batterydata/paper-abstracts huggingface dataset:
In the early 1960s, a PhD student in physics, Costas Papaliolios, designed a simple—and playful—system of Polaroid polarizer filters with a specific goal in mind: explaining the core principles behind Julian Schwinger’s quantum mechanical measurement algebra, developed at Harvard in the late 1940s and based on the Stern-Gerlach experiment confirming the quantization of electron spin. Papaliolios dubbed his invention “quantum toys.” This article looks at the origins and function of this amusing pedagogical device, which landed half a century later in the Collection of Historical Scientific Instruments at Harvard University. Rendering the abstract tangible was one of Papaliolios’s demonstration tactics in reforming basic teaching of quantum mechanics. This article contends that Papaliolios’s motivation in creating the quantum toys came from a renowned endeavor aimed, inter alia, at reforming high-school physics training in the United States: Harvard Project Physics. The pedagogical study of these quantum toys, finally, compels us to revisit the central role playful discovery performs in pedagogy, at all levels of training and in all fields of knowledge.
Large variations exist in the revenue prediction of grid-scale storage due to uncertainties in operations of storage technologies. Here the authors integrate the economic evaluation of energy storage with key battery parameters for a realistic measure of revenues.
To obtain a good estimation of particle size distribution and concentration encountered by car passengers during their journeys, an electrical low-pressure impactor was installed in a car. Two measurement campaigns were carried out. The first one covered various traffic conditions in urban and rural areas near Rouen (France). The second campaign covered several journeys up and down the same tunnel. Measurements were recorded in the range 30nm–10μm at 1Hz frequency. The size distributions show two main shapes depending mainly on the concentration. For high concentrations the distributions correspond to diesel emissions with the mode comprised between 60 and 100nm. For low concentrations the maximum of the distribution is located in the finest particle class of the device, between 30 and 60nm. The concentrations observed are generally less than 50000 partcm−3 but may reach more than 106 partcm−3 during specific road events. Likewise high-concentration values may be regularly observed at the end of the tunnel along which the concentration increases linearly, after a surprising decrease. One main conclusion is that on-road measurements are necessary for a correct evaluation of the conditions encountered by car passengers.
Profiles of verbal learning and memory performance were compared for typically developing children and for four developmental disorders characterized by different patterns of language functioning: specific language impairment, early focal brain damage, Williams Syndrome, and Down Syndrome. A list-learning task was used that allowed a detailed examination of the process of verbal learning, recall, and recognition (California Verbal Learning Test—Children’s Version). Distinct patterns of performance characterized the four disorders. These patterns were consistent with the language deficits typically seen in the disorders, with the exception of a dissociation seen in Williams Syndrome.
Spinel Ni-dopped MnCo2O4 powder with fast Li+ intercalation pseudocapacitance is prepared from transition metal carbonates of Ni, Co and Mn as precursors through a solvothermal synthesis followed by an annealing treatment. As-made products are nanovoids submicron-spheres (the diameter is 500 nm–700nm) with an obvious yolk-shell structure and uniform elements distribution. As an anode material with fast Li+ intercalation pseudocapacitance for lithium-ion battery (LIB), the Ni-dopped MnCo2O4 submicron-spheres exhibit an impressively first discharge efficiency (70%) and outstanding large-current cycling performance. The excellent electrochemical performance is closely ascribed to Li+ intercalation pseudocapacitance and the yolk-shell structure, which can effectively prevent the particles from being pulverized, and alleviate the volume changes of particles during the cycling process. In addition, the doping of Ni metal element to MnCo2O4 greatly enhances the electrochemical stability of MnCo2O4, due to the complementarities and synergies between the three metallic elements during the process of Li insertion or extraction reactions.
