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DOE OSTI · 1839921

Predicting Catalytic Pyrolysis Aromatic Selectivity from Pyrolysis Vapor Composition Using Mass Spectra Coupled with Statistical Analysis

Starace, Anne K.·Lee, David D.·Hietala, Kristen T.·Kim, Yeonjoon·Kim, Seonah·Harman-Ware, Anne E.·Carpenter, Daniel L.
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Abstract

The behavior of fast pyrolysis (FP) and catalytic FP (CFP) of 20 renewable feedstocks was studied in a microscale reactor with molecular beam mass spectral analysis of products generated. A partial least-squares (PLS) model was constructed based on the FP vapor spectra that predicts the aromatic selectivity when upgrading over a ZSM-5 catalyst. Additionally, principal component analysis of both FP and CFP spectra was performed for comprehensive spectral analysis. This work highlighted the value of vapor-phase mass spectral screening to predict the subsequent feedstock performance and demonstrated that the quantity of coke deposited on the catalyst is not a reliable measure of catalyst deactivation when the feedstock type is varied.

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09 BIOMASS FUELSHZSM-5bio-oilbiomass feedstockscatalytic fast pyrolysispartial least squaresprincipal component analysis

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Starace, Anne K., Lee, David D., Hietala, Kristen T., Kim, Yeonjoon, Kim, Seonah, Harman-Ware, Anne E., Carpenter, Daniel L.. 2021-12-23. Predicting Catalytic Pyrolysis Aromatic Selectivity from Pyrolysis Vapor Composition Using Mass Spectra Coupled with Statistical Analysis. https://doi.org/10.1021/acssuschemeng.1c05916

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