Abstract
This work describes the design and implementation of an automated device for catalytic materials testing by direct modifications to a gas chromatograph (GC). The setup can be operated as a plug-flow isothermal reactor and enables the control of relevant parameters such as reaction temperature and reactant partial pressures directly from the GC. High-quality kinetic data (including reaction rates, product distributions, and activation barriers) can be obtained at almost one-tenth of the fabrication cost of analogous commercial setups. With these key benefits including automation, low cost, and limited experimental equipment instrumentation, this implementation is intended as a high-throughput catalyst screening reactor that can be readily utilized by materials synthesis researchers to assess the catalytic properties of their synthesized structures in vapor-phase chemistries.
Original language | English (US) |
---|---|
Pages (from-to) | 805-823 |
Number of pages | 19 |
Journal | Matter |
Volume | 3 |
Issue number | 3 |
DOIs | |
State | Published - Sep 2 2020 |
Bibliographical note
Funding Information:We acknowledge financial support of the Catalysis Center for Energy Innovation, a US Department of Energy – Energy Frontier Research Center under Grant DE-SC0001004 .
Keywords
- MAP4: Demonstrate
- alcohol dehydration
- automated analysis
- automated kinetic measurements
- high-throughput experimentation
- micro-flow reactor
- packed bed reactors
- reactive gas chromatography
Fingerprint
Dive into the research topics of 'Catalysis-in-a-Box: Robotic Screening of Catalytic Materials in the Time of COVID-19 and Beyond'. Together they form a unique fingerprint.Datasets
-
Supporting data for "Catalysis-in-a-Box: Robotic Screening of Catalytic Materials in the Times of COVID-19 and Beyond"
Kumar, G., Bossert, H., McDonald, D., Chatzidimitriou, A., Ardagh, A., Pang, Y., Lee, C., Tsapatsis, M., Abdelrahman, O. A. & Dauenhauer, P. J., Data Repository for the University of Minnesota, 2020
DOI: 10.13020/6jvw-kq77, http://hdl.handle.net/11299/213839
Dataset