Far-Infrared Therapy Based on Graphene Ameliorates High-Fat Diet-Induced Anxiety-Like Behavior in Obese Mice via Alleviating Intestinal Barrier Damage and Neuroinflammation.

The consumption of a high-fat diet (HFD) has been implicated in the etiology of obesity and various neuropsychiatric disturbances, including anxiety and depression. Compelling evidence suggests that far-infrared ray (FIR) possesses beneficial effects on emotional disorders. However, the efficacy of FIR therapy in addressing HFD-induced anxiety and the underlying mechanisms remain to be elucidated. Here, we postulate that FIR emitted from a graphene-based therapeutic device may mitigate HFD-induced anxiety behaviors. The graphene-FIR modify the gut microbiota in HFD-mice, particularly by an enriched abundance of beneficial bacteria Clostridiaceae and Erysipelotrichaceae, coupled with a diminution of harmful bacteria Lachnospiraceae, Anaerovoracaceae, Holdemania and Marvinbryantia. Graphene-FIR also improved intestinal barrier function, as evidenced by the augmented expression of the tight junction protein occludin and G protein-coupled receptor 43 (GPR43). In serum level, we observed the decreased free fatty acids (FFA), lipopolysaccharides (LPS), diamine oxidase (DAO) and D-lactate, and increased the glucagon-like peptide-2 (GLP-2) levels in graphene-FIR mice. Simultaneously, inflammatory cytokines IL-6, IL-1ß, and TNF-α manifested a decrease subsequent to graphene-FIR treatment in both peripheral and central system. Notably, graphene-FIR inhibited over expression of astrocytes and microglia. We further noticed that the elevated the BDNF and decreased TLR4 and NF-κB expression in graphene-FIR group. Overall, our study reveals that graphene-FIR rescued HFD-induced anxiety via improving the intestine permeability and the integrity of blood-brain barrier, and reduced inflammatory response by down regulating TLR4/NF-κB inflammatory pathway.

Visible-Light-Driven Oxidation of Benzene to Phenol with O2 over Photoinduced Oxygen-Vacancy-Rich WO3.

Direct photocatalytic conversion of benzene to phenol with O2 is a green alternative to the traditional synthesis. The key is to find an effective photocatalyst to do the trick. Defect engineering of semiconductors with oxygen vacancies (OVs) is an emerging strategy for catalyst fabrication. OVs can trap electrons to promote charge separation and serving as adsorption sites for O2 activation. However, randomly distribution of OVs on the semiconductor surface often results in mismatching the charge carrier dynamics under irradiation, thus failing to fulfill the unique advantages of OVs for photoredox functions. Herein, we demonstrate that abundant OVs can be facilely generated and precisely located adjacent to the reductive sites on reducible oxide semiconductors such as tungsten oxide (WO3) via a simple photochemistry strategy. Such photoinduced OVs are well suited for photocatalytic benzene oxidation with O2 as they readily capture photogenerated electrons from the reductive sites of WO3 to activate adsorbed O2. 18O-labeling experiments further confirm that the OVs also facilitate the integration of oxygen atoms from O2 into phenol, revealing in detail the pathway for photocatalytic benzene hydroxylation. This study demonstrates that the photochemistry approach is an appealing strategy for the synthesis of high-performance OVs-rich photocatalysts for solar-induced chemical conversion.

Incorporation of Pd Single-Atom Sites in Perovskite with an Excellent Selectivity toward Photocatalytic Semihydrogenation of Alkynes.

Semihydrogenation is a crucial industrial process. Noble metals such as Pd have been extensively studied in semihydrogenation reactions, owing to their unique catalytic activity toward hydrogen activation. However, the overhydrogenation of alkenes to alkanes often happens due to the rather strong adsorption of alkenes on Pd active phases. Herein, we demonstrate that the incorporation of Pd active phases as single-atom sites in perovskite lattices such as SrTiO3 can greatly alternate the electronic structure and coordination environment of Pd active phases to facilitate the desorption of alkenes rather than further hydrogenation. Furthermore, the incorporated Pd sites can be well stabilized without sintering by a strong host-guest interaction with SrTiO3 during the activation of H species in hydrogenation reactions. As a result, the Pd incorporated SrTiO3 (Pd-SrTiO3) exhibits an excellent time-independent selectivity (>99.9 %) and robust durability for the photocatalytic semihydrogenation of phenylacetylene to styrene. This strategy based on incorporation of active phases in perovskite lattices will have broad implications in the development of high-performance photocatalysts for selective hydrogenation reactions.

