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Published on: November 24, 2021
Modular Open-Source Stirred Tank Reactor (MOSTR), an Internet of Things (IoT) system for engineering education
Krys Bangert1, Edward Browncross1, Chalak Omar1
1Multidisciplinary Engineering Education, The University of Sheffield, The Diamond, 32 Leavygreave Road, Sheffield S3 7RD, United Kingdom.
The Modular Open-Source Stirred Tank Reactor (MOSTR) offers a low-cost, IoT-enabled platform for chemical engineering education. Its adaptable design enhances student engagement in practical experiments like residence time distribution and flow balancing.
Area of Science:
- Chemical Engineering Education
- Process Control Systems
- Open-Source Hardware
Background:
- Traditional chemical engineering labs often use expensive, inflexible equipment.
- There is a need for scalable, cost-effective, and pedagogically sound practical learning tools.
- Open-source solutions can foster wider adoption and adaptation in engineering education.
Purpose of the Study:
- To present the Modular Open-Source Stirred Tank Reactor (MOSTR) as an educational tool.
- To enable teaching of core chemical engineering principles in higher education.
- To provide a low-cost, reproducible, and maintainable alternative to commercial reactor systems.
Main Methods:
- Development of an IoT-enabled stirred tank reactor with modular components.
- Integration of an M5Stack control unit with flow, temperature, and conductivity sensors.
- Utilisation of 3D printing for accessible fabrication and Wi-Fi for real-time data streaming.
Main Results:
- The MOSTR system is sensitive to mixing variations and modular configurations, demonstrating versatility.
- Characterisation tests confirm the system's suitability for diverse educational experiments.
- The open-source nature facilitates global adoption and adaptation.
Conclusions:
- The MOSTR provides a valuable, scalable, and cost-effective platform for chemical engineering education.
- Its modularity and open-source design promote inclusivity and collaborative learning.
- The system effectively supports the teaching of residence time distribution, flow balancing, and process instrumentation.
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