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  Scopus ID: 21100926589

Machine Learning for Improved Nanomaterial Applications in Biology and Medicine: A Catalytic Perspective

Pramod Sridhara, Luis Buenaño, Sayuri Bonilla, Freddy Ajila, Rolando Marcel Torres Castillo, Mahaboob Khan Sulaiman and Mayakannan Selvaraju

Abstract

Nanotechnology is the study of materials whose structures are between 0.1 and 100 nanometers in size, and their applications. The size effect, surface effect, and other unique characteristics of this material mean that it has a wide range of potential uses beyond those of more conventional materials. The increasing usage of nanoparticles in today’s industries and lifestyles has sparked growing concern, particularly in the fields of biology and medicine. Researchers are now focusing on how to create multifunctional nanomaterials with features like magnetism and catalytic capabilities, and how to apply these materials more effectively in the field of biology. In addition to enhancing the quality of the wood, automatic detection of subpar wood is possible due to machine learning, which eliminates the possibility of human error due to eye tiredness or other subjective elements in the manual identification process. A measure of frequency of use. In this research, we focus on the application of the fuzzy analytic hierarchy approach to the investigation of nanocomposites and their catalytic performance in the oxidation of glucose. When comparing Ni3 S2 /IL-GR/GCE to glassy carbon bare electrode (GCE) and IL-GR/GCE, the latter has demonstrated much greater electrocatalytic activity for glucose oxidation. Using a sensitivity of S/N = 4, the linear range is from 0 to 1000 µm, and the detection limit is 0.162 µm. Ni3 S2 /ILGR/GCE was shown to have a high level of anti-interference since the glucose current response was not considerably altered.

Published on: November 03, 2023
doi: 10.17756/nwj.2023-s3-171
Citation: Sridhara P, Buenaño L, Bonilla S, Ajila F, Castillo RMT, et al. 2023. Machine Learning for Improved Nanomaterial Applications in Biology and Medicine: A Catalytic Perspective. NanoWorld J 9(S3): S966-S972.

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