A new method to study polarons in insulators and semiconductors

phys.org | 9/13/2017 | Staff
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A team of researchers at the University of Oxford have recently introduced a new way to model polarons, a quasiparticle typically used by physicists to understand interactions between electrons and atoms in solid materials. Their method, presented in a paper published in Physical Review Letters, combines theoretical modeling with computational simulations, enabling in-depth observations of these quasiparticles in a wide range of materials.

Polaron - Particle - Electron - Cloud - Phonons

Essentially, a polaron is a composite particle comprised of an electron surrounded by a cloud of phonons (i.e. lattice vibrations). This quasiparticle is heavier than the electron itself and due to its substantial weight it can sometimes become trapped in a crystal lattice.

Polarons contribute to the electric current that powers several technological tools, including organic light-emitting diodes and touchscreens. Understanding their properties is thus of key importance, as it could help to develop the next generation of various devices for lighting and optoelectronics.

Work - Polarons - Models - Prof - Feliciano

"Previous work on polarons relied on idealized mathematical models," Prof. Feliciano Giustino, the head of the team who carried out the study, told Phys.org. "These models have been very useful to understand the basic properties of polarons, but they do not take into account the structure of materials at the atomic scale, therefore they are not sufficient when we try to study real materials for practical applications. Our idea was to develop a computational methodology that would enable systematic investigations of polarons with predictive accuracy."

The method devised by Giustino's team is based on the density-functional theory, which is currently the most popular tool for predictive materials modeling and design using quantum mechanics. One of the primary challenges encountered when studying polarons based on this theory is that the required computational resources (CPU hours) are proportional to the third power of the number of atoms to be simulated. In other words, if one was...
(Excerpt) Read more at: phys.org
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