摘要
Various scaling relations have long been established in the field of heterogeneous catalysis,but the resultant volcano curves inherently limit the catalytic performance of catalyst candidates.On the other hand,it is still very challenging to develop universal descriptors that can be used in various types of catalysts and reaction systems.For these reasons,several strategies have recently been proposed to break and rebuild scaling relations to go beyond the top of volcanoes.In this review,some previously proposed descriptors have been briefly introduced.Then,the strategies for breaking known and establishing new and more generalized scaling relations in complex catalytic systems have been summarized.Finally,the application of machine-learning techniques in identifying universal descriptors for future computational design and high-throughput screening of heterogeneous catalysts has been discussed.
基金
supported by the National Natural Science Founda-tion of China(21473053,91645122,and 22073027)
the Natural Science Foundation of Shanghai(20ZR1415800)
the Funda-mental Research Funds for the Central Universities(222201718003).
