Molybdenum disulfide (MoS2) has been extensively studied as a potential storage material for batteries. However, the electrochemical performance of MoS2 is far from ideal, and it exhibits severe activity fading resulting from its low electronic conductivity. The present work synthesizes nitrogen (N)-doped 1T MoS2 nanoflowers made of ultrathin nanosheets via the one-step hydrothermal sulfurization of a molybdenum-based metal–organic framework precursor. The resulting metallic phase shows improved conductivity and hydrophilicity, and characterization demonstrates that N doping effectively expands the interlayer spacing and increases the concentration of sulfur vacancies serving as defects. This material demonstrates high rate performance and good cycling stability when used as the cathode in an aqueous rechargeable zinc-ion battery (ARZIB). Its performance is superior to those of pure 1T MoS2 and 2H MoS2 synthesized with MoO3 as the molybdenum source. Ex situ X-ray photoelectron spectroscopy and X-ray diffraction analyses are performed to explore the reaction mechanism during charging and discharging of the N-doped 1T MoS2. A three-cell series ARZIB system containing this material is used to power five light-emitting diodes to confirm the possible practical applications of this technology.

Global models dominate historical documents on fire danger modelling. However, local variations may exist in the relationships between fire presence and fire-influencing factors. In this study, 50 fire danger models (10 global logistic models and 40 geographically weighted logistic models, i.e. local models), were developed to model daily fire danger in Heilongjiang province in north-east China and cross-validation was performed to evaluate the predictive performance of the various developed models. In modelling, multi-temporal spatial sampling and repeated random sub-sampling were applied to obtain 10 groups of training sub-samples and inner testing sub-samples. For each of the 10 groups of training sub-samples, principal component analysis, in which muticollinearity among variables can be removed, was used to create nine principal components that were then employed as covariates to develop one global logistic model and four geographically weighted logistic models. Compared to global models, all local models showed better model fitting, less spatial autocorrelation of residuals and more desirable modelling of fire presence. In particular, not only was local spatial variation in fire–environment relationships accounted for in the adaptive Gaussian geographically weighted logistic models, but spatial autocorrelation of residuals was significantly reduced to acceptable levels, indicating strong inferential performance.

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It is a highly desirable but still a challenging task to find a simple, fast and straightforward method to greatly improve the electrochemical properties of a Co3O4 electrode for pseudocapacitors.