摘要 : Electrochemical reduction of CO2 to chemical fuel offers a promising strategy for managing the global carbon balance, but presents challenges for chemistry due to the lack of effective electrocatalyst. Here we report atomically dispersed nickel on nitrogenated graphene as an efficient and durable electrocatalyst for CO2 reduction. Based on operando X-ray absorption and photoelectron spectroscopy measurements, the monovalent Ni(i) atomic center with a d9 electronic configuration was identified as the catalytically active site. The single-Ni-atom catalyst exhibits high intrinsic CO2 reduction activity, reaching a specific current of 350âAâgcatalystâ1 and turnover frequency of 14,800âhâ1 at a mild overpotential of 0.61âV for CO conversion with 97% Faradaic efficiency. The catalyst maintained 98% of its initial activity after 100âh of continuous reaction at CO formation current densities as high as 22âmAâcmâ2.

摘要 : Abstract Active carbons have unique physicochemical properties, but their conductivities and surface to weight ratios are much poorer than graphene. A unique and facile method is innovated to chemically process biomass by “drilling” holes with H 2 O 2 and exfoliating into graphene‐like nanosheets with HAc, followed by carbonization at a high temperature for highly graphitized activated carbon with greatly enhanced porosity, unique pore structure, high conductivity, and large surface area. This graphene‐like carbon exhibits extremely high specific capacitance (340 F g −1 at 0.5 A g −1 ) and high specific energy density (23.33 to 16.67 W h kg −1 ) with excellent rate capability and long cycling stability (remains 98% after 10 000 cycles), which is much superior to all reported carbons including graphene. Synthesis mechanism for deriving biomass into porous graphene‐like carbons is discussed in detail. The enhancement mechanism for the porous graphene‐like carbon electrode reveals that rationally designed meso‐ and macropores are very critical in porous electrode performance, which can network micropores for diffusion freeways, high conductivity, and high utilization. This work has universal significance in producing highly porous and conductive carbons from biomass including biowastes for various energy storage/conversion applications.

摘要 : MXenes refer to a family of 2D transition metal carbides/nitrides that are rich in chemistry. The first member of the family, Ti3C2Tx, was reported in 2011. Since then MXenes have opened up an exciting new field in 2D inorganic functional materials by virtue of their intrinsic electronic conductivity, superior hydrophilicity, rich surface chemistry and layered structure, as evidenced by the fact that the number of papers on MXenes has increased exponentially. The unique properties and ease of processing have positioned them as promising materials for a variety of applications including energy storage, especially for supercapacitors. In this review, we aim to summarize the current advances in MXene research on supercapacitors. We begin by reviewing various fabrication routes and their influence on the structure and surface chemistry of MXenes. The structure, properties, stability, and species of layered MXenes are then introduced. The focus then turns to the capacitive energy-storage mechanisms and the factors determining the electrochemical behavior and performance in supercapacitors. Besides, various types of MXene-based supercapacitors are summarized to highlight the significance of MXenes in constructing energy storage devices. Finally, challenges and prospects in this booming field are proposed to promote further development of MXenes in supercapacitors.

摘要 : SummaryThe electrochemical oxygen reduction reaction in acidic media offers an attractive route for direct hydrogen peroxide (H2O2) generation and on-site applications. Unfortunately there is still a lack of cost-effective electrocatalysts with high catalytic performance. Here, we theoretically designed and experimentally demonstrated that a cobalt single-atom catalyst (Co SAC) anchored in nitrogen-doped graphene, with optimized adsorption energy of the *OOH intermediate, exhibited a high H2O2 production rate, which even slightly outperformed the state-of-the-art noble-metal-based electrocatalysts. The kinetic current of H2O2 production over Co SAC could reach 1 mA/cmdisk2 at 0.6 V versus reversible hydrogen electrode in 0.1 M HClO4 with H2O2 faraday efficiency > 90%, and these performance measures could be sustained for 10 h without decay. Further kinetic analysis and operando X-ray absorption study combined with density functional theory (DFT) calculation demonstrated that the nitrogen-coordinated single Co atom was the active site and the reaction was rate-limited by the first electron transfer step.

摘要 : 2D nanomaterials with unique nanosheet structures, large surface areas, and extraordinary physicochemical properties have attracted tremendous interest. In the area of nanomedicine, research on graphene and its derivatives for diverse biomedical applications began as early as 2008. Since then, many other types of 2D nanomaterials, including transition metal dichalcogenides, transition metal carbides, nitrides and carbonitrides, black phosphorus nanosheets, layered double hydroxides, and metal–organic framework nanosheets, have been explored in the area of nanomedicine over the past decade. In particular, a large surface area makes 2D nanomaterials highly efficient drug delivery nanoplatforms. The unique optical and/or X‐ray attenuation properties of 2D nanomaterials can be harnessed for phototherapy or radiotherapy of cancer. Furthermore, by integrating 2D nanomaterials with other functional nanoparticles or utilizing their inherent physical properties, 2D nanomaterials may also be engineered as nanoprobes for multimodal imaging of tumors. 2D nanomaterials have shown substantial potential for cancer theranostics. Herein, the latest progress in the development of 2D nanomaterials for cancer theranostic applications is summarized. Current challenges and future perspectives of 2D nanomaterials applied in nanomedicine are also discussed.

