Module manager: Dr Andrea Laybourn
Email: A.Laybourn@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2026/27
A bachelor degree with a 2:1 (hons) in engineering, environmental science, physical science or mathematics discipline
CHEM5900M
This module is not approved as an Elective
Innovative technologies are transforming how data are collected, and experiments are conducted, empowering scientists to achieve precision and efficiency in their workflows. This module introduces you to the cutting-edge technologies enabling autonomous collection of large datasets, focusing on their applications across diverse scientific challenges. You 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, you will acquire the skills to leverage these technologies effectively, preparing you to tackle complex scientific problems in a rapidly evolving research landscape.
To introduce students to the different enabling technologies for data collection and automated synthesis and enable them to design appropriate experimental platforms for a variety of applications.
Subject specific learning outcomes:
1. Understand the key principles of digital chemistry and its role in modern scientific research.
2. Evaluate and select suitable enabling technologies - such as high-throughput experimentation (HTE), flow chemistry, non-conventional reaction methods, and process analytical technologies - for specific experimental needs, and identify appropriate platforms for automation and multistep synthesis.
3. Extract and process data from online databases and apply visualisation techniques to analyse and interpret the data.
4. Design experimental platforms using a combination of automated synthesis equipment tailored to diverse applications.
Skills learning outcomes:
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.
1. Introductory/scene setting overview of digital chemistry.
2. Batch automation:
a) HTE approaches for synthesis: introduction to types of experimental campaign, examples of platforms (batch (kinetics), multiwell/plate, etc.), data processing/visualisation for HTE, extracting data from databases (e.g., ORD)
b) Equipment: delivery devices, reactors, characterisation techniques, separation/purification, process analytical technologies
c) Automated multistep synthesis
3. Enabling technologies:
a) Flow chemistry: Considerations from batch to flow, introduction to different equipment, mixing and pressure considerations, downstream processing, how to build a suitable lab-scale flow set-up, non-conventional techniques and their applications (e.g. microwave technology, electrochem, mechanochem, photochem etc)
b) Digital chemistry for materials: materials synthesis, materials characterisation and process integration (e.g. solid state NMR, XRD, FTIR, RAMAN, SEM etc.), databases: design and applications of materials
| 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.
Check the module area in Minerva for your reading list
Last updated: 29/05/2026
Errors, omissions, failed links etc should be notified to the Catalogue Team