NSF Grant To Support Tully’s Work on Behavior of Atoms
Given that the ancient Greeks theorized the existence of atoms more than 2,500 years ago, it might seem that scientists must know everything about these tiny elements of matter and how they interact with one another by now.
But John Tully insists there’s much more to learn. The Sterling Professor of Chemistry has been awarded a grant by the National Science Foundation to come up with an entirely new model for understanding the behavior and movement of atoms.
“Until now, we’ve relied on classical mechanics to understand how atoms and molecules move around during chemical reactions — how they transfer energy, their chemical reaction rates, and how bonds are made and broken,” he says. “But atoms behave in a quantum mechanical way, and that’s something our current models don’t properly take into account.”
In order to come up with a new theory of molecular dynamics, Tully will work to incorporate the strange properties of quantum mechanics, which stipulates that atoms “jump” between discrete energy states and can even “tunnel” through barriers. One aspect that particularly interests him is how protons are transferred from atom to atom, which is involved in many of the natural processes we take for granted everyday, such as plant photosynthesis, the composition of the atmosphere and even our own vision.
The grant, which totals more than $500,000 over four years, will primarily go toward supporting the work on these new theoretical models by postdoctoral associate Ryan Steele and graduate student Jill Zwickl, both members of Tully’s team.
While the world of atoms and quantum mechanics might seem like obscure topics without much relation to the everyday, there are lots of practical applications, Tully explains.
For example, Intel uses a hydrogen isotope called deuterium to reduce electron-induced damage in silicon/silicon oxide transistors. How the isotope manages to reduce the damage is the result of some sort of quantum effect, Tully says, but the process is not understood. If he and his team can better understand the physics behind the effect, it might one day lead to more efficient transistors.
“We like to apply our models to real-world experiences that people are interested in,” he says.
— By Suzanne Taylor Muzzin