Automated and data-driven laboratories

CH-400 / 2 credits

Teacher: Miéville Pascal

Language: English

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
  • Courses: 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
  • Courses: 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
  • Courses: 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
  • Courses: 2 Hour(s) per week x 14 weeks
  • Type: optional

Reference week

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