No abstract

No abstract

Network slicing is born as an emerging business to operators, by allowing them to sell the customized slices to various tenants at different prices. In order to provide betterperforming and cost-efficient services, network slicing involves challenging technical issues and urgently looks forward to intelligent innovations to make the resource management consistent with users' activities per slice. In that regard, deep reinforcement learning (DRL), which focuses on how to interact with the environment by trying alternative actions and reinforcing the tendency actions producing more rewarding consequences, is assumed to be a promising solution. In this paper, after briefly reviewing the fundamental concepts of DRL, we investigate the application of DRL in solving some typical resource management for network slicing scenarios, which include radio resource slicing and priority-based core network slicing, and demonstrate the advantage of DRL over several competing schemes through extensive simulations. Finally, we also discuss the possible challenges to apply DRL in network slicing from a general perspective.

transfer and sluggish kinetics process. [4][5][6] Although precious metals, such as Ir and Ru, as well as their oxides have been approved as efficient electrocatalysts for the OER, their high cost and scarcity undoubtedly prohibit the large-scale application in practice, to some extent. [5,6,7,8a] As a result, a great amount of efforts have been devoted to exploit earth-abundant metalsbased electrocatalysts, such as metal phosphates, oxides, hydroxides, chalcogenides, and nitrides for promoting the OER. However, the performance of explored catalysts is still discounted by their low conductivity and inadequate active surface area, resulting in high overpotential and limited kinetics in the OER. [9a,10b] Thus, to satisfy the requirement of efficient water splitting, the development of new materials and/or methodologies to exploit novel electrocatalysts with advantages of fast reaction rate, minimum overpotential, and long-term stability is one of current research hot topics in several research fields.Among resource-rich transition metalbased electrocatalysts, Co-based materials (e.g., Co, Co 3 O 4 , Co 8 S 9 , CoP, and CoN 4 ) have emerged as important candidates for the water splitting due to their low cost-efficiency, environmental benignity, and theoretically high catalytic activity. [11][12][13][14][15] Despite a great deal of efforts, the low intrinsic conductivity and easy self-agglomeration of these catalysts usually lead to a high overpotential and decreased reaction rate. Alternatively, the integration of Co-based materials and other electrocatalysts has been demonstrated to be able to enhance OER activity, however the poor compatibility between them in some composites is an obstacle to further optimize their efficiency. [16][17][18][19] Moreover, in some cases the active components are still not stable enough when being subjected to long time operation or accelerated degradation measurements under strong alkaline electrolytes, which also limits their application.Recently, it was demonstrated that deliberately designing well-defined 3D structures directly grown on the current collectors can endow electrocatalysts with superior water splitting performance, owing to the advantages of their fast electrolyte penetration, great electrical conductivity, and more exposed active sites. [20][21][22][23] It was noticed that Co-based metal-organic frameworks (MOFs) (as the template) derived materials with The ever-increasing demand for clean and renewable power sources has sparked intensive research on water splitting to produce hydrogen, in which the exploration of electrocatalysts is the central issue. Herein, a new strategy, metal-organic framework template-directed fabrication of hierarchically structured Co 3 O 4 @X (X = Co 3 O 4 , CoS, C, and CoP) electrocatalysts for efficient oxygen evolution reaction (OER) is developed, where Co 3 O 4 @X are derived from cobalt carbonatehydroxide@zeolitic-imidazolate-framework-67 (CCH@ZIF-67). Unique hierarchical structure and synergistic effect of resulting catalysts endo...

No abstract

A highly stable porphyrinic MOF with free-carboxylic group functionalized pore surfaces exhibits a high proton conductivity of 3.9 × 10−2 S cm−1 at 80 °C and 97% RH, which is comparable to most of the reported proton conductive MOFs.

No abstract

Tens of thousands of metal–organic frameworks (MOFs) have been developed in the past two decades, and only ≈100 of them have been demonstrated as porous and hydrophobic. These hydrophobic MOFs feature not only a rich structural variety, highly crystalline frameworks, and uniform micropores, but also a low affinity toward water and superior hydrolytic stability, which make them promising adsorbents for diverse applications, including humid CO2 capture, alcohol/water separation, pollutant removal from air or water, substrate‐selective catalysis, energy storage, anticorrosion, and self‐cleaning. Herein, the recent research advancements in hydrophobic MOFs are presented. The existing techniques for qualitatively or quantitatively assessing the hydrophobicity of MOFs are first introduced. The reported experimental methods for the preparation of hydrophobic MOFs are then categorized. The concept that hydrophobic MOFs normally synthesized from predesigned organic ligands can also be prepared by the postsynthetic modification of the internal pore surface and/or external crystal surface of hydrophilic or less hydrophobic MOFs is highlighted. Finally, an overview of the recent studies on hydrophobic MOFs for various applications is provided and suggests the high versatility of this unique class of materials for practical use as either adsorbents or nanomaterials.