Free-standing bimetallic Co/Ni-MOF foams toward enhanced methane dry reforming under non-thermal plasma catalysis.

Understanding of the structure and interfacial merits that reactive metal-organic frameworks (MOFs) undergo is critical for constructing efficient catalysts for non-thermal plasma-assisted conversion of greenhouse gases. Herein, we proposed a free-standing bimetallic (Co/Ni) MOFs supported on bacterial cellulose (BC) foams (Co/Ni-MOF@BC) toward the coaxial dielectric barrier discharge (DBD) plasma-catalytic system, of which the Co/Ni ions coordination demonstrated an intriguing textual uplifting of the malleable BC nanofiber network with abundant pores up to micrometer-scale, which could impart a more intensive predominant filamentary microdischarge current to 180 mA with stronger plasma-catalytic interaction. Remarkably, compared to the monometallic MOF@BC foams, this bimetallic Co/Ni-MOF@BC also delivered a substantially improved alkaline absorption ability as further confirmed by the CO- temperature-programmed desorption (TPD) result.

Decade Milestone Advancement of Defect-Engineered g-CN for Solar Catalytic Applications.

Over the past decade, graphitic carbon nitride (g-CN) has emerged as a universal photocatalyst toward various sustainable carbo-neutral technologies. Despite solar applications discrepancy, g-CN is still confronted with a general fatal issue of insufficient supply of thermodynamically active photocarriers due to its inferior solar harvesting ability and sluggish charge transfer dynamics. Fortunately, this could be significantly alleviated by the "all-in-one" defect engineering strategy, which enables a simultaneous amelioration of both textural uniqueness and intrinsic electronic band structures.

Coordination modulation of hydrated zinc ions to enhance redox reversibility of zinc batteries.

The dendrite growth of zinc and the side reactions including hydrogen evolution often degrade performances of zinc-based batteries. These issues are closely related to the desolvation process of hydrated zinc ions. Here we show that the efficient regulation on the solvation structure and chemical properties of hydrated zinc ions can be achieved by adjusting the coordination micro-environment with zinc phenolsulfonate and tetrabutylammonium 4-toluenesulfonate as a family of electrolytes.

Precise Defect Engineering on Graphitic Carbon Nitrides for Boosted Solar H Production.

Defect engineering has been regarded as an "all-in-one strategy" to alleviate the insufficient solar utilization in g-CN. However, without appropriate modification, the defect benefits will be partly offset due to the formation of deep localized defect states and deteriorated surface states, lowering the photocarrier separation efficiency. To this end, the defective g-CN is designed with both S dopants and N vacancies via a dual-solvent-assisted synthetic approach.

Atomic bismuth induced ensemble sites with indium towards highly efficient and stable electrocatalytic reduction of carbon dioxide.

Structural reconstruction is commonly observed during electrocatalytic CO reduction (CORR) process. However, the proper modulation of interface and defect sites remains challenging with the mechanism understanding to realize the favorable electrocatalysis. Herein, the atomic bridging of bismuth with indium atoms is elaborately designed for improving electrocatalysis of CORR via electrochemical reduction and in situ anchoring strategy.

Recent Advances in Application of Graphitic Carbon Nitride-Based Catalysts for Photocatalytic Nitrogen Fixation.

Ammonia, the second most-produced chemical, is widely used in agricultural and industrial applications. However, traditional industrial ammonia production dominated by the Haber-Bosch process presents huge resource and environment issues due to the massive energy consumption and CO emission. The newly emerged nitrogen fixation technology, photocatalytic N reduction reaction (p-NRR), uses clean solar energy with zero-emission, holding great prospect to achieve sustainable ammonia synthesis.

Hybrid Pyramid Convolutional Network for Multiscale Face Detection.

Face detection remains a challenging problem due to the high variability of scale and occlusion despite the strong representational power of deep convolutional neural networks and their implicit robustness. To handle hard face detection under extreme circumstances especially tiny faces detection, in this paper, we proposed a multiscale Hybrid Pyramid Convolutional Network (HPCNet), which is a one-stage fully convolutional network. Our HPCNet consists of three newly presented modules: firstly, we designed the Hybrid Dilated Convolution (HDC) module to replace the fully connected layers in VGG16, which enlarges receptive field and reduces its loss of local information; secondly, we constructed the Hybrid Feature Pyramid (HFP) to combine semantic information from higher layers together with details from lower layers; and thirdly, to deal with the problem of occlusion and blurring effectively, we introduced Context Information Extractor (CIE) in HPCNet.