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Efficiently obtaining tobacco planting area is significant for rationally allocating tobacco resources and realizing the balance between supply and demand. However, tobacco fields are characterized by fragmentation in hilly areas, which brings various challenges to extracting the tobacco planting area. A 16-square-kilometre tobacco planting region in Xuancheng City, Anhui Province, China, was selected as the study area in this paper. First, the single-temporal full-feature sets (STFFS), a time-series full-feature set (TFFS) and a time-series optimal-feature set (TOFS) were constructed from multi-period Sentinel-2 images, respectively. Then, we applied Random Forest (RF), Support Vector Machine (SVM), Neural Network Classification (NNC) and Maximum Likelihood Classification (MLC) to classify the feature sets and compare the classification accuracy. The experimental results demonstrate that: (1) The best growth stage of tobacco remote sensing recognition is the mulching film phase of the spherical plant stage (ST1 period). (2) The classification accuracy indicates that TOFS outperforms the STFFS. (3) TOFS can still maintain the same classification accuracy as TFFS with fewer feature dimensions. (4) The RF classifier has great stability and robustness, which achieve an overall accuracy (OA) of 90.65%, 93.50%, and 93.09% based on the feature sets of ST1 period, TFFS, and TOFS, respectively. [ABSTRACT FROM AUTHOR]

Polyvinylidene fluoride (PVDF) binder is an important part of lithium-ion batteries, where a slight structural difference can significantly affect the capacitance and service life of batteries. Herein, ATR-FTIR technology and a rheological test were employed to investigate the crystal forms and rheological behavior of three different PVDF binders, respectively. The results showed that PVDF-CG has low molecular weight, high α/β phase ratio, strong adhesive action and stripping strength, which are closely associated with the durability and electrochemical properties of LiNi0.5Co0.2Mn0.3O2 single-crystal (denoted as SC) materials. The SCs with PVDF-CG binder exhibited a capacity retention of 93.44% after 100 cycles at a rate of 1C and high rate performance (92 mA h g−1 at 10C), which was higher than that of PVDF-HSV900 (90.31%, 86 mA h g−1 at 10C) and PVDF-Solvay 5130 (90.52%, 72 mA h g−1 at 10C). The XPS and HR-TEM analysis showed that the cycled SCs bonded with HSV900 and Solvay 5130 as binders suffered from severe interface structural degradation, while SCs with PVDF-CG maintained a well-layered structure and the formation of a surface NiO-like rock-salt phase was greatly inhibited. This work demonstrated that the capacity, rate capability and interface stability of SC cathodes are significantly affected by the mode and strength of the adhesion and stripping strength of PVDF binders, which are closely associated with α/β phase ratios, providing a useful reference for the development of efficient binders. [ABSTRACT FROM AUTHOR]

Porous carbon supported FeNx catalysts have become one of the candidates to replace platinum group metal (PGM) catalysts for the oxygen reduction reaction (ORR) due to their high intrinsic reactivity and substantial accessible active sites. However, FeNx sites suffer from insufficient long-term stability due to migration and aggregation of isolated Fe atoms or decomposition of FeNx active moieties arising from undesired Fenton reactions. Herein, an effective core–shell structured Fe–N–C@NC catalyst composed of ultra-thin porous conductive carbon shells and carbon supported-FeNx active cores was prepared by constructing a polyvinylpyrrolidone (PVP) molecular adsorbed Fe-doped ZIF-8 precursor followed by high temperature pyrolysis. Applied to the ORR, the Fe–N–C@NC catalyst displayed a much higher half-wave potential (0.876 V) than that of 20% Pt/C (0.854 V) and significantly increased durability in an alkaline electrolyte. In practical application, the Fe–N–C@NC-assembled Zn–air battery can reach a peak power density of 170.8 mW cm−2, which is superior to that of 20% Pt/C (163.1 mW cm−2) and that of the pristine Fe–N–C (130.7 mW cm−2). More impressively, no apparent decay was observed after 150 h of charge and discharge testing. The XRD and XPS results after cycling revealed that the outer ultrathin carbon shells of Fe–N–C@NC could prevent the loss of the inner FeNx active sites, maintaining stable and efficient ORR activity. [ABSTRACT FROM AUTHOR]

As an independent characteristic of electromagnetic radiation, the polarization of light is sensitive to the scattering and absorption characteristics of the mineral particles. The combination of polarization and infrared absorption spectroscopy is conducive to rapidly and accurately detecting the SiO2 content of metallurgical sandstone deposits. In this study, the 8–14 μm polarized infrared absorption spectra and the grade of the sandstone ore samples were used to analyse the spectral characteristics of the sandstone powder samples. Principal component analysis (PCA) and the successive projection algorithm (SPA) were used to reduce the dimension of the original data, first-order derivative, reciprocal logarithm, and multivariate scattering correction (MSC) data. Then, generalized regression neural network (GRNN), partial least squares regression (PLSR), and convolutional neural network (CNN) were employed to establish a hyperspectral prediction model of SiO2 grade. The results show that the quantitative model by the PCA-CNN algorithm has the better prediction precision for the reciprocal logarithm data, with a coefficient of determination (R2), root mean square error (RMSE), and ratio of performance to interquartile range (RPIQ) of 0.907, 0.023, and 5.11, respectively. This method indicates that the polarized infrared absorption spectra and the PCA-CNN model can provide a more robust and significant spectral interpretation than single infrared spectra, and it is expected to be applied to any high-purity quartz deposit type for in situ and rapid analysis. [ABSTRACT FROM AUTHOR]

