Monolayer molybdenum disulfide (MoS 2 ) has attracted tremendous attention due to its promising applications in high-performance field-effect transistors, phototransistors, spintronic devices and nonlinear optics. The enhanced photoluminescence effect in monolayer MoS 2 was discovered and, as a strong tool, was employed for strain and defect analysis in MoS 2 . Recently, large-size monolayer MoS 2 has been produced by chemical vapour deposition, but has not yet been fully explored. Here we systematically characterize chemical vapour deposition-grown MoS 2 by photoluminescence spectroscopy and mapping and demonstrate non-uniform strain in single-crystalline monolayer MoS 2 and strain-induced bandgap engineering. We also evaluate the effective strain transferred from polymer substrates to MoS 2 by three-dimensional finite element analysis. Furthermore, our work demonstrates that photoluminescence mapping can be used as a non-contact approach for quick identification of grain boundaries in MoS 2 .

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for CO 2 sequestration and environmental remediation, the utilization of CO 2 in metal (Li)-CO 2 batteries with a high theoretical specific capacity has recently attracted considerable attention. [3,4] Apart from the CO 2 sequestration, Li-CO 2 batteries offer an advantage for energy conversion and storage, particularly for exploration of the planet Mars with an atmosphere consisting of 96% CO 2 . [3] The driving force for energy conversion and storage in Li-CO 2 batteries is the reversible redox reaction between a lithium anode and CO 2 gas cathode to form/decompose Li 2 CO 3 during the discharge/charge processes. The sluggish CO 2 reduction and evolution reactions that take place at the air cathode often impede the kinetics of Li-CO 2 batteries, leading to a high voltage (>4.5 V vs Li/Li + ) for decomposing the discharge product (Li 2 CO 3 ). [5][6][7] Under such a high anodic potential, the electrolyte oxidation limits the energy efficiency and cycling life of the Li-CO 2 batteries. [5][6][7] Therefore, efficient A highly efficient cathode catalyst for rechargeable Li-CO 2 batteries is successfully synthesized by implanting single iron atoms into 3D porous carbon architectures, consisting of interconnected N,S-codoped holey graphene (HG) sheets. The unique porous 3D hierarchical architecture of the catalyst with a large surface area and sufficient space within the interconnected HG framework can not only facilitate electron transport and CO 2 /Li + diffusion, but also allow for a high uptake of Li 2 CO 3 to ensure a high capacity. Consequently, the resultant rechargeable Li-CO 2 batteries exhibit a low potential gap of ≈1.17 V at 100 mA g −1 and can be repeatedly charged and discharged for over 200 cycles with a cut-off capacity of 1000 mAh g −1 at a high current density of 1 A g −1 . Density functional theory calculations are performed and the observed appealing catalytic performance is correlated with the hierarchical structure of the carbon catalyst. This work provides an effective approach to the development of highly efficient cathode catalysts for metal-CO 2 batteries and beyond.The ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/adma.201907436.The overuse of fossil fuel has caused a rapid increase in CO 2 emissions and the associated severe environmental issues, including global warming, polar ice melting, sea level rising, rain acidification, and species extinction. [1,2] As a new strategy

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energy such as wind and solar energy has attracted enormous interest for its significant roles in mitigating CO 2 emissions and reducing dependence on petrochemicals. [1,2] At the heart of the CO 2 conversion technology, electrocatalysts are needed to promote a critical reaction, CO 2 reduction reaction (CO 2 RR) that determines the efficiency and selectivity. To date, the electrocatalysts have confronted severe bottlenecks issue: poor selectivity about various accessory products in CO 2 conversion process, and loss of efficiency toward competing hydrogen evolution. [3] The former involves associated multielectron transfer process and is difficult to accurately control the reaction process by external conditions, [4] while the latter is mainly due to the fact that the equilibrium potentials for most of the CO 2 RR are very close to hydrogen evolution reaction (HER) toward undesirable side-products in aqueous electrolytes, which degrades the electrocatalytic performance during the CO 2 RR process. [5,6] Therefore, CO 2 RR is much more complex than other energy-related electrochemical reactions such as oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), and it is still a great challenge to design and synthesize electrocatalytic materials with higher product selectivity and catalytic activity for CO 2 RR.Among the electrocatalysts including metals oxides and metal-doped carbon materials, single-atom catalysts (SACs) represent an exciting class of catalysts with monodispersed metal catalytic centers and have emerged as the frontier science in both homogeneous and heterogeneous catalysis, including CO 2 conversion. [7][8][9][10] This type of catalysts contains M-N-C moiety with single atoms and is common in building metalorganic frameworks (MOFs), [11] covalent organic frameworks (COFs) [12] with transition metal macrocyclic clusters, such as porphyrin, phthalocyanine, and tetraazannulene, as well as metal-doped carbon materials [13] (e.g., graphene, carbon nanotubes, fullerene). In nature, the biomolecules, like chlorophyll (Mg-porphyrin) in leaves, and iron porphyrins in cytochrome c oxidase in blood cells, have similar structures as SACs, with special ability in photosynthesis and transforming CO 2 from cells with high efficiency and selectivity. [14] Through the selection of appropriate motifs, the construction principles of Direct conversion of CO 2 into carbon-neutral fuels or industrial chemicals holds a great promise for renewable energy storage and mitigation of greenhouse gas emission. However, experimentally finding an electrocatalyst for specific final products with high efficiency and high selectivity poses serious challenges due to multiple electron transfer, complicated intermediates, and numerous reaction pathways in electrocatalytic CO 2 reduction. Here, an intrinsic descriptor that correlates the catalytic activity with the topological, bonding, and electronic structures of catalytic centers on M-N-C based single-atom catalysts is discovered. The "volcano"-shaped relationships betwee...

Recently, the recognition task of spontaneous facial micro-expressions has attracted much attention with its various real-world applications. Plenty of handcrafted or learned features have been employed for a variety of classifiers and achieved promising performances for recognizing micro-expressions. However, the micro-expression recognition is still challenging due to the subtle spatiotemporal changes of micro-expressions. To exploit the merits of deep learning, we propose a novel deep recurrent convolutional networks based micro-expression recognition approach, capturing the spatial-temporal deformations of micro-expression sequence. Specifically, the proposed deep model is constituted of several recurrent convolutional layers for extracting visual features and a classificatory layer for recognition. It is optimized by an end-to-end manner and obviates manual feature design. To handle sequential data, we exploit two types of extending the connectivity of convolutional networks across temporal domain, in which the spatiotemporal deformations are modeled in views of facial appearance and geometry separately. Besides, to overcome the shortcomings of limited and imbalanced training samples, temporal data augmentation strategies as well as a balanced loss are jointly used for our deep network. By performing the experiments on three spontaneous microexpression datasets, we verify the effectiveness of our proposed micro-expression recognition approach compared to the state-ofthe-art methods.

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Highly efficient electrocatalysts derived from metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) for oxygen reduction reaction (ORR) have been developed. However, the subsequent pyrolysis is often needed owing to their poor intrinsic electrical conductivity, leading to undesirable structure changes and destruction of the original fine structure. Now, hybrid electrocatalysts were formed by self-assembling pristine covalent organic polymer (COP) with reduced graphene oxide (rGO). The electrical conductivity of the hybridized COP/rGO materials is increased by more than seven orders of magnitude (from 3.06×10 to 2.56×10 S m ) compared with pure COPs. The ORR activities of the hybrid are enhanced significantly by the synergetic effect between highly active COP and highly conductive rGO. This COP/rGO hybrid catalyst exhibited a remarkable positive half-wave (150 mV).