Journal of Computational Intelligence in Materials Science


A Critical Review of Nanoparticles and Nano Catalyst



Journal of Computational Intelligence in Materials Science

Received On : 20 November 2022

Revised On : 25 December 2022

Accepted On : 02 January 2023

Published On : 09 January 2023

Volume 01, 2023

Pages : 012-022


Abstract


Catalysis holds a significant position in the field of chemistry, wherein it manifests in three distinct directions that exhibit minimal overlap: heterogeneous, enzymatic, and homogeneous. Heterogeneous and homogeneous catalysis are recognized as distinct fields championed by two scientific societies, namely solid state and molecular chemistry. Despite their differences, both domains share a common goal of seeking to enhance catalytic performance. Nanocatalysis has gained prominence as a burgeoning scientific discipline in recent times, owing to its exceptional levels of activity, selectivity, and productivity. The distinctive characteristics of nanocatalysts arise from their nanoscale dimensions, morphology, and significantly elevated surface area to volume ratio. These structural and electronic modifications distinguish them from their bulk counterparts, resulting in unique properties. At the nanoscale level, the principles of quantum chemistry and classical physics are not applicable. In materials characterised by robust chemical bonding, the degree of electron delocalization can be substantial and may exhibit size-dependent variability. The primary objective of this review is to expound upon the critical understanding of nanocatalysis, detailing how the different catalytic feature and other particle features of nanomaterials are contingent on their structure and size at an atomic level.


Keywords


Nanoparticles, Nanomaterials, Nanoscience, Carbon Nanotubes, Homogeneous Catalysis, Heterogeneous Catalysis.


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Cite this article


Tian Chen and Davin Meng, “A Critical Review of Nanoparticles and Nano Catalyst”, Journal of Computational Intelligence in Materials Science, vol.1, pp. 012-022, 2023. doi: 10.53759/832X/JCIMS202301002.


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© 2023 Tian Chen and Davin Meng. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.