batterydata/paper-abstracts huggingface dataset:
A novel Ru-catalyzed hydrogenation of carbon dioxide proceeds with an unprecedented high formic acid to amine ratio (AAR of 2.69), which results in an improved energy content. The presented catalyst system allows for reversible fast hydrogen loading (even at RT) and unprecedented unloading (TON for H2 liberation of 800000).
Nowadays, machine learning classification techniques have been successfully used while building data-driven intelligent predictive systems in various application areas including smartphone apps. For an effective context-aware system, context pre-modeling is considered as a key issue and task, as the representation of contextual data directly influences the predictive models. This paper mainly explores the role of major context pre-modeling tasks, such as context vectorization by defining a good numerical measure through transformation and normalization, context generation and extraction by creating new brand principal components, context selection by taking into account a subset of original contexts according to their correlations, and eventually context evaluation, to build effective context-aware predictive models utilizing multi-dimensional contextual data. For creating models, various popular machine learning classification techniques such as decision tree, random forest, k-nearest neighbor, support vector machines, naive Bayes classifier, and deep learning by constructing a neural network of multiple hidden layers, are used in our study. Based on the context pre-modeling tasks and classification methods, we experimentally analyze user-centric smartphone usage behavioral activities utilizing their contextual datasets. The effectiveness of these machine learning context-aware models is examined by considering prediction accuracy, in terms of precision, recall, f-score, and ROC values, and has been made an empirical discussion in various dimensions within the scope of our study.
By using multi-wall carbon nanotube (MWCNT), a well-dispersed composite of Cu(NO3)2 ·xH2O/MWCNT (2.5<x<3.0) is prepared by a simple solution route. Morphology and structure observations show that Cu(NO3)2 ·xH2O/MWCNT is composed of Cu(NO3)2 ·xH2O particles with particle size of 50–400nm embedded in the three-dimensional conductive network of MWCNT. The existence of MWCNT not only inhibits the agglomeration of primary Cu(NO3)2 ·xH2O blocks into bigger secondary particles but also improves the electronic conductivity of Cu(NO3)2 ·xH2O. As a result, Cu(NO3)2 ·xH2O/MWCNT reveals a stable and conductive structure for lithium storage. Charge/discharge results display that Cu(NO3)2 ·xH2O/MWCNT delivers a lower initial discharge capacity of 2177.1 mAh g−1 at a current density of 50mAg−1 than that of pure Cu(NO3)2 ·xH2O (2383.2mAhg−1.). However, Cu(NO3)2 ·xH2O/MWCNT maintains a higher reversible lithium storage capacity of 980.2 mAh g−1 with a higher capacity retention of 83.6% after 30 cycles compared to pure Cu(NO3)2 ·xH2O (264.6 mAh g−1, 47.1%). Contributed to the introduction of MWCNT, Cu(NO3)2 ·xH2O/MWCNT also shows outstanding rate performance. It can provide the reversible lithium storage capacities of 943.4, 813.5, 702.9 and 642.0mAhg−1 at 100, 150, 200 and 250mAg−1, respectively. Therefore, Cu(NO3)2 ·xH2O/MWCNT may be a promising lithium storage material.
Three-dimensionally assembled LiFePO4/C/graphene nanofiber composites were successfully prepared via a suspension mixing method followed by heat-treatment at 400°C. A faster electron transfer, lower electrochemical polarization as well as higher diffusion coefficient of Li+ are obtained with the assistance of graphene nanofibers. The 5wt% graphene nanofibers modified electrode (G-5) delivers the best electrochemical kinetics including the lowest charge transfer resistance and highest diffusion coefficient of Li+ at 0°C and −20°C, respectively. Likewise, the G-5 exhibits the highest charge-discharge capability and the most stable cycling performance at low operation temperatures compared with those of LiFePO4/C, 3wt% and 7wt% graphene nanofibers modified LiFePO4/C (G-3 and G-7) composites. The G-5 electrode shows a capacity of 92.8mAhg−1 with 92.0% capacity retention after 200 cycles at 1C at −20°C. The reasons for the significant improvement of the low operation temperatures electrochemical performances can be ascribed to the enhanced conductivity and reduced agglomeration of pristine particles due to the introduction of graphene nanofibers. These excellent low temperature performances show that graphene nanofibers modified LiFePO4/C electrodes are promising cathode candidates for lithium-ion batteries applications at low temperatures.
