Computational Screening of All Stoichiometric Inorganic Materials
D W Davies et al. "Computational Screening of All Stochiometric Inorganic Materials." Chem, 1 (2016).
CV
Education
- PhD in Sustainable Chemical Technologies, University of Bath, 2018
- MRes in Sustainable Chemical Technologies, University of Bath, 2015
- MChem in Chemistry, University of Bath, 2014
Work experience
- 2021-present: Imperial College London (Senior Research Software Engineer)
- Developing software to enable research across a range of disciplines
- Scoping and writing proposals for new software projects
- Teaching graduate students about software development and version control
- 2019-2021: University College London (Postdoctoral Research Fellow)
- Investigating mixed-anion compounds for energy generation
- Writing software and machine learning models for fast materials discovery
- 2018-2019: Imperial College London (EPSRC Doctoral Prize Fellowship)
- Developed data-driven materials tools in python to design better battery cathodes
- Investigated anion redox activity in battery cathodes
- April 2018: Lawrence Berkeley National Laboratory, CA (postgraduate placement)
- Applied machine learning techniques to large materials databases
- 2012-2013: Merk KGaA, Southampton (undergraduate placement)
- Fabrication of nanowire-based biosensors and organic infrared sensors
Skills
- Software engineering
- Expert in Python
- Webapp development with Django and Dash
- Git version control
- Unit tests, continuous integration and deployment
- Containerisation with Docker
- Cloud computing on Azure
- Experience with FORTRAN and Julia
- Machine learning and data science
- Pandas, Scikit-learn, MongoDB and SQL (postgres, sqlite, timescaledb), TensorFlow
- Implement supervised learning models such as random forest, GBR and SVM
- Agile
- Experience working in an agile environment
- Working knowledge of Scrum and Kanban
- Use of Jira, Aha! and GitHub Projects
- Chemistry
- Expert user of quantum chemistry codes VASP and GPAW
- Manage automated calculations with Fireworks and Atomate
- Developer of SMACT code and expert user of Pymatgen, Matminer, ASE and OpenBabel
- Writing
- Lead author on publications in high-impact journals
- Experience writing proposals for HPC access at national (tier 1) and international (tier 0) levels
- Regularly write proposals and progress reports overseeing research software projects
Publications
Computer-aided Design of Metal Chalcohalide Semiconductors: From Chemical Composition to Crystal Structure
D W Davies et al. "Computer-aided design of metal chalcohalide semiconductors: from chemical composition to crystal structure." Chem. Sci., 9 (2018).
Applications of Crystal Structure Prediction–Inorganic and Network Structures: General Discussion
V Burger et al. "Applications of crystal structure prediction–inorganic and network structures: general discussion." Faraday Discuss., 211 (2018).
Materials Discovery by Chemical Analogy: Role of Oxidation States in Structure Prediction
D W Davies et al. "Materials Discovery by Chemical Analogy: Role of Oxidation States in Structure Prediction." Faradau Discuss., 211 (2018).
Machine Learning for Molecular and Materials Science
K T Butler, D W Davies, H Cartwright, O Isayev and A Walsh. "Machine Learning for Molecular and Materials Science" Nature, 559 (2018).
Data-driven Discovery of Photoactive Quaternary Oxides using First-principles Machine Learning
D W Davies, K T Butler and A Walsh. "Data-driven Discovery of Photoactive Quaternary Oxides using First-principles Machine Learning" Chem. Mater., 31 (2019).
Breaking the Aristotype: Featurization of Polyhedral Distortions in Perovskite Crystals
K. Morita et al, "Breaking the Aristotype: Featurization of Polyhedral Distortions in Perovskite Crystals" Chem. Mater., 34 (2022).
SMACT: Semiconducting Materials by Analogy and Chemical Theory
D W Davies et al., "SMACT: Semiconducting Materials by Analogy and Chemical Theory" JOSS, 4 (2019).
Identification of Lone-Pair Surface States on Indium Oxide
D W Davies et al., "Identification of Lone-Pair Surface States on Indium Oxide" J. Phys. Chem. C, 123 (2019).
Modelling the Dielectric Constants of Crystals Using Machine Learning
K Morita, D W Davies, K T Butler and A Walsh, "Modelling the Dielectric Constants of Crystals Using Machine Learning" J. Chem. Phys., 153 (2020).
