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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.

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Articles
Copyright
Copyright © Materials Research Society 2017 

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References

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