As the second most abundant greenhouse gas after carbon dioxide (CO2), methane not only plays an important role in global and regional photochemical reactions, but also has an important impact on energy balance and climate change. To explore the long-term trends and spatiotemporal variation of methane concentration over China, we verified the accuracy of the column-averaged, dry air-mixing ratio of CH4 (abbreviated as XCH4 hereafter) merged by SCIAMACHY and GOSAT products, utilizing the data of six surface observation stations in China and the surrounding areas. The root mean square error (RMSE) was mostly less than 2.5%, and the correlation coefficients (r) were 0.77, 0.84, 0.66, 0.42, 0.62 and 0.75. Furthermore, we analyzed the temporal and spatial variation patterns of the XCH4 concentration over China from 2003 to 2020. The results showed that the XCH4 concentration had an increasing trend over China from 2003 to 2020; the average growth rate was 6.64 ppb·a−1, and the value range of the increase rate was from 4.66 ppb·a−1 to 8.46 ppb·a−1. The lowest XCH4 concentration was located over Tibet (1764.03 ppb), and the high values were located in the Sichuan Basin, Central China (Hunan, Hubei, and Henan) and East China (Anhui and Jiangxi) (1825–1845 ppb). The XCH4 concentration was higher in autumn and summer, low in winter and spring, and had obvious seasonal variations. Human factors such as population density, GDP and energy consumption have a significant impact on the XCH4 concentration over China. [ABSTRACT FROM AUTHOR]

Small metal clusters have received increasing attention due to their attractive and superior performance in electrocatalytic energy conversion. However, the design and synthesis of well-dispersed metal clusters is a great challenge owing to their ease of aggregation. Here, we develop a biomass in situ conversion strategy to synthesize Fe single atomic sites (Fe–N4) combined with ultra-small Fe2O3 nanoclusters embedded in N, S codoped porous carbons (FeSA/FeONC/NSC) for the oxygen reduction reaction (ORR). The resultant FeSA/FeONC/NSC exhibits a high half-wave potential (E1/2 = 0.86 V vs. RHE) and an outstanding kinetic current density at 0.80 V (Jk = 32.15 mA cm−2), which even surpasses those of commercial Pt/C (E1/2 = 0.85 V, Jk = 16.5 mA cm−2). Atomic level dispersed Fe–N4 sites integrated with Fe2O3 clusters embedded in N, S-mediated carbon are mainly responsible for the excellent ORR activity. More importantly, the assembled Zn–air battery can output a prominent power density of 179.0 mW cm−2 and energy density of 837.4 W h kg−1 along with robust stability, outperforming the commercial Pt/C and most non-platinum catalysts. This work opens up an avenue for biomass in situ conversion into non-precious metal electrocatalysts for energy conversion and storage technologies. [ABSTRACT FROM AUTHOR]

Developing highly efficient non-precious metal bifunctional catalysts towards both the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is vital for pushing the development of Zn–air batteries. Here, we propose a nitrogen source-mediated strategy to synthesize active-N-rich defective carbon nanotube encapsulated Fe/Fe3C nanoparticles (denoted as Fe-N-OCNT) via one-step pyrolysis of OCNTs, Fe-Phen and an additional small molecule nitrogen source. N-source-regulated N configuration and steric hindrance effect of Fe-Phen coordination structures is proved to be a key factor affecting the electrocatalytic activity towards ORR and OER. The resulting Fe-N-OCNT exhibits a high half-wave potential of 0.86 V (vs. RHE) for ORR, and a low overpotential of 0.353 V for OER as well as a reversible oxygen electrode index of 0.723 V, superior to those of most recently reported advanced bifunctional catalysts. Multiple active component Fe/Fe3C cores strongly synergized with active N-rich carbon layers are responsible for the superior bifunctional electrocatalytic activity by forming a favorable interfacial electron interaction. Impressively, the assembled Zn–air batteries with the Fe-N-OCNT catalyst as the bifunctional air electrode deliver excellent charging–discharging performance, high power density (128.8 mW cm−2), energy density (779.3 W h kg−1) and long lifespan, demonstrating great potential for practical implementation. [ABSTRACT FROM AUTHOR]

Carbon encapsulated transition metal catalysts receive extensive attention in electrochemical catalytic oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) due to the unique structure and highly adjustable electronic configuration. Herein, we synthesized 3D porous Active-N-rich graphene-like carbon layer-encapsulated Fe/Fe3C (Fe@NCG) via pyrolysis of a mixture of solvent-free assembled Fe-chitosan chelates and additional small molecule nitrogen source urea, wherein space-confinement effect of chelates suppressed agglomeration of Fe 3 + ions and small molecule nitrogen source facilitated regulation of N configurations. The optimized catalyst Fe@NCG shows remarkable ORR/OER bifunctional catalytic activity with a half-wave potential of 0.86 V for ORR and a moderate potential difference of 0.85 V in alkaline medium. Comparative studies revealed that Active-N-rich carbon layer and inner well-dispersed Fe/Fe3C nanoparticles and the favorable interface structures between them were responsible for high catalytic activity. Excitingly, the assembled zinc-air battery with Fe@NCG catalysts exhibits a high open-circuit potential (1.45 V), extremely high peak power density (204.50 mW/cm 2) and energy density (814.70 Wh kg − 1 ) as well as robust charge–discharge durability, surpassing those of noble metal catalyst. This proposed simple and universal strategy can also be extended to synthesize carbon encapsulated other transition metal electrocatalysts. Fe@NCG was prepared by pyrolyzing solvent-free-formed Fe-chitosan chelates and additional small molecule nitrogen source urea. The formed catalyst exhibits bifunctional catalytic performance toward ORR and OER in alkaline medium, higher power density and superior charge–discharge durability in zinc–air battery. [ABSTRACT FROM AUTHOR]