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Article

Capturing the kinetics of escape

OCT 23, 2017
Experiments with an optically trapped glass nanosphere have revealed the elusive Kramers turnover, at which the particle’s odds of escape peak.
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Wait long enough, and a nanoparticle in an optical trap will eventually break free. Collisions with the surrounding molecules impart the particle with random velocity fluctuations known as Brownian motion; in time, that motion will carry the particle out of its confining potential well. Depending on the collective pressure exerted by the molecules, however, the escape could take an instant or an eternity. At low pressures, the collisions are so infrequent that the particle is slow to gather steam, and the escape rate falls to practically zero. The escape rate also becomes negligibly small at high pressures, where the constant barrage from the background molecules strongly damps the particle’s momentum. Somewhere between those extremes is thought to lie a point, known as Kramers turnover, where the odds of escape peak.

Kramers turnover and its underlying theory is relevant not only to trapped nanoparticles but to folding proteins, current-switching Josephson junctions, and virtually all other damped systems that have metastable energy states. But because the damping in most systems can’t be easily tuned, researchers haven’t been able to pinpoint Kramers turnover in experiments.

Now ETH Zürich’s Lukas Novotny and his colleagues have identified Kramers turnover for a silica nanosphere levitated in a double-well optical trap, as illustrated above. To control damping, the researchers enclosed the trap in a variable-pressure vacuum chamber. They could then measure the nanosphere’s escape rate—defined as the hopping rate between the two wells—over pressures spanning more than two orders of magnitude. Kramers turnover occurred at a pressure roughly equal to two-hundredths of an atmosphere, in agreement with the team’s analytical model. The researchers next plan to try more complicated trapping potentials in order to explore the kinetics of more complex systems, including those with time-dependent energy landscapes. (L. Rondin et al., Nat. Nanotechnol., in press .)

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