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Electrochemical noise analysis of Ti-15Mo alloy samples exposed to Hanks solution: association between milling time and corrosion resistance

Published online by Cambridge University Press:  05 December 2017

J.C. Betancourt-Ruiz
Affiliation:
Facultad de Ingeniería, Universidad Autónoma de Chihuahua, Circuito Universitario s/n, Nuevo Campus Universitario, Chihuahua, Chihuahua. C.P. 31100. México
C.G. Nava-Dino*
Affiliation:
Facultad de Ingeniería, Universidad Autónoma de Chihuahua, Circuito Universitario s/n, Nuevo Campus Universitario, Chihuahua, Chihuahua. C.P. 31100. México
Claudia Lerma
Affiliation:
Departamento de Instrumentación Electromecánica, Instituto Nacional de Cardiología Ignacio Chávez, Juan Badiano 1, Col. Sección 16, Ciudad de México. C.P. 14080. México
R.R. Torres-Knight
Affiliation:
Facultad de Ingeniería, Universidad Autónoma de Chihuahua, Circuito Universitario s/n, Nuevo Campus Universitario, Chihuahua, Chihuahua. C.P. 31100. México
*
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Abstract

The aim of this work was to evaluate the corrosion resistance of Ti15Mo alloys prepared with different milling times (0, 3, 5 and 8 hours) and exposed to Hanks solution. The alloys of Ti-15Mo were prepared by mechanical milling under an Ar atmosphere. SPEX 8000M was connected to a hardened steel container with 13 mm (Ø) balls as milling media, using alternate cycles of 30 minutes milling and 30 min resting. Milling time longer than 8 hours using Ti alloys were avoided to prevent oxidation. The electrochemical noise time series of current (I) and voltage (V) were used to calculate the Rn corrosion index = voltage SD / current SD; SD = standard deviation. Rn was calculated from the original data and also from data after drift removal with two fitting procedures: cubic polynomial (degree 3) and moving average. A significant inverse association (p < 0.05, Spearman’s correlation analysis) between milling time and Rn was found in time series fitted by a polynomial, which indicates higher corrosion resistance among samples prepared with longer milling times. The recurrence plot analysis showed that the fitting method also influenced the dynamical behaviour of these time series.

Type
Articles
Copyright
Copyright © Materials Research Society 2017 

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References

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