batterydata/paper-abstracts huggingface dataset:
The ZnO/SnO2 composites are synthesized by a simple hydrothermal route and proposed as a novel anodic material for Zn/Ni secondary cells. The structures and morphologies of the samples are characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM). The composite materials are composed of homogeneous grain-like nanoparticles, and a prismatic microstructure is formed between ZnO and SnO2. The electrochemical performances of composite material electrodes are comparatively analyzed through cyclic voltammetry, tafel plot and galvanostatic charge–discharge tests. The tests results show that the ZnO/SnO2 composite exhibit the best electrochemical performances as anode material for Zn/Ni secondary batteries.
Robust battery management system is critical for a safe and reliable electric vehicle operation. One of the most important functions of the battery management system is to accurately estimate the battery state using minimal on-board instrumentation. This paper presents a recursive Bayesian filtering framework for on-board battery state estimation by assimilating measurables like cell voltage, current and temperature with physics-based reduced order model (ROM) predictions. The paper proposes an improved Particle filtering algorithm for implementation of the framework, and compares its performance against the unscented Kalman filter. Functionality of the proposed framework is demonstrated for a commercial NCA/C cell state estimation at different operating conditions including constant current discharge at room and low temperatures, hybrid power pulse characterization (HPPC) and urban driving schedule (UDDS) protocols. In addition to accurate voltage prediction, the electrochemical nature of ROM enables drawing of physical insights into the cell behavior. Advantages of using electrode concentrations over conventional Coulomb counting for accessible capacity estimation are discussed. In addition to the mean state estimation, the framework also provides estimation of the associated confidence bounds that are used to establish predictive capability of the proposed framework.
Vehicle-to-grid and Grid-to-vehicle strategies are often cited as promising to mitigate the intermittency of renewable energy on electric power grids. However, their impact on the vehicle battery degradation has not been investigated in detail. The aim of this work is to understand the impact of bidirectional charging on commercial Li-ion cells used in electric vehicles today. Results show that additional cycling to discharge vehicle batteries to the power grid, even at constant power, is detrimental to cell performance. This additional use of the battery packs could shorten the lifetime for vehicle use to less than five years. By contrast, the impact of delaying the charge in order to reduce the impact on the power grid is found to be negligible at room temperature, but could be significant in warmer climates.
The formation and the evolution of lithium-containing species on the surface of grains of a layered 4V material such as LiNi1/2Mn1/2O2 along the electrochemical cycling have been followed using 7Li MAS NMR, electrochemical impedance spectroscopy (EIS) and XPS. Materials displaying different specific surface areas and stored in different atmospheres have been investigated in order to study the influence of the surface/volume ratio and the influence of the initial surface state, respectively. It is shown that the presence of an initial interphase of Li2CO3 influences the electrochemical behavior of the electrode, emphasizing the importance of the history of the electrode prior cycling. 7Li MAS NMR experiments performed upon cycling indicate the formation of interphase species in reduction and their partial removal in oxidation, indicating the dynamic character of the interphase upon cycling. Combined NMR, EIS and XPS experiments show the strong influence of the electrode/electrolyte interphase evolution on the electrochemical performance. Such results lead us to draw conclusions on the optimal storage conditions of layered 4V materials for Li-ion batteries such as LiNi1/2Mn1/2O2.
This paper investigates the new trends in the field of “pervasive” or “ubiquitous” computing in logistics. Over the past two decades, research challenges in pervasive computing have evolved following the rapid progress of information and communication technology. Researchers are working to create an “Internet of Things” that globally interconnects smart devices and sensor networks. Technologies such as wireless communication, ubiquitous sensors, and passive or semi-passive RFID, are essential to monitor the transport chain. “Pervasive adaptation” is a new research challenge that has been recently introduced to describe system's ability to autonomously recognize the situation and adapt to situational changes. For example, it is expected that intelligent parcels that can observe and evaluate current environmental conditions including traffic information, velocity, new orders, temperature, or storage conditions, and decide adaptations such as changing transport route or destination and swapping vehicle. In order modern ubiquitous computing devices to become fully functional they need to overcome compatibility and security problems; these issues as well as potential solutions are explored in this paper. On the other hand, as new technology such as Ultra High Frequency RFID becomes more mature, it is launching into ubiquitous status in commerce and society.
