Abstract
Mechanical metamaterial actuators achieve pre-determined input–output operations exploiting architectural features encoded within a single 3D printed element, thus removing the need for assembling different structural components. Despite the rapid progress in the field, there is still a need for efficient strategies to optimize metamaterial design for a variety of functions. We present a computational method for the automatic design of mechanical metamaterial actuators that combines a reinforced Monte Carlo method with discrete element simulations. 3D printing of selected mechanical metamaterial actuators shows that the machine-generated structures can reach high efficiency, exceeding human-designed structures. We also show that it is possible to design efficient actuators by training a deep neural network which is then able to predict the efficiency from the image of a structure and to identify its functional regions. The elementary actuators devised here can be combined to produce metamaterial machines of arbitrary complexity for countless engineering applications.
Highlights
Mechanical metamaterial actuators achieve pre-determined input–output operations exploiting architectural features encoded within a single 3D printed element, removing the need for assembling different structural components
To overcome the limitations of manual design, we propose an automatic optimization method for the automatic design of mechanical metamaterial actuators (MMA), searching for the optimal output response to an applied input through iterative modifications of the structure
We have proposed algorithms for the automatic design of MMAs with a broad set of possible movements and efficiency—exceeding those of human-designed solutions
Summary
Mechanical metamaterial actuators achieve pre-determined input–output operations exploiting architectural features encoded within a single 3D printed element, removing the need for assembling different structural components. The increasing interest in metamaterials is stimulated by the recent advances in digital manufacturing technologies e.g. 3D printing and automated assembly, which enable rapid manufacture of such material structures with the removal of many of the constraints in scale and geometry at lower and decreasing cost[19] Metamaterials derive their properties not from the inherent nature of the bulk materials, but from their artificially designed internal geometry composed of multiple sub-elements, or cells, which are usually arranged in repeated regular patterns[20,21]. Metamaterials can be considered as true machines[36], able to accomplish mechanical functions through the transformation of input stimuli into a programmable set of outputs In this case, constituent cells work together in a well-defined manner to obtain the final controlled directional macroscopic movement. Conventional design strategies for metamaterial structures and machines are often based on manual operations, which work reasonably well in specific conditions but are not guaranteed to yield maximum efficiency for all cases
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