Aqueous supercapacitors are attracting increasing attention owing to their high power density, cyclability and environmental friendliness. However, the energy density of common aqueous supercapacitors are restricted by low cell voltage and narrow voltage window. Here we demonstrate that such limitations can be overcome with advanced hybrid supercapacitors using multi-layered water-stable protected lithium negative electrode combined with high concentration “water-in-salt” electrolyte. 4 V-class cell voltage with wide voltage window can be delivered for advanced hybrid supercapacitors with capacitive or pesudocapacitive positive electrodes. A typical advanced hybrid supercapacitor with MnO2 electrode shows a 4.4 V maximum cell voltage with a 1.5 V window, an energy density of 405 Wh kg MnO 2 − 1 at a power density of 0.88 kW kg MnO 2 − 1 . A high energy density of 163 Wh kg MnO 2 − 1 is maintained at a power density of 16.7 kW kg MnO 2 − 1 . These advanced hybrid supercapacitors show acceptable cycle stability and good energy retentions (around 90% within 3000 cycles).
Recent research has described the structure of psychopathology as including one general and multiple specific factors, and this structure has been found in samples across development. However, little work has examined whether this structure is consistent across time, particularly in young children, within the same sample. Further, few studies have examined factors that influence the magnitude of the stability of latent dimensions of psychopathology. In the present study, we examine these issues in a community sample of 545 children assessed at ages 3 and 6. In addition, we explored child temperament, parental history of psychopathology, and parenting behaviors as potential moderators of the longitudinal stability of latent dimensions of psychopathology. We found that the same bifactor model structure identified at age 3 provided an adequate fit to the data at age 6. Further, our model revealed significant homotypic stability of the general, internalizing, and externalizing specific factors. We also found evidence of differentiation of psychopathology over time with the general factor at age 3 predicting the externalizing factor at age 6. However, we failed to identify moderators of the longitudinal associations between psychopathology latent factors. Overall, our results bolster support for the bifactor structure of psychopathology, particularly in early childhood.
Transition-metal phosphides are considered as candidates for sodium-ion batteries (SIBs) due to the high theoretical specific capacity. However, serious volume variation and agglomeration during sodiation-desodiation hamper their development. Hence, a microporous structure of Ni2P@C–N polyhedrons embedding in highly rough carbon fiber (Ni2P@C–N⊂CF) is designed as self-supporting anode material. The synergistic effect of ultrasmall Ni2P particles (∼5 nm), graphitic carbon shell and adequate free space of carbon fibers buffer the volume change, the uniform distribution of Ni2P particles shorten Na+ diffusion path, the microporous structure endow adequate electrolyte penetration, the graphitic carbon shell and carbon fibers provide high conductive channel, and thus boosting a remarkable sodium storage performance. The Ni2P@C–N⊂CF delivers long cycling stability (196.8 mAh g−1 at 1000 mA g−1 over 1000 cycles with a capacity dropping of 0.04% cycle−1), superior rate capability (197.1 mAh g−1 at 2000 mA g−1, and returned to 752.5 mAh g−1 at 100 mA g−1). Moreover, the flexible half-cell based on the Ni2P@C–N⊂CF electrode still maintains 81.7% capacity retention after repeated bending states. The full cell based on Ni2P@C–N⊂CF and Na3V2(PO4)3 manifests a capacity of 185.9 mAh g−1 over 100 cycles and energy density of ∼217.4 Wh kg−1 for SIBs. Furthermore, the hybrid energy storage mechanism can also contribute to the outstanding electrochemical performance. The Ni2P@C–N⊂CF shows a potential in flexible electrode materials for Na-storage device.
Network neuroscience has relied on a node-centric network model in which cells, populations and regions are linked to one another via anatomical or functional connections. This model cannot account for interactions of edges with one another. In this study, we developed an edge-centric network model that generates constructs ‘edge time series’ and ‘edge functional connectivity’ (eFC). Using network analysis, we show that, at rest, eFC is consistent across datasets and reproducible within the same individual over multiple scan sessions. We demonstrate that clustering eFC yields communities of edges that naturally divide the brain into overlapping clusters, with regions in sensorimotor and attentional networks exhibiting the greatest levels of overlap. We show that eFC is systematically modulated by variation in sensory input. In future work, the edge-centric approach could be useful for identifying novel biomarkers of disease, characterizing individual variation and mapping the architecture of highly resolved neural circuits.