This study investigates the concentration effect of chitosan on the formation of iron oxide composites and their electrochemical performance as anode materials in Li–ion batteries. The molecular bridging effect of chitosan chains induces the clustered aggregation of citrate–capped Fe3O4 (C–Fe3O4) through the electrostatic interactions between carboxylate groups of C–Fe3O4 and amine groups of chitosan. The thermal calcination of chitosan–linked Fe3O4 leads to carbon–coated Fe2O3 (Fe2O3@carbon) with the mesopore range of porosity (20–30nm). The mesoporous Fe2O3@carbon exhibits an improved electrochemical performance as anode materials in Li–ion batteries. The capacity retention of Fe2O3@carbon is twice that of bare Fe2O3 after the 50th cycle at 0.1C. During the charge–discharge process, the Fe2O3@carbon (3ml of chitosan) exhibits the highest retention capacity among as–prepared samples, whereas Fe2O3@carbon (1ml of chitosan) exhibits the lowest retention capacity owing to the weakly cross–linked iron oxides. The improved performance of Fe2O3@carbon as anode materials is mainly attributed to the optimal cross–linking effect and structural integrity of mesoporous composite which is beneficial for the effective transport of electrolytes and/or Li–ons, suggesting a useful guideline for preparing porous electrode materials using metal oxide particles.
Evolution of bromine gas in the positive half cell of the Generation 2 (G2) vanadium bromide (V/Br) battery during charging is a concern which can be resolved by the use of bromine complexing agents. In this paper, for the first time, we report the effect of the addition of two quaternary ammonium bromides; N-ethyl-N-methyl-morpholinium bromide (MEM) and N-ethyl-N-methyl-pyrrolidinium bromide (MEP) to the positive and negative half cell electrolytes of the V/Br. Cyclic voltammetry (CV), linear sweep voltammetry and electrochemical impedance spectroscopy (EIS) studies showed that the addition of MEM–MEP effectively reduce Br2 vapours. Although the presence of MEM and MEP did not affect the mechanism of the electrode reactions, performance tests conducted in lab scale V/Br cells employing the VF11 cation exchange membrane resulted in lower average cell efficiencies possibly due to the increase in membrane resistance caused by membrane fouling.
Ni-doped spinel LiNi x Mn2−x O4 (x =0, 0.05, 0.10) samples were prepared by a sol–gel method. Structure and morphology of the samples were characterized by X-ray diffraction, scanning electron microscopy, Brunnauer–Emmet–Teller method and inductively coupled plasma atomic absorption spectrometry. The electrochemical behavior as a cathode material (positive mass) for aqueous rechargeable lithium batteries (ARLBs) was investigated by cyclic voltammetry, electrochemical impedance spectroscopy, capacity measurements and cycling tests. The results show that the LiNi0.1Mn1.9O4 electrode presents the best rate and cycling performance but low reversible capacity. In contrast, the LiNi0.05Mn1.95O4 electrode shows a higher reversible capacity and relatively good cycling behavior. At a current density of 150mAg−1, LiNi0.05Mn1.95O4 delivers a reversible capacity of 102mAhg−1. At the relative high current densities of 1500 and 3000mAg−1, the LiNi0.05Mn1.95O4 electrode still delivers reversible capacities of 95.0 and 88.7mAhg−1, respectively. The Ni-doped samples show excellent cycling life in 0.5molL−1 Li2SO4 aqueous solution. The capacity retention ratios for LiNi0.05Mn1.95O4 and LiNi0.10Mn1.90O4 after 800 cycles at a current density of 1500mAg−1 are 79.4% and 91.1%, respectively, much higher than that for the undoped LiMn2O4 at only 37.8%.
Despite the fact that the fear of cancer recurrence is to varying degrees almost universal in cancer survivors, there is a lack of validated multidimensional instruments to evaluate this issue specifically.
