Stretching of a monolithic silicon-based sensor network for large area embedded structural health monitoring

A concept of stretchable silicon-based sensor networks for large area coverage was recently proposed. These networks are fabricated using standard silicon foundry processing. Their area can be stretched by several orders of magnitude because they are structured as two-dimensional networks of circuit nodes interconnected by springs. The use of foundry silicon means that a large amount of electronic functionality (amplifiers, processors, wireless communication) can be integrated into the sensor network. This will ultimately lead to low-power, high-performance, low-cost smart materials with embedded sensor networks that sense structural parameters on very fine scale (millimetres). To facilitate the concept development, an investigation was performed to evaluate the mechanical performance of stretching a silicon-based network with emphasis on a particular network pattern, in which the sensor nodes in the network remain stationary while the network is being stretched. To support the design and validate finite-element models, a micro-scale force measurement device was designed and built into the network. The network can be deployed by unrolling the spiral wires up to its final size that is in several orders of magnitude higher than the original size giving rise to a regular array. Since the stretchable silicon sensor networks are built entirely from silicon and since the smallest dimensions are microns, special handling is required to prevent damaging the networks. Techniques were developed to pick up and transfer the extremely thin and flexible network from the parent substrate to other substrate. A built-in force measurement device was used to monitor the force as low as a few micro-Newton while stretching. This study demonstrates a procedure for the transfer/ stretching of the networks and shows that the proposed network pattern is stable during its wire unrolling process. We anticipate that the proposed network pattern can be scaled up without difficulty.