Nanostructured FeS2 has been synthesized and used as the cathode material in LiSi/FeS2 thermal batteries. With the same weight, the nanostructured cathode pellets are 23% thinner than conventional counterparts resulting in 31% increase of pellet density. Therefore, the volume of batteries can be reduced significantly. With the nanostructure, the electrode materials of the thermal batteries react more rapidly and completely during discharge resulting with a remarkable increase of energy output. The discharge tests show that the energy density of the nanostructured thermal batteries is two times higher (109J/g) than the conventional counterpart (58J/g). The nanostructured pellets are more robust mechanically than the conventional counterparts that could increase productivity and lower manufacturing cost.
In this paper, an overview of future energy option for charging mechanism associated with the full electric vehicle (FEV) is carried out. This review emphasizes the basic types of electric vehicles (EVs), various factors affecting to increase the number of FEVs to use, the CO2 emission and fuel economy, and a new charging mechanism for increasing the usage of FEVs. The EVs such as plug-in hybrid electric vehicles (PHEVs), the hybrid electric vehicles (HEVs), and the FEVs are recharged externally. The HEVs are the one will cover longer traveling distance compared to PHEVs and FEVs because of internal combustion engine. The PHEVs provides on-board charging and an option for sustaining mode of operation. On the other hand, FEVs run only with the help of batteries and the electricity required for recharging the batteries is generated from the conventional power plants which produces more greenhouse gas emission. In order to overcome this problem, a new recharging mechanism is proposed, which has both the renewable sources (wind and solar) moreover it automatically recharges the battery banks present in the FEVs. A wind duct is incorporated for increasing the velocity of the wind and the model of both the wind and the photovoltaic (PV) system have been studied. Furthermore, the streamline plot of wind duct is simulated at various values of Reynolds number and the PV array is modeled using Simscape. The performance and comparison results indicate that the proposed system can be used for charging the batteries of EVs.
Lithium-ion batteries, already capable of addressing the requirements of electric vehicles and renewable electricity storage, will be in the focus for the next decade. However, the transition from the small batteries for portable electronic to ultra-high capacity batteries requires safety improvements and cost-cutting efforts. Intensive research has been performed in the last three decades to optimize specific and volumetric capacity of electrodes. Recently the attention is focusing on increasing the electrodes areal capacity to enable the substantial reduction of the current collectors, porous separator, and electrolyte resulting in large gravimetric and volumetric energy density improvements as well as cost savings. Here we propose a lithium-ion battery based on thick, additive-free ceramic negative and positive electrodes, i.e. LTO (Li4Ti5O12) and LFP (LiFePO4), obtained by a solvent-free technology called powder extrusion moulding. Against all odds, the LTO/LFP cell based on these thick ceramic electrodes (areal capacity of 13.3 mA h cm−2) achieved the very high energy of about 23.9 mW h cm−2. Such an excellent performance, achieved simulating a typical day-night charge/discharge cycle, opens the way for the deployment of low cost, effective household (and small industry) energy storage in combination with photovoltaic energy harvesting.