Enhanced Metal-Semiconductor Interaction for Photocatalytic Hydrogen-Evolution Reaction.

The selective immobilization of noble metals right at the place where photogenerated electrons migrate through the photodeposition approach is a unique strategy to load cocatalysts on semiconductors for solar hydrogen production. However, a poor metal-semiconductor interaction is often formed, which not only hinders the interfacial charge transfer, but also results in the easy aggregation and shedding of cocatalysts during photocatalytic reactions. Herein, it is demonstrated that the photodeposited ultrafine metals, such as nanosized Au, can be well stabilized on TiO2 nanocrystallines without sintering by employing a sacrificial carbon coating annealing strategy to strengthen the metal-support interaction. Benefiting from the improved interfacial contact between Au and TiO2 for fast charge transfer and the well-preserved size-dependent catalytic behavior of Au nanoparticles toward hydrogen evolution reaction, the annealed Au/TiO2 exhibits a significant enhanced activity toward photocatalytic H2 production with good durability.

Titania-Samarium-Manganese Composite Oxide for the Low-Temperature Selective Catalytic Reduction of NO with NH3.

A novel Ti-doped Sm-Mn mixed oxide (TiSmMnOx) was first designed for the selective catalytic reduction (SCR) of NOx with NH3 at a low temperature. The TiSmMnOx catalyst exhibited a superior catalytic performance, in which NOx conversion higher than 80% and N2 selectivity above 90% could be achieved in a wide-operating temperature window (60-225 °C). Specially, the catalyst also showed high durability against the large space velocity and excellent SO2/H2O resistance. Ti incorporation can efficiently inhibit MnOx crystallization and tune the MnOx phase during calcination at a high temperature. Subsequently, a high specific surface area as well as an increased amount of acid sites on the TiSmMnOx catalysts were produced. Further, the reducibility of the Sm-doped MnOx catalyst was modulated, facilitating NO oxidation and inhibiting NH3 nonselective oxidation. Consequently, a superior SCR activity was achieved at a low temperature and the operating temperature window of the TiSmMnOx catalyst was significantly widened. These findings may provide new insights into the reasonable design and development of the new non-vanadium catalysts with a high NH3-SCR activity for industrial application.

Mapping Tobacco Fields Using UAV RGB Images.

Tobacco planting information is an important part of tobacco production management. Unmanned aerial vehicle (UAV) remote sensing systems have become a popular topic worldwide because they are mobile, rapid and economic. In this paper, an automatic identification method for tobacco fields based on UAV images is developed by combining supervised classifications with image morphological operations, and this method was used in the Yunnan Province, which is the top province for tobacco planting in China. The results show that the produce accuracy, user accuracy, and overall accuracy of tobacco field identification using the method proposed in this paper are 92.59%, 96.61% and 95.93%, respectively. The method proposed in this paper has the advantages of automation, flow process, high accuracy and easy operation, but the ground sampling distance (GSD) of the UAV image has an effect on the accuracy of the proposed method. When the image GSD was reduced to 1 m, the overall accuracy decreased by approximately 10%. To solve this problem, we further introduced the convolution method into the proposed method, which can ensure the recognition accuracy of tobacco field is above 90% when GSD is less than or equal to 1 m. Some other potential improvements of methods for mapping tobacco fields were also discussed in this paper.

Capturing Maize Stand Heterogeneity Across Yield-Stability Zones Using Unmanned Aerial Vehicles (UAV).

Despite the new equipment capabilities, uneven crop stands are still common occurrences in crop fields, mainly due to spatial heterogeneity in soil conditions, seedling mortality due to herbivore predation and disease, or human error. Non-uniform plant stands may reduce grain yield in crops like maize. Thus, detecting signs of variability in crop stand density early in the season provides critical information for management decisions and crop yield forecasts. Processing techniques applied on images captured by unmanned aerial vehicles (UAVs) has been used successfully to identify crop rows and estimate stand density and, most recently, to estimate plant-to-plant interval distance. Here, we further test and apply an image processing algorithm on UAV images collected from yield-stability zones in a commercial crop field. Our objective was to implement the algorithm to compare variation of plant-spacing intervals to test whether yield differences within these zones are related to differences in crop stand characteristics. Our analysis indicates that the algorithm can be reliably used to estimate plant counts (precision >95% and recall >97%) and plant distance interval (R2 ~0.9 and relative error <10%). Analysis of the collected data indicated that plant spacing variability differences were small among plots with large yield differences, suggesting that it was not a major cause of yield variability across zones with distinct yield history. This analysis provides an example of how plant-detection algorithms can be applied to improve the understanding of patterns of spatial and temporal yield variability.

