batterydata/paper-abstracts huggingface dataset:
It is demonstrated that the rate capacities of TiO2 anatase nanoparticles can be improved substantially by annealing in NH3 at 450–500 °C. At a high nominal rate of 25C, the average discharge capacity of specimens annealed in NH3 at 450 °C for 7 h is more than double of that of the controlled specimens annealed in dry air under the same heat treatment condition. A critical comparison with literature shows that this simple and cost-effective low-temperature nitridation process can achieve high-rate capacities that are better than those reported in prior comparable studies. The enhanced high-rate capacities are attributed to moderate surface nitridation with less-disordered nitridated regions, which may enhance the surface electronic conductivity without forming discrete, nanoscale, surface amorphous films to block the lithium transport. Surface nitridation was confirmed by XPS measurements.
In this paper we report on the use of 0.7M Et4NBF4 in ADN as electrolyte in EDLCs. 0.7M Et4NBF4 in ADN displays a wide electrochemical stability window and promising values of conductivity and viscosity. Using this electrolyte it is possible to realize EDLCs with an operative voltage as high as 3.75V. At RT, these high voltage EDLCs display high coulombic efficiencies, low ESRs and high specific capacitances stable for several thousands of cycles. The wide electrochemical stability of ADN contributes to preserve the integrity of the electrolyte at potentials in which other conventional organic electrolytes (e.g. ACN) are normally subject to deterioration and/or decomposition processes. Thanks to this intrinsic stability, EDLCs containing 0.7M Et4NBF4 ADN as electrolyte display high capacitance retention over 35,000 cycles carried out with cell voltage as high as 3.5V.
ZnO-coated LiCoO2 particles are prepared by plasma-enhanced chemical vapour deposition (PE-CVD) in a coating range from 0.08 to 0.49wt.%, and examined using field emission-scanning electron microscopy (FE-SEM), X-ray diffraction (XRD), and atomic absorption spectroscopy (AAS), with particular focus on surface characteristics. From charge-discharge cycling tests in the range of 3.0–4.5V, the ZnO coating has little effect on the discharge capacity in the first few cycles, but the coating effectively improves the capacity retention after prolonged cycling. In the experimental range studied, the optimum amount of ZnO coating which maximizes the capacity retention is found to be 0.21wt.%. An excessive amount of ZnO coating causes a decrease in both cyclic performance and thermal stability. The possible reasons for enhanced cycleability and thermal stability afforded by the ZnO coating are discussed from the viewpoint of the surface morphology of the bare and coated LiCoO2 particles and their impedance spectra.
Electric vehicles (EVs) and distributed generation are expected to play a major role in modern power systems. Although many studies have introduced novel models to integrate distributed generation into high levels of EV-adoption scenarios, none has considered EV-embedded battery performance degradation and its economic effect on system planning. Based on well-established models and data to emulate the capacity fading of lithium-ion batteries, the current work presents a mixed-integer linear programming optimization framework with decision variables to size renewable energy resources (RESs) in modern microgrids. The objective function aims to minimize the total cost of the system while guaranteeing a profitable operation level of vehicle-to-grid (V2G) application, narrowing the gap between design stage and real-life daily operation patterns. Stochastic modeling is used to incorporate the effect of different uncertainties involved in the issue. A case study on a residential system in Okinawa, Japan, is introduced to quantitatively illustrate how a profitable V2G operation can affect RES sizing. The results reveal that accounting for the economic operation of EVs leads to the integration of significantly higher capacities of RESs compared with a sizing model that excessively relies on V2G and does not recognize battery-fading economics.
The solid electrolyte interphase (SEI) significantly affects the energy density and safety performance of lithium ion batteries. Previous studies have shown that conventional analyses cannot characterize the real-time molecule interactions of SEI formation on the surface of an electrode. In this study, a novel in situ electrochemical-surface plasmon resonance (EC-SPR) was developed for evaluating the kinetic changes of ionic dissociation, SEI formation, and Li-Au alloying reaction. The novel EC-SPR not only indicates the rates of each reaction stage but also reveals the characteristics of the passivated layers. This research demonstrates that the dissociation rates of ionic clusters are affected by several reactions on the surface of an electrode. The rate and mass of the SEI formation from the reduction of ethylene carbonate (EC) are calculated at 0.004 ngs-1 and 5.858 ng, respectively. The EC-SPR is a powerful tool for further in situ kinetic investigations of different electrolyte and electrode systems.
