Evolution of the Seebeck effect in nanoparticle-percolated networks under applied strain

Abstract

Nanoparticle clouds feature a unique evolution of the Seebeck coefficient under applied strain. At low strain, the Seebeck effect is very stable while, when a critical strain threshold is reached, it sharply decreases to zero. The evolution mechanism of this phenomenon that contributes to the development of various strain-insensitive sensors has yet to be documented. We elucidate here this evolution by proposing a phenomenological model supported by strong experimental evidence. We realize a full study of the Seebeck effect evolution for a network of nanoparticles under variable strain. We describe the evolution of this network as three subsequent stages: completely connected, partially connected, and disconnected. Based on the conductance-weighted formula, we theoretically analyze the evolution of the Seebeck coefficient in each stage. The Seebeck coefficient's initial stability is attributed to the connected pathways that exist in the first two stages. We validated these theoretical results by constructing percolated networks with embedded silver nanowires in elastomers and calculating the Seebeck coefficient under various stretching conditions. Finally, using the theoretical results as a guide, we created a temperature sensor that is highly resistant to mechanical damage.