Semi-Supervised Graph Structure Learning via Dual Reinforcement of Label and Prior Structure.

Graph neural networks (GNNs) have achieved considerable success in dealing with graph-structured data by the message-passing mechanism. Actually, this mechanism relies on a fundamental assumption that the graph structure along which information propagates is perfect. However, the real-world graphs are inevitably incomplete or noisy, which violates the assumption, thus resulting in limited performance.

Clustering Enhanced Multiplex Graph Contrastive Representation Learning.

Multiplex graph representation learning has attracted considerable attention due to its powerful capacity to depict multiple relation types between nodes. Previous methods generally learn representations of each relation-based subgraph and then aggregate them into final representations. Despite the enormous success, they commonly encounter two challenges: 1) the latent community structure is overlooked and 2) consistent and complementary information across relation types remains largely unexplored.

Crumpled graphene microspheres anchored on NiCoO nanoparticles as an advanced composite electrode for asymmetric supercapacitors with ultralong cycling life.

The rational design of composite electrodes that may take full advantage of pseudocapacitive metal oxides and graphene is still challenging. Herein, nickel cobaltate (NiCoO) nanoparticle-anchored crumpled graphene microspheres (CGMs) were fabricated through a simple spray-assisted self-assembly process and used as a composite electrode for aqueous supercapacitors. Due to the porous spherical architecture and well-dispersed NiCoO nanoparticles on graphene, the NiCoO/CGM electrode displays ideal electrochemical performance, including a specific capacitance of 369.

FeO nanoplates anchored on TiCT MXene with enhanced pseudocapacitive and electrocatalytic properties.

TiCT, as novel members of the two-dimensional material family, hold great promise for electrochemical energy storage and catalysis, however, the electrochemical performance of TiCT is largely limited by the self-restacking of their layers due to van der Waals forces. In this study, we report a high-performance electrode material, TiCT supported FeO nanoplates (denoted as MXene-Fe), synthesized by a simple wet chemistry method in a solvothermal system. The mesoporous MXene-Fe material as a supercapacitor electrode exhibits a high specific capacitance of 368.