This paper presents a methodology that uses the Monte Carlo Method (MCM) to estimate the behavior of economic parameters which may help decision, considering the risk in project sustainability. In order to show how this methodology can be used, a Grid-Connected Photovoltaic System (GCPVS) of 1.575 kWp, located on the roof top of the laboratory building of the Grupo de Estudos e Desenvolvimento de Alternativas Energéticas – GEDAE, at the Universidade Federal do Pará – UFPA, Belém – Pará – Brazil, and operating since December 2007, is analyzed. This system was chosen because it was the first GCPVS installed in the Brazilian Amazon Region, being the first risk evaluation on using a renewable energy source connected to the grid in the Region. This work also presents a similar treatment for the case of a stand-alone photovoltaic system (SAPVS) installed in the remote Santo Antônio Village, municipality of Breves, Pará, Brazil, considering the risk of investment assumed by an investor in power generation projects with similar characteristics or using other renewable energy sources. The last case allows a better assessment for other important applications of renewable energy in the Amazon Region, where the demand for energy is growing, but is still costly and often not a priority in government actions.
In this study, the ionic conductivity of a nanocomposite polymer electrolyte system (PEO–LiPF6–EC–CNT), which has been produced using solution cast technique, is obtained using artificial neural networks approach. Several results have been recorded from experiments in preparation for the training and testing of the network. In the experiments, polyethylene oxide (PEO), lithium hexafluorophosphate (LiPF6), ethylene carbonate (EC) and carbon nanotubes (CNT) are mixed at various ratios to obtain the highest ionic conductivity. The effects of chemical composition and temperature on the ionic conductivity of the polymer electrolyte system are investigated. Electrical tests reveal that the ionic conductivity of the polymer electrolyte system varies with different chemical compositions and temperatures. In neural networks training, different chemical compositions and temperatures are used as inputs and the ionic conductivities of the resultant polymer electrolytes are used as outputs. The experimental data is used to check the system’s accuracy following the training process. The neural network is found to be successful for the prediction of ionic conductivity of nanocomposite polymer electrolyte system.
Despite intensive management, the increasing conflict between humans and saltwater crocodiles in places such as Queensland, Australia, has led to the investigation of alternative techniques to improve public safety. The reliability of digital video surveillance systems (DV) placed above water and multi-beam sonar (sonar) placed under water to detect and monitor saltwater crocodiles was tested in a seminatural freshwater environment over a 2 h period (16:00–18:00 h). A total of 29 crocodiles were detected within the study area using DV, and 28 with sonar. One was obscured by a section of bank, and thus not visible on sonar. Of the 28 crocodiles detected by both methods, sonar recorded both entry and exit for all, while DV recorded both entry and exit for 15 crocodiles. The length of time that crocodiles were detected was longer on average for sonar (4 min 27 s) compared with DV (2 min 50 s). This reflected the time spent above (detected by sonar and DV) or below water (not detected by DV), as only sonar was able to detect crocodiles underwater. The use of sonar may provide a valuable management tool for detecting and monitoring saltwater crocodiles in areas frequented by people (e.g. beaches, boat ramps, upper freshwater areas) where there is a high chance of a negative interaction.
Li-ion batteries (LIBs) are ubiquitous in mobile devices and increasingly popular for powering large-sized transportation applications. However, current LIBs are undesirable to drive the further penetration of electric vehicles due to insufficient kinetics (long charging time, limited power) and high cost. In the quest of high-power, affordable, and environmentally friendly energy storage, here we design a new type of hybrid device composed of a low-cost Na2Ti3O7 anode and a high-voltage LiNi0.5Mn1.5O4 cathode. For the first time, we investigated Na2Ti3O7 nanotubes as Li+ host, which exhibit superior rate performance due to the domination of Li+ capacitance (over 85%) in a safe potential window (1–3 V vs. Li/Li+). Attributing to the synergy between the pseudo-capacitive anode and the fast Li+ intercalating cathode, the newly designed device delivers an extraordinary power density of 18631 W kg−1 while maintaining an energy density of 85 W h kg−1 based on total mass of cathode and anode materials. Such a combination of energy and power densities makes it exceptional compared to known LIBs and capacitors. The device also shows excellent capacity retention of 71% after 1000 cycles, highlighting the key advantages of this type of low-cost configuration towards scalable high-power energy storage application.
