Combinatorial study of phase transformation characteristics of a Ti–Ni–Pd shape memory thin film composition spread in view of microactuator applications

Zarnetta, Robert; Savan, Alan; Thienhaus, Sigurd; Ludwig, Alfred

doi:10.1016/j.apsusc.2007.03.074

Cited by 46 publications

(31 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As the Ni to Pd ratio is varied at fairly constant Ti and Cu contents, a crossover between a S-shaped R(T) curve, characteristic for Ti-Ni-Pd SMAs [19,20] and an inverse S-shaped R(T) curve, characteristic for Ti-Ni-Cu SMAs [21] is observed. Where both characteristic shapes of the R(T) curves merge, alloys with DT approaching zero were found.…”

Section: Full Papermentioning

confidence: 99%

Identification of Quaternary Shape Memory Alloys with Near‐Zero Thermal Hysteresis and Unprecedented Functional Stability

Zarnetta

Takahashi

Young

et al. 2010

Adv Funct Materials

336

207

View full text Add to dashboard Cite

Improving the functional stability of shape memory alloys (SMAs), which undergo a reversible martensitic transformation, is critical for their applications and remains a central research theme driving advances in shape memory technology. By using a thin‐film composition‐spread technique and high‐throughput characterization methods, the lattice parameters of quaternary Ti–Ni–Cu–Pd SMAs and the thermal hysteresis are tailored. Novel alloys with near‐zero thermal hysteresis, as predicted by the geometric non‐linear theory of martensite, are identified. The thin‐film results are successfully transferred to bulk materials and near‐zero thermal hysteresis is observed for the phase transformation in bulk alloys using the temperature‐dependent alternating current potential drop method. A universal behavior of hysteresis versus the middle eigenvalue of the transformation stretch matrix is observed for different alloy systems. Furthermore, significantly improved functional stability, investigated by thermal cycling using differential scanning calorimetry, is found for the quaternary bulk alloy Ti50.2Ni34.4Cu12.3Pd3.1.

show abstract

Section: Full Papermentioning

confidence: 99%

Identification of Quaternary Shape Memory Alloys with Near‐Zero Thermal Hysteresis and Unprecedented Functional Stability

Zarnetta

Takahashi

Young

et al. 2010

Adv Funct Materials

336

207

View full text Add to dashboard Cite

show abstract

“…26 37 87 55 7.16 0.277 [23] Ni 50 Ti 45 Ta 5 44 76 53 7.05 0.255 [14] Ni 48 Ti 50 W 2 55 70 29 6.92 0.266 [22] Ni 50 Ti 47 Ta 3 58 90 48 7.03 0.264 [14] Ni 30 Ti 50 Cu 20 58 60 6 7.20 0.285 [28] Ni 25 [24] Ni 48 Ti 50 Au 2 75 --7.02 0.268 [13] Ni 29 Ti 51 Pd 20 85 -20 6.94 0.243 [31] Ni 49.5 Ti 40.5 Zr 10 90 170 68 6.97 0.260 [11] Ni 30 Ti 50 Pd 20 90 7.00 0.244 [4] Ni 40 Ti 50 Pt 10 90 100 20 7.00 0.233 [38] Ni 26.5 Ti 51 Pd 22.5 95 -6.94 0.239 [31] Ni 50 Ti 40 Hf 10 120 165 65 7.00 0.233 [24] Ni 40 [38] Ni 20 Ti 50 Pt 30 560 594 55 7.00 0.176 [39] Ni 15 Ti 50 Pt 35 680 750 -7.00 0.164 [38] Ni 10 Ti 50 Pt 40 810 850 -7.00 0.155 [38] Ni 5 Ti 50 Pt 45 900 950 -7.00 0.145 [38] temperature data are scattered with no clear tendency with respect to e v /a (Fig. 1), and 3) e v /a > 7.2 in which M s and A s temperatures both slightly decrease with increasing e v /a.…”