A gridable vehicle (GV) can be used as a small portable power plant (S3P) to enhance the security and reliability of utility grids. Vehicle-to-grid (V2G) technology has drawn great interest in the recent years and its success depends on intelligent scheduling of GVs or S3Ps in constrained parking lots. V2G can reduce dependencies on small expensive units in existing power systems, resulting in reduced operation cost and emissions. It can also increase reserve and reliability of existing power systems. Intelligent unit commitment (UC) with V2G for cost and emission optimization in power system is presented in this paper. As number of gridable vehicles in V2G is much higher than small units of existing systems, UC with V2G is more complex than basic UC for only thermal units. Particle swarm optimization (PSO) is proposed to balance between cost and emission reductions for UC with V2G. PSO can reliably and accurately solve this complex constrained optimization problem easily and quickly. In the proposed solution model, binary PSO optimizes on/off states of power generating units easily. Vehicles are presented by integer numbers instead of zeros and ones to reduce the dimension of the problem. Balanced hybrid PSO optimizes the number of gridable vehicles of V2G in the constrained parking lots. Balanced PSO provides a balance between local and global searching abilities, and finds a balance in reducing both operation cost and emission. Results show a considerable amount of cost and emission reduction with intelligent UC with V2G. Finally, the practicality of UC with V2G is discussed for real-world applications.
A novel epitaxial thin-film electrode for lithium batteries, with a composition of Li0.92Co0.65Mn1.35O4 and a cubic spinel structure, is fabricated on a SrTiO3(111) single-crystal substrate. Fabrication is carried out by layer-by-layer pulsed laser deposition of LiCoO2 with a layered rock-salt structure and LiMn2O4 with a spinel structure. The electrode is found to exhibit unique disordering of the lithium (8a) and transition-metal (16d) sites, leading to a higher rate capability and cycle retention ratio than those for a thin-film electrode with the same composition prepared by a conventional single-step deposition process. The proposed layer-by-layer deposition method allows an expanded range of compositional and structural variations for lithium battery electrode materials.
A novel preparation technique was developed for synthesizing carbon-coated LiFePO4 nanoparticles through a combination of spray pyrolysis (SP) with wet ball milling (WBM) followed by heat treatment. Using this technique, the preparation of carbon-coated LiFePO4 nanoparticles was investigated for a wide range of process parameters such as ball-milling time and ball-to-powder ratio. The effect of process parameters on the physical and electrochemical properties of the LiFePO4/C composite was then discussed through the results of X-ray diffraction (XRD) analysis, field-emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), the Brunauer–Emmet–Teller (BET) method and the use of an electrochemical cell of Li|1M LiClO4 in EC:DEC=1:1|LiFePO4. The carbon-coated LiFePO4 nanoparticles were prepared at 500°C by SP and then milled at a rotating speed of 800rpm, a ball-to-powder ratio of 40/0.5 and a ball-milling time of 3h in an Ar atmosphere followed by heat treatment at 600°C for 4h in a N2 +3% H2 atmosphere. SEM observation revealed that the particle size of LiFePO4 was significantly affected by the process parameters. Furthermore, TEM observation revealed that the LiFePO4 nanoparticles with a geometric mean diameter of 146nm were coated with a thin carbon layer of several nanometers by the present method. Electrochemical measurement demonstrated that cells containing carbon-coated LiFePO4 nanoparticles could deliver markedly improved battery performance in terms of discharge capacity, cycling stability and rate capability. The cells exhibited first discharge capacities of 165mAhg−1 at 0.1C, 130mAhg−1 at 5C, 105mAhg−1 at 20C and 75mAhg−1 at 60C with no capacity fading after 100 cycles.
