Improved silicon nitride for advanced heat engines

The results of a four year program to improve the strength and reliability of injection-molded silicon nitride are summarized. Statistically designed processing experiments were performed to identify and optimize critical processing parameters and compositions. Process improvements were monitored by strength testing at room and elevated temperatures, and microstructural characterization by optical, scanning electron microscopes, and scanning transmission electron microscope. Processing modifications resulted in a 20 percent strength and 72 percent Weibull slope improvement of the baseline material. Additional sintering aids screening and optimization experiments succeeded in developing a new composition (GN-10) capable of 581.2 MPa at 1399 C. A SiC whisker toughened composite using this material as a matrix achieved a room temperature toughness of 6.9 MPa m(exp .5) by the Chevron notched bar technique. Exploratory experiments were conducted on injection molding of turbocharger rotors

Improved silicon nitride for advanced heat engines

The technology base required to fabricate silicon nitride components with the strength, reliability, and reproducibility necessary for actual heat engine applications is presented. Task 2 was set up to develop test bars with high Weibull slope and greater high temperature strength, and to conduct an initial net shape component fabrication evaluation. Screening experiments were performed in Task 7 on advanced materials and processing for input to Task 2. The technical efforts performed in the second year of a 5-yr program are covered. The first iteration of Task 2 was completed as planned. Two half-replicated, fractional factorial (2 sup 5), statistically designed matrix experiments were conducted. These experiments have identified Denka 9FW Si3N4 as an alternate raw material to GTE SN502 Si3N4 for subsequent process evaluation. A detailed statistical analysis was conducted to correlate processing conditions with as-processed test bar properties. One processing condition produced a material with a 97 ksi average room temperature MOR (100 percent of goal) with 13.2 Weibull slope (83 percent of goal); another condition produced 86 ksi (6 percent over baseline) room temperature strength with a Weibull slope of 20 (125 percent of goal)

Liquid biopsy genotyping in lung cancer: ready for clinical utility?

Liquid biopsy is a blood test that detects evidence of cancer cells or tumor DNA in the circulation. Despite complicated collection methods and the requirement for technique-dependent platforms, it has generated substantial interest due, in part, to its potential to detect driver oncogenes such as epidermal growth factor receptor (EGFR) mutants in lung cancer. This technology is advancing rapidly and is being incorporated into numerous EGFR tyrosine kinase inhibitor (EGFR-TKI) development programs. It appears ready for integration into clinical care. Recent studies have demonstrated that biological fluids such as saliva and urine can also be used for detecting EGFR mutant DNA through application other user-friendly techniques. This review focuses on the clinical application of liquid biopsies to lung cancer genotyping, including EGFR and other targets of genotype-directed therapy and compares multiple platforms used for liquid biopsy

Large Enhancement of Spontaneous Emission Rates of InAs Quantum Dots in GaAs Microdisks

Control of spontaneous emission in a microcavity has many important applications, e.g. improvement of the efficiency of light emitting devices. InAs quantum dots (QDs) embedded in microdisks are ideal systems for spontaneous emission control. The whispering gallery (WG) modes of microdisks have low volume and high quality factor. The homogeneous linewidth of InAs quantum dots is smaller than the spectral width of WG modes. Thus, a large enhancement of the spontaneous emission rates should be expected for QDs coupled to WG modes. However, large inhomogeneous broadening of the QD energy levels and random spatial distribution of the QDs in a microdisk lead to a broad distribution of the spontaneous emission rates. Using an efficient regularized method based on the truncated singular value decomposition and the non-negative constraints, we extract the distribution of spontaneous emission rates from the temporal decay of emission intensity. The maximum spontaneous emission enhancement factor exceeds 10

The Acoustic Peak in the Lyman Alpha Forest

We present the first simulation of the signature of baryonic acoustic oscillations (BAO) in Lyman alpha forest data containing 180,000 mock quasar sight-lines. We use eight large dark-matter only simulations onto which we paint the Lyman alpha field using the fluctuating Gunn-Peterson approximation. We argue that this approach should be sufficient for the mean signature on the scales of interest. Our results indicate that Lyman alpha flux provides a good tracer of the underlying dark matter field on large scales and that redshift space distortions are well described by a simple linear theory prescription. We compare Fourier and configuration space approaches to describing the signal and argue that configuration space statistics provide useful data compression. We also investigate the effect of a fluctuating photo-ionizing background using a simplified model and find that such fluctuations do add smooth power on large scales. The acoustic peak position is, however, unaffected for small amplitude fluctuations (<10%). Larger amplitude fluctuations make the recovery of the BAO signal more difficult and may degrade the achievable significance of the measurement.Comment: 10 pages, 8 figures; v2: minor revision matching version accepted by JCAP (new references, better figures, clarifications

