Electrochemically reconfigurable architected materials

Xia, Xiaoxing; Afshar, Arman; Yang, Hanyu; Portela, C.M.; Kochmann, Dennis M.; Leo, Claudio V. Di; Greer, Julia R.

doi:10.1038/s41586-019-1538-z

Cited by 187 publications

(190 citation statements)

References 49 publications

Supporting

Mentioning

189

Contrasting

Order By: Relevance

“…[14,32] These can be pre-bent beams, which, therefore, have different stiffness in tension and compression, electrochemically activated beams, or temperature-sensitive beams. [33][34][35] Alternatively, non-linearity of the elastic response can be achieved by playing with the node construction (hinged/fixed). [36] In this case, the properties of the archimat will also depend on the magnitude and direction of the load, which can be used for imparting to the archimat some desired functionalities.…”

Section: Discussionmentioning

confidence: 99%

Architectured Lattice Materials with Tunable Anisotropy: Design and Analysis of the Material Property Space with the Aid of Machine Learning

et al. 2020

View full text Add to dashboard Cite

Materials with anisotropic mechanical properties play an important role in nature and technology. Thus, many biomechanical processes in living organisms, which govern their growth, muscular activity, and oxygen and nutrient supply, are based on an anisotropic response of cells to various mechanical stimuli. [1,2] In engineering practice, materials with controlled anisotropy are used in various sensitive structures. [3] Directional dependence of the propagation velocity of acoustic waves stemming from the elastic anisotropy of the medium makes it possible to produce various materials and devices for breaking acoustic waves or damping of vibrations. [4] These are but a few illustrations of the significance of mechanical anisotropy. Elastic anisotropy can be achieved in many ways. In composites, it is produced using a special arrangement of the constituents. [5] The paradigm of architectured materials, [6,7] also referred to in the literature as hybrid materials, or metamaterials, and for brevity called archimats in the following, opens remarkable new possibilities for creating anisotropic properties. It builds on the idea of Ashby that the inner architecture of a material can be regarded as an extra "degree of freedom" in materials design, which can be exploited to provide the material with desired properties. [8] Some architectured materials with artificially created mechanical anisotropy are already in existence; see the previous studies. [3,4,9,10] Among them, periodic beam lattice materials take a special place due to the variability of properties they possess. [6] The properties are determined by the architecture of the elementary cell of the lattice. Commonly, it is the lattice geometry that is varied to achieve targeted characteristics of the material, while

show abstract

Section: Discussionmentioning

confidence: 99%

Architectured Lattice Materials with Tunable Anisotropy: Design and Analysis of the Material Property Space with the Aid of Machine Learning

et al. 2020

View full text Add to dashboard Cite

show abstract

“…They also allow for real-time or even time-dependent tunability of properties with most recent advances reporting abilities to dynamically reconfigure metamaterial topologies as a function of electrochemical or acoustic stimuli. 41 While significant progress continues in bringing this new class of materials into a range of engineering applications, a number of challenges remain, including the development of scalable and cost-effective manufacturing methods.…”

Section: Perspectivementioning

confidence: 99%

Three-dimensional architected materials and structures: Design, fabrication, and mechanical behavior

Greer

Deshpande

2019

MRS Bull.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Such a unique function has been showcased in a wide range of length scales, from nanolattice to the Eiffel Tower. Frontier studies in this field have focused on advanced design approaches 45,46 , geometric mechanics [47][48][49][50][51] , fabrication [52][53][54][55][56] , and potential applications at multiple length scales [57][58][59] . Yet, most studies to date usually focus on unit cells with an assumption of a periodic pattern over a larger domain, while aperiodic patterns with non-uniform cells bring infinite possibilities for achieving high tailorability in failure mode, energy absorption, etc.…”

Section: Introductionmentioning

confidence: 99%

Accelerated design and characterization of non-uniform cellular materials via a machine-learning based framework

Zhang

Luce

et al. 2020

npj Comput Mater

View full text Add to dashboard Cite

Cellular materials, widely found in engineered and nature systems, are highly dependent on their geometric arrangement. A nonuniform arrangement could lead to a significant variation of mechanical properties while bringing challenges in material design. Here, this proof-of-concept study demonstrates a machine-learning based framework with the capability of accelerated characterization and pattern generation. Results showed that the proposed framework is capable of predicting the mechanical response curve of any given geometric pattern within the design domain under appropriate neural network architecture and parameters. Additionally, the framework is capable of generating matching geometric patterns for a targeted response through a databank constructed from our machine learning model. The accuracy of the predictions was verified with finite element simulations and the sources of errors were identified. Overall, our machine-learning based framework can boost the design efficiency of cellular materials at unit level, and open new avenues for the programmability of function at system level.

show abstract

Electrochemically reconfigurable architected materials

Cited by 187 publications

References 49 publications

Architectured Lattice Materials with Tunable Anisotropy: Design and Analysis of the Material Property Space with the Aid of Machine Learning

Architectured Lattice Materials with Tunable Anisotropy: Design and Analysis of the Material Property Space with the Aid of Machine Learning

Three-dimensional architected materials and structures: Design, fabrication, and mechanical behavior

Accelerated design and characterization of non-uniform cellular materials via a machine-learning based framework

Contact Info

Product

Resources

About