Until now, the discovery of new catalysts for desired reactions has mainly relied on trial and error. This, however, is both cost- and time-consuming. Owing to new advances in theoretical methods, software, and hardware, computational chemistry has evolved into a powerful tool that allows the study of reaction mechanisms and the origin of various selectivity and reactivity properties at the atomic level, without the involvement of real catalysts and substrates. Challenges do remain, such as the cost of evaluating entropy effect in the solution, or attaining sufficient accuracy in computational methods. However, relative accuracy from computational results are trustworthy, especially when coupled with and compared to experiments. For this reason, computational chemistry plays an increasingly significant role not only in elucidating mechanisms of complex reactions, but also in guiding experiments for the improvement of synthetic methods or the rational design of new catalysts through meaningful predictions of the structure-reactivity relationship.
This Research Topic deals with computational chemistry as a powerful tool for chemical discovery and design, focusing on recent progress in homogeneous catalysis. In that vein, this collection of articles will discuss contributions in:
i) exploiting computational chemistry to understand mechanisms and the origin of various selectivity properties (such as chemo-, regio-, and stereoselectivities) of complex reactions, especially when computations provide mechanistic details that are unavailable or difficult to be obtained from experiments and are helpful for guiding experiments for improving synthesis or the rational design of new catalysts;
ii) screening of existing catalysts or rational design of new catalysts for desired reactions on the basis of reactivity descriptors and guiding design principles predicted by computational studies;
iii) developing new computational methods or tools allowing computational chemists to automatically search transitions states or determine different reaction pathways, which are helpful to accelerate the process of screening catalysts for desired reactions.
The purpose of this Research Topic is to highlight the new trends in this theme by gathering articles that describe the predictive power of modern computational chemistry in the field of homogeneous catalysis, and how chemical discovery and design could be made faster and better than ever before by combining computation and experiments.
Until now, the discovery of new catalysts for desired reactions has mainly relied on trial and error. This, however, is both cost- and time-consuming. Owing to new advances in theoretical methods, software, and hardware, computational chemistry has evolved into a powerful tool that allows the study of reaction mechanisms and the origin of various selectivity and reactivity properties at the atomic level, without the involvement of real catalysts and substrates. Challenges do remain, such as the cost of evaluating entropy effect in the solution, or attaining sufficient accuracy in computational methods. However, relative accuracy from computational results are trustworthy, especially when coupled with and compared to experiments. For this reason, computational chemistry plays an increasingly significant role not only in elucidating mechanisms of complex reactions, but also in guiding experiments for the improvement of synthetic methods or the rational design of new catalysts through meaningful predictions of the structure-reactivity relationship.
This Research Topic deals with computational chemistry as a powerful tool for chemical discovery and design, focusing on recent progress in homogeneous catalysis. In that vein, this collection of articles will discuss contributions in:
i) exploiting computational chemistry to understand mechanisms and the origin of various selectivity properties (such as chemo-, regio-, and stereoselectivities) of complex reactions, especially when computations provide mechanistic details that are unavailable or difficult to be obtained from experiments and are helpful for guiding experiments for improving synthesis or the rational design of new catalysts;
ii) screening of existing catalysts or rational design of new catalysts for desired reactions on the basis of reactivity descriptors and guiding design principles predicted by computational studies;
iii) developing new computational methods or tools allowing computational chemists to automatically search transitions states or determine different reaction pathways, which are helpful to accelerate the process of screening catalysts for desired reactions.
The purpose of this Research Topic is to highlight the new trends in this theme by gathering articles that describe the predictive power of modern computational chemistry in the field of homogeneous catalysis, and how chemical discovery and design could be made faster and better than ever before by combining computation and experiments.
