Ed Yong in The Atlantic:
Light and sound are predictable. Smells are not.
If you knew the wavelength of a beam of light, you could tell me what most people would see when they looked at it: 480 nanometers looks blue, and 650 nanometers looks red. If you knew the frequency of a musical note, you could name that note: 261 Hertz is middle C.
But if you saw the chemical structure of a molecule, you wouldn’t know what it smelled like—or even if it smelled of anything at all. Unless you actually stick your nose over some benzaldehyde, you wouldn’t be able to predict that it smelled like almonds. If you saw dimethyl sulfide drawn on a page, you couldn’t foresee that it carried the scent of the sea.
This is a longstanding problem, but one that a team of scientists—and a horde of volunteers and citizen scientists—have come a little closer to cracking. Through a crowdsourced competition, Andreas Keller and Leslie Vosshall at Rockefeller University and Pablo Meyer at IBM have developed algorithms that can reverse-engineer the smell of a molecule—to predict what it smellslike from what it is.