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Nanoscience & Nanotechnology-Asia publishes expert reviews, original research articles, letters and guest edited issues on all the most recent advances in nanoscience and nanotechnology with an emphasis on research in Asia and Japan. All aspects of the field are represented including chemistry, physics, materials science, biology and engineering mainly covering the following; synthesis, characterization, assembly, theory, and simulation of nanostructures (nanomaterials and assemblies, nanodevices, nano-bubbles, nano-droplets, nanofluidics, and self-assembled structures), nanofabrication, nanobiotechnology, nanomedicine and methods and tools for nanoscience and nanotechnology.


Agnieszka Gajewicz, Tomasz Puzyn, Bakhtiyor Rasulev, Danuta Leszczynska and Jerzy Leszczynski
Nanoscience & Nanotechnology-Asia, 2011, 1, 53-58

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Abstract

Most of physicochemical properties of nanoparticles alter with their varying size. Therefore, understanding the size-property relationships is essential to design nanoparticles characterized by desired features. We have studied those relationships based on a series of 6 representative metal oxides molecular clusters with diameters ranging from 5 Å to 50 Å. We investigated effects of the variation in the clusters size on values of the selected molecular (quantum-mechanical) parameters, that could be consider as potential nanodescriptors for QSAR/QSPR studies.

We noticed that the studied parameters change according to two main schemes: (i) increase/decrease non-linearly till it reaches a given value (saturation point) and (ii) increase/decrease linearly with size of a nanoparticle. Our results show that the saturation effect for some molecular properties of nanometer-sized metal oxides can be reached even in clusters containing dozens of atoms. Calculations based on small clusters representing smaller fragments of a nanoparticle at semiempirical PM6 level of the quantum-mechanical theory can be efficiently used for investigation and prediction of the properties of nanometer-scale metal oxides; they are not computationally demanding. We believe that the molecular properties calculated this way would be utilized in future as structural descriptors for quantitative modeling of the relationships between structure and activity of nanomaterials (Nano-QSAR).

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