W911NF-17-S-0002_LCE-LM Composites for Soft-Matter Embodied Intelligence
Abstract
The objective of this proposal is to engineer a soft elastomer composite that exhibits embodied intelligence- i.e. the ability to sense, process, and dynamically respond to external conditions in an autonomous manner. The ultimate goal is a framework for engineering soft materials capable of intrinsic sensing, actuation, and processing. Such "algorithmic materials" could be reprogrammed for a variety of tasks and functions and autonomously adapt their shape or internal material properties in response to damage or changing functional demands. In contrast to existing efforts in "robotic materials" and programmable matter, this work will focus on achieving autonomy through intrinsic material functionality. Rather than rely on embedded or surface-mounted devices, the proposed composite will perform sensing, signal processing, and actuation through internal electro-thermo-mechanical coupling of the material phases. We will accomplish the project objective by introducing a new class of materials composed of liquid crystal elastomers (LCEs) embedded with liquid metal (LM) nanodroplets. These LCE-LM composites will exhibit a unique combination of electrical, thermal, and dynamic properties not observed in other soft material systems. Functionalities include spatial mapping of stress, strain, or mechanical failure and electro-thermo-mechanical coupling that enables autonomous reconfiguration in response to external loading conditions or material failures. Research tasks will focus on (Task I) synthesis of LM nanodroplets and methods for uniform dispersion in LCE, (Task 2) fabrication and evaluation of algorithmic LCE-LM materials, including implementations with 3D printing, and (Task 3) characterization and computational modeling to examine sensing modalities and autonomy. Such efforts will build on recent accomplishments by the PIs in the fields of soft-matter engineering, polymer science, additive manufacturing, and multi-scale modeling. This includes digital patterning of LCEs for shape programmable matter and an LM-embedded elastomer (LMEE) composite that couples rubber-like elasticity with metal-like electrical and thermal properties. In this project, we will explore the embodied materials intelligence that can be achieved by combining these material architectures. Referring to Fig. IC, nanoscale LM droplets embedded in an LCE will be used to control the local order of polymer chains during processing. Moreover, phase transformations in the LCE after polymerization induced through electrical or thermal stimulation can modulate the internal stresses that cause the droplets to elongate, align, or form connected pathways. The reverse effect is also possible - concentrated mechanical loading or failure can (i) deform the LM droplets, (ii) reconfigure the electrically or thermally conductive pathways, and (iii) redirect electrical/thermal stimulation to induce localized phase change. In this way, the embedded LM droplets not only sense mechanical loading (through electro-elastostatic coupling) but also process it through reconfiguration to induce a dynamic response. Soft multifunctional materials for stretchable circuit wiring, sensing, and dynamic mechanical response have the potential to revolutionize Army warfighting capabilities. These soft and elastic materials could be incorporated into inflatable structures, clothing and wearable technologies, and other host systems that undergo extreme deformations and loadings. Progress in these military application domains requires new classes of materials that can enable the host structure to adapt its functionality to changing operational tasks, natural environmental conditions, or enemy threats.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 07, 2018
- Source ID
- W911NF1810150
Entities
People
- Carmel Majidi
Organizations
- Army Contracting Command
- Massachusetts Institute of Technology
- United States Army