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A simple model for vapor‐moisture equilibrium in biomass subtrates
Author(s) -
Vásquez V. R.,
Coronella C. J.
Publication year - 2009
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.11762
Subject(s) - water content , moisture , biomass (ecology) , substrate (aquarium) , water vapor , process engineering , adsorption , water activity , equilibrium moisture content , mixing (physics) , environmental science , chemistry , biological system , biochemical engineering , physics , engineering , organic chemistry , agronomy , ecology , geotechnical engineering , sorption , quantum mechanics , biology
Equilibrium moisture content (EMC) plays a fundamental role on the properties of bioderived solids such as food, waste biomass, seeds, and many others. For foods, the moisture content affects flavor, texture, and the way the food is stored. In other applications, moisture affects drying conditions and energy requirements for biomass processing. Adequate modeling of EMC in biomass as a function of the water activity is very important in many engineering applications. Most models used to correlate EMC with water activity are based on traditional adsorption models which take into account the adsorption energy of water with the substrate only and do not consider other nonadsorption interactions of water within the substrate such as mixing and swelling effects. Many other models are empirical, which are commonly used for interpolation. Although a detailed description of this type of substrate is very complex, we present a simple model based on standard molecular‐thermodynamic models and standard statistical mechanics formulations to correlate the EMC with water activity that attempts to consider both adsorption and nonadsorption interactions of the water with the substrate. Although the model is basic, it captures the behavior of water in this type of systems fairly well and it can be used to fit experimental data with parameters that provide better physical insight on the nature of system. We suggest how to improve the model fundamentally if better knowledge of the water interactions in the substrate are available. © 2009 American Institute of Chemical Engineers AIChE J, 2009