Pairing fluctuations in trapped fermi gases

We examine the contribution of pairing fluctuations to the superfluid order parameter for harmonically trapped atomic Fermi gases in the BCS regime. In the limit of small systems we consider, both analytically and numerically, their space and temperature dependence. We predict a parity effect, i.e., that pairing fluctuations show a maximum or a minimum at the center of the trap, depending on the value of the last occupied shell being even or odd. We propose to detect pairing fluctuations by measuring the density-density correlation function after a ballistic expansion of the gas.     

In vivo quantitative 1H MRS of cerebellum and evaluation of quantitation reproducibility by simulation of different levels of noise and spectral resolution

A quantitative analysis of cerebellar metabolites in normal subjects has been performed by proton MR spectroscopy (MRS) with relaxation time correction. Quantitation was carried out in seven healthy human subjects with the well-established LCModel program. The prior knowledge utilized for quantitation was obtained from solutions containing the major brain metabolites and MRS investigated under the same experimental conditions. The tissue water signal was used as an internal standard for the in vivo studies. Both in vitro (for the prior knowledge template) and in vivo data were acquired separately at 1.5 T by PRESS sequence (TR, 1500 ms; TE, 30 ms). The absolute concentration of main cerebellar metabolites was corrected for relaxation time effects. Different noise and line broadening conditions were considered and simulated in the spectral processing in order to evaluate the effect of spectral quality on the concentration estimates.     

Integral and differential form of the protein folding problem

The availability of the complete genomic sequences of many species, including human, has raised enormous expectations in medicine, pharmacology, ecology, biotechnology and forensic sciences. However, knowledge is only a first step toward understanding, and we are only at the early stage of a scientific process that might lead us to satisfy all the expectations raised by the genomic projects. In this review I will discuss the present status of computational methods that attempt to infer the unique three-dimensional structure of proteins from their amino acid sequences. Although this problem has been defined as the “holy grail” of biology, it represents only one of the many hurdles in our path towards the understanding of life at a molecular level.     

Trapped ion chain as a neural network: error resistant quantum computation

We demonstrate the possibility of realizing a neural network in a chain of trapped ions with induced long range interactions. Such models permit one to store information distributed over the whole system. The storage capacity of such a network, which depends on the phonon spectrum of the system, can be controlled by changing the external trapping potential. We analyze the implementation of error resistant universal quantum information processing in such systems.     

Determining the efficacy of a nanotechnology media product in enhancing children’s engagement with nanotechnology

Public engagement in nanotechnology media products can lead to a greater interest in understanding of nanotechnology. A study was undertaken to determine middle school student engagement in Nanooze, a magazine featuring nanotechnology research that has been developed for a young adult audience. Teachers at 116 Detroit middle schools distributed two issues of the magazine to their students, and surveys were collected from 870 students after reading the magazines. Results suggest that the majority of students liked reading the magazine and learned something about nanotechnology. Engagement in nanotechnology led to understanding of nanotechnology. The Nanooze magazine was an effective medium for engaging middle school students in learning about nanotechnology.     

Nano organic carbon and soot in turbulent non-premixed ethylene flames

Spectral optical techniques are combined to characterise the distribution of large-molecule soot precursors, nanoparticles of organic carbon, and soot in two turbulent non-premixed ethylene flames with differing residence times. Laser-induced fluorescence, laser-induced incandescence and light scattering are used to define distributions across the particle size distribution. From the scattering and laser-induced emission measurements it appears that two classes of particles are formed. The first ones are preferentially formed in the fuel-rich region of the flame closer to the nozzle, have sizes of the order of few nanometers but are not fully solid particles, because the constituent molecules still maintain their individual identity exhibiting strong broadband fluorescence in the UV. The second class of particles constituted by solid particles, with sizes of the order of tens of nanometers are able to absorb a sufficient number of photons to be heated to incandescent temperatures. These larger particles are formed at larger residence times in the flame since they are the result of slow growth processes such as coagulation or carbonization. The flames are also modeled in order to produce mixture fraction maps. A new discovery is that nanoparticles of organic carbon concentration, unlike soot, does correlate well with mixture fraction, independent of position in the flame. This is likely to be a significant benefit to future modelling of soot inception processes in turbulent non-premixed flames.     

Examining metal nanoparticle surface chemistry using hollow-core, photonic-crystal, fiber-assisted SERS

In this Letter, we demonstrate the efficacy of hollow core photonic crystal fibers (HCPCFs) as a surface-enhanced Raman spectroscopy (SERS) platform for investigating the ligand exchange process on the surface of gold nanoparticles. Raman measurements carried out using this platform show the capability to monitor minute amounts of surface ligands on gold nanoparticles used as an SERS substrate. The SERS signal from an HCPCF exhibits a tenfold enhancement compared to that in a direct sampling scheme using a cuvette. Using exchange of cytotoxic cetyltrimethylammonium bromide with α-methoxy-ω-mercaptopoly(ethylene glycol) on the surface of gold nanorods as an exemplary system, we show the feasibility of using HCPCF SERS to monitor the change in surface chemistry of nanoparticles.     

Theoretical diagnostic and prediction of physical properties of quaternary InGaAsP compound using artificial neural networks optimized by the Levenberg Maquardt algorithm

The quaternaries \(In_{1 - x} Ga_{x} As_{y} P_{1 - y}\) are the main promising elements for the fabrication of optoelectronic devices. The adjustment of their physical parameters is assumed by the change of the molar fraction \(x\) and \(y\). These parameters can be affected by the variation of temperature and pressure. To make the theoretical diagnosis of these materials, it is fundamental to know the energy gap ‘\(\varvec{E}_{\varvec{g}}\)’ and the lattice parameter ‘\(a\)’, over a wide range of chemical compositions \(0 \le x \le 0.47\) and \(0 \le y \le 1\), at different temperatures and pressures. We show that by using the Artificial Neural Network method optimized by the Levenberg Maquardt algorithm ANN-LM, it is possible to obtain results very close to the experiment. The scatter plot and error calculation show that the ANN-LM model provides more accurate values of the lattice parameter than those calculated by Vegard’s law. On the other hand, the energy gap values \(Eg (x, y, T)\) estimated, using the ANN-LM model, proved to be close to the experimental values that those calculated by the empirical equations. In addition, the ANN-LM method allowed us to estimate with great accuracy the values of the energy gap at different temperatures and pressures \(Eg (P, T)\). Our work provides crucial information on the physical properties of the quaternary without the use of approximations, and without taking into account the hypothesis of a perfect agreement between \(InGaAsP\) and \(InP\) substrate.