| Title |
Recent Progress in First Principle Calculation and High-Throughput Screening of Electrocatalysts: A Review |
| Authors |
이창수(Changsoo Lee); 방기훈(Kihoon Bang); 홍두선(Doosun Hong); 이혁모(Hyuck Mo Lee) |
| DOI |
https://doi.org/10.3365/KJMM.2019.57.1.1 |
| ISSN |
1738-8228(ISSN), 2288-8241(eISSN) |
| Keywords |
electrocatalysts; density functional theory; first principle calculation; high-throughput screening; machine learning |
| Abstract |
There are many ongoing efforts to develop sustainable, clean, efficient, and economical pathways to produce renewable energy sources to satisfy worldwide energy demands. Electrochemical conversion processes, such as water splitting, CO2 conversion and N2 electroreduction, have been considered as successful approaches to solve these energy issues. Over the past decade, combining of theory and experiment has proven to be an innovative strategy, providing a framework for the design of high-performance catalysts and to investigate their mechanisms. This review introduces recent progress in theoretical strategies for state-of-theart heterogeneous electrocatalysts. Theoretical approaches are essential for grasping the intrinsic nature of the catalytic materials. Various levels of model system, with corresponding descriptions to capture the realistic environment, are addressed. Meanwhile, machine learning using data obtained by high-throughput screening, exploited as a new scientific approach, is discussed. Based on this review, it is expected that theoretical approaches will shed light on the future design of electrocatalysts, allowing for the development of sustainable energy sources.(Received October 17, 2018; Accepted November 27, 2018) |