Total Oxidation of Propane over a Ru/CeO2 Catalyst at Low Temperature.

Ruthenium (Ru) nanoparticles (∼3 nm) with mass loading ranging from 1.5 to 3.2 wt % are supported on a reducible substrate, cerium dioxide (CeO2, the resultant sample is called Ru/CeO2), for application in the catalytic combustion of propane. Because of the unique electronic configuration of CeO2, a strong metal-support interaction is generated between the Ru nanoparticles and CeO2 to stabilize Ru nanoparticles for oxidation reactions well. In addition, the CeO2 host with high oxygen storage capacity can provide an abundance of active oxygen for redox reactions and thus greatly increases the rates of oxidation reactions or even modifies the redox steps. As a result of such advantages, a remarkably high performance in the total oxidation of propane at low temperature is achieved on Ru/CeO2. This work exemplifies a promising strategy for developing robust supported catalysts for short-chain volatile organic compound removal.

Fibers with Hyper-Crosslinked Functional Porous Frameworks.

The incorporation of robust porous frameworks into polymer fibers with handleable morphologies and flexible chemical compositions exhibits significant advantages for device fabrication in a wide range of applications. However, the soft linear polymeric chains of the fibers make the generation of nanopores extremely challenging. Herein, a facile synthetic strategy based on a combination of functional monomer grafting and hyper-crosslinking technology is developed for the porous engineering of polymeric fibers. In this methodology, the nanoporous framework originating from the hyper-crosslinking of aromatic monomers is covalently grafted onto fibers, which is beneficial to retaining their unique fiber morphology and to preserving their excellent mechanical properties. Moreover, this promising protocol can be further extended to the porous functionalization of polymeric matrices with diverse morphologies for target-specific applications.

Bioinspired cobalt cubanes with tunable redox potentials for photocatalytic water oxidation and CO2 reduction.

The development of efficient, robust and earth-abundant catalysts for photocatalytic conversions has been the Achilles' heel of solar energy utilization. Here, we report on a chemical approach based on ligand designed architectures to fabricate unique structural molecular catalysts coupled with appropriate light harvesters (e.g., carbon nitride and Ru(bpy)32+) for photoredox reactions. The "Co4O4" cubane complex Co4O4(CO2Me)4(RNC5H4)4 (R = CN, Br, H, Me, OMe), serves as a molecular catalyst for the efficient and stable photocatalytic water oxidation and CO2 reduction. A comprehensive structure-function analysis emerged herein, highlights the regulation of electronic characteristics for a molecular catalyst by selective ligand modification. This work demonstrates a modulation method for fabricating effective, stable and earth-abundant molecular catalysts, which might facilitate further innovation in the function-led design and synthesis of cubane clusters for photoredox reactions.

Crystal Structural Effect of AuCu Alloy Nanoparticles on Catalytic CO Oxidation.

Controlling the physical and chemical properties of alloy nanoparticles (NPs) is an important approach to optimize NP catalysis. Unlike other tuning knobs, such as size, shape, and composition, crystal structure has received limited attention and not been well understood for its role in catalysis. This deficiency is mainly due to the difficulty in synthesis and fine-tuning of the NPs' crystal structure. Here, Exemplifying by AuCu alloy NPs with face centered cubic (fcc) and face centered tetragonal (fct) structure, we demonstrate a remarkable difference in phase segregation and catalytic performance depending on the crystal structure. During the thermal treatment in air, the Cu component in fcc-AuCu alloy NPs segregates more easily onto the alloy surface as compared to that in fct-AuCu alloy NPs. As a result, after annealing at 250 °C in air for 1 h, the fcc- and fct-AuCu alloy NPs are phase transferred into Au/CuO and AuCu/CuO core/shell structures, respectively. More importantly, this variation in heterostructures introduces a significant difference in CO adsorption on two catalysts, leading to a largely enhanced catalytic activity of AuCu/CuO NP catalyst for CO oxidation. The same concept can be extended to other alloy NPs, making it possible to fine-tune NP catalysis for many different chemical reactions.

Mesoporous Carbon Materials with Functional Compositions.

Since the 1990s, there has been rapidly expanding development of solid materials with mesoporous structure, of which mesoporous carbons are an important family. Toward the design of functional materials, mesoporous carbons with various compositions have been prepared for specific uses, such as catalysts, adsorbents, and electrode materials. Some of those novel materials indeed show promising performance in several fields, such as nitrogen-doped mesoporous carbon for oxygen reduction reactions in fuel cells and mesoporous carbon nitride for photocatalysis. This Minireview summarizes recent advances in the design, synthesis, characterization, and application of mesoporous carbons with functional compositions and briefly discusses next-generation mesoporous carbons.

Support Vector Data Description Model to Map Specific Land Cover with Optimal Parameters Determined from a Window-Based Validation Set.

This paper developed an approach, the window-based validation set for support vector data description (WVS-SVDD), to determine optimal parameters for support vector data description (SVDD) model to map specific land cover by integrating training and window-based validation sets. Compared to the conventional approach where the validation set included target and outlier pixels selected visually and randomly, the validation set derived from WVS-SVDD constructed a tightened hypersphere because of the compact constraint by the outlier pixels which were located neighboring to the target class in the spectral feature space. The overall accuracies for wheat and bare land achieved were as high as 89.25% and 83.65%, respectively. However, target class was underestimated because the validation set covers only a small fraction of the heterogeneous spectra of the target class. The different window sizes were then tested to acquire more wheat pixels for validation set. The results showed that classification accuracy increased with the increasing window size and the overall accuracies were higher than 88% at all window size scales. Moreover, WVS-SVDD showed much less sensitivity to the untrained classes than the multi-class support vector machine (SVM) method. Therefore, the developed method showed its merits using the optimal parameters, tradeoff coefficient (C) and kernel width (s), in mapping homogeneous specific land cover.

Surfactant-Assisted Stabilization of Au Colloids on Solids for Heterogeneous Catalysis.

The stabilization of surfactant-assisted synthesized colloidal noble metal nanoparticles (NPs, such as Au NPs) on solids is a promising strategy for preparing supported nanocatalysts for heterogeneous catalysis because of their uniform particle sizes, controllable shapes, and tunable compositions. However, surfactant removal to obtain clean surfaces for catalysis through traditional approaches (such as solvent extraction and thermal decomposition) can easily induce the sintering of NPs, greatly hampering their use in synthesis of novel catalysts. Such unwanted surfactants have now been utilized to stabilize NPs on solids by a simple yet efficient thermal annealing strategy. After being annealed in N2 flow, the surface-bound surfactants are carbonized in situ as sacrificial architectures that form a conformal coating on NPs and assist in creating an enhanced metal-support interaction between NPs and substrate, thus slowing down the Ostwald ripening process during post-oxidative calcination to remove surface covers.

Electrostatic-Assisted Liquefaction of Porous Carbons.

Porous liquids are a newly developed porous material that combine unique fluidity with permanent porosity, which exhibit promising functionalities for a variety of applications. However, the apparent incompatibility between fluidity and permanent porosity makes the stabilization of porous nanoparticle with still empty pores in the dense liquid phase a significant challenging. Herein, by exploiting the electrostatic interaction between carbon networks and polymerized ionic liquids, we demonstrate that carbon-based porous nanoarchitectures can be well stabilized in liquids to afford permanent porosity, and thus opens up a new approach to prepare porous carbon liquids. Furthermore, we hope this facile synthesis strategy can be widely applicated to fabricate other types of porous liquids, such as those (e.g., carbon nitride, boron nitride, metal-organic frameworks, covalent organic frameworks etc.) also having the electrostatic interaction with polymerized ionic liquids, evidently advancing the development and understanding of porous liquids.

A Sacrificial Coating Strategy Toward Enhancement of Metal-Support Interaction for Ultrastable Au Nanocatalysts.