The UltraBattery, developed by CSIRO Energy Technology in Australia, is a hybrid energy storage device which combines an asymmetric super-capacitor and a lead–acid battery in single unit cells. This takes the best from both technologies without the need for extra, expensive electronic controls. The capacitor enhances the power and lifespan of the lead–acid battery as it acts as a buffer during high-rate discharging and charging, thus enabling it to provide and absorb charge rapidly during vehicle acceleration and braking. The initial performance of the prototype UltraBatteries was evaluated according to the US FreedomCAR targets and was shown to meet or exceed these in terms of power, available energy, cold cranking and self-discharge set for both minimum and maximum power-assist hybrid electric vehicles (HEVs). Other laboratory cycling tests showed a fourfold improvement over previous state-of-the-art lead–acid batteries under the RHOLAB test profile and better life than commercial nickel/metal hydride (NiMH) cells used in a Honda Insight when tested under the EUCAR HEV profile. As a result of this work, a set of twelve 12V modules was built by The Furukawa Battery Co., Ltd. in Japan and were fitted into a Honda Insight instead of the NiMH battery by Provector Ltd. The battery pack was fitted with full monitoring and control capabilities and the car was tested at Millbrook Proving Ground under a General Motors road test simulation cycle for an initial target of 50000 miles which was extended to 100000 miles. This was completed on 15th January 2008 without any battery problems. Furthermore, the whole test was completed without the need for any conditioning or equalisation of the battery pack.
We employed a polypyrrole hydrogel precursor to create a carbon framework that possesses both huge heteroatom content (13wt% nitrogen and 11wt% oxygen) and high surface area (945m2 g−1) that is equally divided between micropores and mesopores. A sodium ion capacitor (NIC, HIC) electrode fabricated from this N and O Functionalized Carbon (NOFC) has tremendous reversible capacity and rate capability, e.g. 437mAhg−1 at 100mAg−1, and 185mAhg−1 at 1600mAg−1. This is among the most favorable reported, and is due to copious nanoporosity that enables fast ion sorption at the many N and O moieties and graphene defects. The NOFC imbues a NIC device with energy–power characteristics that are not only state-of-the-art for Na hybrids, but also rival Li systems: Ragone chart placement is 111Whkg−1 and 38Whkg−1 at 67Wkg−1 and 14,550Wkg−1, respectively, with 90% capacity retention at over 5000 charge/discharge cycles.
A computational model is developed to describe the fluid flow in the small channel network systems that are typical of planar fuel cells. The model solves mass and momentum equations to predict pressure drop and flow uniformity within individual channels. By formulating the problem in dimensionless variables, the solutions are generalized in terms of two nondimensional groups. The results are presented in graphical form, facilitating their application without the need to solve the model for any particular application.
Prediction of lithium-ion batteries remaining useful life (RUL) plays an important role in an intelligent battery management system. The capacity and internal resistance are often used as the batteries health indicator (HI) for quantifying degradation and predicting RUL. However, on-line measurement of capacity and internal resistance are hardly realizable due to the not fully charged and discharged condition and the extremely expensive cost, respectively. Therefore, there is a great need to find an optional way to deal with this plight. In this work, a novel HI is extracted from the operating parameters of lithium-ion batteries for degradation modeling and RUL prediction. Moreover, Box-Cox transformation is employed to improve HI performance. Then Pearson and Spearman correlation analyses are utilized to evaluate the similarity between real capacity and the estimated capacity derived from the HI. Next, both simple statistical regression technique and optimized relevance vector machine are employed to predict the RUL based on the presented HI. The correlation analyses and prediction results show the efficiency and effectiveness of the proposed HI for battery degradation modeling and RUL prediction.
