Modeling biomass hydrothermal carbonization by the maximum information entropy criterion
文献情報
Alberto Gallifuoco, Alessandro Antonio Papa, Luca Taglieri
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.
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Reaction Chemistry & Engineering

Reaction Chemistry & Engineering is an interdisciplinary journal reporting cutting-edge research focused on enhancing the understanding and efficiency of reactions. Reaction engineering leverages the interface where fundamental molecular chemistry meets chemical engineering and technology. Challenges in chemistry can be overcome by the application of new technologies, while engineers may find improved solutions for process development from the latest developments in reaction chemistry. Reaction Chemistry & Engineering is a unique forum for researchers whose interests span the broad areas of chemical engineering and chemical sciences to come together in solving problems of importance to wider society. All papers should be written to be approachable by readers across the engineering and chemical sciences. Papers that consider multiple scales, from the laboratory up to and including plant scale, are particularly encouraged.










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