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A Raspberry Pi Pico Based Low-Cost, Research-Grade, Open-Source Thermal Conductivity Cell Detector for Chemical Laboratory Analysis (Journal Article)

By: Contributor(s): Material type: TextTextSeries: Journal of Chemical Society ; , Volume 100: Number 9, September 2023Publication details: Washington DC : American Chemical Society , 2023Description: 3477–3483pISSN:
  • 0021-9584
Subject(s): Online resources:
Contents:
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Summary: Abstract: The “maker” movement is gaining widespread attention, especially in the field of laboratory education. Here we have built a low-cost, “do-it-yourself”, open-source thermal conductivity cell detector (TCD) for chemical laboratory analysis, which is assembled from thermal conductivity gas sensor elements and 3D-printed flow cell parts based on a Raspberry Pi Pico microcontroller. An ADS1115 digital-to-analog converter (with 16-bit acquisition resolution) is used to acquire the electrical signal from the thermal conductivity sensor response via a Wheatstone bridge. The device is programmed to acquire data based on the open-source Thonny Micro Python IDE software via I2C communication. Temperature programming analysis (TPA) is an important technique to characterize heterogeneous catalysts; therefore, we apply the assembled TCD to characterize the reduction properties of commercial Cu/ZnO/Al2O3 catalysts. The hydrogen temperature-programmed reduction (H2-TPR) profile of the commercial Cu/ZnO/Al2O3 catalyst shows a broad peak in the range of 150–250 °C with a peak position at 213 °C, which is consistent with previous reports. The total amount of hydrogen consumed by the commercial catalyst during H2-TPR is 10.7 mmol/gcat, which can be calculated from the calibrated H2 vol % TCD signal result and the peak area of the H2-TPR profile. The results show that the fabricated TCD detector exhibits excellent performance during the testing process and is capable of meeting research-grade applications. In summary, students will learn a wide range of skills in a hands-on learning environment of a chemistry laboratory course.
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Abstract: The “maker” movement is gaining widespread attention, especially in the field of laboratory education. Here we have built a low-cost, “do-it-yourself”, open-source thermal conductivity cell detector (TCD) for chemical laboratory analysis, which is assembled from thermal conductivity gas sensor elements and 3D-printed flow cell parts based on a Raspberry Pi Pico microcontroller. An ADS1115 digital-to-analog converter (with 16-bit acquisition resolution) is used to acquire the electrical signal from the thermal conductivity sensor response via a Wheatstone bridge. The device is programmed to acquire data based on the open-source Thonny Micro Python IDE software via I2C communication. Temperature programming analysis (TPA) is an important technique to characterize heterogeneous catalysts; therefore, we apply the assembled TCD to characterize the reduction properties of commercial Cu/ZnO/Al2O3 catalysts. The hydrogen temperature-programmed reduction (H2-TPR) profile of the commercial Cu/ZnO/Al2O3 catalyst shows a broad peak in the range of 150–250 °C with a peak position at 213 °C, which is consistent with previous reports. The total amount of hydrogen consumed by the commercial catalyst during H2-TPR is 10.7 mmol/gcat, which can be calculated from the calibrated H2 vol % TCD signal result and the peak area of the H2-TPR profile. The results show that the fabricated TCD detector exhibits excellent performance during the testing process and is capable of meeting research-grade applications. In summary, students will learn a wide range of skills in a hands-on learning environment of a chemistry laboratory course.

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