Temperature-Dependent Radiation Induced Conductivity of Diverse Highly Disordered Insulating Materials

Incident high energy electron radiation deposits energy in highly disordered insulating materials, exciting electrons from localized trap states into the conduction band, thereby enhancing the radiation induced conductivity (RIC) of these extremely poor conductors. RIC depends on the power deposited in the material and sample temperature, through the details of the energy density of disordered states within the band gap. We compare RIC measurements from 30 K to 300 K for two materials—polymeric polyimide (Kapton) and glassy fused silica (SiO2/SiOx)—that exhibit different temperature dependence and response as the electron beam is turned on and off. A simple theory for RIC, based on thermally-assisted hopping conductivity, is presented to explain the observed differences in terms of constant, exponential and Gaussian densities of disordered states. We also discuss the differences seen which result from the use of very high energy (10’s MeV) penetrating radiation (which deposits primarily energy in the thin samples) and high energy (100’s keV) nearly-penetrating radiation (which deposits both energy and some charge in the materials)

Stereoselective Phosphine-Catalyzed Synthesis of Highly Functionalized Diquinanes

Two rings to rule them all: A versatile method has been developed for the room‐temperature synthesis of diquinanes from acyclic precursors, thereby generating two rings, three stereocenters, and a double bond with high selectivity. The products of the double cyclization can be derivatized with excellent diastereoselection into an array of highly functionalized compounds. [reaction image] In 2003, Tomika and co‐workers reported an intriguing PnBu3‐catalyzed diastereoselective cyclization of certain yne‐diones to form bicyclic furanones with two new stereocenters (Figure 1).1 They proposed that conjugate addition of the phosphine to the alkyne is followed by tautomerization, which furnishes zwitterionic enolate A. Next, an intramolecular aldol reaction provides B, and then a second conjugate addition generates bicycle C (the conversion of A into C by a concerted cycloaddition may also be considered). Tautomerization and then elimination of the phosphine affords the bicyclic furanone. The investigation by Tomita et al. focused mainly on symmetrical substrates (R1=-C≡CR), although they did report reactions of two unsymmetrical yne‐diones which cyclized in relatively modest yield (41–50 %)

Predictive Formula for Electron Penetration Depth of Diverse Materials over Large Energy Ranges

An empirical model that predicts the approximate electron penetration depth—or range—of some common materials has been extended to predict the range for a broad assortment of other materials. The electron range of a material is the maximum distance electrons can travel through a material, before losing all of their incident kinetic energy. The original model used the Continuous Slow Down Approximation (CSDA) for energy deposition in a material to develop a composite analytical formula which estimated the range from10 MeV with an uncertainty of200 materials which have tabulated range and inelastic mean free path data in the NIST ESTAR and IMFP databases. Correlations of with key material constants (e.g., density, atomic number, atomic weight, and band gap) were established for this large set of materials. Somewhat different correlations were found for different sub-classes of materials (e.g., solids/liquids/gases, conductors/semi-conductors/insulators, elements/compounds/polymers/ composites). A predictive formula was developed to accurately determine for arbitrary materials

MAP Estimation for Hyperspectral Image Resolution Enhancement Using an Auxiliary Sensor

This paper presents a novel maximum a posteriori (MAP) estimator for enhancing the spatial resolution of an image using co-registered high spatial-resolution imagery from an auxiliary sensor. Here we focus on the use of high-resolution panchomatic data to enhance hyperspectral imagery. However, the estimation framework developed allows for any number of spectral bands in the primary and auxiliary image. The proposed technique is suitable for applications where some correlation, either localized or global, exists between the auxiliary image and the image being enhanced. To exploit localized correlations, a spatially varying statistical model, based on vector quantization, is used. Another important aspect of the proposed algorithm is that it allows for the use of an accurate observation model relating the “true” scene with the low-resolutions observations. Experimental results with hyperspectral data derived from the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) are presented to demonstrate the efficacy of the proposed estimator

Properties of PAN Fibers Solution Spun into a Chilled Coagulation Bath at High Solvent Compositions