Despite the growing importance of social cognition in schizophrenia, fundamental issues concerning the nature of social cognition in schizophrenia remain unanswered. One issue concerns the strength of the relationships between social cognition and key features of the disorder such as neurocognitive deficits and negative symptoms. The current study employed structural equation modeling to examine three key questions regarding the nature of social cognition in schizophrenia: 1) Are social cognition and neurocognition in schizophrenia better modeled as one or two separate constructs? 2) Are social cognition and negative symptoms in schizophrenia better modeled as one or two separate constructs?, and 3) When social cognition, neurocognition, and negative symptoms are included in a single model, is social cognition more closely related to neurocognition or to negative symptoms? In this cross sectional study, one hundred outpatients with schizophrenia or schizoaffective disorder were administered measures of social cognition, neurocognition, and negative symptoms. A two-factor model that represented social cognition and neurocognition as separate constructs fit the data significantly better than a one-factor model, suggesting that social cognition and neurocognition are distinct, yet highly related, constructs. Likewise, a two-factor model that represented social cognition and negative symptoms as separate constructs fit the data significantly better than a one-factor model, suggesting that social cognition and negative symptoms are distinct constructs. A three-factor model revealed that the relationship between social cognition and neurocognition was stronger than the relationship between social cognition and negative symptoms. The current findings start to provide insights into the structure of social cognition, neurocognition, and negative symptoms in schizophrenia.
Background Very preterm children (VPT) are at high risk for developmental coordination disorder (DCD). The Movement Assessment Battery for Children-2 (MABC-2) Test is commonly used to identify children with DCD, but little is known about the predictive validity of this assessment in this population. Aims The aims of this study were to determine if MABC-2 scores at 3 years can predict DCD at 4.5 years and if DCD can be reliably identified in VPT children at 3 years. Methods and procedures In a retrospective sample of 165 VPT children, logistic regression was used to determine if the MABC-2 score at 3 years is predictive of DCD at 4.5 years. Cross-tabulations were used to determine the relationship between scores at 3 years and DCD at 4.5 years. Outcomes and results MABC-2 scores at age 3 were a significant predictor (OR = 0.82, p = 0.001) of DCD diagnosis at 4.5 years. The MABC-2 has excellent sensitivity (90%), moderate specificity (69%), small to moderate positive predictive value (38%) and high negative predictive value (97%). Conclusions and implications The MABC-2 is highly sensitive in identifying VPT children with DCD, but also has many false positives. MABC-2 scores can reliably predict VPT children who are not at risk of DCD.
We designed a novel aqueous rechargeable lithium battery with LiFePO4/C (LFP) and LiMn2O4/C (LMO) as the anode and cathode, respectively; then investigated the battery in Li2SO4 aqueous electrolyte. We also studied the electrochemical behavior of LFP in aqueous electrolyte using cyclic voltammetry (CV). The material exhibited excellent electrochemical performance in the aqueous electrolyte, including good oxidation/reduction reversibility and cycling stability; almost no decays were observable after 200CV cycles. The diffusion coefficients of Li ions through the interface between the liquid electrolyte and the solid LiFePO4 in terms of intercalation and deintercalation were 1.22×10−14 and 9.97×10−15 cm2/s, respectively. The material could be completely intercalated/deintercalated with Li ions in the aqueous electrolyte, indicating the excellent performance of LFP in an aqueous solution. Further, an aqueous rechargeable lithium battery (ARLB), which we fabricated using LFP as the anode and LMO as the cathode, also exhibited quite good performance in aqueous Li2SO4 solution: after 1,000 charge–discharge cycles at 2C, the capacity loss was less than 30%, indicating that this type of ARLB has excellent cycling stability and may be promising for future research and application.
Battery state-of-charge estimation is an important component in battery management system design. Many known issues with lithium ion batteries such as performance decay, accelerated aging and even hazardous incidents were associated with faulty state-of-charge estimation. Different estimation algorithms can be summarized in a nutshell as: 1) modeless approaches, i.e. columbic counting; 2). model based observers, i.e. extended Kalman filter; and 3). data driven nonlinear models, i.e. neural networks, and learning machines. This paper adopts the third approach, and proposes a new architecture for SoC estimation using a load-classifying neural network. This approach pre-processes battery inputs and categorizes battery operation modes as idle, charge and discharge, with three neural networks trained in parallel. Using a vehicle drive cycle load profile for model training and a pulse test duty cycle for validation, the proposed method yields a 3.8% average estimation error. This result demonstrates that data driven machine learning approach can deliver estimation performance comparable with other advanced observer designs. The neural network however has a simpler model training procedure, boarder choice of training data, and smaller computational cost. In addition, with simple filtering and output constraints, estimation error spikes associated with ‘uncharted’ inputs can be effectively suppressed.
Sn27Cu33C40 produced by mechanical milling is compared with Sn27Cu31C42 and Sn26Cu31C43 produced by magnetron sputtering for use as anode materials in Li-ion batteries. The sputtered samples were found to be amorphous/nanostructured and had a greater degree of atomic intermixing in comparison to the milled sample, which was more crystalline. Samples were incorporated as electrodes in Li-half cells and had a capacity of about 400 mAh g−1. Significant capacity loss was observed beginning near the 50th cycle for the mechanically milled sample, while little capacity loss was observed for the sputtered samples after 100 cycles. Despite its good cycling performance, amorphous Cu6Sn5 + C was found to crystallize as Li is cycled, resulting in the aggregation of Cu6Sn5 grains. Structural changes during lithiation and delithiation as well as the evolution of the electrochemistry are compared and contrasted for the two materials.
A hydrometallurgical route is proposed to recover zinc and manganese from spent alkaline batteries in order to separate base metals such as nickel, copper, aluminium, cadmium, lithium and cobalt which constitute the main metallic species of spent NiCd, NiMH and Li-ion rechargeable batteries. The route comprises the following main steps: (1) sorting batteries by type, (2) battery dismantling to separate the spent battery dust from plastic, iron scrap and paper, (3) leaching of the dust with sulphuric acid and (4) metal separation by a liquid–liquid extraction using Cyanex 272 (bis-2,4,4-trimethylpentyl phosphinic acid) as extractant. The metal content of NiCd, NiMH and Li-ion batteries from three distinct manufacturers has been evaluated. A factorial design of experiments was used to investigate the leaching step using operational variables such as temperature, H2SO4 concentration, S/L ratio and H2O2 concentration. Analysis of metal separation by the liquid–liquid extraction with Cyanex 272 identified a pH1/2 2.5–3.0 for zinc and aluminium, pH1/2 4.0–4.5 for manganese, cadmium, copper and cobalt, pH1/2 6.5 for nickel and pH1/2 8.0 for lithium. These results indicate that batteries must be previously sorted by type and treated separately. In addition, data fitting to an equilibrium model proposed for the reactive test system by the European Federation of Chemical Engineering (EFChE) have indicated that MR2(RH)2 and MR2 complexes (where M=Zn, Mn, Co, Cd and Cu) co-exist in the organic phase with Cyanex 272 depending on the loading conditions. The route has been found technically viable to separate the main metallic species of all batteries considered in this study.
The transfer processes proceeding in insertion electrodes with surface control on the application of a potential or current step are considered theoretically. The theoretical relationships have been verified by the determination of the kinetic and diffusion parameters of electrochemical lithium intercalation into thin carbon films. The overall electrode polarization is divided, both theoretically and experimentally, into the kinetic component, related to hindered ion transfer in the passive surface layer, and the diffusion one, related to decelerated lithium diffusion in the carbon matrix. The polarization dependence of kinetic current is shown to obey the same regularities that the current–potential function of the lithium electrode. The concentration dependences of the surface layer parameters and the diffusion coefficient of lithium in carbon have been determined.
