Jonathan Hirst | Professor of Computational Chemistry
University of Nottingham

Jonathan Hirst, Professor of Computational Chemistry, University of Nottingham

Jonathan Hirst is Professor in Computational Chemistry at the University of Nottingham. In 2020, he was awarded a Chair in Emerging Technologies by the Royal Academy of Engineering, focusing on research that will empower the development of next-generation molecules that chemical engineers and chemists make, by using machine learning to augment human decision-making. His tenure as Head of School (2013-2017) saw some significant transformations under his leadership, including the building of the GSK Carbon Neutral Laboratory and a successful bid for an Athena Swan Silver Award.


Day 1 (26th June) @ 17:00

GSK carbon neutral laboratory for sustainable chemistry

Located on the University of Nottingham’s award winning Innovation Park, the GSK Carbon Neutral Laboratory building provides unrivalled facilities for chemistry. The focus on sustainability is reflected in the building itself, which incorporates the latest technologies to allow it to be carbon-neutral over its lifetime. The laboratory is built from natural materials, and energy required to run the laboratory is met by renewable sources, such as solar power and sustainable biomass. Excess energy created by the building provides enough carbon credits over 25 years to pay back the carbon used in its construction. The building occupies 4500 square metres over two floors and in addition to laboratory space for around 100 researchers, it contains dedicated instrument rooms, a teaching laboratory for advanced undergraduate classes, and space for a range of outreach activities. In April 2017, the building was awarded the BREEAM Outstanding and LEED Platinum certifications – the highest levels of green building certifications.

Traditionally, chemical laboratories are highly energy-intensive and most are operational 24 hours a day, due to complex temperature needs for the manufacture and storage of chemicals. For example, energy-intensive cooling systems are required to stop temperatures reaching levels where solvents will evaporate. Meanwhile, recovering excess heat from processes can be challenging due to the risk of chemical and fume corrosion on the ventilation systems. Throughout the project development, cooling systems were only incorporated where absolutely required – for example, the Nuclear Magnetic Resonance lab, which is mechanically ventilated. A single lab in the centre of the building has been fitted with a natural ventilation system, to test its viability elsewhere. Chemicals at the facility are held in special storage units, meaning individual laboratories can shut down operations at night, leading to substantial energy reductions in ventilation and cooling requirements. A 125kWe biofuel combined heat and power (CHP) system was built on-site, providing the majority of heat needed for the buildings. As well as lowering carbon emissions, the CHP system exports excess heat to adjacent buildings on the University of Nottingham campus. A 230.9kWp solar array covers approximately 45% of the main building’s roof, while LED lighting has been fitted throughout, at an average of 5.4 Watts/sq.m. Overall, the building is estimated to deliver power savings of more than 60% and will use just 15% of the heat needed for a more traditional building design.

Day 2 (27th June) @ 14:00

AI4Green-An open source ELN for green and sustainable chemistry

Digital tools will be a critical part of making chemistry research laboratories more sustainable. However, there are many barriers, including hardware, software and change management. The newly released, open-source AI4Green electronic laboratory notebook,, combines features, including data archival, collaboration tools. AI4Green is a web-based application and free to use. As users plan their reactions and record them in the electronic laboratory notebook, green and sustainable chemistry is encouraged by calculating green metrics and colour-coding hazards, solvents, and reaction conditions. A Summary Table is automatically generated by AI4Green, showing Red-Amber-Green colour-coded metrics from CHEM21 and other considerations related to the Design Principles of Green Chemistry. Several metrics are calculated automatically, like the sustainability of the chemical elements used in the reaction and the atom efficiency. Other metrics must be inputted by the user, such as the temperature of the reaction, batch or flow reaction conditions, the isolation method, the use of a catalyst, and whether that catalyst was recovered. A risk assessment section allows users to identify standard protocols, disposal of waste materials, spillage procedures, and any other risks. An overall risk score is computed by self-assessment of the reaction’s hazards, risks, and consequences. The application's design facilitates the development of auxiliary sustainability applications. AI4Green features a user-friendly sustainable solvent selection tool, which comprises the Solvent Guide and the Solvent Surfer. Future deployments of AI4Green will use inputted reaction data to make intelligent sustainability suggestions. This may be to suggest using a less hazardous solvent or reagent, predict milder suitable reaction conditions, or simulate Life Cycle Analysis for process scale-up.

last published: 17/Apr/24 08:15 GMT

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