Background Startle and its inhibition by weak lead stimuli (“prepulse inhibition”: PPI) are studied to understand the neurobiology of information processing in patients and community comparison subjects (CCS). PPI has a strong genetic basis in infrahumans, and there is evidence for its heritability, stability and reliability in humans. PPI has gained increasing use as an endophenotype to identify vulnerability genes for brain disorders, including schizophrenia. Genetic studies now often employ multiple, geographically dispersed test sites to accommodate the need for large and complex study samples. Here, we assessed the feasibility of using PPI in multi-site studies. Methods Within a 7-site investigation with multiple measures, the Consortium on the Genetics of Schizophrenia conducted a methodological study of acoustic startle and PPI in CCS. Methods were manualized, videotaped and standardized across sites with intensive in-person training sessions. Equipment was acquired and programmed at the “PPI site” (UCSD), and stringent quality assurance (QA) procedures were used. Testing was completed on 196 CCS over 2.5 years, with 5 primary startle dependent measures: eyeblink startle magnitude, habituation, peak latency, latency facilitation and PPI. Results Analyses identified significant variability across sites in some but not all primary measures, and determined factors both within the testing process and subject characteristics that influenced a number of test measures. QA procedures also identified non-standardized practices with respect to testing methods and procedural “drift”, which may be particularly relevant to multi-site studies using these measures. Conclusion With thorough oversight and QA procedures, measures of acoustic startle PPI can be acquired reliably across multiple testing sites. Nonetheless, even among sites with substantial expertise in utilizing psychophysiological measures, multi-site studies using startle and PPI as dependent measures require careful attention to methodological procedures.
The state-of-charge (SOC) estimation for LiFePO4 batteries is one of the most important issues in battery management system (BMS) on electric vehicles (EVs). Significant temperature changes and drift current noises are inevitable in EVs and cause strong interference in SOC estimation, therefore a SOC-Particle filter (PF) estimator is proposed for SOC estimation. This paper tries to make three contributions: (1) a temperature composed battery model is established based on commercial LiFePO4 cells which can be used for SOC estimation at dynamic temperatures. (2) A capacity retention ratio (CRR) aging model is established based on the real history statistical analysis of the running mileage of the battery on an urban bus. (3) The proposed models are combined with an electrochemical model and the PF method is employed for SOC estimation to eliminate the drift noise effects. Experiments under dynamic current and temperature conditions are designed and performed to verify the accuracy and robustness of the proposed method. The numeral results of the validation experiments have verified that accurate and robust SOC estimation results can be obtained by the proposed method.
Objective To identify a standard physical performance test, which can predict 3-year incident mobility disability independent of demographics. Design Longitudinal cohort study. Setting Population-based middle-aged and older adult cohort assessment performed at a local geriatric clinical center. Participants Community-living middle-aged and older persons (age, 50–85y) without baseline mobility disability (N=622). Interventions Not applicable. Main Outcome Measures Mobility disability was ascertained at baseline and at 3-year follow-up using an established self-report method: self-reported inability to walk a quarter mile without resting or inability to walk up a flight of stairs unsupported. Physical performance tests included self-selected usual gait speed, time required to complete 5 times sit-to-stand (5TSTS), and 400-m brisk walking. Demographic variables age, sex, height, and weight were recorded. Results Overall, 13.5% participants reported 3-year incident mobility disability. Usual gait speed <1.2m/s, requiring >13.6 seconds to complete 5TSTS, and completing 400m at <1.19m/s walking speed were highly predictive of future mobility disability independent of demographics. Conclusions Inability to complete 5TSTS in <13.7 seconds can be a clinically convenient guideline for monitoring and for further assessment of middle-aged and older persons, in order to prevent or delay future mobility disability.
A one-dimensional mathematical model of the positive electrode of a sodium–iron chloride battery for an isothermal, constant-current discharge–charge cycle is presented. Macroscopic theory of porous electrodes and concentrated solution theory are used in the model to describe the transport processes. The change in the solubility of FeCl2 with position and time within the cell is included in the model by defining an equilibrium constant that is a function of the NaCl:NaAlCl4 molar ratio. The concentrated solution theory for a three-ion system with common cation is extended to account for a diffusive flux of a sparingly soluble ferrous complex. It is seen that this flux is important, especially at moderate depths of discharge. The effect of the assumed solubility constant K sp,FeCl on the battery performance is characterized. When K sp,FeCl is higher than 106, its variation does not change the short-time behavior of the system appreciably. Simulations suggest that the iron accumulates near the sodium tetrachloroaluminate reservoir during discharge. When charging, the net movement is reversed. As a result of continuous cycling, simulations predict that iron is depleted at this boundary. For instance, at the end of the fifth cycle, the iron amount decreases by ∼1% near the reservoir.