This work is focused on the responses of some energy metabolism variables in Cnesterodon decemmaculatus adults exposed to cadmium under controlled laboratory conditions. This species has been used as bioindicator for evaluating the effects of different chemicals on diverse biological processes and is frequently used as test organism in ecotoxicity studies that include cadmium as reference toxicant. Animals were exposed for 12 days to the following concentrations: 0, 0.45, and 0.8 mg Cd/L. Food intake, fecal production, specific assimilation, condition factor, mortality percentage, oxygen consumption, oxygen extraction efficiency, specific metabolic rate, ammonia excretion, and ammonia quotient were measured. The overall balance was expressed as scope for growth (SFG). Cadmium-exposed groups showed a significant decrease in food assimilation and condition factor at the end of the exposure. There was an increase in specific metabolic rate and a decrease in SFG in the group exposed to 0.8 mg Cd/L. The condition factor and the SFG appeared as sensitive biomarkers of health status and growth of the animals, respectively. Cadmium-exposed fish reduced food intake, which was reflected in a decreased assimilation with concomitant decline in the external energy supply from feeding. Our results highlight the importance of considering the metabolic status of the test organisms when analyzing the responses of the biomarkers usually used as effect parameters in ecotoxicological evaluations under experimental conditions.
Hollow core–shell nanorods with a nanogap are designed and constructed with the assistance of atomic layer deposition (ALD) for energy storage applications. As a demonstration, CoO nanorods and NiO nanowalls are enclosed by a TiO2 nanotube shell, forming the “wire in tube” and “wall in box” structures, respectively. A thin sacrificial layer of Al2O3 is deposited by ALD and removed eventually, forming a nanogap between the CoO core (or the NiO nanowall) and the TiO2 shell. When they are tested as supercapacitor electrodes, an evident difference between the solid core–shell nanostructure and hollow ones can be found; for example, the hollow structure shows ∼2 to 4 times the capacitance compared to the solid wires. The electrochemical properties are also superior compared to the bare nanorods without the nanotube shell. The enhancement is ascribed to the conformal hollow design which provides enlarged specific surface areas and a shorter ion transport path. It is prospected that such a positive nanogap effect may also exist in other electrochemical cell electrodes such as lithium ion batteries and fuel cells.
Nowadays, the energy storage technology is bringing new opportunities to the power systems, not only providing the electric grid with regulation, reserve and backup services, but also filling the gap between the timing of production and consumption. This enables price arbitrage techniques, aimed at maximising the economic revenue obtained by charging or discharging the storage, based on the time variation of electricity prices. This paper shows how to optimise the operation of a storage device in presence of a PV generating plant, possibly combined with a local load. An optimisation technique based on a dynamic programming tool implemented with the open source Modelica language is here proposed and tested on different case studies. In particular, different storage sizes and losses models have been considered, as well as the dependence of the storage lifetime on the depth of discharge of its operational cycles. Finally, a payback analysis calibrated on present and future cost scenarios is presented and discussed.
Mobile cloud computing is a new paradigm that uses cloud computing resources to overcome the limitations of mobile computing. Due to its complexity, dependability and performance studies of mobile clouds may require composite modeling techniques, using distinct models for each subsystem and combining state-based and non-state-based formalisms. This paper uses hierarchical modeling and four different sensitivity analysis techniques to determine the parameters that cause the greatest impact on the availability of a mobile cloud. The results show that distinct approaches provide similar results regarding the sensitivity ranking, with specific exceptions. A combined evaluation indicates that system availability may be improved effectively by focusing on a reduced set of factors that produce large variation on the measure of interest. The time needed to replace a fully discharged battery in the mobile device is a parameter with high impact on steady-state availability, as well as the coverage factor for the failures of some cloud servers. This paper also shows that a sensitivity analysis through partial derivatives may not capture the real level of impact for some parameters in a discrete domain, such as the number of active servers. The analysis through percentage differences, or the factorial design of experiments, fulfills such a gap.
