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Full-Text Articles in Engineering Science and Materials
Liquid Metal-Elastomer Soft Composites With Independently Controllable And Highly Tunable Droplet Size And Volume Loading, Ravi Tutika, Steven Kmiec, A. B. M. Tahidul Haque, Steve W. Martin, Michael D. Bartlett
Liquid Metal-Elastomer Soft Composites With Independently Controllable And Highly Tunable Droplet Size And Volume Loading, Ravi Tutika, Steven Kmiec, A. B. M. Tahidul Haque, Steve W. Martin, Michael D. Bartlett
Michael Bartlett
Soft composites are critical for soft and flexible materials in energy harvesting, actuators, and multifunctional devices. One emerging approach to create multifunctional composites is through the incorporation of liquid metal (LM) droplets such as eutectic gallium indium (EGaIn) in highly deformable elastomers. The microstructure of such systems is critical to their performance, however, current materials lack control of particle size at diverse volume loadings. Here, we present a fabrication approach to create liquid metal-elastomer composites with independently controllable and highly tunable droplet size (100 nm ≦ D ≦ 80 μm) and volume loading (0 ≦ φ ≦ 80%). This is …
Deformation Correlations And Machine Learning: Microstructural Inference And Crystal Plasticity Predictions, Michail Tzimas
Deformation Correlations And Machine Learning: Microstructural Inference And Crystal Plasticity Predictions, Michail Tzimas
Graduate Theses, Dissertations, and Problem Reports
The present thesis makes a connection between spatially resolved strain correlations and material processing history. Such correlations can be used to infer and classify prior deformation history of a sample at various strain levels with the use of Machine Learning approaches. A simple and concrete example of uniaxially compressed crystalline thin films of various sizes, generated by two-dimensional discrete dislocation plasticity simulations is examined. At the nanoscale, thin films exhibit yield-strength size effects with noisy mechanical responses which create an interesting challenge for the application of Machine Learning techniques. Moreover, this thesis demonstrates the prediction of the average mechanical responses …