Fe3O4/carbon (Fe3O4/C) composite microspheres with a high content of Fe3O4 nanoparticles as an active material are prepared by suspension polymerization and heat treatment. A significant difference is observed in the morphology of the Fe3O4/C composite microspheres with the introduction of different amounts of Fe3O4 nanoparticles. The morphological and structural differences of the Fe3O4/C composite microspheres are characterized by focused ion beam cross-section, scanning electron microscopy, transmission electron microscopy, and X-ray diffraction analysis. Thermogravimetric analysis is conducted to measure the amount of Fe3O4 nanoparticles introduced into a carbon matrix. We fix two samples with Fe3O4 contents of 72 wt.% and 98 wt.%, respectively. Fe3O4/C composite microspheres containing 72 wt.% Fe3O4 nanoparticles show much higher capacity retention with an excellent columbic efficiency of 99% at every cycle in comparison with that of the Fe3O4/C composite microspheres containing 98 wt.% Fe3O4 nanoparticles when used as anodes for LIBs. These results indicate that the particle morphology and weight ratio of incorporated Fe3O4 to carbon matrix affects the electrochemical performance of Li-ion cells.
To minimize greenhouse gas emissions, the logistic field has seen an increasing usage of electric vehicles. The resulting distribution planning problems present new computational challenges. We address a problem, called Electric Traveling Salesman Problem with Time Windows. We propose a mixed integer linear formulation that can solve 20-customer instances in short computing times and a Three-Phase Heuristic algorithm based on General Variable Neighborhood Search and Dynamic Programming. Computational results show that the heuristic algorithm can find the optimal solution in most small-size instances within a tenth of a second and achieves goods solutions in instances with up to 200 customers.
Although current collectors take up more weight than active materials in most lithium ion battery cells, so far research has been focused mainly on improving gravimetric capacities of active materials. To address this issue of improving gravimetric capacities based on overall cell components, we develop freestanding nanocomposites made of carbon nanofibers (CNFs) and silicon nanowires (SiNWs) as metal current collector-free anode platforms. Intrinsically large capacities of SiNWs as active materials in conjunction with the light nature of freestanding CNF films allow the nanocomposites to achieve 3–5 times improved gravimetric capacities compared to what have been reported in the literature. Moreover, three-dimensional porous structures in the CNF films facilitate increased mass loadings of SiNWs when compared to flat substrates and result in good cycle lives over 40 cycles. This type of nanocomposite cell suggests that 3D porous platforms consisting of light nanomaterials can provide for higher gravimetric and areal capacities when compared to conventional battery cells based on flat, heavy metal substrates.
Low-crystalline β-FeOOH and vanadium ferrite were prepared by a simple hydrolysis method. XRD measurement revealed that the former material had a framework of β-FeOOH with somewhat amorphous structure, and that the latter one gave a crystalline structure analogous to that of the hydrated iron orthovanadate. From the electrochemical measurements, it was found that the low-crystalline β-FeOOH positive electrode showed a discharge capacity of 230mAh/g in the potential range of 4.3V and 1.6V versus Li/Li+, and better cycle performance than the high-crystalline one. The vanadium ferrite positive electrode also showed a high discharge capacity over 300mAh/g and superior cycle performance.
In recent years, grid-connected residential PV generation systems have been greatly encouraged in China. In a residential power system containing PV, three types of power sources, namely, PV generation, battery storage and the utility grid, need to be properly scheduled. The time-of-use tariff and step tariff have been widely accepted in China. Correspondingly, this paper proposes two optimal energy management strategies for residential power systems to adapt to the two tariffs towards largest benefits. The strategies are formulated as optimization problems, where minimizing the household energy cost is taken as the objective and the dispatching ratio of electricity sold to the grid and used locally is treated as the optimization variable. A genetic algorithm (GA) is then employed to solve the formulated nonlinear optimization problems. A typical residential power system, containing grid-connected PV panels and a battery storage system, is used for verification study. The results show that the proposed energy management strategies, along with a GA based solving method, are effective in scheduling the operation status of the three power sources optimally to achieve maximum economic benefits under the time-of-use tariff and step tariff, respectively.