Low-cost descriptors of electrostatic and electronic contributions to anion redox activity in batteries
D W Davies, B J Morgan, D O Scanlon and A Walsh, "Low-cost descriptors of electrostatic and electronic contributions to anion redox activity in batteries" IOP SciNotes, 1 (2020).
Bandgap lowering in mixed alloys of Cs2Ag(SbxBi1−x)Br6 double perovskite thin films
Z Li et al., "Bandgap lowering in mixed alloys of Cs2Ag(SbxBi1−x)Br6 double perovskite thin films" J. Mater. Chem. A, 8 (2020).
Surfaxe: Systematic Surface Calculations
K. Brlec, D. W. Davies and D. O. Scanlon, "Surfaxe: Systematic Surface Calculations" JOSS, 6 (2021).
Low Electronic Conductivity of Li7La3Zr2O12 (LLZO) Solid Electrolytes from First Principles
A. G. Squires et al., "Low Electronic Conductivity of Li7La3Zr2O12 (LLZO) Solid Electrolytes from First Principles" Phys. Rev. Mater., 6 (2021).
Investigation of factors affecting the stability of compounds formed by isovalent substitution in layered oxychalcogenides, leading to identification of Ba3Sc2O5Cu2Se2, Ba3Y2O5Cu2S2, Ba3Sc2O5Ag2Se2 and Ba3In2O5Ag2Se2
G. J. Limburn et al., "Investigation of factors affecting the stability of compounds formed by isovalent substitution in layered oxychalcogenides, leading to identification of Ba3Sc2O5Cu2Se2, Ba3Y2O5Cu2S2, Ba3Sc2O5Ag2Se2 and Ba3In2O5Ag2Se2" J. Mater. Chem. C, 10 (2022).
Talks
Using chemical heuristics to filter the search space of possible compounds
Talk at SNU Workshop on Electronic Structures of Materials, Seoul National University (SNU), Korea
High-throughput computation of all inorganic materials
Talk at CECAM iPolymoprhs Conference, San Sebastian, Spain
Low-cost high-throughput screening of all inorganic compounds
Talk at RSC MC13 Conference, Liverpool, UK
Using hierarchical workflows for low-cost materials screening
Talk at RSC Solid State Chemistry Group Christmas Meeting, Reading, UK
Machine learning and first principles calculations for materials discovery
Talk at MRS Spring Meeting 2018, Phoenix, AZ
Supercharging the materials discovery process with machine learning
Talk at University of Bath High Performance Computing Symposium, Bath, UK
(Invited) Predicting optical band gaps in high throughput
Invited talk at CECAM workshop on accelerating materials discovery by smart high-throughput computations, Liverpool, UK
(Invited) Property prediction using first-principles machine learning
Invited talk at Challenges in Computational Materials Science Workshop, Yonsei University, Korea
(Invited) High-throughput discovery of quaternary oxide materials using first-principles machine learning
Invited talk at National University of Singapore, Department of Research Science and Engineering, Singapore
(Invited) Chemical heuristics, ML and first-principles calculations for high-throughput materials discovery
Invited talk at Agency for Science, Technology and Research(A*STAR) Departmental Seminar, Singapore
Combining chemical heuristics, machine Learning, and first-principles calculations for rapid materials screening
Talk at RSC MC14 conference, Birmingham, UK
Descriptors for the nature of electron and hole charge carriers from first-principles calculations data
Talk at MRS Fall Meeting 2019, Boston, MA
Computational search of anion redox Li-ion battery composition space
Talk at MRS Fall Meeting 2019, Boston, MA
Virtual high-throughput screening of photoactive quaternary oxides
Talk at MRS Fall Meeting 2019, Boston, MA
(Invited) Low cost descriptors for surrogate modelling of energy generation and storage
Invited talk at STFC, SciML group, Online
(Invited) Combining chemical heuristics, automated calculations and machine learning in the search for solar active materials
Invited talk at University College London, Department of Chemistry, UCL, UK
Descriptors for electron and hole charge carriers in metal oxides
Talk at MRS Spring-Fall Virtual Meeting 2020, Online
Teaching
Service and leadership
- Member of Royal Society of Chemistry and part of Solid State Chemistry subdivision
- Reviewer for various journals including Materials Horizons, Chemical Science, Machine Learning: Science and Technology and Journal of Chemical Physics