The effect in the film thickness reducing mechanism of functional groups in porous carbon sulfuric acid supercapacitor

In this paper, the different types and number of functional groups in porous carbon–carbon pore channels are discussed in the thinning mechanism of ionic solvent thin films, which has a significant impact on the absorption of H2SO4 electrolyte based Electric Double Layer Capacitors (EDLC). By exploring the binding energy of –OH, –COOH, –SO3H, –NO2 and other four functional groups with sulfuric acid and hexahydrate sulfuric acid of porous carbon channel and hexahydrate sulfuric acid, it was found that –OH had no repulsive effect on the cathode of the battery, and –COOH, –SO3H, –NO2 and other functional groups had obvious repulsive effect on the cathode of EDLC with the increase of the functional groups number, that is, there was an effect of increasing the capacitance of EDLC by increasing the number of sulfide molecular. This will excavate the potential electrode material in the practical application

Interfaces Between Cathode and Electrolyte in Solid State Lithium Batteries: Challenges and Perspectives

Solid state lithium batteries are widely accepted as promising candidates for next generation of various energy storage devices with the probability to realize improved energy density and superior safety performances. However, the interface between electrode and solid electrolyte remain a key issue that hinders practical development of solid state lithium batteries. In this review, we specifically focus on the interface between solid electrolytes and prevailing cathodes. The basic principles of interface layer formation are summarized and three kinds of interface layers can be categorized. For typical solid state lithium batteries, a most common and daunting challenge is to achieve and sustain intimate solid-solid contact. Meanwhile, different specific issues occur on various types of solid electrolytes, depending on the intrinsic properties of adjacent solid components. Our discussion mostly involves following electrolytes, including solid polymer electrolyte, inorganic solid oxide and sulfide electrolytes as well as composite electrolytes. The effective strategies to overcome the interface instabilities are also summarized. In order to clarify interfacial behaviors fundamentally, advanced characterization techniques with time, and atomic-scale resolution are required to gain more insights from different perspectives. And recent progresses achieved from advanced characterization are also reviewed here. We highlight that the cooperative characterization of diverse advanced characterization techniques is necessary to gain the final clarification of interface behavior, and stress that the combination of diverse interfacial modification strategies is required to build up decent cathode-electrolyte interface for superior solid state lithium batteries

Incorporation and solidification mechanism of manganese doped cement clinker

Using municipal and industrial solid waste as a substitute raw material and fuel in cement rotary kiln co-processing is considered an economic and environmentally friendly alternative to the use of traditional fuels. However, the presence of heavy metals in solid waste is a growing concern in the cement rotary kiln co-processing technique. The solidification mechanism of heavy metals in cement clinker is directly related to their stabilization. Cement clinkers doped with manganese oxide (MnO2: 0.0%–5.0% wt%) were prepared in a laboratory to investigate the impacts of extrinsic Mn on cement clinker calcination. The insignificant changes in X-ray diffractometer patterns indicated that the fixed Mn had little influence on the mineral lattice structure. Raman spectra and X-ray photoelectron spectroscopy revealed the transformation of the silicate phase when the Mn dose was increased. Moreover, the satisfactory solidification ratio confirmed the incorporation of Mn in the cement clinker. These results provided evidence of the influence rule of Mn in the cement clinker calcination process. Furthermore, Raman spectroscopy showed great potential for the qualitative and semi-quantitative analysis of the cementitious materials derived from cement rotary kiln co-processing. These results will be important for the further development of green cement manufacturing technology

In situ Observation of Sodium Dendrite Growth and Concurrent Mechanical Property Measurements Using an Environmental Transmission Electron Microscopy–Atomic Force Microscopy (ETEM-AFM) Platform

