Research PaperA statistical approach to understand the role of inclusions on the fatigue resistance of superelastic Nitinol wire and tubing
Introduction
The detriment of chemical impurities on the fatigue resistance of biomedical materials is well documented. For example, the high-purity composition of extra low interstitials (ELI) Ti–4Al–6V ELI covered by ASTM F136 has become the preferred version for fatigue- and fracture-critical medical implant applications (ASTM F136-13, 2013). Similarly, in recent years, the effects of impurities, primarily C and O, that may form non-metallic inclusions (NMIs), in biomedical-grade NiTi (Nitinol) have been studied. In particular, investigations have demonstrated fatigue crack nucleation in Nitinol from NMIs (and/or voids) in the simple raw material form (Wick et al., 2004, Schaffer and Plumley, 2009, Rahim et al., 2013), surrogate medical device implant fatigue specimens (Tolomeo et al., 2000, Pelton, 2011, Robertson and Ritchie, 2008, Gall et al., 2008, Lin et al., 2011, Lin et al., 2012, Pike et al., 2011, Robertson et al., 2012, Pelton et al., 2008), and even finished commercial devices (Pelton et al., 2008, Hull and Robertson, 2009). On a commercial scale, Nitinol is melted by vacuum arc remelting (VAR), vacuum induction melting (VIM) or a combination of the two. The purity of the raw materials, combined with these different melting techniques leads to variations in the size, abundance, and chemical composition of NMI׳s. Consequently, it is difficult to ascertain the most promising route for improvements in fatigue behavior of Nitinol medical devices without extensive studies.
The industry standard for acceptable NMI limits in Nitinol materials governs the maximum NMI length and area fraction (ASTM F2063-12, 2012). While, these are important parameters that influences fatigue resistance, there are other variables with potentially equal or greater importance. Specifically, to fully evaluate the fatigue resistance of Nitinol we subdivided the possible contributing variables into three distinct categories:
- 1)
Stress-concentrations: microscale phenomena that locally elevate the stress levels, thereby promoting the nucleation of a fatigue crack.
Lmax=maximum inclusion length in the drawing direction
Lmedian=median inclusion length in the drawing direction
Lmean=mean inclusion length in the drawing direction
G=grain size
a=surface defect size, e.g. scratch or gouge depth
- 2)
Probabilistic considerations: variables that increase the likelihood of stress concentration residing in a susceptible region of the device that would prematurely nucleate a fatigue crack.
A=total area fraction of inclusions measured in percent
ρ=density of inclusions measured in number of inclusions per unit area or unit volume
- 3)
Macro-mechanics: variables governing the overall stress or strain state of the specimen
Af=austenite finish temperature
εa=strain amplitude
εm=mean strain
σU=upper plateau stress
σL=lower plateau stress
σH=stress hysteresis (σU – σL)
σY=yield stress, as defined by a 0.2% offset line measured from the martensitic elastic loading portion of the stress–strain diagram
Manufacturing the specimens to have similar mechanical properties (σU, σL, σH, σY), transformation temperature (Af), surface smoothness (a), and grain sizes (G) allowed us to investigate in isolation the influence of the inclusion size (Lmax, Lmedian, Lmean) and population distribution (A, ρ) on the fatigue resistance of Nitinol. However, it is difficult, if not impossible, to isolate the role of each of these variables to determine which, if any, is the dominant variable in improving fatigue resistance. Herein we present data comparing Nitinol with five different NMI-profiles to gain a deeper understanding of the role of each of these variables. Furthermore, this paper presents fatigue data on two forms of testing methodology: wire tension–tension fatigue and bending fatigue on laser-cut “diamond” surrogates from tubing. As such, this research provides the most comprehensive fatigue data on Nitinol with respect to composition and specimen form.
Section snippets
Materials
Five unique materials were examined in this study: Standard VAR, Standard VIM+VAR, Standard VIM, Process-Optimized VIM+VAR, and High-Purity VAR. The designation “Standard” indicates that the material underwent conventional melting techniques with normal purity input raw materials. Two new grades of materials have recently become commercially available that we designated “Process-Optimized” and “High-Purity”. The Process-Optimized material is manufactured using raw materials with purity levels
Wire
To isolate the role of inclusions, the round wire samples were tested in tension–tension fatigue under simple mode-I loading conditions. This method of loading imparts a uniform stress across the entire cross-section, thereby involving all inclusions within the gauge length rather than isolating only the near-surface inclusions or surface processing conditions that dominate rotary bend or stent-surrogate fatigue tests. Fatigue testing was performed using a 5-station Instron Model E3000 (each
Microstructural analysis
Statistical microstructural analysis was done on all three versions of the wire and five versions of the tubing. Here we concentrate on the microstructural analysis of the tubing, although similar trends were observed in the finished wire characterization. Fig. 5 shows representative micrographs of the finished tubes.
There exist several key differences among the five material types. Of the two Standard alloys, the VIM+VAR alloy has a smaller maximum inclusion length and greater inclusion area
Discussion
The trends in fatigue limit at 107 cycles for the various Nitinol compositions are comparable between the two testing methods, albeit with greater strain amplitude ranges for the diamond fatigue testing in bending. The resultant 107-cycle fatigue strain amplitudes for each material and test method are summarized in Table 3. The difference between uniaxial and bending fatigue behavior is well known and speaks to the difference in volume of stressed material with each cycle. Macherauch (2002)
Limitations
Herein we presented fundamental material data and drew comparisons to finished products manufactured from those differing Nitinol melting techniques. However, there are a few key limitations that must be considered before adopting the information.
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While the fatigue strain-life curves and consequent probability plots draw upon hundreds of individual data points, each set of specimens was manufactured from a single tubing lot (diamonds) or wire lot from a single melting campaign. Variations during
Conclusions
Each of the alloys investigated in this study has a different inclusion-profile. Therefore, when that knowledge is combined with the probabilistic fatigue evaluation it provides us valuable insight on the role of the inclusions on fatigue resistance of Nitinol.
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Both a low-inclusion-density, larger inclusion size (Std. VAR) and a high-inclusion-density, smaller inclusion size (Std. VIM+VAR, and Std. VIM) material have statistically indifferent medium- and high-cycle (>105) fatigue performance.
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