Micro-Mechanosensory insights from Nature’s Mimosa leaves to shape memory adaptive robotics
This study is focused on the micromechanics of the Mimosa Pudica plant to develop an adaptive robot that is 3D-printed using shape memory polymer-graphene composite. Traditionally, leaf-folding responses of Mimosa are examined at the pinna (leaflet) level due to the difficulty of applying small, loc...
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Elsevier
2025-01-01
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| Series: | Materials & Design |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0264127524009420 |
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| author | Lihua Lou Kazue Orikasa Lopez Arya B. Nair William Desueza Arvind Agarwal |
| author_facet | Lihua Lou Kazue Orikasa Lopez Arya B. Nair William Desueza Arvind Agarwal |
| author_sort | Lihua Lou |
| collection | DOAJ |
| description | This study is focused on the micromechanics of the Mimosa Pudica plant to develop an adaptive robot that is 3D-printed using shape memory polymer-graphene composite. Traditionally, leaf-folding responses of Mimosa are examined at the pinna (leaflet) level due to the difficulty of applying small, localized forces without causing damage. Here, we use both hand touch and nanoindentation to analyze the micro-mechanosensory properties of the smaller leaf structures, pinnule and pulvinule. We found that pulvinules respond 1.5 times faster than pinnules when touched by hand due to faster osmotic processes. When using a nanoindenter, the pulvinules showed response times, trigger forces, and reactive forces that were approximately 2.3, 1.7, and 2.9 times faster, respectively, compared to pinnules. Nanoindentation also proved to be more effective than touch, with response times 1.4 times faster and displacement magnitudes 1.2–5.1 times greater. Inspired by these findings, we developed a bioinspired, 3D-printed soft robotic “MIMOSA” device using shape memory polyurethane (SMPU) with graphene nanoplatelets (GNP). This device exhibited shape changes 3.63 times faster than pure SMPU due to the high thermal conductivity of GNP. Our research demonstrates how biomimicry can lead to the development of adaptive robotic systems with potential applications in wearable technology and electronics. |
| format | Article |
| id | doaj-art-e38ae63a50524d5895142147b204e375 |
| institution | Kabale University |
| issn | 0264-1275 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Materials & Design |
| spelling | doaj-art-e38ae63a50524d5895142147b204e3752025-01-09T06:12:27ZengElsevierMaterials & Design0264-12752025-01-01249113567Micro-Mechanosensory insights from Nature’s Mimosa leaves to shape memory adaptive roboticsLihua Lou0Kazue Orikasa Lopez1Arya B. Nair2William Desueza3Arvind Agarwal4Mechanical and Materials Engineering, College of Engineering and Computing, Florida International University, Miami, FL 33174, United States; Mechanical Engineering, College of Engineering, Computing, and Applied Science, Clemson University, Clemson, SC 29634, United StatesMechanical and Materials Engineering, College of Engineering and Computing, Florida International University, Miami, FL 33174, United StatesMechanical and Materials Engineering, College of Engineering and Computing, Florida International University, Miami, FL 33174, United StatesElectrical and Electronics Engineering, University of Miami, Coral Gables, FL 33146, United StatesMechanical and Materials Engineering, College of Engineering and Computing, Florida International University, Miami, FL 33174, United States; Corresponding author.This study is focused on the micromechanics of the Mimosa Pudica plant to develop an adaptive robot that is 3D-printed using shape memory polymer-graphene composite. Traditionally, leaf-folding responses of Mimosa are examined at the pinna (leaflet) level due to the difficulty of applying small, localized forces without causing damage. Here, we use both hand touch and nanoindentation to analyze the micro-mechanosensory properties of the smaller leaf structures, pinnule and pulvinule. We found that pulvinules respond 1.5 times faster than pinnules when touched by hand due to faster osmotic processes. When using a nanoindenter, the pulvinules showed response times, trigger forces, and reactive forces that were approximately 2.3, 1.7, and 2.9 times faster, respectively, compared to pinnules. Nanoindentation also proved to be more effective than touch, with response times 1.4 times faster and displacement magnitudes 1.2–5.1 times greater. Inspired by these findings, we developed a bioinspired, 3D-printed soft robotic “MIMOSA” device using shape memory polyurethane (SMPU) with graphene nanoplatelets (GNP). This device exhibited shape changes 3.63 times faster than pure SMPU due to the high thermal conductivity of GNP. Our research demonstrates how biomimicry can lead to the development of adaptive robotic systems with potential applications in wearable technology and electronics.http://www.sciencedirect.com/science/article/pii/S0264127524009420Mimosa PudicaNanoindentationBiomimeticShape memory polyurethaneMicromechanicsResponsive materials |
| spellingShingle | Lihua Lou Kazue Orikasa Lopez Arya B. Nair William Desueza Arvind Agarwal Micro-Mechanosensory insights from Nature’s Mimosa leaves to shape memory adaptive robotics Materials & Design Mimosa Pudica Nanoindentation Biomimetic Shape memory polyurethane Micromechanics Responsive materials |
| title | Micro-Mechanosensory insights from Nature’s Mimosa leaves to shape memory adaptive robotics |
| title_full | Micro-Mechanosensory insights from Nature’s Mimosa leaves to shape memory adaptive robotics |
| title_fullStr | Micro-Mechanosensory insights from Nature’s Mimosa leaves to shape memory adaptive robotics |
| title_full_unstemmed | Micro-Mechanosensory insights from Nature’s Mimosa leaves to shape memory adaptive robotics |
| title_short | Micro-Mechanosensory insights from Nature’s Mimosa leaves to shape memory adaptive robotics |
| title_sort | micro mechanosensory insights from nature s mimosa leaves to shape memory adaptive robotics |
| topic | Mimosa Pudica Nanoindentation Biomimetic Shape memory polyurethane Micromechanics Responsive materials |
| url | http://www.sciencedirect.com/science/article/pii/S0264127524009420 |
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