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90plus 納米粒度儀應用案例-11
閱讀：392 發(fā)布時間：2014-3-17文獻名：Stability of Superparamagnetic Iron Oxide Nanoparticles at Different pH Values: Experimental and Theoretical Analysis
作者：Yoonjee Park†,Ragnhild D. Whitaker†,Rikkert J. Nap§,Jeffrey L. Paulsen ,Vidhya Mathiyazhagan‡,Linda H. Doerrer‡,Yi-Qiao Song ,Martin D. Hürlimann ,Igal Szleifer§, and Joyce Y. Wong*†
†Department of Biomedical Engineering and ‡Department of Chemistry, Boston University, Boston, Massachusetts 02215, United States
§Department of Biomedical Engineering and Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois 60208, United States
Schlumberger-Doll Research, Cambridge, Massachusetts 02139, United States
摘要：The detection of superparamagnetic nanoparticles using NMR logging has the potential to provide enhanced contrast in oil reservoir rock formations. The stability of the nanoparticles is critical because the NMR relaxivity (R2＝1/T2) is dependent on the particle size. Here we use a molecular theory to predict and validate experimentally the stability of citric acid-coated/PEGylated iron oxide nanoparticles under different pH conditions (pH 5, 7, 9, 11). The predicted value for the critical surface coverage required to produce a steric barrier of 5kBT for PEGylated nanoparticles (MW 2000) was 0.078 nm–2, which is less than the experimental value of 0.143 nm–2, implying that the nanoparticles should be stable at all pH values. Dynamic light scattering (DLS) measurements showed that the effective diameter did not increase at pH 7 or 9 after 30 days but increased at pH 11. The shifts in NMR relaxivity (from R2 data) at 2 MHz agreed well with the changes in hydrodynamic diameter obtained from DLS data, indicating that the aggregation behavior of the nanoparticles can be easily and quantitatively detected by NMR. The unexpected aggregation at pH 11 is due to the desorption of the surface coating (citric acid or PEG) from the nanoparticle surface not accounted for in the theory. This study shows that the stability of the nanoparticles can be predicted by the theory and detected by NMR quantitatively, which suggests the nanoparticles to be a possible oil-field nanosensor.