Bakhtiyor Rasulev - Zeta Potential for Metal Oxide Nanoparticles: A Predictive Model Developed by a Nano-Quantitative Structure-Property Relationship

Document created by Bakhtiyor Rasulev on Jun 12, 2015Last modified by Bakhtiyor Rasulev on Jun 12, 2015
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  Publication Details (including relevant citation   information):

  Mikolajczyk, Alicja; Gajewicz, Agnieszka; Rasulev, Bakhtiyor;   Schaeublin, Nicole; Maurer-Gardner, Elisabeth; Hussain, Saber;   Leszczynski, Jerzy; Puzyn, Tomasz

  CHEMISTRY OF MATERIALS, 2015, 27 (7), 2400-2407


  Physico-chemical characterization of nanoparticles in the context   of their transport and fate in the environment is an important   challenge for risk assessment of nanomaterials. One of the main   characteristics that defines the behavior of nanoparticles in   solution is zeta potential (zeta). In this paper, we have   demonstrated the relationship between zeta potential and a series   of intrinsic physico-chemical features of 15 metal oxide   nanoparticles revealed by computational study. The here-developed   quantitative structureproperty relationship model (nano-QSPR) was   able to predict the zeta of metal oxide nanoparticles utilizing   only two descriptors: (i) the spherical size of nanoparticles, a   parameter from numerical analysis of transmission electron   microscopy (TEM) images, and (ii) the energy of the highest   occupied molecular orbital per metal atom, a theoretical   descriptor calculated by quantum mechanics at semiempirical level   of theory (PM6 method). The obtained consensus model is   characterized by reasonably good predictivity (Q(EXT)(2) = 0.87).   Therefore, the developed model can be utilized for in silico   evaluation of properties of novel engineered nanoparticles.

  This study is a first step in developing a comprehensive and   computationally based system to predict physicochemical   properties that are responsible for aggregation phenomena in   metal oxide nanoparticles.

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