I know that IEEE 754 defines NaNs to have the following bitwise representation:
0 or 1
The statistical environment R uses NaN payloads to distinguish one specific NaN as representing a statistical "missing value", which prints as NA. This allows 'missing' to propagate through numeric calculations -- although when combining a missing value with another NaN it is not predictable which one is propagated.