Automated and data-driven laboratories
Summary
In this course, taught by experts from the Swiss CAT+ West Hub, students will be introduced to key concepts in automation and data-driven chemistry. Using real-world cases, students will learn the theoretical skills and practical tools needed to automate a laboratory.
Content
1 Key aspects of automation in chemistry
1.1 Overview of the different approaches existing in the field of lab automation 1.2 Study of existing and currently developed equipment
2 The automation tools
2.1 The workflow analysis (+ practical session)
2.2 Elements of robotics (+ practical session)
2.3 Interfacing equipment (+ practical session)
2.4 IT structure of an automated laboratory
3 Data management
3.1 Data ontology and data treatment
3.2 Closing the loop (use of algorithms to accelerate research)
3.3. Toward a self driving lab
Keywords
Labautomation, HTE, HTS, high-troughput, data-driven
Learning Prerequisites
Required courses
Bachelor level in chemistry or chemical engineering.
Learning Outcomes
By the end of the course, the student must be able to:
- Analyze a chemistry automation project in terms of feasibility, main features and equipment requirements.
- Design an automated chemical laboratory process and convert it into a logical workflow.
- Demonstrate a good level of understanding of data management, data chaining and data processing in the context of an automated laboratory.
- Explain an automated chemical workflow in clear terms to a microtechnic engineers and IT-developers.
Transversal skills
- Access and evaluate appropriate sources of information.
- Make an oral presentation.
- Write a scientific or technical report.
- Communicate effectively with professionals from other disciplines.
Teaching methods
power point presentation + practical sessions + continuous small group projects
Expected student activities
active participation to the lecture, active participation to practical sessions (organized in groups) and project follow-up throughout the semester (same group as for the practical sessions)
Assessment methods
Oral presentation of the project (25%)
Written project report (75%)
Supervision
| Office hours | No |
| Assistants | No |
| Forum | Yes |
Resources
Bibliography
Power point presentations + extra material depending on the program
Moodle Link
In the programs
- Semester: Fall
- Exam form: During the semester (winter session)
- Subject examined: Automated and data-driven laboratories
- Lecture: 2 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Fall
- Exam form: During the semester (winter session)
- Subject examined: Automated and data-driven laboratories
- Lecture: 2 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Fall
- Exam form: During the semester (winter session)
- Subject examined: Automated and data-driven laboratories
- Lecture: 2 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Fall
- Exam form: During the semester (winter session)
- Subject examined: Automated and data-driven laboratories
- Lecture: 2 Hour(s) per week x 14 weeks
- Type: optional