27 research outputs found
Synthesis of carbon nanotubes by microwave heating: Influence of diameter of catalytic Ni nanoparticles on diameter of CNTs
We rapidly synthesized multi walled carbon nanotubes (MWCNTs) by calcination of granulated polystyrene with nickel nanoparticles having different average diameter (D-Ni = 10, 20, 50 or 90 nm) under nitrogen gas at a certain temperature and time (700 degrees C, 15 min or 800 degrees C, 10 min), using a domestic microwave oven in order to systematically investigate the influence of the diameter of nickel nanoparticles on the diameter of MWCNTs. The MWCNTs synthesized here were characterized by a transmission electron microscope, a Raman spectrophotometer and a wide angle X-ray diffractometer. We found that for the calcination condition of (800 degrees C, 10 min), a relationship between the outer diameter of the resulted carbon nanotubes (D-CNT) and the diameter of catalytic nickel nanoparticles (D-Ni) can be described as a linear function, D-CNT = 1.01D(Ni) + 14.79 nm with the correlation coefficient R = 0.99, and that for the calcination condition of 700 degrees C, 15 min, D-CNT = 1.12D(Ni) + 7.80 nm with R = 0.95. Thus, we revealed that when the diameter of the catalytic nickel nanoparticles (D-Ni) increases by 1 nm, the outer diameter of the obtained MWCNTs (D-CNT) increases by about 1 nm.ArticleJOURNAL OF MATERIALS CHEMISTRY A. 2(8):2773-2780 (2014)journal articl
Exploring the baryonic effect signature in the Hyper Suprime-Cam Year 3 cosmic shear two-point correlations on small scales: the tension remains present
The baryonic feedback effect is considered as a possible solution to the
so-called tension indicated in cosmic shear cosmology. The baryonic
effect is more significant on smaller scales, and affects the cosmic shear
two-point correlation functions (2PCFs) with different scale- and
redshift-dependencies from those of the cosmological parameters. In this paper,
we use the Hyper Suprime-Cam Year 3 (HSC-Y3) data to measure the cosmic shear
2PCFs () down to 0.28 arcminutes, taking full advantage of the high
number density of source galaxies in the deep HSC data, to explore a possible
signature of the baryonic effect. While the published HSC analysis used the
cosmic shear 2PCFs on angular scales, which are sensitive to the matter power
spectrum at , the smaller scale HSC cosmic shear
signal allows us to probe the signature of matter power spectrum up to . Using the accurate emulator of the nonlinear matter power
spectrum, DarkEmulator2, we show that the dark matter-only model can provide an
acceptable fit to the HSC-Y3 2PCFs down to the smallest scales. In other words,
we do not find any clear signature of the baryonic effects or do not find a
systematic shift in the value with the inclusion of the smaller-scale
information as would be expected if the baryonic effect is significant.
Alternatively, we use a flexible 6-parameter model of the baryonic effects,
which can lead to both enhancement and suppression in the matter power spectrum
compared to the dark matter-only model, to perform the parameter inference of
the HSC-Y3 2PCFs. We find that the small-scale HSC data allow only a fractional
suppression of up to 5 percent in the matter power spectrum at , which is not sufficient to reconcile the tension.Comment: 30 pages, 16 figure
Influence of substituent modifications on the binding of 2-amino-1,8-naphthyridines to cytosine opposite an AP site in DNA duplexes: thermodynamic characterization
Here, we report on a significant effect of substitutions on the binding affinity of a series of 2-amino-1,8-naphthyridines, i.e., 2-amino-1,8-naphthyridine (AND), 2-amino-7-methyl-1,8-naphthyridine (AMND), 2-amino-5,7-dimethyl-1,8-naphthyridine (ADMND) and 2-amino-5,6,7-trimethyl-1,8-naphthyridine (ATMND), all of which can bind to cytosine opposite an AP site in DNA duplexes. Fluorescence titration experiments show that the binding affinity for cytosine is effectively enhanced by the introduction of methyl groups to the naphthyridine ring, and the 1:1 binding constant (106 M−1) follows in the order of AND (0.30) < AMND (2.7) < ADMND (6.1) < ATMND (19) in solutions containing 110 mM Na+ (pH 7.0, at 20°C). The thermodynamic parameters obtained by isothermal titration calorimetry experiments indicate that the introduction of methyl groups effectively reduces the loss of binding entropy, which is indeed responsible for the increase in the binding affinity. The heat capacity change (ΔCp), as determined from temperature dependence of the binding enthalpy, is found to be significantly different between AND (−161 cal/mol K) and ATMND (−217 cal/mol K). The hydrophobic contribution appears to be a key force to explain the observed effect of substitutions on the binding affinity when the observed binding free energy (ΔGobs) is dissected into its component terms
Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method
A particle-based cloud model was developed for meter- to submeter-scale-resolution simulations of warm clouds. Simplified cloud microphysics schemes have already made meter-scale-resolution simulations feasible; however, such schemes are based on empirical assumptions, and hence they contain huge uncertainties. The super-droplet method (SDM) is a promising candidate for cloud microphysical process modeling and is a particle-based approach, making fewer assumptions for the droplet size distributions. However, meter-scale-resolution simulations using the SDM are not feasible even on existing high-end supercomputers because of high computational cost. In the present study, we overcame challenges to realize such simulations. The contributions of our work are as follows: (1) the uniform sampling method is not suitable when dealing with a large number of super-droplets (SDs). Hence, we developed a new initialization method for sampling SDs from a real droplet population. These SDs can be used for simulating spatial resolutions between meter and submeter scales. (2) We optimized the SDM algorithm to achieve high performance by reducing data movement and simplifying loop bodies using the concept of effective resolution. The optimized algorithms can be applied to a Fujitsu A64FX processor, and most of them are also effective on other many-core CPUs and possibly graphics processing units (GPUs). Warm-bubble experiments revealed that the throughput of particle calculations per second for the improved algorithms is 61.3 times faster than those for the original SDM. In the case of shallow cumulous, the simulation time when using the new SDM with 32–64 SDs per cell is shorter than that of a bin method with 32 bins and comparable to that of a two-moment bulk method. (3) Using the supercomputer Fugaku, we demonstrated that a numerical experiment with 2 m resolution and 128 SDs per cell covering 13 824²×3072 m³ domain is possible. The number of grid points and SDs are 104 and 442 times, respectively, those of the highest-resolution simulation performed so far. Our numerical model exhibited 98 % weak scaling for 36 864 nodes, accounting for 23 % of the total system. The simulation achieves 7.97 PFLOPS, 7.04 % of the peak ratio for overall performance, and a simulation time for SDM of 2.86×10¹³ particle ⋅ steps per second. Several challenges, such as incorporating mixed-phase processes, inclusion of terrain, and long-time integrations, remain, and our study will also contribute to solving them. The developed model enables us to study turbulence and microphysics processes over a wide range of scales using combinations of direct numerical simulation (DNS), laboratory experiments, and field studies. We believe that our approach advances the scientific understanding of clouds and contributes to reducing the uncertainties of weather simulation and climate projection