Akin to Li, Na deposits in a dendritic form to cause a short circuit in Na metal batteries. However, the growth mechanisms and related mechanical properties of Na dendrites remain largely unknown. Here we report real-time characterizations of Na dendrite growth with concurrent mechanical property measurements using an environmental transmission electron microscopy–atomic force microscopy (ETEM-AFM) platform. In situ electrochemical plating produces Na deposits stabilized with a thin Na2CO3 surface layer (referred to as Na dendrites). These Na dendrites have characteristic dimensions of a few hundred nanometers and exhibit different morphologies, including nanorods, polyhedral nanocrystals, and nanospheres. In situ mechanical measurements show that the compressive and tensile strengths of Na dendrites with a Na2CO3 surface layer vary from 36 to >203 MPa, which are much larger than those of bulk Na. In situ growth of Na dendrites under the combined overpotential and mechanical confinement can generate high stress in these Na deposits. These results provide new baseline data on the electrochemical and mechanical behavior of Na dendrites, which have implications for the development of Na metal batteries toward practical energy-storage applications

In Situ TEM Studies on Electrochemical Mechanisms of Rechargeable Ion Battery Cathodes

Due to recent developments in secondary ion batteries for high‐energy‐density applications, a thorough understanding of the underlying mechanism of advanced cathode materials is of vital importance. In situ transmission electron microscopy (TEM) techniques capable of high spatial and temporal resolution in operando analysis of dynamic battery systems have attracted significant interest. However, the complex electrochemical reaction mechanisms of cathode materials have not been extensively investigated using in situ TEM due to technical difficulties in implementation. This perspective provides an overview on the recent development of in situ TEM for studying representative layered and olivine‐type cathode materials in secondary ion batteries; it further discusses the critical challenges and possible breakthroughs of this technique in deepening fundamental understandings in the near future

A Siamese Network Combining Multiscale Joint Supervision and Improved Consistency Regularization for Weakly Supervised Building Change Detection

Building change detection (BCD) from remote sensing images is essential in various practical applications. Recently, inspired by the achievement of deep learning in semantic segmentation (SS), methods that treat the BCD problem as a binary SS task using deep siamese networks have attracted increasing attention. However, similar to their counterparts, these approaches still face the challenge of collecting massive pixel-level annotations. To address this issue, this article presents a novel weakly supervised method for BCD from remote sensing images using image-level labels. The proposed method elaborately designs a siamese network to integrate a multiscale joint supervision (MJS) module and an improved consistency regularization (ICR) module into a unified framework to improve the so-called class activation maps (CAMs), which is vital for producing high-quality pseudomasks using image-level annotations to support pixel-level BCD. To be specific, the MSJ is used for generating refined multiscale CAMs to well capture changes at different scales corresponding to various buildings of varying sizes. The ICR contributes to improving the consistency of CAMs to highlight the boundaries of changed buildings. Extensive experiments on two public BCD datasets have demonstrated that the proposed method outperforms the current state-of-the-art approaches. Furthermore, the visual detection maps also indicate that the proposed method can achieve scale-adaptive change detection results and preserve object boundaries more effectively

Topic Modelling for Object-Based Unsupervised Classification of VHR Panchromatic Satellite Images Based on Multiscale Image Segmentation

Image segmentation is a key prerequisite for object-based classification. However, it is often difficult, or even impossible, to determine a unique optimal segmentation scale due to the fact that various geo-objects, and even an identical geo-object, present at multiple scales in very high resolution (VHR) satellite images. To address this problem, this paper presents a novel unsupervised object-based classification for VHR panchromatic satellite images using multiple segmentations via the latent Dirichlet allocation (LDA) model. Firstly, multiple segmentation maps of the original satellite image are produced by means of a common multiscale segmentation technique. Then, the LDA model is utilized to learn the grayscale histogram distribution for each geo-object and the mixture distribution of geo-objects within each segment. Thirdly, the histogram distribution of each segment is compared with that of each geo-object using the Kullback-Leibler (KL) divergence measure, which is weighted with a constraint specified by the mixture distribution of geo-objects. Each segment is allocated a geo-object category label with the minimum KL divergence. Finally, the final classification map is achieved by integrating the multiple classification results at different scales. Extensive experimental evaluations are designed to compare the performance of our method with those of some state-of-the-art methods for three different types of images. The experimental results over three different types of VHR panchromatic satellite images demonstrate the proposed method is able to achieve scale-adaptive classification results, and improve the ability to differentiate the geo-objects with spectral overlap, such as water and grass, and water and shadow, in terms of both spatial consistency and semantic consistency