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DLVO Approximation Methods for Predicting the Attachment of Silver Nanoparticles to Ceramic Membranes.
Mikelonis, Anne M; Youn, Sungmin; Lawler, Desmond F.
Afiliación
  • Mikelonis AM; Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin , 301 E. Dean Keeton Street, Mail Stop C1786, Austin, Texas 78712-1173, United States.
  • Youn S; Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin , 301 E. Dean Keeton Street, Mail Stop C1786, Austin, Texas 78712-1173, United States.
  • Lawler DF; Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin , 301 E. Dean Keeton Street, Mail Stop C1786, Austin, Texas 78712-1173, United States.
Langmuir ; 32(7): 1723-31, 2016 Feb 23.
Article en En | MEDLINE | ID: mdl-26797148
ABSTRACT
This article examines the influence of three common stabilizing agents (citrate, poly(vinylpyrrolidone) (PVP), and branched poly(ethylenimine) (BPEI)) on the attachment affinity of silver nanoparticles to ceramic water filters. Citrate-stabilized silver nanoparticles were found to have the highest attachment affinity (under conditions in which the surface potential was of opposite sign to the filter). This work demonstrates that the interaction between the electrical double layers plays a critical role in the attachment of nanoparticles to flat surfaces and, in particular, that predictions of double-layer interactions are sensitive to boundary condition assumptions (constant charge vs constant potential). The experimental deposition results can be explained when using different boundary condition assumptions for different stabilizing molecules but not when the same assumption was assumed for all three types of particles. The integration of steric interactions can also explain the experimental deposition results. Particle size was demonstrated to have an effect on the predicted deposition for BPEI-stabilized particles but not for PVP.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Langmuir Asunto de la revista: QUIMICA Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Langmuir Asunto de la revista: QUIMICA Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos