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Research Papers

Statistical Characteristics of Fatigue Failure of Copper Thin Films

[+] Author and Article Information
Jae-Won Jang, Soon-Bok Lee

Department of Mechanical Engineering,
Korea Advanced Institute of Science and Technology,
291 Daehak-ro, Yuseong-gu,
Daejeon 305-701, South Korea

Yun Hwangbo

e-mail: ofs@kimm.re.kr

Alexander E. Mag-isa

Department of Nano Convergence
Mechanical Systems Research Division,
Korea Institute of Machinery and Materials,
104, Sinseongno, Yuseong-gu,
Daejeon 305-343, South Korea

1Corresponding author.

Contributed by the Materials Division of ASME for publication in the JOURNAL OF ENGINEERING MATERIALS AND TECHNOLOGY. Manuscript received May 3, 2013; final manuscript received August 1, 2013; published online September 17, 2013. Assoc. Editor: Joost Vlassak.

J. Eng. Mater. Technol 135(4), 041007 (Sep 17, 2013) (9 pages) Paper No: MATS-13-1074; doi: 10.1115/1.4025319 History: Received May 03, 2013; Revised August 01, 2013

Tension–tension fatigue tests were conducted on an electrodeposited copper film with a thickness of 12 μm under four levels of maximum stress and two levels of mean stress. Statistical characteristics of the measured fatigue lives were analyzed using three estimation methods for cumulative distribution function and five probability distributions in order to identify the dominant probability distribution for the fatigue life of copper film. It was found that while the 3-parameter Weibull distribution provided the best fit for the measured data in most cases, the other distributions also provide a similar coefficient of correlation for the fit. The absence of the dominant probability distribution was discussed with considerations of the deformation mode and the scanning electron microscope (SEM) measurements of fatigue-fractured surfaces. Based on the statistical analysis, the probabilistic stress-life (PSN) curves were obtained for statistical prediction of fatigue life of the copper film in the intermediate life regime.

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Figures

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Fig. 1

Copper thin film for test specimens: (a) configuration of the specimen and (b) TEM image of the specimen's microstructure

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Fig. 2

Testing system and load control procedure: (a) fatigue tester and (b) flow chart for load control

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Fig. 3

Fatigue test results: (a) S-N curves at each mean stress and (b) SmaxN and Smaxtf curves

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Fig. 4

An example of fitting estimation results to probability distributions: (a) modified Kaplan–Meier rank, (b) mean rank, and (c) median rank

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Fig. 5

Variations in R values among the rankings: (a) modified Kaplan–Meier rank, (b) mean rank, and (c) median rank

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Fig. 6

Fracture appearances: (a) illustration of fracture appearance, (b) tensile specimen, and (c) statically loaded specimen tested at S = 290 MPa (tf = 0.6 h). Fatigue specimen tested at (d) Smax = 250 MPa (Smean = 210 MPa, ΔS = 80 MPa, Nf = 1.05 × 108 cycles), and (e) Smax = 300 MPa (Smean = 210 MPa, ΔS = 180 MPa, Nf = 2.40 × 104 cycles).

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Fig. 7

PSN curves of copper thin film: (a) modified Kaplan–Meier rank, (b) mean rank, and (c) median rank

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