4D printing of polylactic acid (PLA)/PLA-thermoplastic polyurethane (TPU)-based metastructure: examining the mechanical, thermal, and shape memory properties

Abstract In the present day and age, increasing demand concerning the enhancement of the mechanical performance of shape memory polymer (SMP) based structures has paved the way for developing newer metastructures of enhanced load-bearing, damping capacity, and durability. The present study focuses on developing SMP-based metastructures made of commercially available polylactic acid (PLA) and 30% by wt. of thermoplastic polyurethane (TPU) blended PLA. The designed metastructures are initially analyzed using numerical modeling to prevent lateral deformation, acute stress concentration zones, and row-wise collapse. Mechanical tests reveal that blending TPU with PLA enhances the material’s flexibility and ductility, further improving the toughness and fracture resistance of the built metastructures. Loading-unloading and shape recovery tests (under compression mode) of the s-shape metastructure reveal that the PLA/TPU metastructure withstands ≅ 170 N load, less than neat PLA’s ≅ 223 N due to TPU’s flexibility. PLA/TPU endures 30 cycles, while PLA fails after the 9th cycle. In shape recovery plots, PLA/TPU metastructures exhibit a lower standard deviation (∼0.32%) than PLA (∼1.4%), attributed to the entropy decrease and cross-linkage disentanglements of PLA. Furthermore, a dynamic mechanical analyzer (DMA) assesses glass transition temperature, energy storage capability, and dissipation in variation with the temperature. The nephograms of ABAQUS result divulge accurate fracture initiation locations of the metastructure unit cells, which involves implementing ductile damage behavior modeling by employing damage initiation and evolution parameters. Finally, assessing compression tests and shape recovery behavior results elucidates that these SMP-based metastructures are promising for load-bearing pallets in the transporting and packaging industries, providing superior damping and self-repairing capabilities during significant plastic deformations.

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Publication Details

Journal
Smart Materials and Structures
Published
2024-09-17
DOI
https://doi.org/10.1088/1361-665x/ad7c0a
Citations
9
Primary Topic
Bone Tissue Engineering Materials
Type
article
Field-Weighted Citation Impact
1.66

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article

4D printing of polylactic acid (PLA)/PLA-thermoplastic polyurethane (TPU)-based metastructure: examining the mechanical, thermal, and shape memory properties

Saiyadali H. Ladakhan, Rakshith B. Sreesha, Somashekara M Adinarayanappa
9 citations
Smart Materials and Structures
Bone Tissue Engineering Materials
1.66
article

4D printing of polylactic acid (PLA)/PLA-thermoplastic polyurethane (TPU)-based metastructure: examining the mechanical, thermal, and shape memory properties

Saiyadali H. Ladakhan, Rakshith B. Sreesha, Somashekara M Adinarayanappa
article en
9 citations

Abstract

Abstract In the present day and age, increasing demand concerning the enhancement of the mechanical performance of shape memory polymer (SMP) based structures has paved the way for developing newer metastructures of enhanced load-bearing, damping capacity, and durability. The present study focuses on developing SMP-based metastructures made of commercially available polylactic acid (PLA) and 30% by wt. of thermoplastic polyurethane (TPU) blended PLA. The designed metastructures are initially analyzed using numerical modeling to prevent lateral deformation, acute stress concentration zones, and row-wise collapse. Mechanical tests reveal that blending TPU with PLA enhances the material’s flexibility and ductility, further improving the toughness and fracture resistance of the built metastructures. Loading-unloading and shape recovery tests (under compression mode) of the s-shape metastructure reveal that the PLA/TPU metastructure withstands ≅ 170 N load, less than neat PLA’s ≅ 223 N due to TPU’s flexibility. PLA/TPU endures 30 cycles, while PLA fails after the 9th cycle. In shape recovery plots, PLA/TPU metastructures exhibit a lower standard deviation (∼0.32%) than PLA (∼1.4%), attributed to the entropy decrease and cross-linkage disentanglements of PLA. Furthermore, a dynamic mechanical analyzer (DMA) assesses glass transition temperature, energy storage capability, and dissipation in variation with the temperature. The nephograms of ABAQUS result divulge accurate fracture initiation locations of the metastructure unit cells, which involves implementing ductile damage behavior modeling by employing damage initiation and evolution parameters. Finally, assessing compression tests and shape recovery behavior results elucidates that these SMP-based metastructures are promising for load-bearing pallets in the transporting and packaging industries, providing superior damping and self-repairing capabilities during significant plastic deformations.

Smart Materials and StructuresVol. 33(10)
Indian Institute of Technology Dharwad (IN)
All India Council for Technical Education, Science and Engineering Research Board
Openalex Percentile: Top 17%
Bone Tissue Engineering Materials
1.66
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