Section: E V /A 6 ¼mentioning

confidence: 99%

Dependence of Transformation Temperatures of NiTi‐based Shape‐Memory Alloys on the Number and Concentration of Valence Electrons

Zarinejad

Liu

2008

Adv Funct Materials

154

105

View full text Add to dashboard Cite

Dependence of transformation temperatures of ternary and quaternary NiTi‐based shape memory alloys on the number (ev/a) and concentration (cv) of valence electrons is investigated. Two distinct trends of transformation temperatures with respect to the number of valence electrons per atom are found depending on whether ev/a = 7 or ev/a ≠ 7. Clear correlations between transformation temperatures and cv exist. Ms and As decrease consistently from 900 to −100 °C, and 950 to −30 °C, respectively, with increasing cv from 0.145 to 0.296. The relationship of electron concentration on the elastic moduli of the NiTi‐based alloys is discussed. The possible influence of the atomic size of alloying elements on transformation hysteresis is introduced.

show abstract

“…As part of the same study, it was shown that the "zero-hysteresis" compositions identified from the CCS experiments, when processed as bulk samples, indeed showed substantially enhanced functional stability due to minimized fatigue behavior. Zarnetta et al 419,420 have also investigated the details of phase transformation behavior across a variety of related SMA systems. Figure 81 shows one such study where data cluster analysis was performed on XRD spectra from a Ni-Ti-Cu CCS library.…”

Section: High-throughput Mapping Of Phase Diagramsmentioning

confidence: 99%

Applications of high throughput (combinatorial) methodologies to electronic, magnetic, optical, and energy-related materials

Green

Takeuchi

Hattrick‐Simpers

2013

Journal of Applied Physics

227

189

View full text Add to dashboard Cite

High throughput (combinatorial) materials science methodology is a relatively new research paradigm that offers the promise of rapid and efficient materials screening, optimization, and discovery. The paradigm started in the pharmaceutical industry but was rapidly adopted to accelerate materials research in a wide variety of areas. High throughput experiments are characterized by synthesis of a "library" sample that contains the materials variation of interest (typically composition), and rapid and localized measurement schemes that result in massive data sets. Because the data are collected at the same time on the same "library" sample, they can be highly uniform with respect to fixed processing parameters. This article critically reviews the literature pertaining to applications of combinatorial materials science for electronic, magnetic, optical, and energy-related materials. It is expected that high throughput methodologies will facilitate commercialization of novel materials for these critically important applications. Despite the overwhelming evidence presented in this paper that high throughput studies can effectively inform commercial practice, in our perception, it remains an underutilized research and development tool. Part of this perception may be due to the inaccessibility of proprietary industrial research and development practices, but clearly the initial cost and availability of high throughput laboratory equipment plays a role. Combinatorial materials science has traditionally been focused on materials discovery, screening, and optimization to combat the extremely high cost and long development times for new materials and their introduction into commerce. Going forward, combinatorial materials science will also be driven by other needs such as materials substitution and experimental verification of materials properties predicted by modeling and simulation, which have recently received much attention with the advent of the Materials Genome Initiative. Thus, the challenge for combinatorial methodology will be the effective coupling of synthesis, characterization and theory, and the ability to rapidly manage large amounts of data in a variety of formats. V C 2013 AIP Publishing LLC. [http://dx

show abstract

Combinatorial study of phase transformation characteristics of a Ti–Ni–Pd shape memory thin film composition spread in view of microactuator applications

Cited by 46 publications

References 14 publications

Identification of Quaternary Shape Memory Alloys with Near‐Zero Thermal Hysteresis and Unprecedented Functional Stability

Identification of Quaternary Shape Memory Alloys with Near‐Zero Thermal Hysteresis and Unprecedented Functional Stability

Dependence of Transformation Temperatures of NiTi‐based Shape‐Memory Alloys on the Number and Concentration of Valence Electrons

Applications of high throughput (combinatorial) methodologies to electronic, magnetic, optical, and energy-related materials

Contact Info

Product

Resources

About