TY - JOUR
T1 - Characterization of the surface properties of nanoparticles using moisture adsorption dynamic profiling
AU - Wang, Hao
AU - Yao, Junpin
AU - Shadman, Farhang
N1 - Funding Information:
This study is a part of the program of the SRC/Sematech Engineering Research Center for Environmentally Benign Semiconductor Manufacturing (CEBSM). The authors acknowledge financial support from SRC, Sematech , and other members of the CEBSM.
PY - 2011/6/15
Y1 - 2011/6/15
N2 - Adsorption and retention of molecular contaminants on nanoparticles (NPs) is a major factor in determining the environmental and health effects of the particles. A method has been developed 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 NP 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 NP 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.
AB - Adsorption and retention of molecular contaminants on nanoparticles (NPs) is a major factor in determining the environmental and health effects of the particles. A method has been developed 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 NP 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 NP 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.
KW - Adsorption
KW - Desorption
KW - Dynamic simulation
KW - Environmental impact
KW - Mathematical modeling
KW - Nanoparticle
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U2 - 10.1016/j.ces.2011.02.057
DO - 10.1016/j.ces.2011.02.057
M3 - Article
AN - SCOPUS:79955020382
SN - 0009-2509
VL - 66
SP - 2545
EP - 2553
JO - Chemical Engineering Science
JF - Chemical Engineering Science
IS - 12
ER -