12 research outputs found
Physicochemical studies of direct interactions between lung surfactant and components of electronic cigarettes mixtures
Direct physicochemical interactions between the major components of electronic cigarette liquids (e-liquids): glycerol (VG) and propylene glycol (PG), and lung surfactant (LS) were studied by determining the dynamic surface tension under a simulated breathing cycle using drop shape method. The studies were performed for a wide range of concentrations based on estimated doses of e-liquid aerosols (up to 2500 × the expected nominal concentrations) and for various VG/PG ratios. The results are discussed as relationships among mean surface tension, surface tension amplitude, and surface rheological properties (dilatational elasticity and viscosity) versus concentration and composition of e-liquid. The results showed that high local concentrations (>200 × higher than the estimated average dose after a single puffing session) may induce measurable changes in biophysical activity of LS; however, only ultra-high e-liquid concentrations inactivated the surfactant. Physiochemical characterization of e-liquids provide additional insights for the safety assessment of electronic nicotine delivery systems (ENDS)
Impact of the synthesis parameters on the microstructure of nano-structured LTO prepared by glycothermal routes and 7Li NMR structural investigations
The efficient materials for Li-ion battery electrodes require suitable composition, high-crystallinity and appropriate structuration. The last one is important to assure an efficient exchange of Li ions between the anode and electrolyte, thus enhancing the kinetics of electrochemical reactions. Therefore, the synthesis of well-crystallized nano-sized electrode materials exhibiting high surface area is of great interest. Herein, we explore the influence of the glycothermal synthesis variations on the structure and porosity of Li4Ti5O12. The utilized precursors and their concentration have a minor influence on crystallites size, but they could be used to control the porosity of assembled particles. The prepared Li-ion battery anode could be charged at low and high rate reaching the theoretical capacity of Li4Ti5O12. The material retains its peculiar porous structuration even after 1000 cycles at charging/discharging rate of 50C which contributes to the lack of capacity fading. Additionally, 7Li NMR is performed on one of synthesized nano-structured Li4Ti5O12 and compared with commercially available nanosized Li4Ti5O12 to understand the excellent electrochemical performance. Open image in new window Glycothermal synthesis of lithium titanate, in 1,4-butanediol leads to crystalline NPs of 4-5 nm assembled into highly porous microstructures. Such structuration assures well-developed contact area between the electrode and an electrolyte in Li-ion batteries, which facilitates exchange of Li-ions. Therefore, the material shows excellent electrochemical performances. LTO characterized by different nanostructuration is obtained by varying the synthesis conditions (precursors type and concentration, temperature and co-solvent). , Highlights Pure nanostructure Li4Ti5O12 was synthesized in varying glycothermal conditions using 1,4-butanediol as the solvent. Simple adjustment of precursors and their concentration tuned the microstructure of the material without affecting the size of crystallites which oscillated around 4 nm. Nano-scaling and proper microstructuration is an effective way to improve kinetics of electrochemical reactions due to the efficient exchange of Li ions between electrodes and electrolytes. 7Li NMR was performed on synthesized material and commercial one in order to understand the peculiar electrochemical properties of the material
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IDEAL: Images Across Domains, Experiments, Algorithms and Learning
Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds