Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-28T02:04:19.619Z Has data issue: false hasContentIssue false
  • English
  • Français

Magneto-Mechanical Actuators with Reversible Stretching and Torsional Actuation Capabilities

Published online by Cambridge University Press:  13 February 2019

M. Yasar Razzaq ,
M. Behl  and
A. Lendlein
M. Yasar Razzaq
Affiliation:
Institute of Biomaterial Science, Helmholtz-Zentrum Geesthacht, Kantstr. 55, 14513Teltow, Germany
M. Behl
Affiliation:
Institute of Biomaterial Science, Helmholtz-Zentrum Geesthacht, Kantstr. 55, 14513Teltow, Germany
A. Lendlein*
Affiliation:
Institute of Biomaterial Science, Helmholtz-Zentrum Geesthacht, Kantstr. 55, 14513Teltow, Germany Institute of Chemistry, University of Potsdam, 14476Potsdam, Germany
*
*(Email: lendlein@uni-potsdam.de)
Get access

Abstract

Composite actuators consisting of magnetic nanoparticles dispersed in a crystallizable multiphase polymer system can be remotely controlled by alternating magnetic fields (AMF). These actuators contain spatially segregated crystalline domains with chemically different compositions. Here, the crystalline domain associated to low melting transition range is responsible for actuation while the crystalline domain associated to the higher melting transition range determines the geometry of the shape change. This paper reports magneto-mechanical actuators which are based on a single crystalline domain of oligo(ω-pentadecalactone) (OPDL) along with covalently integrated iron(III) oxide nanoparticles (ioNPs). Different geometrical modes of actuation such as a reversible change in length or twisting were implemented by a magneto-mechanical programming procedure. For an individual actuation mode, the degree of actuation could be tailored by variation of the magnetic field strengths. This material design can be easily extended to other composites containing other magnetic nanoparticles, e.g. with a high magnetic susceptibility.

Keywords

actuationmagneticpolymerizationshape memory
Type
Articles
Information
MRS Advances , Volume 4 , Issue 19: Broader Impact/Machine Learning and Robotics , 2019 , pp. 1057 - 1065
Copyright
Copyright © Materials Research Society 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Garcia-Marquez, A., Demortiere, A., Heinrich, B., Guillon, D., Begin-Colin, S. and Donnio, B., J Mater Chem 21, 8994 (2011).CrossRefGoogle Scholar
Park, J.M., Kim, S.J., Jang, J.H., Wang, Z.J., Kim, P.G., Yoon, D.J., Kim, J., Hansen, G. and DeVries, K.L., Compos Part B-Eng 39, 1161 (2008).CrossRefGoogle Scholar
Said, M.M., Yunas, J., Bais, B., Hamzah, A.A. and Majlis, B.Y., Micromachines-Basel 9 (2018).Google Scholar
Fuhrer, R., Athanassiou, E.K., Luechinger, N.A. and Stark, W.J., Small 5, 383 (2009).CrossRefGoogle Scholar
Said, M.M., Yunas, J., Pawinanto, R.E., Majlis, B.Y. and Bais, B., Sensor Actuat A-Phys 245, 85 (2016).CrossRefGoogle Scholar
Thevenot, J., Oliveira, H., Sandre, O. and Lecommandoux, S., Chem Soc Rev 42, 7099 (2013).CrossRefGoogle Scholar
Woodward, R.T., Olariu, C.I., Hasan, E.A., Yiu, H.H.P., Rosseinsky, M.J. and Weaver, J.V.M., Soft Matter 7, 4335 (2011).CrossRefGoogle Scholar
Lagorce, L.K., Brand, O. and Allen, M.G., J Microelectromech S 8, 2 (1999).CrossRefGoogle Scholar
Szabo, D., Szeghy, G. and Zrinyi, M., Macromolecules 31, 6541 (1998).CrossRefGoogle Scholar
Lee, H., Kim, J., Kim, J., Chung, S.E., Choi, S.-E. and Kwon, S., Nat Mater 10, 747 (2011).CrossRefGoogle Scholar
Zrinyi, M., Colloid Polym Sci 278, 98 (2000).Google Scholar
Nguyen, V.Q., Ahmed, A.S. and Ramanujan, R.V., Adv Mater 24, 4041 (2012).CrossRefGoogle Scholar
Razzaq, M.Y., Behl, M., Kratz, K. and Lendlein, A., Adv Mater 25, 5730 (2013).CrossRefGoogle Scholar
Wang, L., Razzaq, M.Y., Rudolph, T., Heuchel, M., Nochel, U., Mansfeld, U., Jiang, Y., Gould, O.E.C., Behl, M., Kratz, K. and Lendlein, A., Mater Horiz 5, 861 (2018).CrossRefGoogle Scholar
Campbell, S., Maitland, D. and Hoare, T., ACS Macro Lett 4, 312 (2015).CrossRefGoogle Scholar
Liu, X.L., Zhao, G., Chen, Z.R., Panhwar, F. and He, X.M., ACS Appl Mater Inter 10, 16822 (2018).CrossRefGoogle Scholar
Zhang, F.H., Zhang, Z.C., Luo, C.J., Lin, I.T., Liu, Y.J., Leng, J.S. and Smoukov, S.K., J Mater Chem C 3, 11290 (2015).CrossRefGoogle Scholar
Meng, H. and Hu, J., J Intel Mat Syst Str 21, 859 (2010).CrossRefGoogle Scholar
Ma, M., Zhang, Y., Shen, X.L., Xie, J., Li, Y. and Gu, N., Nano Res 8, 600 (2015).CrossRefGoogle Scholar
Lien, Y.H., Wu, T.M., Wu, J.H. and Liao, J.W., J Nanopart Res 13, 5065 (2011).CrossRefGoogle Scholar
Behl, M., Kratz, K., Zotzmann, J., Nochel, U. and Lendlein, A., Adv Mater 25, 4466 (2013).CrossRefGoogle Scholar
Razzaq, M.Y., Behl, M. and Lendlein, A., MRS Advances, doi:10.1557/adv.2018.613 (2018).Google Scholar
Arnebold, A. and Hartwig, A., Polymer 83, 40 (2016).CrossRefGoogle Scholar
Razzaq, M.Y., Behl, M., Frank, U., Koetz, J., Szczerba, W. and Lendlein, A., J Mater Chem 22, 9237 (2012).CrossRefGoogle Scholar
Razzaq, M.Y., Behl, M., Nochel, U. and Lendlein, A., Polymer 55, 5953 (2014).CrossRefGoogle Scholar
Razzaq, M.Y., Behl, M. and Lendlein, A., MRS Soc Symp Proc 1718, 71 (2015).CrossRefGoogle Scholar