The oxidoreductase NQO1 plays a prominent role in maintaining the cellular homeostasis. NQO1 is mainly a cytosolic enzyme which catalyzes the metabolism of quinones and is present in almost all tissue types providing protection against different stresses including xenobiotics, oxidants, UV light, and ionizing radiation. This enzyme is overexpressed in many cancerous tissues and its function in carcinogenesis remains unclear. Due to the relative lack of information on the role of NQO1 in melanoma pathogenesis, we attempted to determine the expression and basic function of NQO1 in melanoma cell proliferation. We found that NQO1 is overexpressed in most melanoma cell lines with respect to melanocytes. Furthermore, the expression of this oxidoreductase significantly induces cell cycle progression by upregulating the expression of cyclins A2, B1 and D1, leading to the proliferation of melanoma cells. Our results also indicate that NQO1 is an upstream regulator of NF-κB p50, a factor linked to melanoma progression and poor patient prognosis. Interestingly, we found that NQO1 stabilizes the transactivator BCL3, which in turn upregulates NF-κB p50. More importantly, our results also indicate that NF-κB p50 correlates with the expression of NQO1 and mediates its role in the proliferation of melanoma cells.
The lithium-rich manganese cathode material Li2MnO3·LiMO2 (M = Mn, Co, Ni, Fe, etc.) has been received extensive attention for Li-ion batteries owing to its ultra-high specific capacity (>250 mAh g−1) and lower cost. Nevertheless, it is still strictly challengeable to achieve encouraging Li-storage behaviors due to its poor cyclability, rate performance, and voltage decay. Li-rich manganese cathode material Li1.2Mn0.54Ni0.13Co0.13O2 (LRNCM) modified by a novel hybrid conductive layer constructed with Li1.4Al0.4Ti1.6(PO4)3 (LATP) and polyaniline (PANI) is prepared. The hybrid modification layer (LATP&PANI) not only serves as a physical barrier to protect the active material from the electrolyte, but also combines the high ionic conductivity of Li1.4Al0.4Ti1.6(PO4)3 with the excellent electronic conductivity of polyaniline, helping for facilitating the transfer of electrons and lithium ions. The hybrid modification cathode material (LRNCM@3 wt%LATP@1 wt%PANI) displays favorable rate capability and cycle performance, whose capacity retention (2.0–4.8 V at 0.2 C, 25 °C) deliveries 79% after 200 cycles. The hybrid modification is a promising route for remarkable enhancement in performance of the lithium-rich manganese-based cathode materials.
The rare-earth-based AB5-type Mm(NiMnSiAl)4.3Co0.6−x Fe x (x =0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6) hydrogen storage alloys were prepared by casting and rapid quenching. The microstructures of the as-cast and quenched alloys were analysed by XRD, SEM and TEM, and electrochemical cycle stabilities of the alloys were measured. The effects of substituting Co with Fe on microstructures and cycle stabilities of the as-cast and quenched alloys were investigated in detail. The obtained results show that the effects of substituting Co with Fe on the phase structures of the as-cast and quenched alloys are imperceptible, but its effects on cycle stabilities of the alloys are notable. Substituting Co with Fe improves slightly the cycle stabilities of the as-cast alloys, but it can significantly enhance the cycle lives of the as-quenched alloys, which is mainly attributed to the grain refinement of the alloys caused by substituting Co with Fe.
This commentary reviews the neural processes underpinning the learning of social norms, as well the enforcement of these norms through second-party and third-party punishment. The authors suggest how these structures may have formed during our evolutionary history.
The Trial-Ready Cohort for Preclinical and Prodromal Alzheimer’s disease (TRC-PAD) aims to accelerate enrollment for Alzheimer’s disease (AD) clinical trials by remotely identifying and tracking individuals who are at high risk for developing symptoms of AD, and referring these individuals to in-person cognitive and biomarker evaluation with the purpose of engaging them in clinical trials. A risk algorithm using statistical modeling to predict brain amyloidosis will be refined as TRC-PAD advances with a maturing data set.
A glassy carbon electrode modified with LaHCF was constructed and was characterized by cyclic voltammetry (CV) and electrochemical impedance spectrum (EIS). The resulting LaHCF modified glassy carbon electrode had a good catalytic character on uric acid (UA) and was used to detect uric acid and ascorbic acid (AA) simultaneously. This modified electrode exhibits potent and persistent electron-mediating behavior followed by well-separated oxidation peaks towards UA and AA with activation overpotential. For UA and AA in mixture, one can well separate from the other with a potential large enough to allow the determination of one in presence of the other. The DPV peak currents obtained increased linearly on the UA in the range of 2.0×10−7 to 1.0×10−4 mol/L with the detection limit (signal-to-noise ratio was 3) for UA 1.0×10−7 mol/L. The proposed method showed excellent selectivity and stability, and the determination of UA and AA simultaneously in urine was satisfactory.
