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At least 865 records · Page 48

Interstellar grain chemistry and organic molecules

The detection of prominant infrared absorption bands at 3250, 2170, 2138, 1670 and 1470 cm(-1) (3.08, 4.61, 4.677, 5.99 and 6.80 micron m) associated with molecular clouds show that mixed molecular (icy) grain mantles are an important component of the interstellar dust in the dense interstellar medium. These ices, which contain many organic molecules, may also be the production site of the more complex organic grain mantles detected in the diffuse interstellar medium. Theoretical calculations employing gas phase as well as grain surface reactions predict that the ices should be dominated only by the simple molecules H2O, H2CO, N2, CO, O2, NH3, CH4, possibly CH3OH, and their deuterated counterparts. However, spectroscopic observations in the 2500 to 1250 cm(-1)(4 to 8 micron m) range show substantial variation from source reactions alone. By comparing these astronomical spectra with the spectra of laboratory-produced analogs of interstellar ices, one can determine the composition and abundance of the materials frozen on the grains in dense clouds. Experiments are described in which the chemical evolution of an interstellar ice analog is determined during irradiation and subsequent warm-up. Particular attention is paid to the types of moderately complex organic materials produced during these experiments which are likely to be present in interstellar grains and cometary ices.

Allamandola, L. J.↗

Novel Microstructures for Polymer-Liquid Crystal Composite Materials

There are a number of interface-dominated composite materials that contain a liquid crystalline (LC) phase in intimate contact with an isotropic phase. For example, polymer- dispersed liquid crystals, used in the fabrication of windows with switchable transparency, consist of micron size LC droplets dispersed in an isotropic polymer matrix. Many other types of liquid crystal composite materials can be envisioned that might have outstanding optical properties that could be exploited in novel chemical sensors, optical switches, and computer displays. This research project was based on the premise that many of these potentially useful LC composite materials can only be fabricated under microgravity conditions where gravity driven flows are absent. In the ground-based research described below, we have focused on a new class of LC composites that we call thermotropic- lyotropic liquid crystal systems (TLLCs). TLLCs consist of nanosize droplets of water dispersed in an LC matrix, with surfactants at the interface that stabilize the structure. By varying the type of surfactant one can access almost an infinite variety of unusual LC composite microstructures. Due to the importance of the interface in these types of systems, we have also developed molecular simulation models for liquid crystals at interfaces, and made some of the first measurements of the interfacial tension between liquid crystals and water.

Magda, Jules J.↗

Chemical and physical studies of type 3 chondrites. XI - Metamorphism, pairing, and brecciation of ordinary chondrites

The present study reports recent measurements of the induced thermoluminescence (TL) properties of 69 type-3 ordinary chondrites, bringing to 125 the number of type-3 ordinary chondrites for which TL data are available. The samples include several of the particularly low petrographic type and many breccias, some of them gas-rich. The significance of the data with respect to the physical conditions affecting metamorphism is discussed. The TL data, olivine heterogeneity, carbon content, and inert-gas content were used to assign the samples to petrologic types. Twelve meteorites were identified as being type 3.0-3.2, and 10 of the breccias were found to contain material that may also be of this type. The temperature and width of the induced TL peak are also related to thermal history, with type 3.2-3.4 chondrites tending to have narrower peaks at lower glow curve temperatures than the type 3.6-3.9 chondrites. Type 3 H chondrites were found to be a higher petrographic type than the type 3 L and LL chondrites.

Sears, D. W. G.↗

Tarda and Tagish Lake: Samples From The Same Outer Solar System Asteroid and Implications for D- and P-Type Asteroids

We report a comprehensive study of the ungrouped type 2 carbonaceous chondrite, Tarda, which fell in Morocco in 2020. This meteorite exhibits substantial similarities to Tagish Lake, Wisconsin Range 91600, and Meteorite Hills 00432, which are generally considered to have originated from a D-type asteroid(s). We constrain the compositions and petrologies of the materials present in a potential sample of a D-type asteroid by reporting the petrography, bulk chemical compositions, bulk H, C, N, Cr, and Ti isotopic compositions, reflectance spectra, and in situ chemical compositions of metals, sulfides, carbonates, and FeO-poor and FeO-rich chondrule silicates of Tarda. We also present new data for Tagish Lake. We then compare Tarda with the other Tagish Lake-like meteorites. Tarda and Tagish Lake appear to be from the same parent body, as demonstrated by their similar petrologies (modal abundances, chondrule sizes), mineral compositions, bulk chemical and isotopic compositions, and reflectance spectra. While the two other Tagish Lake-like meteorites, Wisconsin Range 91600 and Meteorite Hills 00432, show some affinities to Tagish Lake and Tarda, they also share similar characteristics to the Mighei-like carbonaceous (CM) chondrites, warranting further study. Similarities in reflectance spectra suggest that P-type asteroids 65 Cybele and 76 Freia are potential parent bodies of Tarda and the Tagish Lake-like meteorites, or at least have similar surface materials. Since upcoming spacecraft missions will spectrally survey D-type, P-type, and C-type Trojan asteroids (NASA's Lucy) and spectrally study and return samples from Mars' moon Phobos (JAXA's Martian Moons eXploration mission), which is spectrally similar to D-type asteroids, these meteorites are of substantial scientific interest. Furthermore, since Tarda closely spectrally matches P-type asteroids (but compositionally matches the D-type asteroid like Tagish Lake meteorite), P-type and D-type asteroids may represent fragments of the same or similar parent bodies.

