74 resultados para Battery anodes

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Scanning probe microscopy methods have been used to electrodeposit and cycle micron-scale Li anodes deposited electrochemically under nanofabricated Au current collectors. An average Li volume of 5 x 10(8) nm(3) was deposited and cycled with 100% coulombic efficiency for similar to 160 cycles. Integrated charge/discharge values agree with before/after topography, as well as in situ dilatometry, suggesting this is a reliable method to study solid-state electrochemical processes. In this work we illustrate the possibility to deposit highly cyclable nanometer thick Li electrodes by mature SPM and nanofab techniques which can pave the way for inexpensive nanoscale battery arrays. 

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Copper-manganese spinel containing anodes were synthesized by a facile sol-gel method and evaluated in lithium-ion battery applications for the first time. The synergistic effects between copper-manganese and the aqueous binder (sodium carboxymethyl cellulose) provided a high specific capacity and excellent cycling performance. It was found that the specific capacity of the copper-manganese spinel remained at 608 mAh g−1 after 100 cycles at a current density of 200 mA g−1. Furthermore, a relatively high reversible capacity of 278 mAh g−1 could be obtained at a current density of 2000 mA g−1, indicating a good rate capability. These studies suggest that copper-manganese spinel is a promising material for lithium-ion battery applications due to a combination of good electrochemical performance and low cost.

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Sympathetic and parasympathetic divisions of the autonomic nervous system constantly control the heart (sympathetic and parasympathetic divisions) and blood vessels (predominantly the sympathetic division) to maintain appropriate blood pressure and organ blood flow over sometimes widely varying conditions. This can be adversely affected by pathological conditions that can damage one or both branches of autonomic control. The set of teaching laboratory activities outlined here uses various interventions, namely, 1) the heart rate response to deep breathing, 2) the heart rate response to a Valsalva maneuver, 3) the heart rate response to standing, and 4) the blood pressure response to standing, that cause fairly predictable disturbances in cardiovascular parameters in normal circumstances, which serve to demonstrate the dynamic control of the cardiovascular system by autonomic nerves. These tests are also used clinically to help investigate potential damage to this control.

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PtRuO/Ti anodes with a varying Pt:Ru ratio were prepared by thermal deposition of a PtRuO catalyst layer onto a Ti mesh for the direct methanol fuel cell (DMFC). The morphology and structure of the catalyst layers were analyzed by SEM, EDX, and XRD. The catalyst coating layers became porous with increase of the Ru content, and showed oxide and alloy characteristics. The relative activities of the PtRuO/Ti electrodes were assessed and compared using half-cell tests and single DMFC experiments. The results showed that these electrodes were very active for the methanol oxidation and that the optimum Ru surface coverage was ca. 38% for a DMFC operating at 20-60 °C. © 2006 Elsevier B.V. All rights reserved.

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PtRu/Ti anodes with varying Pt : Ru ratio were prepared by electrodeposition of a thin PtRu catalyst layer onto Ti mesh for a direct methanol fuel cell (DMFC). The morphology and structure of the catalyst layers were analyzed by SEM, EDX and XRD. The catalyst coating layer shows an alloy character. The relative activities of the PtRu/Ti electrodes were assessed and compared in half cell and single DMFC experiments. The results show that these electrodes are very active for the methanol oxidation and that the optimum Ru surface coverage was ca. 9 at.% for DMFC operating at 20°C and 11 at.% at 60°C. The PtRu/Ti anode shows a performance comparable to that of the conventional carbon-based anode in a DMFC operating with 0.25 M or 0.5 M methanol solution and atmosphere oxygen gas at 90°C. © the Owner Societies 2006.

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A novel anode structure based on Ti mesh for the direct methanol fuel cell (DMFC) has been prepared by thermal deposition of ~5 µm PtRuO2 catalyst layer on ~50 µm Ti mesh. The preparation procedures and the main characteristics of the anode were studied by half-cell testing, scanning electron microscopy analysis, energy-dispersive X-ray measurement, and single-cell testing. The optimum calcination temperature is 450°C, calcination time is 90- 120 min, PtRuO2 catalyst loading is 5.0 mg cm-2, Pt precursor concentration range of solution is 0.14- 0.4 M, and solution aging time is 1 day. The performances of the anodes prepared using the solution kept within 20 days showed no significant difference. When it was used in DMFC feed with low-concentration methanol solution at 90°C, this new anode shows better performance than that of the conventional anode, because its thin hydrophilic structure is a benefit to the transport of methanol and carbon dioxide. However, due to its opening structure, when higher concentration methanol was employed, the performance of the cell with new anode became worse. © 2006 The Electrochemical Society. All rights reserved.

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An anode structure based on Ti mesh has been developed for the direct methanol fuel cell (DMFC). This new anode was prepared by electrochemical deposition of a ~ 3 µ m PtRu catalyst layer on ~ 50 µ m Ti mesh. It has a thinner structure compared to that of a porous carbon-based conventional anode. The Ti mesh anode shows a performance comparable to, and exceeding that, of the conventional anode in a DMFC operating with 0.25 or 0.5 M methanol solution and atmosphere oxygen at 90 C. However, it shows a lower performance of the cell when higher concentrations of methanol was employed. This may be attributed to its thin and open structure, which could facilitate the transport of methanol from the flow field to the anode catalyst layer and carbon dioxide in the opposite direction. © 2006 International Association for Hydrogen Energy.

