MaterialDistrict

Learning from Chocolate Coatings to Predict the Thickness of Shell Structures

Initially inspired by videos of chocolatiers making bonbons and other sweets, Professor Pedro Reis and his MIT team wondered if there was a way to precisely predict the final thickness of a shell, as well as other shells that start out as a liquid film. Their delicious finding have the potential to perfect shell structures ranging from small chocolates and tiny capsules, to airplane and rocket bodies.

The study involved pouring a liquid polymer over dome-shaped or sphere-shaped moulds such as ping pong balls and allowing the liquid coat to cure and solidify over a 15 minute period. They then peeled the solidified shell off the mould in order to analyse its smoothness, thickness and other key characteristics. Combining a theory they derived with this pouring technique, the team proceeded to create shells of different thicknesses by varying parameters such as the radius of the sphere and the density of the liquid polymer material.

Contrary to what they anticipated, they found that the thickness of a shell isn’t influenced by the volume of the liquid or the height from which it was poured. Instead, they were able to use their finding to develop a new formula to estimate the final thickness of a shell, which should equal the square root of the fluid’s viscosity, times the mould’s radius, divided by the curing time of the polymer, times the polymer’s density and the acceleration of gravity as the polymer flows down the mould.

Put more simply: The larger a mould’s radius, the longer it takes for fluid to flow to the bottom, resulting in a thicker shell; the longer the curing time, the faster the fluid will drain to the bottom, creating a thinner shell.

‘Think of this formula as a recipe,’ says Pedro Reis, the Gilbert W. Winslow Associate Professor of mechanical engineering and civil and environmental engineering at MIT. ‘I’m sure chocolatiers have come up with techniques that give empirically a set of instructions that they know will work.’

Read more on this story at MIT news.

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