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POSTECH LabCumentary Donghwa Lee (Materials Science Engineering)

Computational Nano-Materials Design Lab

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Computational Nano-Materials Design Lab

Donghwa Lee (Materials Science Engineering)

Atoms are the smallest unit of matter, and the most fundamental building block of any given material. As atoms stack up, become mobile and interact between themselves, they begin to assume the physical properties that characterize materials. The implication of this underscores the relation of our atomic-level understanding of a material with our ability to  determine which materials will be best for which applications. Though it may sound relatively straight-forward in theory, the actual process of tracking down the movement of these tiny atoms that measure no larger than 1 nanometer (1 nanometer equals one billionth of a meter) and identifying their characteristics is anything but easy.

 

The Computational Nano-Materials Design (CNMD) Lab headed by Professor Donghwa Lee at the Department of Materials Science Engineering, POSTECH, follows just how atoms move as tiny separate entities through the use of computer calculations. The Lab characterizes atoms based on such calculations so that the physical properties of a targeted material can be analyzed, before using these findings to optimize the material for varying applications. The researchers at the Lab are specifically focused on understanding the electrons within an atom and how they move around and are distributed within the material, which ultimately lends itself to the expression of the physical property of a material.

 

The key in discovering the movement of electrons is through the use of first principles calculations, which are rooted in quantum mechanics. First principles calculations enable scientists to calculate how atoms or electrons move – solely through the help of basic physics laws and constants. As their accuracy and efficiency is demonstrated, such findings have recently garnered much attention. Probing into the interactions among electrons within a specific material that consists of a multitude of electrons requires a tremendous capacity to calculate. The CNMD Lab harnesses a supercomputer cluster created through the connection of 2,500 computer cores to unravel the mysteries of such materials one by one.

 

Upon discovering new properties within a target material, the Lab begins the process of searching for their possible applications. Some of the novel materials the Lab has discovered over the years have found their applications in such diverse areas as in energy, batteries, and in fuel and solar cells. Based on the Lab’s findings that copper-based perovskites demonstrate increased light transmittance at lower temperatures, the Lab featured the application of such properties to the smart windows at the Journal of the American Chemical Society last September.

 

If the physical properties of a material are identified through calculations, the laborious process of conducting numerous experiments to search for each and every material is greatly minimized. The CNMD Lab, however, aims to take a step further and improve both efficiency and speed in revealing the potential performance of materials. One active area of research currently underway at the Lab is the application of machine learning to material data that has been discovered through first principles calculations. This ultimately helps optimize the discovery of materials and identify their composition and/or additional elements.

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