Research areas

• Materials discovery using first principles simulations and surrogate models.
• Materials and chemical data management for experiment and theory.
• Crystal structure databases and associated software development for reproducible science (OPTIMADE).
• High-throughput computational materials science workflows and crystal structure prediction with AIRSS, genetic algorithms and other related methods.
• Transition-metal phosphides for beyond-Li battery anodes.

Software

Most of my software work can be found on my GitHub.

• Codename: datalab is a web API and Vue front-end app for materials chemistry data management, tracking samples, devices and their connections, and performing simple analysis of characterisation experiments (XRD, NMR, electrochemistry).
• optimade-python-tools is a Python library of tools for implementing and consuming OPTIMADE APIs, which I develop and maintain.
• OPTIMADE is the specification repository for OPTIMADE, a common REST API for access to materials databases, which I help to develop and maintain. [7]
• MaRDA Extractors WG: I founded and co-lead a MaRDA working group (open to all!) on the topic of metadata extractors for materials science and chemistry.
• MODNet is a package for materials property prediction focused on small datasets, which I help develop and maintain. [6]
• matador is a Python package for the aggregation, standardisation and analysis of the results of first-principles computations, with a focus on battery materials [5].
• ilustrado is a Python package that implements a highly-customisable, massively-parallel genetic algorithm for ab initio crystal structure prediction.
• odbx.science is a public OPTIMADE API that hosts the Morris group’s crystal structures.