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A lack of suitable high-performance cathode materials has become the major barrier to their applications in future advanced communication equipment and electric vehicle power systems. In this paper, we have developed a layer-by-layer self-assembly approach for fabricating a novel sandwich nanoarchitecture of multilayered LiV3O8 nanoparticle/graphene nanosheet (M-nLVO/GN) hybrid electrodes for potential use in high performance lithium ion batteries by using a porous Ni foam as a substrate. The prepared sandwich nanoarchitecture of M-nLVO/GN hybrid electrodes exhibited high performance as a cathode material for lithium-ion batteries, such as high reversible specific capacity (235 mA h g-1 at a current density of 0.3 A g-1), high coulombic efficiency (over 98%), fast rate capability (up to a current density of 10 A g-1), and superior capacity retention during cycling (90% capacity retention with a current density of 0.3 A g-1 after 300 cycles). Very significantly, this novel insight into the design and synthesis of sandwich nanoarchitecture would extend their application to various electrochemical energy storage devices, such as fuel cells and supercapacitors.

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Ni-substituted Sr2Fe1.5-xNixMo0.5O6-δ (SFNM) materials have been investigated as anode catalysts for intermediate temperature solid oxide fuel cells. Reduced samples (x = 0.05 and 0.1) maintained the initial perovskite structure after reduction in H2, while metallic nickel particles were detected on the grain surface for x = 0.2 and 0.3 using transmission electron microscopy. Temperature programmed reduction results indicate that the stable temperature for SFNM samples under reduction conditions decreases with Ni content. In addition, X-ray photoelectron spectroscopy analysis suggests that the incorporation of Ni affects the conductivity of SFNM through changing the ratios of Fe3+/Fe2+ and Mo6+/Mo5+. Sr2Fe1.4Ni0.1Mo0.5O6-δ shows the highest electrical conductivity of 20.6 S cm-1 at 800 °C in H2. The performance of this anode was further tested with electrolyte-supported cells, giving 380 mW cm-2 at 750 °C in H2, hence demonstrating that Ni doping in the B-site is beneficial for Sr2Fe1.5Mo0.5O6-δ anode performance. 

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Electric vehicles (EVs) and hybrid electric vehicles (HEVs) are rapidly gaining popularity as a means of de-carbonization in the transport sector in tackling sustainable energy supply and environment pollution problems. To build a proper battery model is essential in predicting battery behaviour under various operating conditions for avoiding unsafe battery operations and developing proper controlling algorithms and maintenance strategies. This paper presents a comprehensive review of battery modelling methods. In particular, the mechanism and characteristics of Li-ion batteries are presented, and different modelling methods are discussed. Considering that equivalent electric circuit models (EECMs) are the most widely used, a detailed analysis of the modelling procedure is presented.

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A new battery modelling method is presented based on the simulation error minimization criterion rather than the conventional prediction error criterion. A new integrated optimization method to optimize the model parameters is proposed. This new method is validated on a set of Li ion battery test data, and the results confirm the advantages of the proposed method in terms of the model generalization performance and long-term prediction accuracy.

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Li-ion batteries have been widely used in the EVs, and the battery thermal management is a key but challenging part of the battery management system. For EV batteries, only the battery surface temperature can be measured in real-time. However, it is the battery internal temperature that directly affects the battery performance, and large temperature difference may exist between surface and internal temperatures, especially in high power demand applications. In this paper, an online battery internal temperature estimation method is proposed based on a novel simplified thermoelectric model. The battery thermal behaviour is first described by a simplified thermal model, and battery electrical behaviour by an electric model. Then, these two models are interrelated to capture the interactions between battery thermal and electrical behaviours, thus offer a comprehensive description of the battery behaviour that is useful for battery management. Finally, based on the developed model, the battery internal temperature is estimated using an extended Kalman filter. The experimental results confirm the efficacy of the proposed method, and it can be used for online internal temperature estimation which is a key indicator for better real-time battery thermal management.

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This paper reports on the solubility and diffusivity of dissolved oxygen in a series of ionic liquids (ILs) based on the bis{(trifluoromethyl)sulfonyl}imide anion with a range of related alkyl and ether functionalised cyclic alkylammonium cations. Cyclic voltammetry has been used to observe the reduction of oxygen in ILs at a microdisk electrode and chronoamperometric measurements have then been applied to simultaneously determine both the concentration and the diffusion coefficient of oxygen in the different ILs. The viscosity of the ILs and the calculated molar volume and free volume is also reported. It is found that, within this class of ILs, the oxygen diffusivity generally increases with decreasing viscosity of the neat IL. An inverse relationship between oxygen solubility and IL free volume is reported for the two IL families implying oxygen is not simply occupying the available empty space. In addition, it is reported that the introduction of ether-group into the IL cation structure promotes the diffusivity of dissolved oxygen but reduces the solubility of the gas.

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Smartphones have undergone a remarkable evolution over the last few years, from simple calling devices to full fledged computing devices where multiple services and applications run concurrently. Unfortunately, battery capacity increases at much slower pace, resulting as a main bottleneck for Internet connected smartphones. Several software-based techniques have been proposed in the literature for improving the battery life. Most common techniques include data compression, packet aggregation or batch scheduling, offloading partial computations to cloud, switching OFF interfaces (e.g., WiFi or 3G/4G) periodically for short intervals etc. However, there has been no focus on eliminating the energy waste of background applications that extensively utilize smartphone resources such as CPU, memory, GPS, WiFi, 3G/4G data connection etc. In this paper, we propose an Application State Proxy (ASP) that suppresses/stops the applications on smartphones and maintains their presence on any other network device. The applications are resumed/restarted on smartphones only in case of any event, such as a new message arrival. In this paper, we present the key requirements for the ASP service and different possible architectural designs. In short, the ASP concept can significantly improve the battery life of smartphones, by reducing to maximum extent the usage of its resources due to background applications.

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Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.