EVALUATION OF THE RELATIONSHIPS BETWEEN METALLIC IONS MIGRATED FROM AISI304 AND AISI321 STAINLESS STEEL SAMPLES INTO FOOD SIMULANT SOLUTIONS AT VARIOUS STIRRING DEGREES
Abstract
The objective of this work was to assess through statistical methods the relationship between metallic ions migrated from AISI304 and AISI321 stainless steel food samples into acid simulant solutions depending on the stirring degrees of corrosive environments. Principal Component Analysis method (PCA) was used to fulfill the purpose aimed at. The metallic samples were immersed into corrosive solutions at diferent stirring degrees: 0 r/min (stationary environment), 125 r/min and 250 r/min. Acetic acid solutions in bidistilled water were used as food simulant environment. After
conducting the migration tests, the concentration of Cr, Mn, Fe and Ni ions migrated from AISI304 stainless steel samples into corrosive solutions and Ti, Cr, Mn, Fe and Ni ions concentration migrated from AISI321 stainless steel samples were analyzed. These concentrations were analyzed by mass spectrometry with inductively coupled plasma (ICP-MS). In order to characterize the diffusion processes occurring under accelerated corrosion, the experimental data obtained were statistically processed in two steps: analysis of the correlation between variables based on Pearson’s correlation matrix and analysis of relationships between variables through the Principal Component Analysis.
PCA method has identified the two significant principal components that explain more than 93% of the original data variance. Significant correlations between the metallic ions migrated into corrosive solutions stirred at 125 and 250 r/min were found.
conducting the migration tests, the concentration of Cr, Mn, Fe and Ni ions migrated from AISI304 stainless steel samples into corrosive solutions and Ti, Cr, Mn, Fe and Ni ions concentration migrated from AISI321 stainless steel samples were analyzed. These concentrations were analyzed by mass spectrometry with inductively coupled plasma (ICP-MS). In order to characterize the diffusion processes occurring under accelerated corrosion, the experimental data obtained were statistically processed in two steps: analysis of the correlation between variables based on Pearson’s correlation matrix and analysis of relationships between variables through the Principal Component Analysis.
PCA method has identified the two significant principal components that explain more than 93% of the original data variance. Significant correlations between the metallic ions migrated into corrosive solutions stirred at 125 and 250 r/min were found.
Full Text:
PDFRefbacks
- There are currently no refbacks.
Food and Environment Safety by Stefan cel Mare University of Suceava is licensed under a Creative Commons Attribution 4.0 International License.
Online ISSN: 2559 - 6381
Print ISSN: 2068 - 6609