Dr Chris HandleyDr Christopher Handley

MChem Chemistry with Chemical Physics (hons)
PhD Computational Chemistry

Email: c.m.handley@sheffield.ac.uk

Address: Department of Materials Science & Engineering, Sir Robert Hadfield Building, Mappin Street, Sheffield, S1 3JD

Dr Christopher Michael Handley joined the Department, under the SUbST grant, working with both the MESAS (Multiscale Engineering and Science Simulations at Sheffield) and the Functional Cermanics group, in May 2015. His work focuses on the design of novel forcefields for the simulation of photovoltaic materials, and solid oxide ion conductors.

Career history
  • 2015 - current: PDRA, University of Sheffield, EPSRC funded - SUbST, "Simulation of Photovoltaic Materials"
  • 2012 - 2015: PDRA, Ruhr-Universitat Bochum, DFG funded, "Neural Network Based Tight Binding for Solid State Materials Simulation"
  • 2009 - 2012: PDRA, University of Warwick, EPSRC funded, "Molecular Modelling for Organometallic Compounds: Ru-Arenes as Catalysts and Anti-Cancer Drugs"
  • 2005 - 2009: PhD, University of Manchester, EPSRC funded,"Polarization for molecular simulation from a neural network trained by ab initio electron densities of clusters"
  • 2001 - 2005: MChem, UMIST/University of Manchester, Chemistry with Chemical Physics (hons), 2.i
Research interests

Chris is interested in the use of modern computing power to develop next generation forcefields in order to perform atomistic simulations of materials. Primarily he focused on the use of machine learning methods that can discover these forcefields, by learning the non-linear relationships between atomic positions, and the properties of the material. He employs machine learning in order to mine vast amounts of quantum mechanical simulations, with the end result being forcefields that give quantum mechanical accuracy, but for the fraction of computer time.

Chris is aware that while computational chemistry and materials simulation is a area of research that is becoming more important, the interface between this field, and traditional synthetic laboratories needs to grow, so that knowledge can be passed each to better enable novel materials discovery.

Chris is also keen to pursue scientific outreach via digital media. He has for 6 year co-hosted a podcast that focuses on his own hobbies, and would like to apply his video and audio editing skills to the promotion of science in order to raise public awareness.

Recent and current research themes
  • Simulation of novel photovoltaic materials
  • Simulation of solid oxide ion conductors
  • Development of machine learning tools for chemical simulation
  • Development of machine learning tools for materials discovery

A snapshot of the methylammonium simulation at 50KA snapshot of the methylammonium simulation at 50K, looking down the c-axis of the supercell. Grey octahedra are PbI_6 units, that share corners, with methylammonium cations represented as rods, with red atoms being carbon and light blue for nitrogen.

Hydrogen atoms have been omitted for clarity. Here two layers of octahedra are shown to have the same tilting motif, which corresponds with the expected orthorhombic structure of methylammonium at lower temperatures. Methylammonium cations clearly display short and long range ordering.

The video belA simulation of methylammonium lead iodide, performed using NPT conditions and at 300K, where the grey octahedra are PbI_6 units, that share corners. The red and light blue tetrahedra represent the methyl and ammonia groups of the methylammonium cations.

Professional activities and recognition

Chris regularly contributes to the teaching and training of undergraduates, PhD and postdoctoral researchers. He chairs the MESAS team meetings, and has recently established AIMSe (Ab Initio Materials Science & Engineering) as an interest group/training group to train users in Density Functional Theory materials simulations. He has also presented his research outside of his field at the OpenData meetings - a place for users of "big data" in computational science.

  • Member of the Royal Society of Chemistry
  • Member of the Deutsche Physikalische Gesellschaft

Selected publications

  • Handley, C.M, Behler, J (2014) Next generation interatomic potentials for condensed systems. The European Physical Journal B 87 (7), 1-16.
  • Deeth RJ, Handley CM, Houghton BJ (2013) Theoretical prediction of spin‐crossover at the molecular level. Spin-Crossover Materials: Properties and Applications, 443-454.
  • Mills MJL, Hawe GI, Handley CM, Popelier PLA (2013) Unified approach to multipolar polarisation and charge transfer for ions: microhydrated Na+. Physical Chemistry Chemical Physics 15 (41), 18249-18261.
  • Handley, C.M, Deeth, R.J (2011) A Multi-Objective Approach to Force Field Optimization: Structures and Spin State Energetics of d6 Fe (II) Complexes. Journal of Chemical Theory and Computation.
  • Handley, C.M, Popelier, P.L.A (2010) Potential energy surfaces fitted by artificial neural networks. The Journal of Physical Chemistry A 114 (10), 3371-3383.
  • Handley, C.M, Popelier, P.L.A (2009) Dynamically Polarizable Water Potential Based on Multipole Moments Trained by Machine Learning. Journal of Chemical Theory and Computation 5 (6), 1474-1489.
  • Handley, C.M, Hawe, G.I, Kell, D.D, Popelier, P.L.A (2009) Optimal construction of a fast and accurate polarisable water potential based on multipole moments trained by machine learning. Physical Chemistry Chemical Physics 11 (30), 6365-6376 60.
  • Darley, M.G, Handley, C.M, Popelier, P.L.A (2008) Beyond point charges: dynamic polarization from neural net predicted multipole moments. Journal of chemical theory and computation 4 (9), 1435-1448.
  • Handley, C.M, Popelier, P.L.A (2008) The asymptotic behavior of the dipole and quadrupole moment of a single water molecule from gas phase to large clusters: a QCT analysis. Synthesis and Reactivity in Inorganic, Metal-Organic, and Nano-Metal.