Digital Chemistry

Digital chemistry covers a wide range of activities across the department, either as research in its own right, or in supporting other research areas. The research theme aims to build a community equipped with the skills, capacity and capability to use new digital and artificial intelligence tools to enhance our capacity to make advanced discoveries within molecular science.

Research activities in this area include:

• AI, machine learning and data-rich discovery

Using machine learning to predict molecular and materials properties, guide reaction and catalyst discovery, analyse large and complex datasets, interpret analytical measurements, and accelerate discovery in areas including polymers, transition metal compounds and photochemistry.

• Robotics, automation and self-driving laboratories

Developing automated workflows for synthesis, screening, reaction monitoring and instrument control, including robotics, closed-loop optimisation, computer vision, and human–AI teaming approaches that lower barriers to reproducible and scalable chemical experimentation.

• Chemical informatics and digital molecular representations

Creating new software tools and digital representations for chemically complex systems, including transition metal compounds, to enable prediction, design, and integration of experimental and computational data. Training of convolutional neural networks to annotate 3D electron density maps and streamline automated atomic model building processes.

• Computational chemistry, simulation and mechanism-led modelling

Applying and advancing quantum chemistry, molecular dynamics, Monte Carlo methods, atmospheric chemical modelling and ML-driven simulation to understand structure, bonding, dynamics, reactivity and mechanism across chemical and biomolecular systems.

• Digital spectroscopy and analytical science

Combining computation, automation and data science to improve the interpretation of NMR, IR, mass spectrometry, laser spectroscopy and colorimetric measurements, including real-time reaction monitoring and advanced data processing.

• DIY digital chemistry tools and custom research infrastructure

Building bespoke research-enabling tools, including 3D-printed components, Arduino- and microcontroller-based devices, custom software, graphical user interfaces, and in-house instruments for automation, measurement and data analysis.

The research theme has a particular interest in the training of students and staff in digital chemistry techniques and is active in the University’s MSc in Data Science.