Tarda↗

Complementary rare earth element patterns in unique achondrites, such as ALHA 77005 and shergottites, and in the earth

Abundances of major, minor, and trace elements are determined in the Antarctic achondrite Allan Hills (ALHA) 77005 via sequential instrumental and radiochemical neutron activation analysis. The rare earth element (REE) abundances of ALHA 77005 reveal a unique chondritic normalized pattern; that is, the REEs are nearly unfractionated from La to Pr at approximately 1.0X chondrites, monotonically increased from Pr to Gd at approximately 3.4X with no Eu anomaly, nearly unfractionated from Gd and Ho and monotonically decreased from Ho to Lu at approximately 2.2X. It is noted that this unique REE pattern of ALHA 77005 can be modeled by a melting process involving a continuous melting and progressive partial removal of melt from a light REE enriched source material. In a model of this type, ALHA 77005 could represent either a crystallized cumulate from such a melt or the residual source material. Calculations show that the parent liquids for the shergottites could also be derived from a light REE enriched source material similar to that for ALHA 77005.

Ma, M.-S.↗

The role of damage-softened material behavior in the fracture of composites and adhesives

Failure mechanisms of materials under very high strains experienced at and ahead of the crack tip such as formation, growth, and interaction of microvoids in ductile materials, microcracks in brittle solids or crazes in polymers and adhesives are represented by one-dimensional, nonlinear stress-strain relations possessing different ways by which the material loses capacity to carry load up to fracture or total separation. A double cantilever beam (DCB) type specimen is considered. The nonlinear material is confined to a thin strip between the two elastic beams loaded by a wedge. The problem is first modeled as a beam on a nonlinear foundation. The pertinent equation is solved numerically as a two-point boundary value problem for both the stationary and the quasi-stationay propagating crack. A finite element model is then used to model the problem in more detail in order to assess the adequacy of the beam model for the reduction of experimental data to determine in-situ properties of the thin interlayer.

Ungsuwarungsri, T.↗

Circumstellar material around young stars in Orion

The star cluster associated with the Orion nebula is one of the richest known. Lying at the nearside of the Orion Molecular cloud and at a distance of about 500 pc from us, it contains many premain-sequence stars with ages of about 300,000 yr. The nebula itself is a blister type, representing a wall of material ionized by the hottest star in the Trapezium group (member C). Although this is not the closest star formation region, it is probably the easiest place to detect circumstellar, possibly proto-planetary, material around these solar mass stars. This is because the same process of photoionization that creates the nebula also photoionizes these circumstellar clouds, thus rendering them easily visible. Moreover, their dust component is made visible by extinction of light from the background nebula. Young stars with circumstellar material were found in Orion on the second set of HST images and were called proplyds, indicating their special nature as circumstellar clouds caused to be luminous by being in or near a gaseous nebula. The brightest objects in the field had previously been seen in the optical and radio, and although their true nature had been hypothesized it was the HST images that made it clear what they are. The forms vary from cometlike when near the Trapezium to elliptical when further away, with the largest being 1000 AU and the bright portions of the smallest, which are found closest to the Trapezium, being about 100 AU in diameter. We now have a second set of HST observations made immediately after the refurbishment mission that provides even greater detail and reveals even more of these objects. About half of all the low-luminosity stars are proplyds. The poster paper describes quantitative tests about their fundamental structure and addresses the question of whether the circumstellar material is a disk or shell. One object (HST 16) is seen only in silhouette against the nebula and is easily resolved into an elliptical form of optical depth monotonically increasing toward the central star.

Odell, C. R.↗

Separation of cells from the rat anterior pituitary gland

Various techniques for separating the hormone-producing cell types from the rat anterior pituitary gland are examined. The purity, viability, and responsiveness of the separated cells depend on the physiological state of the donor, the tissue dissociation procedures, the staining technique used for identification of cell type, and the cell separation technique. The chamber-gradient setup and operation, the characteristics of the gradient materials, and the separated cell analysis of velocity sedimentation techniques (in particular Staput and Celsep) are described. Consideration is given to the various types of materials used in density gradient centrifugation and the operation of a gradient generating device. The use of electrophoresis to separate rat pituitary cells is discussed.

