Combinatorial Computational Chemistry Approach for Materials Design:Applications in deNOx Catalysis, Fischer-Tropsch Synthesis, Lanthanoid Complex, and Lithium Ion Secondary Battery

Abstract

Computational chemistry can provide fundamental knowledge regarding various aspects of materials. While its impact in scientific research is greatly increasing, its contributions to industrially important issues are far from satisfactory. In order to realize industrial innovation by computational chemistry, a new concept "combinatorial computational chemistry" has been proposed by introducing the concept of combinatorial chemistry to computational chemistry. This combinatorial computational chemistry approach enables theoretical high-throughput screening for materials design. In this manuscript, we review the successful applications of combinatorial computational chemistry to deNO(x) catalysts, Fischer-Tropsch catalysts, lanthanoid complex catalysts, and cathodes of the lithium ion secondary battery.

A review on mechanistic understanding of MnO2in aqueous electrolyte for electrical energy storage systems

“…For instance, the exact location of hydrogen needs to be known to construct a proper model and intermediate phases should be considered in the reaction scheme. Through considering these parameters, new materials can be proposed minimising the unnecessary syntheses [277,278].…”

“…While novel materials need to be applied, exploring these routes require screening [275]. Since searching every possible solution can take too much time and effort, first principles high-throughput computation methods should be utilised to find promising materials [276,277]. In order to perform the high-throughput screening, different traits of the potential property need to be established.…”