TY - JOUR
T1 - Recent progress in first principle calculation and high-throughput screening of electrocatalysts
T2 - A review
AU - Lee, Changsoo
AU - Bang, Kihoon
AU - Hong, Doosun
AU - Lee, Hyuck Mo
N1 - Publisher Copyright:
© The Korean Institute of Metals and Materials
PY - 2019
Y1 - 2019
N2 - 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, CO 2 conversion and N 2 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-the-art 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.
AB - 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, CO 2 conversion and N 2 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-the-art 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.
KW - Density functional theory
KW - Electrocatalysts
KW - First principle calculation
KW - High-throughput screening
KW - Machine learning
UR - https://www.scopus.com/pages/publications/85062809877
U2 - 10.3365/KJMM.2019.57.1.1
DO - 10.3365/KJMM.2019.57.1.1
M3 - Review article
AN - SCOPUS:85062809877
SN - 1738-8228
VL - 57
SP - 1
EP - 9
JO - Journal of Korean Institute of Metals and Materials
JF - Journal of Korean Institute of Metals and Materials
IS - 1
ER -