Autonomous kinetic model identification using optimal experimental design and retrospective data analysis: methane complete oxidation as a case study

Automation and feedback optimization are combined in a smart laboratory platform for the purpose of identifying appropriate kinetic models online. In the platform, model-based design of experiments methods are employed in the feedback optimization loop to design optimal experiments that generate data needed for rapid validation of kinetic models. The online sequential decision-making in the platform, involving selection of the most appropriate kinetic model structure followed by the precise estimation of its parameters is done by autonomously switching the respective objective functions to discriminate between competing models and to minimise the parametric uncertainty of an appropriate model. The platform is also equipped with data analysis methods to study the behaviour of models within their uncertainty limits. This means that the platform not only facilitates rapid validation of kinetic models, but also returns uncertainty-aware predictive models that are valuable tools for model-based decision systems. The platform is tested on a case study of kinetic model identification of complete oxidation of methane on Pd/Al2O3 catalyst, employing a micro packed bed reactor. A suitable kinetic model with precise estimation of its parameters was determined by performing a total of 20 automated experiments, completed in two days

Rapid Screening of Kinetic Models for Methane Total Oxidation using an Automated Gas Phase Catalytic Microreactor Platform

An automated flow micropacked bed catalytic reactor platform was developed to conduct pre-planned experiments for rapid screening of kinetic models. The microreactor was fabricated using photolithography and deep reactive ion etching of a silicon wafer, with a reaction channel width and depth of 2 mm and 420 μm respectively. It was packed with ca. 10 mg of 5 wt. % Pd/Al2O3 catalyst to perform methane combustion, which was the selected reaction to test the developed platform. The experimental system was monitored and controlled by LabVIEW to which Python scripts for online design of experiments and data analysis were integrated. Within each experimental campaign, the platform automatically adjusted the experimental conditions, and the analysis of the product stream was conducted by online gas chromatography. The experimental platform demonstrated the capability of identifying the most probable kinetic models amidst potential models within two days

Comparative Production of Bio-Oil from In Situ Catalytic Upgrading of Fast Pyrolysis of Lignocellulosic Biomass

Catalytic upgrading of fast pyrolysis bio-oil from two different types of lignocellulosic biomass was conducted using an H-ZSM-5 catalyst at different temperatures. A fixed-bed pyrolysis reactor has been used to perform in situ catalytic pyrolysis experiments at temperatures of 673, 773, and 873 K, where the catalyst (H-ZSM-5) has been mixed with wood chips or lignin, and the pyrolysis and upgrading processes have been performed simultaneously. The fractionation method has been employed to determine the chemical composition of bio-oil samples after catalytic pyrolysis experiments by gas chromatography with mass spectroscopy (GCMS). Other characterization techniques, e.g., water content, viscosity, elemental analysis, pH, and bomb calorimetry have been used, and the obtained results have been compared with the non-catalytic pyrolysis method. The highest bio-oil yield has been reported for bio-oil obtained from softwood at 873 K for both non-catalytic and catalytic bio-oil samples. The results indicate that the main effect of H-ZSM-5 has been observed on the amount of water and oxygen for all bio-oil samples at three different temperatures, where a significant reduction has been achieved compared to non-catalytic bio-oil samples. In addition, a significant viscosity reduction has been reported compared to non-catalytic bio-oil samples, and less viscous bio-oil samples have been produced by catalytic pyrolysis. Furthermore, the obtained results show that the heating values have been increased for upgraded bio-oil samples compared to non-catalytic bio-oil samples. The GCMS analysis of the catalytic bio-oil samples (H-ZSM-5) indicates that toluene and methanol have shown very similar behavior in extracting bio-oil samples in contrast to non-catalytic experiments. However, methanol performed better for extracting chemicals at a higher temperature

Comparative Production of Bio-Oil from In Situ Catalytic Upgrading of Fast Pyrolysis of Lignocellulosic Biomass

Catalytic upgrading of fast pyrolysis bio-oil from two different types of lignocellulosic biomass was conducted using an H-ZSM-5 catalyst at different temperatures. A fixed-bed pyrolysis reactor has been used to perform in situ catalytic pyrolysis experiments at temperatures of 673, 773, and 873 K, where the catalyst (H-ZSM-5) has been mixed with wood chips or lignin, and the pyrolysis and upgrading processes have been performed simultaneously. The fractionation method has been employed to determine the chemical composition of bio-oil samples after catalytic pyrolysis experiments by gas chromatography with mass spectroscopy (GCMS). Other characterization techniques, e.g., water content, viscosity, elemental analysis, pH, and bomb calorimetry have been used, and the obtained results have been compared with the non-catalytic pyrolysis method. The highest bio-oil yield has been reported for bio-oil obtained from softwood at 873 K for both non-catalytic and catalytic bio-oil samples. The results indicate that the main effect of H-ZSM-5 has been observed on the amount of water and oxygen for all bio-oil samples at three different temperatures, where a significant reduction has been achieved compared to non-catalytic bio-oil samples. In addition, a significant viscosity reduction has been reported compared to non-catalytic bio-oil samples, and less viscous bio-oil samples have been produced by catalytic pyrolysis. Furthermore, the obtained results show that the heating values have been increased for upgraded bio-oil samples compared to non-catalytic bio-oil samples. The GCMS analysis of the catalytic bio-oil samples (H-ZSM-5) indicates that toluene and methanol have shown very similar behavior in extracting bio-oil samples in contrast to non-catalytic experiments. However, methanol performed better for extracting chemicals at a higher temperature