In this work, multifilament, continuous polyacrylonitrile (PAN) fiber tow was solution spun mimicking industrial processing at the small pilot scale (0.5 k tow), while carefully altering the composition of the coagulation bath, in order to determine the effect on the resulting fiber shape, density, orientation, and tensile properties at varying points in the spinning process. Novel here are the abnormally high coagulation bath solvent compositions investigated, which surpass those often reported in the literature. In addition, the coagulation bath was maintained at a slightly chilled temperature, contrary to reported methods to produce round fibers. Further, by altering the composition of the bath in a step-wise fashion during a single spinning run, variations in all other process parameters were minimized. We found that with increasing solvent composition in the coagulation bath, the fibers not only became round in cross section, but also became smaller in diameter, which persisted down the spin line. With this decrease in diameter, all else equal, came an accompanying increase in apparent fiber density via a reduction in microvoid content. In addition, molecular orientation and tensile properties also increased. Therefore, it was found that inadequate understanding of the coagulation bath effects, and spinning at low coagulation bath solvent compositions, can hinder the ability of the fiber to reach optimum properties

Predictive Formula for Electron Range over a Large Span of Energies

An empirical model developed by the Materials Research Group that predicts the approximate electron penetration depth—or range—of some common materials has been extended to predict the range for a broad assortment of other materials. The electron range of a material is the maximum distance electrons can travel through a material, before losing all of their incident kinetic energy. The original model used the Continuous-Slow-Down-Approximation for energy deposition in a material to develop a composite analytical formula which estimated the range from 10 MeV with an uncertainty of v, which describes the effective number of valence electrons. NV was empirically calculated for \u3e200 materials which have tabulated range and inelastic mean free path data in the NIST ESTAR and IMFP databases. Correlations of NV with key material constants (e.g., density, atomic number, atomic weight, and band gap) were established for this large set of materials. Somewhat different correlations were found for different sub-classes of materials (e.g., solids/liquids/gases, conductors/semiconductors/insulators, elements/compounds/polymers/composites). Values of the average energy lost per inelastic collision were related to band gap and plasmon energies for solids and first excitation energies for liquids and gases. Simulations were performed to test the sensitivity of NV and the range to materials parameters; these suggest that reasonably accurate results were achievable with modest precision of the parameters. These correlations have led to methods using only basic material properties to predict Nv and the range for additional untested materials which have no supporting range data. Estimates for both simple compounds (e.g., BN and AlN), composites, and complex biological materials (e.g., brain tissue and cortical bone tissue) are presented, along with tests of the validity and accuracy of the predictive formula. These calculations are of great value for studies involving high energy electron bombardment, such as electron spectroscopy, spacecraft charging, or electron beam therapy. Efforts are underway to create a user tool available to the scientific community to estimate the range of an arbitrary material with modest accuracy over an extended width of incident electron energies. *Supported through funding from NASA Goddard Space Flight Center and a USU URCO Fellowship

Secondary Electron Yield Measurements of Carbon Nanotube Forests: Dependence on Morphology and Substrate

Total, secondary, and backscatter electron yield data were taken with beam energies between 15 eV and 30 keV, in conjunction with energy emission data, to determine the extent of suppression of yield caused by carbon nanotube (CNT) forest coatings on substrates. CNT forests can potentially lower substrate yield due to both its inherently low-yield, low-atomic number (Z) carbon composition, and its bundled, high-aspect ratio structure. Rough surfaces, and in particular, surfaces with deep high-aspect-ratio voids, can suppress yields, as the electrons emitted from lower lying surfaces are recaptured by surface protrusions rather than escaping the near-surface region. Yields of multilayered materials can be modeled essentially serially as a combination of the constituents. However, it is shown that suppression of yields due to CNT forest morphology is more significant than simple predicted contributions of homogeneous layered components. This effect is found to be most pronounced at low energies, where the incident electrons interact preferentially with the CNTs. CNT forests between 20 and 50 μm tall were grown on a thick silicon substrate capped with a 3-nm diffusion barrier of evaporated aluminum using a wet injection chemical vapor deposition (CVD) method. Yields of an annealed substrate and constituent bulk materials were also investigated. At incident electron energies above ~1200 eV, the substrate secondary yield dominated those of the CNT forests, as incident electrons penetrated through the low-density, low-Z CNT forests, and backscattered from the higher-Z substrate. At lower energies \u3c1200 \u3eeV, the CNT forests substantially reduced the overall yields of the substrate, and for \u3c500 eV CNT forest yields were \u3c1, well below the already low yields of bulk graphite. This suppressed yield at low energies is attributed to the porosity and preferred vertical alignment of the CNT forest. The yield’s dependence on the height and density of the CNT forest is also discussed