Figure 4 is a high-magnification back-scattered electron (BSE) image of a longitudinal section of a diamond strut made from TM-1: Std VIM-VAR; 2-1 tubing. This image is exemplary of matrix healing that can occur during drawing operations resulting in two distinct NMI often with a remnant void between them. Extensive matrix healing was found in TM-1 processed tubing. Matrix healing of voids is an important aspect in fatigue life of drawn materials.
Results and Discussion
Overall, little difference was found between NMI inclusion count and volume fraction of inclusions between the three TM-1 tube lots in longitudinal and transverse sections. Large NMI were found in the two TM-2: Std VIM-VAR and TM-2: Std VAR tubing samples, but not to the size reported by Robertson. In addition to differences in sample preparation and analytical techniques, this may be the result of light etching that tends to increase feature contrast and may result in exaggerated dimensional measurements used by Robertson whereas current samples were polished only. NMI number density, ρ, in transverse sections is found to be 1.5–3 times that in longitudinal sections for all materials examined in the current study. This is simply the result of sectional view and microstructural anisotropy of NMI.
More importantly, for the TM-1: 2-1 NMI density for tube lot is on average 3–5 times greater than that for the other tube lots in this study (TM-1: 1-1 and 1-2). The higher ρ for tube lot 2-1 appears to correlate well with reduced mean and median NMI lengths and diameters compared with lots 1-1 and 1-2, which show larger dimensions and smaller ρ. These same trends are also seen for the TM-2: Std VIM-VAR and TM-2: Std VAR transverse and longitudinal samples. NMI dimensional relations are shown to be important aspects to understanding the fatigue lives of materials found in this and the Robertson work.
Diamond fatigue data for tubing processed using TM-1 are shown in Figure 5 on a standard strain-life plot with strain amplitude, εa, plotted as a function of number of cycles to fracture, Nf, for tube lots TM-1: 1-1 (filled red circles), 1-2 (open red circles), and, 2-1 (filled green circles). Black arrows indicate runout samples. An increasing number of runouts were observed with reduced strain amplitudes. Runouts were observed at all strain amplitudes except at 2.9 percent where all samples fractured in the low cycle region Nf ≤ 105 cycles. No fractures were seen below 1.3 percent strain amplitude. Immediately apparent in Figure 5 is the dearth of fractures in the high-cycle fatigue region, i.e., for 105 cycles < Nf ≤ 107 cycles. This is likely the result of the relatively small volume of highly stressed material during fatigue testing of diamonds.15 The estimated stressed volume, V, in a strut based on 10 percent of the peak strain amplitude is 0.7 × 10–4 mm3 for the diamonds used in this study.
This same trend is observed in the Robertson et al. diamond fatigue data for the five materials they tested. Robertson also performed tension-tension fatigue testing of 0.229 mm diameter nitinol wires made from the Standard VAR, Standard VIM-VAR, and HP-VAR materials under the same conditions as the diamonds albeit with a slightly reduced Af = 17C ±3C. The gauge length of their wire was 4 mm, resulting in a stressed volume V = 4 mm3 or more than 103 times that (estimated) of the diamonds used in either study. There are two noteworthy features of their data:
There is a plethora of wire fractures in the high-cycle fatigue region compared to the diamond data in both the current study and the Robertson study.
There is a considerable reduction in the high-cycle fatigue (HCF) limit of all three materials tested in the wire configuration compared to diamonds.
These phenomena are thought to be the result of the significantly larger volume of stressed material in the wires during fatigue testing compared to that in the diamonds. The large V (stressed volume) provides a statistical basis for activating the intrinsic distribution of highest potency crack nucleation sites resulting from normal processing.15 In contrast, the probability of incorporating a highly potent crack-nucleant in the relatively small volume of highly stressed material in a diamond strut is significantly reduced resulting in:
The typical bimodal distribution of fatigue fractures observed in diamond (or apex) testing of nitinol (or other structural materials in which Vσ is relatively small): diamond-type samples tend to exhibit either low-cycle fatigue fractures or runouts.
An increased high-cycle fatigue limit — less potent defects result in higher driving forces (stresses or strains) necessary to nucleate a fatigue crack.
As a side note, the HCF limit of the HP-VAR material approaches those for the standard grades of nitinol at the runout condition is thought to be indicative of a similar distribution of the highest potency nucleating defects in all three materials. The Vσ in the wire sample is sufficiently large to incorporate and activate these most potent, although sparse, defects in the HP-VAR. Improvement of the low-probability fatigue life, important in medical devices, is likely best achieved by reducing the maximum size defect in the material used in production as size is one critical parameter in defining defect potency in nucleating a fatigue crack.
This article compares the effects of two tube manufacturing techniques, TM-1 and TM-2, on the high-cycle fatigue life of three standard grades and two high-purity grades of SE nitinol used in the manufacture of cardiovascular medical devices. The results suggest that the tube manufacturing technique has a significant impact on fatigue life of a finished SE nitinol component. Part 2 of this article will address probabilistic fatigue results that were correlated to statistical micro-analyses performed on samples representative of both tube manufacturing techniques.
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This article was written by Paul Adler, Invariant-Plane Solutions, LLC, Wheeling, IL; Rudolf Frei, Vascotube GmbH, a Cirtec Medical company, Birkenfeld, Germany; Michael Kimiecik, Paul Briant, and Brad James, Exponent, Inc., Menlo Park, CA; and Chuan Liu, Northwestern University, Evanston, CA. For more information, Click Here .