Online analysis method for pyrolysis products with large volatility difference at high temperature and pressure: Pyrolysis kinetics of supercritical pressure n-decane.

[Display omitted] • Novel online analysis method for pyrolysis products with significant volatility differences. • Sampling based on instant cooling–flashing to avoid gas–liquid separation. • The accuracy of measured mass fraction was highly improved, by 40–80% for C 3 –C 4. • The kinetic constants of SCP n-decane pyrolysis were determined and verified. Pyrolysis is widely applied in industrial fields including waste-to-energy conversion and hypersonic-vehicle cooling technology. Traditional offline analysis methods for fluid products based on cooling, depressurization, and separation processes often impart measurement uncertainties. Here, we propose a novel online analysis method for fluid pyrolysis products with significant volatility differences. High-frequency sampling based on instant cooling–flashing was used to avoid gas–liquid separation, where the fluid mixture is directly transported into an online-GC system as a vapor through a preheated vacuum tube. The method reliability was evaluated experimentally. Pyrolysis of supercritical-pressure n-decane (3–7 MPa) in a mini-tubular reactor was analyzed using both the proposed online method and an offline method. The gas yield measured using the offline method is significantly lower than that measured online due to the dissolution and volatilization loss of gaseous products during gas–liquid separation. The mass fraction of C 3 –C 4 products measured using the offline method was 40–80% less than the online results. The maximum deviation in the mass fraction of the main products obtained offline was reduced to 20–25% after dissolution-loss correction. The kinetic constants of n-decane pyrolysis were determined based on product-yield data, and the calculated residence time was experimentally verified using particle image statistics. The proposed model was implemented in a computational fluid dynamics model. The deviation between the predicted conversion and experimental results was below 11%, while the deviations of the predicted mass fraction of typical products was significantly higher based on the offline model than the online model. [ABSTRACT FROM AUTHOR]