Te Faye Yap (left) and Daniel Preston Photo Credit: Jeff Fitlow/Rice University |
Soft robots use pliant materials such as elastomers to interact safely with the human body and other challenging, delicate objects and environments. A team of Rice University researchers has developed an analytical model that can predict the curing time of platinum-catalyzed silicone elastomers as a function of temperature. The model could help reduce energy waste and improve throughput for elastomer-based components manufacturing.
“In our study, we looked at elastomers as a class of materials that enables soft robotics, a field that has seen a huge surge in growth over the past decade,” said Daniel Preston, a Rice assistant professor of mechanical engineering and corresponding author on a study published in Cell Reports Physical Science. “While there is some related research on materials like epoxies and even on several specific silicone elastomers, until now there was no detailed quantitative account of the curing reaction for many of the commercially available silicone elastomers that people are actually using to make soft robots. Our work fills that gap.”
The platinum-catalyzed silicone elastomers that Preston and his team studied typically start out as two viscoelastic liquids that, when mixed together, transform over time into a rubbery solid. As a liquid mixture, they can be poured into intricate molds and thus used for casting complex components. The curing process can occur at room temperature, but it can also be sped up using heat.
Manufacturing processes involving elastomers have typically relied on empirical estimates for temperature and duration to control the curing process. However, this ballpark approach makes it difficult to predict how elastomers will behave under varying curing conditions. Having a quantitative framework to determine exactly how temperature impacts curing speed will enable manufacturers to maximize efficiency and reduce waste.