This paper provides a methodology and identifies opportunities for battery pack downsizing in a hybrid electric vehicle (HEV). A new term of power denial and a new metric of lost energy opportunities are introduced and analyzed in addition to utilization, temperature, life, and cost. A model-based power limiting algorithm is used in computing real-time power capability of the battery. The downsized pack with a shifted SOC window is evaluated in a light-duty HEV. A parameterized electro-thermal model is used to capture voltage, state-of-charge, and temperature. A semi-empirical ageing model is integrated to predict the capacity loss and resistance increase of the downsized pack. The battery ageing model is developed based on a set of experiments carefully designed to clarify the influence of operating SOC on battery degradation. The parametric study shows that the number of cells in the pack could be reduced from 76 to 64 while shifting nominal operating SOC from 50% to 35% without changing the pack energy throughput. This would result in a 19% increase in energy utilization per cell, a 0.5% increase in capacity fade and a 2.9% increase in internal resistance, while the pack cost will be reduced by 10%.
Our goal was to identify the specific contribution of fear of falling (FoF) and falls with quantitative gait impairments and cognition capabilities in multiple sclerosis (MS) patients. Patients were separated into four individual subgroups as to the presence of FoF and falls (i.e., fearless/non-fallers, fearless/fallers, FoF/non-fallers and FoF/fallers). The Falls Efficacy Scale International questionnaire was used to assess the level of concern of falling. Participants were defined as “fallers” and “non-fallers” based on their fall history. Spatio-temporal parameters of gait were analyzed using an electronic mat. Cognitive performance was assessed by a computerized cognitive battery of tests. The study included 540 MS patients, 47% were defined as fallers and 61.9% reported a FoF. Non-significant differences were found between the fearless/non-fallers and fearless/fallers in all clinical, gait and cognitive scores. FoF/non-fallers walked significantly slower compared to fearless MS individuals who had previously fallen. Furthermore, the same patient group exhibited a poorer performance in the motor skills cognitive subdomain. A significant reverse relationship was found between FoF and cognitive motor skills in the fallers and non-fallers groups. FoF characterizes a more disabling symptom than falling in the MS population.
A macaroni-like Li1.2V3O8 nanomaterial was directly prepared through a facile solution route using β-cyclodextrin (β-CD) as a template reagent. Its crystal structure was determined by the X-ray diffraction (XRD) pattern. From the scanning electron microscopy (SEM) and transmission electron microscopy (TEM) micrographs, we observed that the as-prepared Li1.2V3O8 material consisted of the aggregated macaroni-like nanoparticles and showed a porous structure. The electrochemical properties of the as-prepared Li1.2V3O8 in 1.0M Li2SO4 aqueous electrolyte were studied through cyclic voltammograms and charge–discharge measurements. The results revealed that the as-prepared Li1.2V3O8 could deliver the initial specific capacities of 189, 140, and 101mAhg−1 at 0.1, 0.5, and 1.0C, respectively. It suggests that the as-prepared Li1.2V3O8 should have an attractive future to be applied in aqueous rechargeable lithium battery (ARLB).
Linear poly(ethylenimine) (LPEI) has been modified by reductive alkylation to form linear poly(N-(2-(2-methoxyethoxy)ethyl)ethylenimine) (LPEI-G2) as verified by nuclear magnetic resonance spectroscopy (NMR). The resulting LPEI-G2 has short methyl-capped oligo(ethylene oxide) side-chains attached to the LPEI backbone. Characterization of pure LPEI-G2 and LPEI-G2 complexed with lithium triflate (LiTf) was carried out over a variety of concentrations using infrared (IR), differential scanning calorimetry (DSC), and impedance techniques. Initial spectroscopic studies indicated that at a 20:1 oxygen atom to lithium ion ratio, “free” ions are the dominant triflate species present. At the same composition, the electrolyte has a Tg of −60°C and a conductivity 7×10−5 S cm−1 at 60°C. The vibrational spectra and conductivity values of samples at O:Li compositions of 20:1 and 5:1 will be discussed.