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Kinetics of particle formation in the gas antisolvent precipitation process
Author(s) -
Elvassore Nicola,
Parton Tiziana,
Bertucco Alberto,
Di Noto Vito
Publication year - 2003
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.690490406
Subject(s) - supersaturation , nucleation , kinetics , precipitation , particle size distribution , particle (ecology) , particle size , chemistry , absorbance , population balance equation , analytical chemistry (journal) , population , chemical engineering , materials science , thermodynamics , chromatography , meteorology , organic chemistry , physics , oceanography , demography , quantum mechanics , sociology , engineering , geology
An original experimental setup based on UV‐vis spectroscopy was developed to study the precipitation kinetics of a biodegradable polymer by gas antisolvent processes (GAS). Poly(L‐lactide) acid (PLA) precipitations were carried out in a high‐pressure optical cell equipped with sapphire windows, working at 1–80 bar and 301.15–307.15 K. The particle formation and precipitation kinetics were investigated in situ by measuring UV‐vis absorbance of polymeric particles at a wavelength of 600 nm. They were measured in a batch system at different pressurization rates (different supersaturation conditions). To rationalize the precipitation kinetics in GAS processes, a population balance model was developed considering particle nucleation, growth, aggregation, and settling. Nucleation and growth were represented by the McCabe model, whereas both independent‐ and nonindependent‐kernel Smoluchowski's coagulation equations were used for aggregation. Settling was approximated by a first‐order kinetic. Absorbance measurements were related to the second moment of the simulated particle‐size distribution, and the kinetic parameters were estimated based on spectroscopic data. The model gave a correct phenomenological representation of all experimental data and fairly predicted the particle‐size distribution of the precipitated PLA microparticles.