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If you took this stuffed animal and chose to splatter paint
on it, what would happen?
Well, besides making a colorful mess,
you'd likely create a shower of liquid droplets ranging
drastically in size and distribution.
To most, the shower of droplets will
appear to be totally random, but to a group of engineers,
this shower isn't random at all.
In fact, according to them, it's 100% predictable.
The ways in which liquids fragment, or break up
into droplets, has interested researchers for decades.
And although there have been successful attempts
in characterizing liquid fragmentation,
they have typically focused on what
are known as Newtonian fluids, fluids such as water
and oil, which are relatively thin,
homogeneous liquids, and not those that are more complex,
such as saliva, blood, and paint.
However, in a newly published study, a team of MIT engineers
show that they can now predict droplet size distribution,
including the largest and smallest droplets
a liquid could possibly produce based
on one main property, its viscoelasticity, or stickiness.
To show how viscoelasticity can affect
the distribution of liquid droplets of a specific size,
the team set up a series of experiments
involving both Newtonian and non-Newtonian fluids.
For each fluid sample, they did three different tests.
First dropping liquids onto a flat surface,
then spraying them through a nozzle,
and finally forming a liquid spray
through two colliding jets.
Their experiment showed that, in general, thinner Newtonian
fluids produced a narrow range of droplet sizes,
regardless of the type of experiment
performed, whereas viscoelastic fluids had broader
distributions, generating larger numbers
of both big and small drops.
They also noticed that no matter if they
were sprayed or dropped, viscoelastic fluids
created long ligaments, or string like projections,
that first stretched, but then eventually broke apart
into a range of droplets.
In other words, using their mathematical model,
the researchers identified the broadest distribution
of droplet sizes that any viscoelastic non-Newtonian
fluid can possibly exhibit.
Having a clearer understanding of fluid fragmentation
could help identify optimal fluids
for a number of industrial applications
that involve complex liquids, like preventing defects
in automotive paint jobs, or optimizing
the efficacy of fertilizing farm fields via aerial spraying.