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Title | Optimization of graphene oxide’s characteristics with TOPSIS using an automated decision-making process |
Authors |
Javanbakht, T.
|
ORCID | |
Keywords |
process innovation energy optimization prediction TOPSIS algorithm |
Type | Article |
Date of Issue | 2023 |
URI | https://essuir.sumdu.edu.ua/handle/123456789/91569 |
Publisher | Sumy State University |
License | Creative Commons Attribution 4.0 International License |
Citation | Javanbakht T. (2023). Optimization of graphene oxide’s characteristics with TOPSIS using an automated decision-making process. Journal of Engineering Sciences, Vol. 10(1), pp. E1-E7, doi: 10.21272/jes.2023.10(1).e1 |
Abstract |
The present study focuses on a new application of TOPSIS to predict and optimize graphene oxide’s
characteristics. Although this carbon-based material has been investigated previously, its optimization with this method
using an automated decision-making process has not been performed yet. The major problem in the design and analysis
of this nanomaterial is the lack of information on comparing its characteristics, which has led to the use of diverse
methods that have not been appropriately compared. Moreover, their advantages and inconveniences could be
investigated better once this investigation provides information on optimizing its candidates. In the current research
work, a novel automated decision-making process was used with the TOPSIS algorithm using the Łukasiewicz
disjunction, which helped detect the confusion of properties and determine its impact on the rank of candidates. Several
characteristics of graphene oxide, such as its antibiofilm activity, hemocompatibility, activity with ferrous ions in
hydrogen peroxide, rheological properties, and the cost of its preparation, have been considered in its analysis with
TOPSIS. The results of this study revealed that the consideration of the criteria of this nanomaterial as profit or cost
criteria would impact the distances of candidates from the alternatives. Moreover, the ranks of the candidates changed
when the rheological properties were considered differently in the data analysis. This investigation can help improve
the use of this nanomaterial in academic and industrial investigations. |
Appears in Collections: |
Journal of Engineering Sciences / Журнал інженерних наук |
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Javanbakht_jes_1_2023.pdf | 461,32 kB | Adobe PDF | 3880094 |
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