Sequential fixed-fluidized bed foam granulation (SFFBFG) and drying: Multivariate model development for water content monitoring with near–infrared spectroscopy
Foam granulation (FG) is a non-conventional technique in which a binding solution is sprayed as aqueous foam. The main objectives of this work are, converting a lab-scale fluidized bed dryer into a fluidized bed foam granulator and dryer. Second, developing a partial least squares regression model for monitoring granules water content during this process, and third, bringing forward sufficient evidence of the fluidized bed foam granulation process feasibility. In this work, a mini-Glatt fluidized bed apparatus was used and aqueous foam was produced through an internal mixing nozzle located above the static powder bed, which is fluidized after foam dispensing.
Highlights
Foam granulation and drying processes are performed in a fluidized bed apparatus.
An internal mixing nozzle producing foam was used to deliver the binder.
A protocol for fluidized bed foam granulation was developed and tested.
Near Infrared spectroscopy was successfully used to monitor water content during the process.
A Partial Least Square model built by cross-validation successfully predicts water content.
A micro-NIR probe was inserted across the powder container and gather spectral data during granulation and drying. The calibration model was built using the spectral data by Random Subset Cross-Validation and validated externally. Concerning the results, an Rcal2 and RMSECV of 0.945 and 1.67% w/w were obtained respectively. Model validation gave an Rval2 and RMSEP of 0.9 and 2.7% w/w respectively, demonstrating the ability of NIR spectroscopy to predict granules water content. The scanning electron microscopy (SEM) pictures validated the process feasibility.
Abdoulah Ly, Inès Esma Achouri, Ryan Gosselin, Nicolas Abatzoglou,
Sequential fixed-fluidized bed foam granulation (SFFBFG) and drying: Multivariate model development for water content monitoring with near–infrared spectroscopy,
Chemical Engineering Science, Volume 262, 2022, 118039, ISSN 0009-2509, https://doi.org/10.1016/j.ces.2022.118039.