Search

Energy is an important component of urban carbon emissions. Assessing the peak of urban energy carbon is a necessary means to implement the national “double carbon” strategy. For this reason, this paper proposes an energy carbon peaking assessment method based on Mann-Kendall trend test for carbon emission of urban energy. By constructing a carbon monitoring system covering elements such as energy carbon emissions, clean energy generation, and transportation electric energy substitution, the total energy carbon emissions of the city are calculated by combining historical data. In view of the seasonality and randomness of energy carbon emissions, the Mann-Kendall trend test was used to establish a model for determining urban energy carbon peaking and to measure regional carbon emissions in different periods. Taking an administrative region in Shanghai as an example, the peak status of energy carbon in this region is judged from the perspective of year and quarter. The results show that based on the annual data, the region has reached its peak energy carbon in 2020. Based on quarterly data, peak energy carbon has been achieved in summer and autumn, while spring and winter are still in plateau. The methods proposed in this paper can be used to assess the carbon peak status in the city, and provide a reference for examining the carbon peak process in other provinces and cities.

Existing calculation methods of carbon emission cannot well meet the needs of gradual refinement and real-time of carbon emission regions. In order to ensure the real-time and accuracy of carbon emissions responsibility allocation, a real-time calculation method of carbon emissions in urban regions is proposed. The improved K-means clustering algorithm is used to cluster and combine the operating periods and operating scenarios of the urban area energy load,so as to obtain the typical carbon emission characteristics. The regional unit electricity carbon emission is proposed as a carbon emission indicator, the operating period and scenario are classified, and the unit electricity carbon emission and the total carbon emission of urban regions for each cluster are calculated. The proposed algorithm is verified based on part of the historical data of energy consumption in the energy brain of a certain region in eastern China. The results show that the clustering method and carbon emission indicators can effectively calculate the total carbon emission of urban regions in real-time.

Er3+‐doped fluoride glass and fiber have been widely used in multiple fields such as mid‐infrared laser, visible laser, and amplifier. However, there is no unified conclusion on the thermal and optical properties with respect to varying concentrations of Er3+ doping. Furthermore, this is a paucity of systematic guidance on the preparation of Er3+‐doped fluoride glass and fiber. In this study, fluorozirconate fiberglass with Er3+ doping is systematically examined. Additionally, a preliminary explanation of the evolutionary behavior of glass devitrification, thermal properties, and fluorescence properties is provided. Energy transition models were built for 1.5 and 2.7 µm emissions in Er3+‐doped fluorozirconate at room temperature. Moreover, a suitable doping concentration is proposed based on the evolutionary behavior of thermal and optical properties. In this study, guidance on appropriate Er3+ doping concentration levels in fluorozirconate glass is provided and potential applications are explored. [ABSTRACT FROM AUTHOR]

Aqueous ammonium ion batteries (AIBs) have emerged as a promising next‐generation rechargeable battery due to their safety, sustainability, abundant resources, and superior electrochemical performance. However, organic anode materials, particularly polyimide anode materials, suffer from low specific capacity caused by limited active sites. Herein, the study has developed a micro‐granular‐structured π‐conjugated enhanced polyimide (PTPD) as the anode material for AIBs. The large π‐conjugated enhanced structure enables long‐range electron delocalization, decreased bandgap, and reduced spatial steric hindrance, resulting in increased active sites capable of storing NH4+ ions. PTPD exhibits reversible oxidation and reduction reaction in (NH4)2SO4 solution, delivering a high specific capacity of 206.67 mAh g−1 at a current density of 0.5 A g−1, exceptional rate capability, and excellent cycling stability with a capacity retention of 74.28% after 2500 cycles at a current density of 10 A g−1. Furthermore, theoretical simulations and materials analysis demonstrate that PTPD undergoes enol‐keto transformation of carbonyl groups, effectively capturing NH4+ to store charges. This study provides an effective strategy for designing polymer‐based AIBs anodes with high specific capacity and cycling stability. [ABSTRACT FROM AUTHOR]

In the context of integrating sports and medicine domains, the urgent resolution of elderly health supervision requires effective data clustering algorithms. This paper introduces a novel higher-order hybrid clustering algorithm that combines density values and the particle swarm optimization (PSO) algorithm. Initially, the traditional PSO algorithm is enhanced by integrating the Global Evolution Dynamic Model (GEDM) into the Distribution Estimation Algorithm (EDA), constructing a weighted covariance matrix-based GEDM. This adapted PSO algorithm dynamically selects between the Global Evolution Dynamic Model and the standard PSO algorithm to update population information, significantly enhancing convergence speed while mitigating the risk of local optima entrapment. Subsequently, the higher-order hybrid clustering algorithm is formulated based on the density value and the refined PSO algorithm. The PSO clustering algorithm is adopted in the initial clustering phase, culminating in class clusters after a finite number of iterations. These clusters then undergo the application of the density peak search algorithm to identify candidate centroids. The final centroids are determined through a fusion of the initial class clusters and the identified candidate centroids. Results showcase remarkable improvements: achieving 99.13%, 82.22%, and 99.22% for F-measure, recall, and precision on dataset S1, and 75.22%, 64.0%, and 64.4% on dataset CMC. Notably, the proposed algorithm yields a 75.22%, 64.4%, and 64.6% rate on dataset S, significantly surpassing the comparative schemes' performance. Moreover, employing the text vector representation of the LDA topic vector model underscores the efficacy of the higher-order hybrid clustering algorithm in efficiently clustering text information. This innovative approach facilitates swift and accurate clustering of elderly health data from the perspective of sports and medicine integration. It enables the identification of patterns and regularities within the data, facilitating the formulation of personalized health management strategies and addressing latent health concerns among the elderly population. [ABSTRACT FROM AUTHOR]

Organic thin‐film transistors (OTFTs) as a vital component among transistors have shown great potential in smart sensing, flexible displays, and bionics due to their flexibility, biocompatibility and customizable chemical structures. Even though linear conjugated polymer semiconductors are common for constructing channel materials of OTFTs, advanced materials with high charge carrier mobility, tunable band structure, robust stability, and clear structure‐property relationship are indispensable for propelling the evolution of OTFTs. Two‐dimensional conjugated polymers (2DCPs), featured with conjugated lattice, tailorable skeletons, and functional porous structures, match aforementioned criteria closely. In this review, we firstly introduce the synthesis of 2DCP thin films, focusing on their characteristics compatible with the channels of OTFTs. Subsequently, the physics and operating mechanisms of OTFTs and the applications of 2DCPs in OTFTs are summarized in detail. Finally, the outlook and perspective in the field of OTFTs using 2DCPs are provided as well. [ABSTRACT FROM AUTHOR]

Surface-enhanced Raman scattering (SERS) spectroscopy is a powerful technology in trace analysis. However, the wide applications of SERS in practice are limited by the expensive substrate materials and the complicated preparation processes. Here we report a simple and economical galvanic-replacement-assisted synthesis route to prepare Ag nanoparticles on Cu(0) foil (nanoAg@Cu), which can be directly used as SERS substrate. The fabrication process is fast (ca. 10 min) and easily scaled up to centimeters or even larger. In addition, the morphology of the nanoAg@Cu (with Ag particles size from 30 nm to 160 nm) can be adjusted by various additives (e.g., amino-containing ligands). Finally, we show that the as-prepared nanoAg@Cu can be used for SERS characterization of two-dimensional polymers, and ca. 298 times relative enhancement of Raman intensity is achieved. This work offers a simple and economical strategy for the scalable fabrication of silver-based SERS substrate in thin film analysis. [ABSTRACT FROM AUTHOR]