Shapes of Gas, Gravitational Potential and Dark Matter in Lambda-CDM Clusters

We present analysis of the three-dimensional shape of intracluster gas in clusters formed in cosmological simulations of the Lambda-CDM cosmology and compare it to the shape of dark matter distribution and the shape of the overall isopotential surfaces. We find that in simulations with radiative cooling, star formation and stellar feedback (CSF), intracluster gas outside the cluster core is more spherical compared to non-radiative (NR) simulations, while in the core the gas in the CSF runs is more triaxial and has a distinctly oblate shape. The latter reflects the ongoing cooling of gas, which settles into a thick oblate ellipsoid as it loses thermal energy. The shape of the gas in the inner regions of clusters can therefore be a useful diagnostic of gas cooling. We find that gas traces the shape of the underlying potential rather well outside the core, as expected in hydrostatic equilibrium. At smaller radii, however, the gas and potential shapes differ significantly. In the CSF runs, the difference reflects the fact that gas is partly rotationally supported. Interestingly, we find that in NR simulations the difference between gas and potential shape at small radii is due to random gas motions, which make the gas distribution more spherical than the equipotential surfaces. Finally, we use mock Chandra X-ray maps to show that the differences in shapes observed in three-dimensional distribution of gas are discernible in the ellipticity of X-ray isophotes. Contrasting the ellipticities measured in simulated clusters against observations can therefore constrain the amount of cooling of the intracluster medium and the presence of random gas motions in cluster cores.Comment: 11 pages, 8 figures, 3 tables, updated to match the version accepted for publication in the Astrophysical Journa

Constraining Cluster Physics with the Shape of X-ray Clusters: Comparison of Local X-ray Clusters versus LCDM Clusters

Simulations of cluster formation have demonstrated that condensation of baryons into central galaxies during cluster formation can drive the shape of the gas distribution in galaxy clusters significantly rounder, even at radii as large as half of the virial radius. However, such simulations generally predict stellar fractions within cluster virial radii that are ~2 to 3 times larger than the stellar masses deduced from observations. In this work we compare ellipticity profiles of clusters simulated with and without baryonic cooling to the cluster ellipticity profiles derived from Chandra and ROSAT observations in an effort to constrain the fraction of gas that cools and condenses into the central galaxies within clusters. We find that the observed ellipticity profiles are fairly constant with radius, with an average ellipticity of 0.18 +/- 0.05. The observed ellipticity profiles are in good agreement with the predictions of non-radiative simulations. On the other hand, the ellipticity profiles of the clusters in simulations that include radiative cooling, star formation, and supernova feedback (but no AGN feedback) deviate significantly from the observed ellipticity profiles at all radii. The simulations with cooling overpredict (underpredict) ellipticity in the inner (outer) regions of galaxy clusters. By comparing the simulations with and without cooling, we show that the cooling of gas via cooling flows in the central regions of simulated clusters causes the gas distribution to be more oblate in the central regions, but makes the outer gas distribution more spherical. We find that late-time gas cooling and star formation are responsible for the significantly oblate gas distributions in cluster cores, but the gas shapes outside of cluster cores are set primarily by baryon dissipation at high redshift z > 2.Comment: 10 pages, 6 figures, matching the published version in ApJ. Corrected missing reference in the arxiv versio

A computational study of diffusion in a glass-forming metallic liquid

Liquid phase diffusion plays a critical role in phase transformations (e.g. glass transformation and devitrification) observed in marginal glass forming systems such as Al-Sm. Controlling transformation pathways in such cases requires a comprehensive description of diffusivity, including the associated composition and temperature dependencies. In the computational study reported here, we examine atomic diffusion in Al-Sm liquids using ab initio molecular dynamics (AIMD) and determine the diffusivities of Al and Sm for selected alloy compositions. Non-Arrhenius diffusion behavior is observed in the undercooled liquids with an enhanced local structural ordering. Through assessment of our AIMD result, we construct a general formulation for Al-Sm liquid, involving a diffusion mobility database that includes composition and temperature dependence. A Volmer-Fulcher-Tammann (VFT) equation is adopted for describing the non-Arrhenius behavior observed in the undercooled liquid. The composition dependence of diffusivity is found quite strong, even for the Al-rich region contrary to the sole previous report on this binary system. The model is used in combination with the available thermodynamic database to predict specific diffusivities and compares well with reported experimental data for 0.6 at.% and 5.6 at.% Sm in Al-Sm alloys

Single-molecule RNA detection at depth via hybridization chain reaction and tissue hydrogel embedding and clearing

Accurate and robust detection of mRNA molecules in thick tissue samples can reveal gene expression patterns in single cells within their native environment. Preserving spatial relationships while accessing the transcriptome of selected cells is a crucial feature for advancing many biological areas, from developmental biology to neuroscience. However, because of the high autofluorescence background of many tissue samples, it is difficult to detect single-molecule fluorescence in situ hybridization (smFISH) signals robustly in opaque thick samples. Here, we draw on principles from the emerging discipline of dynamic nucleic acid nanotechnology to develop a robust method for multi-color, multi-RNA, imaging in deep tissues using single-molecule hybridization chain reaction (smHCR). Using this approach, single transcripts can be imaged using epifluorescence, confocal or selective plane illumination microscopy (SPIM) depending on the imaging depth required. We show that smHCR has high sensitivity in detecting mRNAs in cell culture and whole-mount zebrafish embryos, and that combined with SPIM and PACT (PAssive CLARITY Technique) tissue hydrogel embedding and clearing, smHCR can detect single mRNAs deep within thick (0.5 mm) brain slices. By simultaneously achieving ∼20-fold signal amplification and diffraction-limited spatial resolution, smHCR offers a robust and versatile approach for detecting single mRNAs in situ, including in thick tissues where high background undermines the performance of unamplified smFISH