Supercomputing Thin Film Growth

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Jacques Amar, Ph.D., professor of physics at the University of Toledo, studies the modeling and growth of materials at the atomic level. Recently, Amar leveraged the Ohio Supercomputer Center’s powerful clusters to implement a “first-passage time approach” to speed up KMC simulations of the creation of materials just a few atoms thick.

The KMC method has been successfully used to carry out simulations of a wide variety of dynamical processes over experimentally relevant time and length scales,” Amar noted. “However, in some cases, much of the simulation time can be ‘wasted’ on rapid, repetitive, low-barrier events.”

Among possible solutions, Amar settled on using a first-passage-time (FPT) approach to improve KMC processing speeds. FP is a statistical model that sets a certain threshold for a process and then estimates factors such as the probability that the process reaches that threshold within a certain amount time or the mean time until which the threshold is reached.

In this approach, one avoids simulating the numerous diffusive hops of atoms, and instead replaces them with the first-passage time to make a transition from one location to another,” Amar said.


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