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Copper-cobalt-nickel oxide nanowire arrays on copper foams as self-standing anode materials for lithium ion batteries
Get PDFNumerous scientists are in the pursuit of energy storage materials with high energy and high power density by assembly of electrochemically active materials into conductive scaffolds, owing to the emerging need for next-generation energy storage devices. In this architectures, the active materials bonded to the conductive scaffold can provide a robust and free-standing structure, which is crucial to the fabrication of materials with high gravimetric capacity. Thus, hierarchical copper-cobalt-nickel ternary oxide (CuCoNi-oxide) nanowire arrays grown from copper foam were successfully fabricated as free- standing anode materials for lithium ion batteries (LIBs). CuCoNi-oxide nanowire arrays could provide more active sites owing to the hyperbranched structure, leading to a better specific capacity of 1191 mAh/g, cycle performance of 73% retention in comparison to CuO nanowire structure, which exhibited a specific capacity of 1029 mAh/g and capacity retention of 43%, respectively. © 2021 Published by Elsevier B.V. on behalf of Chinese Chemical Society and Institute of Materia Medica, Chinese Academy of Medical Sciences
「後九七香港青年作家」小說中的城市與自然 : Skyscrapers and Shopping Malls: Hyper Density City Writing by Ho Lok, Hon Lai-chu, Chan Chi-wa
Get PDF自從西西《我城》(1975)出版以來，以香港城市空間爲想象起點的作品漸次出現，當中不少出於“後九七香港青年作家”之手。他們的創作風格多元，但自覺地以小說書寫1997年以後的香港城市空間，或從城市空間生發各種文學想象的取向，幾無二致。本文聚焦於三位“後九七香港青年作家”：可洛、陳志華，韓麗珠，以他們小說的城市空間想象為切入點，考察他們筆下的超密度城市空間。本文發掘小說呈現的香城市空間特色──首先是資本塑造而成的超密度，其次是全面商場化的空間運用。通過闡釋“後九七香港青年作家”構築的各種文字城市(“O城”“幻城”“H地”)，本文繼探討小說如何展現青年作家對香港的憂思，以及作家如何嘗試通過召喚想象力來重塑城市空間
Investigation of 20 August 2019 Catastrophic Debris Flows Triggered by Extreme Rainstorms Near Epicentre of Wenchuan Earthquake
Get PDFA strong earthquake could trigger a large number of co-seismic landslides and induce large amount of loose materials on steep slopes and in the gullies. Under strong rainfall conditions, these loose materials could induce devastating debris flows, which will endanger the resettled population and destroy the re-built infrastructures. From 19 to 20 August 2019, fourteen debris flows were triggered by extreme rainstorms near the epicentre of the Wenchuan Earthquake. Among the fourteen incidents, three of them produced debris flow dams, which changed the course of the Minjiang River and resulted in flooding at different parts of the reconstructed Miansi town. In addition, sixteen casualties, twenty two missing persons, and destruction of four main roads were reported. In this paper, one typical catchment, named as “Dengxi gully”, near the epicentre of the Wenchuan earthquake (Sichuan Province, China) was chosen as a case study for remote sensing analysis, field investigation of landslide evolution and debris flow development before and after the catastrophic events. The debris flow in the study area was initiated in four stages: (a) generation of a large amount of loose materials from the Wenchuan Earthquake; (b) run-off erosion from co-seismic landslide material on hilly slopes and repeated mobilizations in steep channels over the years; (c) development of high intensity localised rainfall events; (d) wash out of accumulated materials in gully by the flood. The study of “8.20 debris flows” can provide a benchmark for analysis of long-term evolution of debris flows in order to identify potential continuing hazards in the earthquake-affected areas and make proper engineering decisions
Smart-Object-Based Reasoning System for Indoor Acoustic Profiling of Elderly Inhabitants
No full textMany countries are facing significant challenges in relation to providing adequate care for their elderly citizens. The roots of these issues are manifold, but include changing demographics, changing behaviours, and a shortage of resources. As has been witnessed in the health sector and many others in society, technology has much to offer in terms of supporting people’s needs. This paper explores the potential for ambient intelligence to address this challenge by creating a system that is able to passively monitor the home environment, detecting abnormal situations which may indicate that the inhabitant needs help. There are many ways that this might be achieved, but in this paper, we will describe our investigation into an approach involving unobtrusively ’listening’ to sound patterns within the home, which classifies these as either normal daily activities, or abnormal situations. The experimental system we built was composed of an innovative combination of acoustic sensing, artificial intelligence (AI), and the Internet-of-Things (IoT), which we argue in the paper that it provides a cost-effective approach to alerting care providers when an elderly person in their charge needs help. The majority of the innovation in our work concerns the AI in which we employ Machine Learning to classify the sound profiles, analyse the data for abnormal events, and to make decisions for raising alerts with carers. A Neural Network classifier was used to train and identify the sound profiles associated with normal daily routines within a given person’s home, signalling departures from the daily routines that were then used as templates to measure deviations from normality, which were used to make weighted decisions regarding calling for assistance. A practical experimental system was then designed and deployed to evaluate the methods advocated by this research. The methodology involved gathering pre-design and post-design data from both a professionally run residential home and a domestic home. The pre-design data gathered the views on the system design from 11 members of the residential home, using survey questionnaires and focus groups. These data were used to inform the design of the experimental system, which was then deployed in a domestic home setting to gather post-design experimental data. The experimental results revealed that the system was able to detect 84% of abnormal events, and advocated several refinements which would improve the performance of the system. Thus, the research concludes that the system represents an important advancement to the state-of-the-art and, when taken together with the refinements, represents a line of research which has the potential to deliver significant improvements to care provision for the elderly
Electrospinning Synthesis of PET-AlN Composite Separators for Advanced Lithium-ion Batteries
Get PDFPlastics are indispensable materials in our society, widely adopted in food packaging, automotive, disposable medical equipment, and electronics, because of their favourable properties, including low density, high strength-to-weight ratio, high durability, ease of design and manufacture, and low cost. In this project, aluminium nitride/polyethylene terephthalate composite fibre-based non-woven membranes (AlN-PETs) were fabricated by electrospinning with dispersing different contents of aluminum nitride (0 to 5 %) in the recycled polyethylene terephthalate (PET) solutions and their electrochemical performance was evaluated for use as separators in lithium-ion batteries. The porosity of the AlN-PETs could reach 74.37 %, which was significantly higher than that of commercialized PP separator (Celgard® 2400) of 62.22 %. No apparent shrinkage and dimensional changes were observed for AlN-PETs with high contents of AlN at 100 oC for 120 minutes. Scanning electron microscope (SEM) observation, electrochemical impedance spectroscopy (EIS), and differential scanning calorimetry (DSC) were conducted in this study. The high porosity value resulted in the improved electrochemical performance for nanofiber separators. The AlN/PET separators prepared had high liquid electrolyte uptake, ionic conductivity, and thermal stability, which is comparable to the commercial microporous polyolefin membranes. The results obtained in this study will definitel
