The DOI matches its Crossref record.
Thin film shape memory alloy microactuators
Abstract
Thin film shape memory alloys (SMAs) have the potential to become a primary actuating mechanism for mechanical devices with dimensions in the micron-to-millimeter range requiring large forces over long displacements. The work output per volume of thin film SMA microactuators exceeds that of other microactuation mechanisms such as electrostatic, magnetic, thermal bimorph, piezoelectric, and thermopneumatic, and it is possible to achieve cycling frequencies on the order of 100 Hz due to the rapid heat transfer rates associated with thin film devices. In this paper, a quantitative comparison of several microactuation schemes is made, techniques for depositing and characterizing Ni-Ti-based shape memory films are evaluated, and micromachining and design issues for SMA microactuators are discussed. The substrate curvature method is used to investigate the thermo-mechanical properties of Ni-Ti-Cu SMA films, revealing recoverable stresses up to 510 MPa, transformation temperatures above 32/spl deg/C, and hysteresis widths between 5 and 13/spl deg/C. Fatigue data shows that for small strains, applied loads up to 350 MPa can be sustained for thousands of cycles. Two micromachined shape memory-actuated devices-a microgripper and microvalve-also are presented.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Huang, W. M., Ding, Z., Wang, C. C., Wei, J., Zhao, Y., & Purnawali, H. (2010) · Materials Today · doi:10.1016/s1369-7021(10)70128-0 · Cited by 747
Origami-inspired active structures: a synthesis and review
Peraza-Hernandez, E. A., Hartl, D. J., Malak Jr, R. J., & Lagoudas, D. C. (2014) · Smart Materials and Structures · doi:10.1088/0964-1726/23/9/094001 · Cited by 421
Metadata
- Authors
- Krulevitch, P., Lee, A. P., Ramsey, P. B., Trevino, J. C., Hamilton, J., & Northrup, M. A.
- Venue
- Journal of Microelectromechanical Systems
- Published
- 1996
- Volume
- 5
- Issue
- 4
- Pages
- 270-282
- ISSN
- 1057-7157 (ISSN-L)
- OpenAlex
- W2001896868
- Cited by
- 529
- References
- 0
- FWCI
- 11.15
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Thin film shape memory alloy microactuators. https://app.cochat.ai/papers/10.1109/84.546407
- The paper
- Krulevitch, P., Lee, A. P., Ramsey, P. B., Trevino, J. C., Hamilton, J., & Northrup, M. A. (1996). Thin film shape memory alloy microactuators. Journal of Microelectromechanical Systems. https://doi.org/10.1109/84.546407
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.