摘要 : Ceria (CeO2) showed a poor activity for the selective catalytic reduction (SCR) of NO with NH3, while CeO2 showed an excellent SCR activity in the presence of SO2 at 300–500 °C. The promotion of SO2 on the SCR reaction over CeO2 was mainly due to the sulfation of CeO2. The SCR reaction over CeO2 and that over sulfated CeO2 both followed the Eley–Rideal mechanism (i.e. the reaction between activated NH3 with gaseous NO). Meanwhile, the catalytic oxidization of NH3 to NO could simultaneously happen during the SCR reaction, resulting in a drop of NOx conversion at high temperatures. The adsorption of NH3 on CeO2 was obviously promoted after the sulfation, resulting in an obvious promotion of the Eley–Rideal mechanism. Meanwhile, the adsorption sites for NH2 adsorption and the oxidization agents for NH2 oxidization on CeO2 were separated after the sulfation. Thus, the probability of the collision between NH2 and Ce4+ on sulfated CeO2 was much less than that on CeO2, resulting in an obvious repression of the catalytic oxidization of NH3 to NO. As a result, the SCR activity of sulfated CeO2 was much better than that over CeO2.

摘要 : Upland cotton is the most important natural-fiber crop. The genomic variation of diverse germplasms and alleles underpinning fiber quality and yield should be extensively explored. Here, we resequenced a core collection comprising 419 accessions with 6.55-fold coverage depth and identified approximately 3.66 million SNPs for evaluating the genomic variation. We performed phenotyping across 12 environments and conducted genome-wide association study of 13 fiber-related traits. 7,383 unique SNPs were significantly associated with these traits and were located within or near 4,820 genes; more associated loci were detected for fiber quality than fiber yield, and more fiber genes were detected in the D than the A subgenome. Several previously undescribed causal genes for days to flowering, fiber length, and fiber strength were identified. Phenotypic selection for these traits increased the frequency of elite alleles during domestication and breeding. These results provide targets for molecular selection and genetic manipulation in cotton improvement.

摘要 : The extraordinary properties of layered graphene and its successful applications in electronics, sensors, and energy devices have inspired and renewed interest in other two-dimensional (2D) layered materials. Particularly, a semiconducting analogue of graphene, molybdenum disulfide (MoS2), has attracted huge attention in the last few years. With efforts in exfoliation and synthetic techniques, atomically thin films of MoS2 (single- and few-layer) have been recently prepared and characterized. 2D MoS2 nanosheets have properties that are distinct and complementary to those of graphene, making it more appealing for various applications. Unlike graphene with an indirect bandgap, the direct bandgap of single-layer MoS2 results in better semiconductor behavior as well as photoluminescence, suggesting its great suitability for electronic and optoelectronic applications. Compared to their applications in energy storage and optoelectronic devices, the use of MoS2 nanosheets as a sensing platform, especially for biosensing, is still largely unexplored. Here, we present a review of the preparation of 2D atomically thin MoS2 nanosheets, with an emphasis on their use in various sensing applications.

摘要 : Abstract In medicine research, drug discovery aims to develop a drug to patients who will benefit from it and try to avoid some side effects. However, the tradition experiment is time consuming and expensive. In recent years, computational approaches provide many effective strategies to deal with this issue. In fact, the known associations between drugs and side-effects are less than unknown associations, thus it can be seen as an imbalance classification problem. Although several classification methods have been developed to predict drug-side effect associations, the performance of predictors could also be further improved. In this paper, we propose a novel predictor of drug-side effect associations. First, we construct multiple kernels from drug space and side-effect space, respectively. Then, these corresponding kernels are linear weighted by optimized Centered Kernel Alignment-based Multiple Kernel Learning (CKA-MKL) algorithm in two different spaces. At last, Kronecker Regularized Least Squares (Kronecker RLS) is employed to fuse drug kernel and side-effect kernel, further identify drug-side effect associations. Compared with many existing methods, our proposed approach achieves better results on three benchmark datasets of drug side-effect associations. The values of Area Under the Precision Recall curve (AUPR) are 0.672, 0.679 and 0.675 on Pauwels’s dataset, Mizutani’s dataset and Liu’s dataset, respectively. The AUPRs are improved by at least 0.012, 0.013 and 0.014 on three different datasets. Experimental results show that our method has outstanding performance among other excellent approaches on identifying drug-side effect associations.