Abstract Future‐oriented Science & Technology (S&T) Strategies trigger the innovative
developments of advanced materials, providing an envision to the significant progress of …

Medium-entropy carbide ceramics have garnered significant attention due to their
outstanding mechanical and chemical properties. However, the underlying physical …

Lattice engineering and distortion have been considered one kind of effective strategies for
discovering advanced materials. The instinct chemical flexibility of high-entropy oxides …

We developed a PyTorch-based architecture called HydraGNN that implements graph
convolutional neural networks (GCNNs) to predict the formation energy and the bulk …

Materials descriptors with multivariate, multiphase, and multiscale of a complex system have
been treated as the remarkable materials genome, addressing the composition–processing …

Multicomponent carbides, as a novel type of nuclear fuel, have attracted significant attention
both domestically and internationally due to their excellent physical and chemical properties …

In this study, we show the transferability of graph convolutional neural network (GCNN)
predictions of the formation energy of the nickel-platinum solid solution alloy across atomic …

Multicomponent ceramics have received much attention due to the tunning physicochemical
properties and the huge compositional space, while multicomponent ceramics with the …

The present work applied the first-principles calculations to investigate the diffusion behavior
of oxygen atoms in Ti/Zr/Ta-alloyed Hf 6 C 5 carbides. Two series of structural units …

Considering charge transfer effects and the variability of the bonding between elements with
different electronegativity opens up a deeper understanding of the electronic structure and …