Due to the fact that chemical reactions happen extremely quickly, it is difficult to identify the principles behind such reactions and the intermediary substances created during the process. To overcome these limitations and to predict and analyze chemical reactions, scientists depend on ‘computational chemistry’, which factors in the shape, movement, binding force or stability of the target particles into mathematical equations and then performs computer simulations.

The Computational Catalysis and Emerging Materials Laboratory headed by professor Jeong Woo Han at the Department of Chemical Engineering, POSTECH, deploys computational chemistry to design novel materials, predict their properties and validate them through experimentation with an aim to develop completely new catalysts and energy materials. Its research primarily focuses on ‘green’ catalysts used to produce fuel cell electrodes, store hydrogen or reduce the emission of exhaust gas.

One of the most notable research outcomes is related to the redesigning of platinum catalysts to improve their efficiency. These Pt catalysts, used to purify such exhaust gases as carbon monoxides or hydrocarbons into carbon dioxide and water, usually exist in clump formations made when the Pt atoms combine. The Pt atoms located on the inner side of these clumps are unable to participate in any chemical reaction. Leveraging computational chemistry, the Lab predicted that specifically-structured supports made from titanium and carbon ensure that Pt atoms do not form such clumps when separated. This was followed by physical experimentation to verify the hypothesis and improve the efficiency of Pt catalysts as a result. These research findings were featured on the 2019 January issue of the international journal of ‘ACS Energy Letters’, and the article made it on the MOST READ list for December 2018 as it was published in advance online.

In 2020, the Lab succeeded in developing an ultra-stable and highly active ceria catalyst used for CO oxidation. This catalyst was designed by co-doping rare earth and transition metals on ceria. Researchers first deployed computational chemistry to verify that simultaneously doping lanthanum (a rare earth metal) and copper (a transition metal) resulted in improvements in both activity and stability, and moved on to design a ceria catalyst. They proved through experimentation that this new type of ceria catalyst was as efficient as its conventional counterparts even at such a low temperature of 150  and yet, still remained stable for nearly 700 hours despite significant temperature fluctuations. The article was selected as a supplementary cover for the Dec. 2020 issue of the international journal of ‘ACS Catalysis’.

Computational chemistry gives researchers a head start as data that is accumulated each year enables them to predict the interactions among particles of interest with higher accuracy. It also allows them time and cost savings in their experimentations. Another plus is that the high-performance computers installed at the Lab can be connected to PCs or smartphones enabling researchers to work from any given location. The Lab aims to build a data network of energy materials to develop and commercialize novel catalysts and energy materials and to leverage this network to harness artificial intelligence in the development of catalysts and materials in order to establish methodologies that aid in the creation of never-before-possible materials.