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Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers.

Mao Y, Yu K, Isakov MS, Wu J, Dunn ML, Jerry Qi H - Sci Rep (2015)

Bottom Line: A simplified reduced-order model is also developed to rapidly and accurately describe the self-folding physics.An important aspect of self-folding is the management of self-collisions, where different portions of the folding structure contact and then block further folding.A metric is developed to predict collisions and is used together with the reduced-order model to design self-folding structures that lock themselves into stable desired configurations.

View Article: PubMed Central - PubMed

Affiliation: The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

ABSTRACT
Folding is ubiquitous in nature with examples ranging from the formation of cellular components to winged insects. It finds technological applications including packaging of solar cells and space structures, deployable biomedical devices, and self-assembling robots and airbags. Here we demonstrate sequential self-folding structures realized by thermal activation of spatially-variable patterns that are 3D printed with digital shape memory polymers, which are digital materials with different shape memory behaviors. The time-dependent behavior of each polymer allows the temporal sequencing of activation when the structure is subjected to a uniform temperature. This is demonstrated via a series of 3D printed structures that respond rapidly to a thermal stimulus, and self-fold to specified shapes in controlled shape changing sequences. Measurements of the spatial and temporal nature of self-folding structures are in good agreement with the companion finite element simulations. A simplified reduced-order model is also developed to rapidly and accurately describe the self-folding physics. An important aspect of self-folding is the management of self-collisions, where different portions of the folding structure contact and then block further folding. A metric is developed to predict collisions and is used together with the reduced-order model to design self-folding structures that lock themselves into stable desired configurations.

No MeSH data available.


(a) The Finite element simulation of shape memory recovery activated sequential self-folding after the strip is firstly programmed at high temperature. (b) The simulations of folding angles of three representative hinges by ROM and compared with those by FEA and experiments. Solid-line only: FEA; round dot: ROM; square: experiments. Red color: H-1; magenta color: H-4; Blue color: H-7. Comparison between ROM simulations and experiments for (c) Sample 1 and (d) Sample 2, where red lines indicate the simulation results.
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f3: (a) The Finite element simulation of shape memory recovery activated sequential self-folding after the strip is firstly programmed at high temperature. (b) The simulations of folding angles of three representative hinges by ROM and compared with those by FEA and experiments. Solid-line only: FEA; round dot: ROM; square: experiments. Red color: H-1; magenta color: H-4; Blue color: H-7. Comparison between ROM simulations and experiments for (c) Sample 1 and (d) Sample 2, where red lines indicate the simulation results.

Mentions: Figure 3a shows finite element simulations of the folding and unfolding processes. In the unfolding process, the structure is opened by rigid surfaces to successively unfold one panel after the other at a high temperature. After lowering the temperature and unloading, the structure is fixed into the flat configuration. Recovery is achieved by heating the structure uniformly and it folds into the original configuration as hinges are sequentially activated due to their individual time-dependent constitutive response. The simulated recovery ratios for representative hinges (H-1, H-4, and H-7) are presented in Fig. 3b along with measurements and results form the ROM. The FEA predictions are in good agreement with the measurements, although they predict slightly faster folding than the experiment, probably due to the resistance from the water in the experiment, which is neglected in the simulation. Figure 3b also shows the ROM simulations and they are in good agreement with the FEA simulations and experiments. Figure 3c,d show ROM simulations of the two samples in Table 1. They describe both the unsuccessful (Fig. 3c) and successful (Fig. 3d) folding sequences well. Importantly the ROM captures the self-collisions that occur during the failed folding; based on this capability, we use it to design more complex folding scenarios in the next section.


Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers.

Mao Y, Yu K, Isakov MS, Wu J, Dunn ML, Jerry Qi H - Sci Rep (2015)

(a) The Finite element simulation of shape memory recovery activated sequential self-folding after the strip is firstly programmed at high temperature. (b) The simulations of folding angles of three representative hinges by ROM and compared with those by FEA and experiments. Solid-line only: FEA; round dot: ROM; square: experiments. Red color: H-1; magenta color: H-4; Blue color: H-7. Comparison between ROM simulations and experiments for (c) Sample 1 and (d) Sample 2, where red lines indicate the simulation results.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4562068&req=5

f3: (a) The Finite element simulation of shape memory recovery activated sequential self-folding after the strip is firstly programmed at high temperature. (b) The simulations of folding angles of three representative hinges by ROM and compared with those by FEA and experiments. Solid-line only: FEA; round dot: ROM; square: experiments. Red color: H-1; magenta color: H-4; Blue color: H-7. Comparison between ROM simulations and experiments for (c) Sample 1 and (d) Sample 2, where red lines indicate the simulation results.
Mentions: Figure 3a shows finite element simulations of the folding and unfolding processes. In the unfolding process, the structure is opened by rigid surfaces to successively unfold one panel after the other at a high temperature. After lowering the temperature and unloading, the structure is fixed into the flat configuration. Recovery is achieved by heating the structure uniformly and it folds into the original configuration as hinges are sequentially activated due to their individual time-dependent constitutive response. The simulated recovery ratios for representative hinges (H-1, H-4, and H-7) are presented in Fig. 3b along with measurements and results form the ROM. The FEA predictions are in good agreement with the measurements, although they predict slightly faster folding than the experiment, probably due to the resistance from the water in the experiment, which is neglected in the simulation. Figure 3b also shows the ROM simulations and they are in good agreement with the FEA simulations and experiments. Figure 3c,d show ROM simulations of the two samples in Table 1. They describe both the unsuccessful (Fig. 3c) and successful (Fig. 3d) folding sequences well. Importantly the ROM captures the self-collisions that occur during the failed folding; based on this capability, we use it to design more complex folding scenarios in the next section.

Bottom Line: A simplified reduced-order model is also developed to rapidly and accurately describe the self-folding physics.An important aspect of self-folding is the management of self-collisions, where different portions of the folding structure contact and then block further folding.A metric is developed to predict collisions and is used together with the reduced-order model to design self-folding structures that lock themselves into stable desired configurations.

View Article: PubMed Central - PubMed

Affiliation: The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

ABSTRACT
Folding is ubiquitous in nature with examples ranging from the formation of cellular components to winged insects. It finds technological applications including packaging of solar cells and space structures, deployable biomedical devices, and self-assembling robots and airbags. Here we demonstrate sequential self-folding structures realized by thermal activation of spatially-variable patterns that are 3D printed with digital shape memory polymers, which are digital materials with different shape memory behaviors. The time-dependent behavior of each polymer allows the temporal sequencing of activation when the structure is subjected to a uniform temperature. This is demonstrated via a series of 3D printed structures that respond rapidly to a thermal stimulus, and self-fold to specified shapes in controlled shape changing sequences. Measurements of the spatial and temporal nature of self-folding structures are in good agreement with the companion finite element simulations. A simplified reduced-order model is also developed to rapidly and accurately describe the self-folding physics. An important aspect of self-folding is the management of self-collisions, where different portions of the folding structure contact and then block further folding. A metric is developed to predict collisions and is used together with the reduced-order model to design self-folding structures that lock themselves into stable desired configurations.

No MeSH data available.