Characterization of the surface properties of nanoparticles using moisture adsorption dynamic profiling  
(2545-2553)  Chemical Engineering Science 66  #12 (2011)
Wang, Yao and Shadman of the University of Arizona, Arizona, developed a method for characterizing the surface properties that contribute to the adsorption and desorption interactions.  This method uses a sample cell and an in-situ FTIR to obtain the time profiles of dynamic interactions of adsorbing species on nanoparticle samples.  The results are then analyzed using a process simulator to determine the fundamental properties such as capacity, affinity, rate expressions, and activation energies of nanoparticle interactions with contaminants.  The method is illustrated using moisture as a representative model compound and particles of SiO2, HfO2, and CeO2, which are three oxides used in semiconductor manufacturing.  The results indicate that the surface interaction parameters are both species and particle size dependent.  SiO2 has the highest adsorption capacity and therefore most prone to the adsorption of moisture and similar contaminants.  However, the affinity of the NPs for H2O retention is highest for CeO2 and lowest for SiO2.  Factors contributing to the environmental and health impact of NPs (extent of surface coverage, capacity, activation energy of retention) are higher for smaller particles of the same oxide.  (RDC 5/5/2011)