwey state (defined by charge ordering and trimeron bonding) persists (on a local scale) to an astonishing 850 K, the magnetic Curie temperature. This confirms that local Fe-Fe trimeron bonding arises due to magnetic ordering, far above their long-range observation (the Verwey transition).
G. Perversi, E. Pachoud, J. Cumby, J.M. Hudspeth, J.P. Wright, S.A.J. Kimber and J.P. Attfield, Co-emergence of magnetic order and structural fluctuations in magnetite, Nature Communications, 10, 2019, 2857.
PhD Studentship Available
A fully-funded (fees and stipend) PhD studentship in the discovery of functional mixed anion materials is available with the functional materials group. The project will combine experimental solid state chemistry with data-driven computational approaches to generate new transition metal oxyfluoride materials.
James presents at Machine Learning for Materials Science (ML4MS), Helsinki
James travelled to Aalto University, Helsinki to the third Machine Learning for Materials Science (ML4MS) workshop. This interdisciplinary workshop covered a huge range of applications of machine learning to materials science, and James was delighted to be awarded the ‘Best Talk by a Young Investigator’ prize.