All Department of Chemistry courses

This course will cover the quantitative background to underpin many of the electrochemical methods exploited by the research groups in the Department. The first part ('Foundations') will cover the background physical chemistry relevant for electrochemical systems: Following a reminder of the basics of electrochemistry, we address the physical chemistry of metals, ionic solutions and the electrode/solution interface, including electrode dynamics, and connection to experimental measurements. The second part ('Applications') will cover specific examples of applications drawn from active research groups in the department.

This course is made up of 8 sessions which will be based around the topics below: unlike other courses in the Graduate Lecture Series, it is essential to attend all 8 sessions to benefit from this training. Places are limited so please be absolutely certain upon booking that you will commit to the entire course.

Once you book this course, you will need to register for each session via Zoom.

This is a practical skills-based course which comprises of 1 optional drop-in session and 6 compulsory instructor-lead statistics sessions. These will take place in Todd Hamied

The Departmental Advanced Safety Training covers basic induction training in how to work safely, including emergency arrangements for fire and evacuation, first aid and incidents including flood and gas leak. By attending, you are made aware of the Department’s Health and Safety Policy and your responsibilities under health and safety law. You will be introduced to the process required to prepare a risk assessment with standard operating procedure (SOP) or method statement, how to select the correct type of protective equipment (PPE) and why it needs to be worn, and reminded of the importance of good house keeping for reducing the likelihood of there being an incident. The hazards associated with display screen equipment (DSE) and manual handling are identified and the need to control them by a suitable and sufficient assessment of the risk is explained. Electrical safety and the requirement for annual Portable Appliance Testing (PAT) is made clear.

• Please note you will find this training on Moodle.

Part of Induction Week

Advanced induction training for experimentalists introduces some of the department’s special chemical hazards including explosives, hydrogen fluoride and cyanide, and restricted chemicals, and illustrates the consequences of incorrect waste disposal. Experimentalists are made aware of the biological hazards in the department and how these are controlled with a suitable risk assessment, safety cabinets and the need for the appropriate inactivation method to be applied. Attendees are alerted to the hazards and damage caused by non-ionising radiation, glassware and sharps, oil baths and lifting equipment. The induction concludes by directing the experimentalist to compulsory University-provided specialist training courses, the requirement for fire awareness training and sources of Health and Safety information.

• This training is will be available on Moodle.

This course will cover safe storage and use of cryogens, safe use and stores of compressed gas, and aspects of oxygen depletion with respect to the above.

• This training will be available on Moodle.

This course will focus on recent progress in the application of kernel-based methods, Random Forests and Deep Neural Networks to modelling in chemistry. The material will build on the content of the core Informatics course and introduce new descriptors, advanced modelling techniques and example applications drawn from the current literature. Lectures will be interactive, with students working through computational exercises during class sessions.

An applied introduction to probabilistic modelling, machine learning and artificial intelligence-based approaches for students with little or no background in theory and modelling. The course will be taught through a series of case studies from the current literature in which modelling approaches have been applied to large datasets from chemistry and biochemistry. Data and code will be made available to students and discussed in class. Students will become familiar with python based tools that implement the models though practical sessions and group based assignments.

This course will introduce students to the central question of how to encode molecules and molecular properties in a computational model. Building on the compulsory informatics course (see previous table entry), it will focus on reactivity parameterisation and prediction. The basics of DFT calculations will be introduced, together with how DFT can be used to model reactions (including flaws, assumptions, drawbacks etc). Lecture based format will be complemented by practical sessions in setting up different DFT-based calculations.