For maximizing the energy efficiency in a wireless network, we propose two forwarding schemes termed single-link and multi-link energy-efficient forwarding that tradeoff delivery ratios against energy costs. Multi-link forwarding improves the network performance substantially by addressing multiple receivers at once during the packet forwarding process. If the first forwarding node does not receive a packet correctly, other nodes may act as backup nodes and perform the forwarding instead. By means of mathematical analyses, we derive how the energy efficiency of a forwarding path can be computed and how a forwarding tree is established. Routing cycles are explicitly taken into account and prevented by means of sequence numbers. Simulations and real-world experiments provide a comparison to other reference strategies, showing a superior performance of our forwarding scheme in terms of energy efficiency.
Despite widespread focus on porous carbons for lithium-sulfur battery cathode materials, electrode design to preserve mass-specific performance and sustained extended cycling stability remains a challenge. Here, we demonstrate electrochemically etched porous silicon as a sacrificial template to produce a new class of functional mesoporous carbons optimized for dual chemical and physical confinement of soluble polysulfides in lithium-sulfur battery cathodes. Melt infiltration loading of sulfur at 60 wt% enables initial discharge capacity of 1350 mAh/gsulfur at rates of 0.1 C - approaching theoretical capacity of 1675 mAh/gsulfur. Cycling performance measured at 0.2 C indicates 81% capacity retention measured over 100 cycles with 830 mAh/gsulfur capacity. Unlike other carbons, this template combines structural properties necessary for sulfur containment and polysulfide confinement to achieve high specific capacity, but also boasts surface-bound oxygen-containing functional groups that are able to chemically anchor the soluble Li2Sn species on the interior of the mesoporous carbon to sustain cycling performance. In turn, this elucidates a scalable and competitive material framework that is capable, without the addition of additional membranes or inactive anchoring materials, of providing the simultaneous anchoring and confinement effects necessary to overcome performance limitations in lithium sulfur batteries.
The cycling performance of graphite/LiNi0.5Co0.2Mn0.3O2 battery in the electrolyte with different content (0, 0.5, 1.0, 2.0wt.%) 1-propylphosphonic acid cyclic anhydride (PACA) is studied in this work. When 0.5wt.% PACA additive is incorporated into the blank electrolyte, the capacity retention of graphite/LiNi0.5Co0.2Mn0.3O2 battery at high voltage after 100 cycles is increased from 79.12% to 91.84%. Electrochemical impedance spectroscopy (EIS), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS) results reveal the mechanism that the surface film derived from PACA can decrease the surface film impedance of the cell (from 40.63 to 16.57Ω), stabilize the structure of cathode material. Moreover, the investigation of PACA on the cycling performance of graphite electrode demonstrates that PACA function on LiNi0.5Co0.2Mn0.3O2 instead of graphite.
The switching pattern between behavioral modes provides a mechanistic basis for understanding how animals perceive and memorize the habitat quality in their home ranges.
Titanium oxides with a one-dimensional nanostructure are of great significance in electrochemical lithium insertion due to their high specific surface area and pore volume. In this paper, anatase TiO2 nanotubes with diameters of about 10nm and lengths of 200–400nm were synthesized by a hydrothermal process. The phase structure and morphology were analyzed by X-ray diffraction, Raman scattering, and transmission electron microscopy. The electrochemical properties were investigated by constant current discharge–charge and cyclic voltammetry. There is a potential plateau at 1.73 and 1.88V in the process of Li insertion and extraction, and the initial Li insertion/extraction capacity is 290 and 238mAhg−1 at 36mAg−1, respectively. The Li insertion capacity at the potential plateau of 1.73V in the first cycle is about 150mAhg−1. In the 20th cycle, the reversible capacity still remains at about 200mAhg−1, and the coulombic efficiency is approximately 98%, exhibiting excellent cycling stability. The discharging capacity is about 168mAhg−1 in the 30th cycle at 210mAg−1, demonstrating a good high-rate performance. Anatase TiO2 nanotubes might be a promising negative material for lithium-ion batteries.