Polymer electrolytes offer the most promising solution to address the all-solid-state battery requirements such as flexibility, leak-proof packing and easy processing. In this study, a polymer blend of 25mol% poly(acrylic acid) (PAA) and 75mol% poly(vinyl alcohol) (PVA) was optimized based on its thermal, mechanical and structural properties. The ionic liquid (IL) electrolyte, 1-butyl-1-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide (PYRTFSI) with 0.2m lithium bis(trifluoromethansulfonyl)imide (LiTFSI), was added to the polymer blend in different molar ratios. A maximum ionic conductivity of 1mScm−1 is observed at 90°C in the membrane with 70mol% IL. Cyclic voltammetry of the polymer electrolytes shows peaks corresponding to lithium stripping (+0.25V vs. Li+/Li) and deposition (−0.3V vs. Li+/Li) processes indicating the occurrence of a highly reversible redox process. The electrochemical stability window of these polymer electrolytes, as determined by linear sweep voltammetry, extends up to 5V, suggesting that these electrolytes could be suitable for batteries that use high voltage cathode materials. A lithium transference number (tLi+) of 0.4 was determined for the polymer electrolytes by using chronoamperometry and impedance measurements. Galvanostatic charge-discharge studies of the polymer electrolytes in a lithium half-cell with LiCoO2 (LCO) as cathode delivers a capacity of about 100mAhg−1 at 60°C. Coin-type half-cell with LiFePO4 (LFP) cathode and the polymer electrolyte containing 70mol% IL delivered a capacity of 172mAhg−1. Interestingly, the LFP/polymer composite cathode (LFP-C) delivers a higher capacity (215mAhg−1 at 60°C) than the pristine LiFePO4 cathode.
In this paper we tackle the optimal Discharge Scheduling of Energy Storage systems Problem (DSESP) in MicroGrids, considering renewable generation, and applying hyper-heuristic (HH) algorithms. The problem consists of, given the generation and load profiles in the MicroGrid, obtaining the optimal discharge scheduling of the Energy Storage System (ESS) that minimizes the consumption from the utility grid. HHs are a novel methodology in optimization problems that constructs a solution to a given problem by means of the application of basic heuristics, evolved using a global search algorithm. This methodology can be easily adapted to solve the DSESP, in this case by using an evolutionary algorithm as global approach. In this paper we detail the adaptations performed to a HH to tackle the DSESP, mainly in the encoding of solutions, and new evolutionary operators that improve the evolution of good solutions to the problem. The performance of the proposed approach has been evaluated in a real Microgrid, with different scenarios of generation and load profiles, obtaining around 5% reduction of the energy consumption from the utility grid.
Capacity building strategies are widely used to increase the use of research in policy development. However, a lack of well-validated measures for policy contexts has hampered efforts to identify priorities for capacity building and to evaluate the impact of strategies. We aimed to address this gap by developing SEER (Seeking, Engaging with and Evaluating Research), a self-report measure of individual policymakers’ capacity to engage with and use research.
Introduction The current criteria for detecting a Clinical High-Risk (CHR) state for psychosis do not address cognitive impairment. A first step for identifying cognitive markers of psychosis risk would be to determine which aspects of neurocognitive performance are related with more severe psychotic-like symptoms. This study assessed cognitive impairment associated with prodromal symptoms in adolescents receiving public psychiatric treatment. Methods 189 adolescents were recruited from consecutive new patients aged 15–18 attending mainly outpatient adolescent psychiatric units in Helsinki. They had been screened for prodromal symptoms using the Prodromal Questionnaire, and all screen-positives as well as a random sample of screen-negatives were interviewed using the Structured Interview for Prodromal Symptoms (SIPS) and underwent testing using a large, standardized neurocognitive test battery. The sample included 62 adolescents who met the CHR criteria (CHR) and 112 who did not (non-CHR). A healthy control sample (n =72) was also included to provide age- and gender-matched norms. Results The CHR group performed worse on visuospatial tasks than the non-CHR group. Among CHR adolescents, negative symptoms were associated with slower processing speed and poorer performance on verbal tasks. Among non-CHR adolescents, positive symptoms were associated with poorer performance on visuospatial tasks, and negative symptoms with poorer performance on verbal tasks. Conclusion Clinical high-risk status is associated with impaired visuospatial task performance. However, both positive, psychotic-like symptoms and negative symptoms are associated with lower levels of neurocognitive functioning among adolescents in psychiatric treatment regardless of whether CHR criteria are met. Thus, even mild positive and negative symptoms may have clinical relevance in adolescents in psychiatric care. Adolescents with both psychotic-like symptoms and neurocognitive deficits constitute a group requiring special attention.