This paper demonstrates an innovation in the kinetic modeling of biomass hydrothermal carbonization based on stochastic techniques. The dynamics of HTC solid-phase transformations is described without assuming a reaction network. Through the maximum-entropy principle, an equation, which fits data flexibly, rises to the status of a lumped kinetic model. The time-course of biomass conversion is described as the macroscopic effect of microreactions, whose frequency is distributed as a continuous probability density function. The mathematics which defines the density function takes advantage of the identified analogies with other scientific fields. The corresponding cumulative frequency distribution is shown to coincide with the empirical fitting equation. The analysis of a wide range of literature data, concerning various waste biomasses, allows testing the new model. The good accordance between previsions and experimental evidence encourages the research to follow this way. Sound procedures for further validating the model are outlined.
Modeling biomass hydrothermal carbonization by the maximum information entropy criterion
Gallifuoco, Alberto
;Papa, Alessandro Antonio;Taglieri, Luca
2021-01-01
Abstract
This paper demonstrates an innovation in the kinetic modeling of biomass hydrothermal carbonization based on stochastic techniques. The dynamics of HTC solid-phase transformations is described without assuming a reaction network. Through the maximum-entropy principle, an equation, which fits data flexibly, rises to the status of a lumped kinetic model. The time-course of biomass conversion is described as the macroscopic effect of microreactions, whose frequency is distributed as a continuous probability density function. The mathematics which defines the density function takes advantage of the identified analogies with other scientific fields. The corresponding cumulative frequency distribution is shown to coincide with the empirical fitting equation. The analysis of a wide range of literature data, concerning various waste biomasses, allows testing the new model. The good accordance between previsions and experimental evidence encourages the research to follow this way. Sound procedures for further validating the model are outlined.File | Dimensione | Formato | |
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