Prediction of FID response factor of pyrolysis bio-oil components by effective carbon number model

The analytical characterization of pyrolysis bio-oil represents a formidable challenge, attributed to its complex composition and inherent corrosive properties. Addressing this, we introduce an improved version of Effective Carbon Number (ECN) model, a novel predictive framework designed to accurately estimate the Flame Ionization Detector (FID) response factors of oxygenated compounds within bio-oil based solely on their molecular structures. The ECN model, underpinned by an analysis of over 150 compounds, leverages the structural attributes of molecules to ascertain their respective response factors, thereby facilitating precise concentration measurements. Central to our findings is the model’s ability to correlate FID detector responses directly with two critical parameters: the total number of carbon atoms within the molecule, and the degree of oxidation of each carbon atom. Additionally, we have compiled a comprehensive table delineating response factors across various oxygenated functionalities, a resource that significantly expedites the analysis process of complex bio-oil mixtures.

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Publication Details

Journal
Vietnam Journal of Catalysis and Adsorption
Published
2024-12-30
DOI
https://doi.org/10.62239/jca.2024.088
Primary Topic
Thermochemical Biomass Conversion Processes
Type
article
Field-Weighted Citation Impact
0.00

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article

Prediction of FID response factor of pyrolysis bio-oil components by effective carbon number model

Daniel E. Resasco, Nhung Duong, Gap Warrakunwit
Vietnam Journal of Catalysis and Adsorption
Thermochemical Biomass Conversion Processes
article

Prediction of FID response factor of pyrolysis bio-oil components by effective carbon number model

Daniel E. Resasco, Nhung Duong, Gap Warrakunwit
article en

Abstract

The analytical characterization of pyrolysis bio-oil represents a formidable challenge, attributed to its complex composition and inherent corrosive properties. Addressing this, we introduce an improved version of Effective Carbon Number (ECN) model, a novel predictive framework designed to accurately estimate the Flame Ionization Detector (FID) response factors of oxygenated compounds within bio-oil based solely on their molecular structures. The ECN model, underpinned by an analysis of over 150 compounds, leverages the structural attributes of molecules to ascertain their respective response factors, thereby facilitating precise concentration measurements. Central to our findings is the model’s ability to correlate FID detector responses directly with two critical parameters: the total number of carbon atoms within the molecule, and the degree of oxidation of each carbon atom. Additionally, we have compiled a comprehensive table delineating response factors across various oxygenated functionalities, a resource that significantly expedites the analysis process of complex bio-oil mixtures.

Vietnam Journal of Catalysis and AdsorptionVol. 13(4)
Vietnam National University Ho Chi Minh City (VN), University of Oklahoma (US)
National Foundation for Science and Technology Development
Responsible consumption and production
Openalex Percentile: Top 77%
Thermochemical Biomass Conversion Processes
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