is inevitable in Li-CO 2 batteries, [11,12] Li-CO 2 /O 2 batteries, [8,13] and even Li-air batteries. [14] Exception is that the discharge products could be different without the generation of Li 2 CO 3 under specific conditions including protected anodes and effective electrolytes. [15,16] Li 2 CO 3 decomposes to CO 2 when the potential is higher than 3.8 V versus Li/Li + . Notably, O 2 evolution is not detected, as is expected according to the decomposition reaction 2Li 2 CO 3 → 4Li + + 4 e -+ 2CO 2 + O 2 . Instead, superoxide radicals or "nascent oxygen" form during the self-decomposition of Li 2 CO 3 . [12,17] More accurate verification was performed through chemical probes, which qualitatively detected the existence of singlet oxygen ( 1 O 2 ). [18] Parasitic reactions of electrolytes and catalyst degradation were then induced by Li 2 CO 3 oxidation. [12,18] Therefore, efficient air cathodes are expected to change this situation.The introduction of metal nanoparticles could limit side reactions and promote the interaction between Li 2 CO 3 and C. [11,[19][20][21] Beyond this, metal-organic frameworks or surface modified carbon materials also brought unexpected electrochemical performance. [22,23] Therefore, catalysts play important roles in Li-CO 2 batteries. [24][25][26][27][28][29] As mentioned above, self-decomposition of Li 2 CO 3 induced a series of parasitic reactions, and further influenced the stability of catalysts during the operation of Li-CO 2 batteries. Only by clarifying the changes of catalysts in this process can we design more stable Li-CO 2 batteries. In previous reports, mono metal catalysts (Ru, Cu, Au, and Ni) exhibited outstanding activity toward Li-CO 2 batteries and revealed some changes in electrochemical processes. [19][20][21] Nevertheless, there exist shortcomings with mono metal catalysts from materials preparation to electrochemical processes. First, for example, the preparation for monodispersed Ru nanoparticles was often achieved under mild experimental conditions without the generation of stable crystal surfaces, further affecting catalytic activity in Li-CO 2 batteries. [21,30] Second, the incompatibility between the discharge products and mono metal nanomaterials might lead to severe agglomeration and dropping during long cycles. [20,31] In this work, we designed a composite of ruthenium-copper nanoparticles highly co-dispersed on graphene (Ru-Cu-G), and this composite cathode endows Li-CO 2 batteries with low overpotential and excellent cyclability through their synergistic Li-CO 2 batteries are attractive electrical energy storage devices; however, they still suffer from unsatisfactory electrochemical performance, and the kinetics of CO 2 reduction and evolution reactions must be improved significantly. Herein, a composite of ruthenium-copper nanoparticles highly co-dispersed on graphene (Ru-Cu-G) as efficient air cathodes for Li-CO 2 batteries is designed. The Li-CO 2 batteries with Ru-Cu-G cathodes exhibit ultra-low overpotential and can be operated for 100 cycles with ...

An important function of a water distribution system (WDS) is to supply drinking water to each demand point using a pipe network that has minimal impact on the surroundings. To produce a reliable WDS, planning usually requires a significant amount of geo-spatial information. Current planning practices for pipeline systems, which gather geographic information based on maps, are time-consuming and cumbersome. With the rapid developments in computer and information technology, it is necessary to propose a new WDS planning method that enhances the current planning practices and facilitates the decision-making process. The proposed method allows project information in building information modeling (BIM) to be incorporated into a geographic information system (GIS) model, using semantic mapping to incorporate WDS project data and geo-spatial information to facilitate the WDS planning process. Moreover, a 3D visualization model of the proposed WDS project and its surroundings is provided. In addition, topological rules are set to identify any conflicts between the WDS project and its surroundings. A real WDS project was used to validate the method. The proposed method can help project participants better understand the WDS project and its surroundings and identify any errors in the planning process, thus improving sustainable development.

Highway infrastructure plays an important role in assuring the proper function of the nation’s transportation. Highway alignment is an essential part of the highway planning and design phase, which has significant effects on the surroundings. Identifying optimal highway routes while using traditional methods requires significant time, cost, and effort, since it requires a comprehensive assessment of multiple factors, such as cost and environmental impacts. This study proposes an approach for managing highway alignment in the context of a larger landscape that integrates building information modelling (BIM) and geographic information system (GIS) capabilities. To support this integration, semantic web technologies are used to integrate data on a semantic level. Moreover, the approach also uses genetic algorithms (GAs) for optimizing highway alignments. A fully automated model is developed that enables data interoperability between BIM and GIS systems and also allows for data exchange between the integration model and the optimization algorithm. The model enables the full exploitation of features of the project and its surroundings for highway alignment planning. The proposed model is also applied to a real highway project to validate its effectiveness. The visualization model of the highway project and its surroundings provides a realistic three-dimensional image that produces a comprehensive virtual environment, where the project could be effectively planned and designed. That can help to reduce design errors and miscommunication, which, in turn, reduces project risks. Moreover, geological and geographical analyses help to identify geohazards and environmentally sensitive regions. The proposed model facilitates highway alignment planning by providing a cross-disciplinary approach to close the gap between the infrastructural and geotechnical planning processes.