Hymer, Wesley C.↗

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Climate change in tundra regions may alter vegetation species composition and ecosystem carbon balance. Remote sensing provides critical tools for monitoring these changes as optical signals provide a way to scale from plot measurements to regional patterns. Gas exchange measurements of pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow AK, show three significantly different values of light use efficiency (LUE) with values of 0.013+/-0.001, 0.0018+/-0.0002, and 0.0012 0.0001 mol C/mol absorbed quanta for vascular plants, mosses and lichens, respectively. Further, discriminant analysis of patch reflectance identifies five spectral bands that can separate each vegetation functional type as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. Patch-level statistical discriminant functions applied to in situ hyperspectral reflectance successfully unmixed cover fractions of the vegetation functional types. These functions, developed from the tram data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine regional variability in distribution of the vegetation functional types and from those distributions, the variability of LUE. Across the landscape, there was a fivefold variation in tundra LUE that was correlated to a spectral vegetation index developed to detect vegetation chlorophyll content.

Huemmrich, Karl F.↗

Laser diode with thermal conducting, current confining film

A laser diode formed of a rectangular parallelopiped body of single crystalline semiconductor material includes regions of opposite conductivity type indium phosphide extending to opposite surfaces of the body. Within the body is a PN junction at which light can be generated. A stripe of a conductive material is on the surface of the body to which the P type region extends and forms an ohmic contact with the P type region. The stripe is spaced from the side surfaces of the body and extends to the end surfaces of the body. A film of germanium is on the portions of the surface of the P type region which is not covered by the conductive stripe. The germanium film serves to conduct heat from the body and forms a blocking junction with the P type region so as to confine the current through the body, across the light generating PN junction, away from the side surfaces of the body.

Hawrylo, Frank Z.↗

RF MEMS Switches with SiC Microbridges for Improved Reliability

Radio frequency (RF) microelectromechanical (MEMS) switches offer superior performance when compared to the traditional semiconductor devices such as PIN diodes or GaAs transistors. MEMS switches have a return loss (RL) better than -25 dB, negligible insertion loss (IL), isolation better than -30 dB, and near zero power consumption. However, RF MEMS switches have several drawbacks the most serious being long-term reliability. The ability for the switch to operate for millions or even billions of cycles is a major concern and must be addressed. MEMS switches are basically grouped in two categories, capacitive and metal-to-metal contact. The capacitive type switch consists of a movable metal bridge spanning a fixed electrode and separated by a narrow air gap and thin insulating material. The metal-to-metal contact type utilizes the same basic design but without the insulating material. After prolonged operation the metal bridges, in most of these switches, begin to sag and eventually fail to actuate. For the metal-to-metal type, the two metal layers may actually fuse together. Also if the switches are not packaged properly or protected from the environment moisture may build up and cause stiction between the top and bottom electrodes rendering them useless. Many MEMS switch designs have been developed and most illustrate fairly good RF characteristics. Nevertheless very few have demonstrated both great RF performance and ability to perform millions/billions of switching cycles. Of these, nearly all are of metal-to-metal type so as the frequency increases RF performance decreases.

Scardelletti, Maximilian C.↗

ArcjetCV: a new machine learning application for extracting time-resolved recession measurements from arc jet test videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession, sting arm motion, and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials.

machine learning↗

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession, sting arm motion, and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials.

machine learning↗

ArcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

machine learning↗

arcjetCV: A New Machine Learning Application for Extracting Time-Resolved Recession Measurements From Arc Jet Test Videos

Arc jet Computer Vision (ArcjetCV) is a software application built to automate analysis of arc jet ground test video footage. This includes tracking material recession and the shock-material standoff distance. This provides a new capability to resolve and validate new physics associated with non-linear processes. This is an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcjetCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

machine learning↗

arcjetCV: automating recession extraction from video

Arc jet Computer Vision (arcjetCV)[1][2] is a software application built to automate time-resolved recession tracking of edges in test videos, specifically for tracking material recession and the shock-material standoff. This provides a new capability to resolve and validate new physics associated with non-linear processes and an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcticCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

Recession tracking↗

ArcjetCV: Automating Recession Tracking

Arc jet Computer Vision (arcjetCV) is a software application built to automate time-resolved recession tracking of edges in test videos, specifically for tracking material recession and the shock-material standoff. This provides a new capability to resolve and validate new physics associated with non-linear processes and an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcticCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

Recession tracking↗

ArcjetCV: Automating Arc Jet Analysis

Arc jet Computer Vision (arcjetCV) is a software application built to automate time-resolved recession tracking of edges in test videos, specifically for tracking material recession and the shock-material standoff. This provides a new capability to resolve and validate new physics associated with non-linear processes and an essential step to reduce testing, modeling, and validation uncertainties for heatshield material performance. ArcticCV uses several types of machine learning (convolutional neural net: CNN, decision tree: DT, k-means unsupervised clustering: KM) to automate the video processing pipeline. These include inferring the start/stop of time segments of interest (1D CNN), measuring the time-dependent 2D recession of the material samples (2D CNN, DT), measuring the time-dependent shock standoff distance (2D CNN, DT), and post-processing cleaning of the recession data (KM). The software also provides a graphical user interface for ease of use. The results of using this tool on arc jet videos show non-linear time-dependent effects can be important for certain materials and characterizing certain failure modes.

Recession tracking↗