Module manager: Dr Andrea Laybourn
Email: a.laybourn@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2025/26
A background in Chemistry equivalent to year 2 undergraduate level or selection of Foundations of Chemistry optional module in Semester 1
This module is not approved as an Elective
Innovative technologies are transforming how data is collected and experiments are conducted, empowering scientists to achieve precision and efficiency in their workflows. This module introduces cutting-edge technologies enabling autonomous collection of large datasets, focusing on their applications across diverse scientific challenges. Students will learn to design and implement experimental platforms tailored to specific needs, combining theoretical insights with practical experience. Through hands-on workshops and interactive examples, students will acquire the skills to leverage these technologies effectively, preparing them to tackle complex scientific problems in a rapidly evolving research landscape.
To introduce students to the wide range of enabling technologies used for data collection and automated synthesis. The module aims to provide a comprehensive understanding of the principles, functionalities, and limitations of these technologies. Additionally, students will learn how to critically evaluate and select appropriate tools and methodologies based on specific experimental requirements and objectives. They will gain skills in designing and developing platforms that address challenges across diverse applications.
On successful completion of the module students will have demonstrated the following learning outcomes relevant to the subject:
1) Understand the key principles of digital chemistry and its role in modern scientific research
2) Describe various high-throughput (HTE) approaches and identify appropriate platforms for batch automation and multistep synthesis
3) Extract and process data from online databases and apply visualisation techniques to analyse and interpret the data
4) Demonstrate familiarity with the use of remote and national research facilities
5) Evaluate and select suitable enabling technologies, including flow chemistry, non-conventional reaction methods, and process analytical technologies, for specific experimental needs
6) Design experimental platforms using a combination of automated synthesis equipment tailored to diverse applications
Skills Learning Outcomes
On successful completion of the module students will have demonstrated the following skills :
A) Design an automated experimental workflow for data collection
B) Extract, process, and visualise experimental data
C) Communicate complex experimental set-ups and outcomes effectively to both technical and non-technical audiences
- Introductory/scene setting overview of digital chemistry
- Batch automation
- HTE approaches for synthesis
- Equipment
- Automated multistep synthesis (e.g., iterative reactions, peptides etc.)
- Using remote and national facilities (RFI, Royce, Diamond)
- Enabling technologies
- Flow chemistry
- Digital chemistry for materials
- Principles of green chemistry and sustainability
Methods of assessment
The assessment details for this module will be provided at the start of the academic year
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Lecture | 10 | 1 | 10 |
| Practical | 5 | 2 | 10 |
| Seminar | 5 | 2 | 10 |
| Independent online learning hours | 10 | ||
| Private study hours | 110 | ||
| Total Contact hours | 30 | ||
| Total hours (100hr per 10 credits) | 150 | ||
Discussions with staff in workshops/seminars.
Marks for assignments and quizzes.
The reading list is available from the Library website
Last updated: 30/04/2025
Errors, omissions, failed links etc should be notified to the Catalogue Team