A battery with variable electrostatic capacity is proposed as a new type battery with increased capacity. If the electrostatic capacity can be significantly changed by redox, then the capacity of a capacitor can be superimposed on the capacity of the battery. Calcination of a mixture of anthracene and sulfur was performed to prepare a sulfur composite material (ANS450) as a model material. Elemental analysis and Raman spectroscopy indicated that ANS450 has a structure in which anthracene frames combined with sulfur are linked together by dithiane structures. Although XPS analysis indicated that sulfur in ANS450 performed a one-electron reduction, ANS450 exhibited an extremely large capacity of 0.86Ahg−1, which was larger than the capacity estimated from the sulfur content. Cyclic voltammetry revealed that the electrostatic capacity of ANS450 was significantly changed by redox. This change in electrostatic capacity is considered to be the main factor for the increase in capacity, which validates the basic concept of a battery with variable electrostatic capacity.
Synthetic and structural studies have been performed for two thiolate complexes of titanium(IV). The reaction between Ti(NEt2)4 and 10 equivalents of C6F5SH at room temperature resulted in the formation of the ionic complex [Et2NH2]3[Ti(SC6F5)5][SC6F5]2. The related reaction between Ti(NEt2)4 and 4 equivalents of C6F5SH at room temperature, in the presence of a two electron donor ligand L (2,6-dimethylpyridine or tetrahydrothiophene), resulted in the isolation of the ionic complex [Et2NH2][Ti(SC6F5)4(NEt2)]. However, if the reaction between Ti(NEt2)4 and 4 equivalents of C6F5SH is carried out without the addition of L, the first compound is formed rather than the second. The two new complexes have been characterised by X-ray crystallography. [Et2NH2]3[Ti(SC6F5)5][SC6F5]2 is the first structurally characterised example of a five-co-ordinate homoleptic sulfur-bonded titanium complex. Both adopt similar sheet structures held together by π–π and C–F⋯π interactions.
The design of toxicological testing strategies aimed at identifying the toxic effects of chemicals without (or with a minimal) recourse to animal experimentation is an important issue for toxicological regulations and for industrial decision-making. This article describes an original approach which enables the design of substance-tailored testing strategies with a specified performance in terms of false-positive and false-negative rates. The outcome of toxicological testing is simulated in a different way than previously published articles on the topic. Indeed, toxicological outcomes are simulated not only as a function of the performance of toxicological tests but also as a function of the physico-chemical properties of chemicals. The required inputs for our approach are QSAR predictions for the LOAELs of the toxicological effect of interest and statistical distributions describing the relationship existing between in vivo LOAEL values and results from in vitro tests. Our methodology is able to correctly predict the performance of testing strategies designed to analyze the teratogenic effects of two chemicals: di(2-ethylhexyl)phthalate and Indomethacin. The proposed decision-support methodology can be adapted to any toxicological context as long as a statistical comparison between in vitro and in vivo results is possible and QSAR models for the toxicological effect of interest can be developed.
In this work, a two-dimensional mathematical model is developed to study the flow patterns and volumetric flow penetrations in a segment of flow channel over porous electrode layered system in vanadium flow battery with flow field design. The flow distributions at the interface between the flow channel and porous electrode are examined. It is found that the non-linear pressure distributions can distinguish the interface flow distributions under the ideal plug flow and ideal parabolic flow inlet boundary conditions. Nevertheless, the volumetric flow penetration within the porous electrode beneath the flow channel through the integration of interface flow velocity reveals that this value is identical under both ideal plug flow and ideal parabolic flow inlet boundary conditions. The volumetric flow penetrations under the advection effects by both flow channel and landing/rib are estimated. The maximum current density achieved in a flow battery with a flow field architecture can be predicted based on the 100% amount of electrolyte flow reactant consumption through the porous electrode beneath flow channel and landing/rib. The corresponding theoretical maximum current densities achieved in vanadium flow battery with one and three layers of SGL 10AA carbon paper electrode have reasonable agreement with experimental results under a proper permeability.