Computational modeling of ionic liquids density by multivariate chemometrics

Kоvаčеvić, Strаhinjа; Podunavac‐Kuzmanović, Sanja O.; Zec, Nebojša; Papović, Snežana; Tot, Aleksandar; Dožić, Sanja; Vastag, Gyöngyi; Gadžurić, Slobodan

doi:10.1016/j.molliq.2015.12.067

Cited by 9 publications

(5 citation statements)

References 70 publications

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“…Cluster analysis (CA) and principal component analysis (PCA) are prominent multivariate techniques utilized for the organization and interpretation of complex and diverse experimental datasets, identifying patterns and relationships within [31][32][33][34]. These methods are praised for their efficiency in classifying extensive data from varied sources and streamlining information by removing redundancies.…”

Section: Methodsmentioning

confidence: 99%

Statistical Methods Applied in Modeling Corrosion Depth Measurement on Three Different Shape Memory Alloys

Kovač,

Ivošević,

Vastag

2024

Corrosion Engineering - Recent Breakthroughs and Innovative Solutions

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This chapter presents a study focused on the corrosion behavior of three distinct shape memory alloys (CuAlNi and two types of NiTi alloys) in varied marine environments—air, tide, and seawater. The research documents corrosion damage after 6, 12, and 18 months, utilizing focused ion beam. Scanning electron microscopy and energy dispersive X-ray analyses were employed to detect the chemical alterations. This study includes both deterministic and stochastic frameworks for modeling corrosion processes. Employing a range of statistical techniques, including linear and multivariate regression, principal component analysis, and correlation analysis (linking corrosion depth with oxygen presence), the research provides an in-depth understanding of corrosion dynamics. The study explores fitting standard two-parameter and advanced multi-parameter distributions to the observed data. The dual treatment of corrosion parameters via linear and non-linear models enhances the robustness and applicability of our findings, offering more precise and effective corrosion management in marine engineering applications.

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Section: Methodsmentioning

confidence: 99%

Statistical Methods Applied in Modeling Corrosion Depth Measurement on Three Different Shape Memory Alloys

Kovač,

Ivošević,

Vastag

2024

Corrosion Engineering - Recent Breakthroughs and Innovative Solutions

Self Cite

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“…As is well known, multivariate analysis, especially the PCA, is becoming increasingly popular in processing this type of data with high dispersion and high interdependence among factors, due to its ability to recognize and eliminate redundant data. [22][23][24][25][26][27] Guided by it, in order to recognize the real effects of the tested marine environment, despite the great dispersion of the obtained results of the corrosive degradation of the tested NiTi alloy, PCA was applied.…”

Section: Influence Of Different Marine Environments On the Corrosion ...mentioning

confidence: 99%

Chemometrics as a tool for monitoring corrosion degradation of the selected alloys in real conditions

Vastag,

Apostolov,

Ivošević

et al. 2024

Journal of Chemometrics

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Monitoring of the corrosion process of alloys in real conditions often results in extensive data, which is characterized by complex interdependence, but by a large degree of mutual deviation. First of all, the large dispersion of the obtained results makes it very difficult to draw accurate conclusions about the real influence of the tested parameters on the corrosion behavior of alloys. On the other hand, in many cases, the high interdependence between the corrosion factors can also greatly burden the analyzed system and thus make it significantly difficult to recognize the main influence. Multivariate analysis, especially the principal component analysis, is becoming increasingly popular in processing of this type of data, due to its ability to recognize and eliminate redundant data. The aim of this study was to examine the possibility of using multivariate analysis methods in the processing of the corrosion test results obtained under real conditions. Based on the obtained results, it can be concluded that used multivariate method in combination with energy dispersive spectrometer analysis can be successfully used to identify the most important corrosion factors (type of corrosion environment, exposure time and technological production processes), as well as their influence on the degradation of the tested TiNi alloys under the given conditions.

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“…Cluster analysis (CA) and principal component analysis (PCA) are mathematical methods that are applied most frequently in natural sciences for the qualification and classification of large amounts of experimental data of different origins and for the determination of relationships between data [24,25,[28][29][30][31].…”

Section: Cluster Analyses and Principal Component Analysesmentioning

confidence: 99%

Corrosion of NiTiDiscs in Different Seawater Environments

et al. 2022

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This paper gives an approach to the corrosion resistance analysis and changes in the chemical composition of anNiTi alloy in the shape of a disc, depending on different real seawater environments. The NiTi discs were analysed after 6 months of exposure in real seawater environments: the atmosphere, a tidal zone, and seawater. The corrosion tests showed that the highest corrosion rate for the discs is in seawater because this had the highest value of current density, and the initial disc had the most negative potential. Measuring the chemical composition of the discs using inductively coupled plasma and X-ray fluorescence before the experiment and semiquantitative analysis after the experiment showed the chemical composition after 6 months of exposure. Furthermore, the applied principal component analysis and cluster analysis revealed the influence of the different environments on the changes in the chemical composition of the discs. Cluster analysis detected small differences between the similar corrosive influences of the analysed types of environments during the period of exposure. The obtained results confirm that PCA can detect subtle quantitative differences among the corrosive influences of the types of marine environments, although the examined corrosive influences are quite similar. The applied chemometric methods (CA and PCA) are, therefore, sensitive enough to register the existence of slight differences among corrosive environmental influences on the analysed NiTi SMA.

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Computational modeling of ionic liquids density by multivariate chemometrics

Cited by 9 publications

References 70 publications

Statistical Methods Applied in Modeling Corrosion Depth Measurement on Three Different Shape Memory Alloys

Statistical Methods Applied in Modeling Corrosion Depth Measurement on Three Different Shape Memory Alloys

Chemometrics as a tool for monitoring corrosion degradation of the selected alloys in real conditions

Corrosion of NiTiDiscs in Different Seawater Environments

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