Supported gold (Au) nanocatalysts hold great promise for heterogeneous catalysis; however, their practical application is greatly hampered by poor thermodynamic stability. Herein, a general synthetic strategy is reported where discrete metal nanoparticles are made resistant to sintering, preserving their catalytic activities in high-temperature oxidation processes. Taking advantage of the unique coating chemistry of dopamine, sacrificial carbon layers are constructed on the material surface, stabilizing the supported catalyst. Upon annealing at high temperature under an inert atmosphere, the interactions between support and metal nanoparticle are dramatically enhanced, while the sacrificial carbon layers can be subsequently removed through oxidative calcination in air. Owing to the improved metal-support contact and strengthened electronic interactions, the resulting Au nanocatalysts are resistant to sintering and exhibit excellent durability for catalytic combustion of propylene at elevated temperatures. Moreover, the facile synthetic strategy can be extended to the stabilization of other supported catalysts on a broad range of supports, providing a general approach to enhancing the thermal stability and sintering resistance of supported nanocatalysts.

An Improved STARFM with Help of an Unmixing-Based Method to Generate High Spatial and Temporal Resolution Remote Sensing Data in Complex Heterogeneous Regions.

Remote sensing technology plays an important role in monitoring rapid changes of the Earth's surface. However, sensors that can simultaneously provide satellite images with both high temporal and spatial resolution haven't been designed yet. This paper proposes an improved spatial and temporal adaptive reflectance fusion model (STARFM) with the help of an Unmixing-based method (USTARFM) to generate the high spatial and temporal data needed for the study of heterogeneous areas. The results showed that the USTARFM had higher accuracy than STARFM methods in two aspects of analysis: individual bands and of heterogeneity analysis. Taking the predicted NIR band as an example, the correlation coefficients (r) for the USTARFM, STARFM and unmixing methods were 0.96, 0.95, 0.90, respectively (p-value < 0.001); Root Mean Square Error (RMSE) values were 0.0245, 0.0300, 0.0401, respectively; and ERGAS values were 0.5416, 0.6507, 0.8737, respectively. The USTARM showed consistently higher performance than STARM when the degree of heterogeneity ranged from 2 to 10, highlighting that the use of this method provides the capacity to solve the data fusion problems faced when using STARFM. Additionally, the USTARFM method could help researchers achieve better performance than STARFM at a smaller window size from its heterogeneous land surface quantitative representation.

Superior Conductive Solid-like Electrolytes: Nanoconfining Liquids within the Hollow Structures.

The growth and proliferation of lithium (Li) dendrites during cell recharge are currently unavoidable, which seriously hinders the development and application of rechargeable Li metal batteries. Solid electrolytes with robust mechanical modulus are regarded as a promising approach to overcome the dendrite problems. However, their room-temperature ionic conductivities are usually too low to reach the level required for normal battery operation. Here, a class of novel solid electrolytes with liquid-like room-temperature ionic conductivities (>1 mS cm(-1)) has been successfully synthesized by taking advantage of the unique nanoarchitectures of hollow silica (HS) spheres to confine liquid electrolytes in hollow space to afford high conductivities (2.5 mS cm(-1)). In a symmetric lithium/lithium cell, the solid-like electrolytes demonstrate a robust performance against the Li dendrite problem, preventing the cell from short circuiting at current densities ranging from 0.16 to 0.32 mA cm(-2) over an extended period of time. Moreover, the high flexibility and compatibility of HS nanoarchitectures, in principle, enables broad tunability to choose desired liquids for the fabrication of other kinds of solid-like electrolytes, such as those containing Na(+), Mg(2+), or Al(3+) as conductive media, providing a useful alternative strategy for the development of next generation rechargeable batteries.

Solar Water Splitting at λ=600†nm: A Step Closer to Sustainable Hydrogen Production.

Overall water splitting with a semiconductor photocatalyst under visible-light irradiation is considered as a "dream reaction" in chemistry. The development of a 600 nm photocatalyst for solar water splitting highlighted here is not only an important milestone towards sustainable hydrogen production, but also a new starting point for artificial photosynthesis. STH=solar-to-hydrogen energy conversion efficiency.

Sol processing of conjugated carbon nitride powders for thin-film fabrication.

The chemical protonation of graphitic carbon nitride (CN) solids with strong oxidizing acids, for example HNO3, is demonstrated as an efficient pathway for the sol processing of a stable CN colloidal suspension, which can be translated into thin films by dip/disperse-coating techniques. The unique features of CN colloids, such as the polymeric matrix and the reversible hydrogen bonding, result in the thin-film electrodes derived from the sol solution exhibiting a high mechanical stability with improved conductivity for charge transport, and thus show a remarkably enhanced photo-electrochemical performance. The polymer system can in principle be broadly tuned by hybridization with desired functionalities, thus paving the way for the application of CN for specific tasks, as exemplified here by coupling with carbon nanotubes.