Decade Milestone Advancement of Defect-Engineered g-C3N4 for Solar Catalytic Applications.

Over the past decade, graphitic carbon nitride (g-C3N4) has emerged as a universal photocatalyst toward various sustainable carbo-neutral technologies. Despite solar applications discrepancy, g-C3N4 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. To this end, we have summarized an unprecedently comprehensive discussion on defect controls including the vacancy/non-metallic dopant creation with optimized electronic band structure and electronic density, metallic doping with ultra-active coordinated environment (M-Nx, M-C2N2, M-O bonding), functional group grafting with optimized band structure, and promoted crystallinity with extended conjugation π system with weakened interlayered van der Waals interaction. Among them, the defect states induced by various defect types such as N vacancy, P/S/halogen dopants, and cyano group in boosting solar harvesting and accelerating photocarrier transfer have also been emphasized. More importantly, the shallow defect traps identified by femtosecond transient absorption spectra (fs-TAS) have also been highlighted. It is believed that this review would pave the way for future readers with a unique insight into a more precise defective g-C3N4 "customization", motivating more profound thinking and flourishing research outputs on g-C3N4-based photocatalysis.

Precise Defect Engineering on Graphitic Carbon Nitrides for Boosted Solar H2 Production.

Defect engineering has been regarded as an "all-in-one strategy" to alleviate the insufficient solar utilization in g-C3 N4 . 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-C3 N4 is designed with both S dopants and N vacancies via a dual-solvent-assisted synthetic approach. The precise defect control is realized by the addition of ethylene glycol (EG) into precursor formation and molten sulfur into the pyrolysis process, which simultaneously induced g-C3N4. with shallow defect states. These shallow defect energy levels can act as a temporary electron reservoir, which are critical to evoke the migrated electrons from CB with a moderate trapping ability, thus suppressing the bulky photocarrier recombination. Additionally, the optimized surface states of DCN-ES are also demonstrated by the highest electron-trapping resistance (Rtrapping ) of 9.56 × 103 Ω cm2 and the slowest decay kinetics of surface carriers (0.057 s-1 ), which guaranteed the smooth surface charge transfer rather than being the recombination sites. As a result, DCN-ES exhibited a superior H2 evolution rate of 4219.9 µmol g-1 h-1 , which is 29.1-fold higher than unmodified g-C3 N4 .

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. The theoretical understanding and in-situ spectroscopy analysis revealed that the favorable coordination of conjugated anions involved in hydrogn bond network minimizes the activate water molecules of hydrated zinc ion, thus improving the zinc/electrolyte interface stability to suppress the dendrite growth and side reactions. With the reversibly cycling of zinc electrode over 2000 h with a low overpotential of 17.7 mV, the full battery with polyaniline cathode demonstrated the impressive cycling stability for 10000 cycles. This work provides inspiring fundamental principles to design advanced electrolytes under the dual contributions of solvation modulation and interface regulation for high-performing zinc-based batteries and others.

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

Structural reconstruction is commonly observed during electrocatalytic CO2 reduction (CO2RR) 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 CO2RR via electrochemical reduction and in situ anchoring strategy. As revealed by in situ structure analysis and theoretical studies, the ensemble sites supported on carbon matrix enable the charge density gradient to significantly promote the adsorption of *OCHO intermediate by the regulation of σ bonding and π* back-donation. Consequently, such unique electrocatalyst achieves the high formate faradaic efficiency of 95.1% over the entire potential range tested and the long-lived stability for 9 d. With coupling of CO2RR, the solar-driven full cell demonstrates the spontaneous production of formate and 2,5-furandicarboxylic acid via the efficient oxidation of 5-hydroxymethylfurfural with an outstanding yield of 88.2%, highlighting the impressive solar-to-fuel conversion selectivity. Monitoring and understanding the intrinsic active sites of biatomic bridge are crucial to elucidate the synergic electrocatalysis for rationally designing high-performance electrocatalysts.

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 CO2 emission. The newly emerged nitrogen fixation technology, photocatalytic N2 reduction reaction (p-NRR), uses clean solar energy with zero-emission, holding great prospect to achieve sustainable ammonia synthesis. Although great efforts are made, the p-NRR catalysts still suffer from poor N2 adsorption and activation, inferior light absorption, and fast recombination of photocarriers. Due to the tunable electronic structure of the metal-free polymeric graphitic carbon nitride (g-C3 N4 ), the above-mentioned issues can be significantly alleviated, making it the most promising p-NRR photocatalyst. This review summarizes the recent development of g-C3 N4 -based catalysts for p-NRR, including the working principle of p-NRR catalysts, the challenges of developing p-NRR catalysts, and corresponding solutions. Particularly, the roles of defect engineering and heterojunction construction on g-C3 N4 to the enhancement of photocatalytic performances are emphasized. In addition, computational studies are introduced to deepen the understanding of reaction pathways. At last, perspectives are provided on the development of p-NRR catalysts.

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. In addition, we presented an improved Online Hard Example Mining (OHEM) strategy, which can enhance the average precision of face detection by balancing the number of positive and negative samples. Our method has achieved an accuracy of 0.933, 0.924, and 0.848 on the Easy, Medium, and Hard subset of WIDER FACE, respectively, which surpasses most of the advanced algorithms.