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At least 307 records · Page 17

Scalable Layer-by-Layer Electrospray-Assisted Interfacial Polymerization: Enabling Large-Area Polyamide Membrane Fabrication

Layer-by-layer electrospray-assisted interfacial polymerization (LBL-EAIP) has recently been proposed as an alternative approach for fabricating polyamide membranes with precisely controlled thickness and polymerization degree, showing great potential for reverse osmosis (RO) membrane synthesis. In this article, we report a scale-up strategy for LBL-EAIP to enable its practical application in RO membrane manufacturing. A multi-jet electrospray apparatus was developed, and the device configuration and process parameters were carefully adjusted to produce polyamide-on-polyethersulfone thin film composite (TFC) membranes with consistently high salt rejection and water permeance across the membrane area. Specifically, an average 97.1% NaCl rejection from a 2000 ppm NaCl feed was achieved with an area-to-area deviation of 1%, along with a deionized water permeance of 0.90 ± 0.11 LMH/bar at 15 bar feed pressure. In addition, a Fourier-transform infrared spectroscopy (FTIR)-based analytical method was developed for semi-quantitative assessment of membrane thickness and compositional uniformity, enabling rapid mapping of film microstructure and chemical variations. This work provides a pathway to scale up LBL-EAIP technology, bridging the gap between laboratory-scale innovation and industrial-scale manufacturing.

Feng, Yue (ORCID:0000000221343980)↗

Common risk segment mapping: Streamlining exploration for carbon storage sites, with application to coastal Texas and Louisiana

Large-scale deployment of Carbon Capture and Storage (CCS) will require a commensurately large number of sites. Efficient screening methods are needed to create investment assurance and focus efforts on the most promising sites. The problem is similar to petroleum exploration, for which there are well-developed (though seldom published) workflows, including Common Risk Segment (CRS) mapping. In brief, the process requires 1) defining the key play elements; 2) identifying candidate geologic intervals for each; 3) creating fact-based maps for those intervals; 4) determining minimum criteria for the success of each element; 5) reinterpreting the fact-based maps in terms of chance of success; and 6) combining the individual maps to form a composite, basin-scale view of prospectivity. We adapt the CRS process to screening for CO 2 storage sites. Critically, we redefine the process in terms of cost of characterization and development, rather than chance of success. For illustration, we apply the process to the example of the Lower Miocene on the Texas and Louisiana Gulf Coast. We show that the predictions are consistent with historic hydrocarbon production volumes and rates. The power of the CRS method is that it creates a systematic approach to geologic evaluation and translates complex, multidimensional analysis into clear, graphical and easily comprehended business inputs. The results highlight sweet spots and identifies critical risks, suggesting a focus for further data collection and analysis. Furthermore, the method developed here can be applied to both surface and subsurface factors anywhere that there is interest in geologic storage of CO 2 .

54 ENVIRONMENTAL SCIENCES↗

A review on recent machine learning applications for imaging mass spectrometry studies

Imaging mass spectrometry (IMS) is a powerful analytical technique widely used in biology, chemistry, and materials science fields that continue to expand. IMS provides a qualitative compositional analysis and spatial mapping with high chemical specificity. The spatial mapping information can be 2D or 3D depending on the analysis technique employed. Due to the combination of complex mass spectra coupled with spatial information, large high-dimensional datasets (hyperspectral) are often produced. Therefore, the use of automated computational methods for an exploratory analysis is highly beneficial. The fast-paced development of artificial intelligence (AI) and machine learning (ML) tools has received significant attention in recent years. These tools, in principle, can enable the unification of data collection and analysis into a single pipeline to make sampling and analysis decisions on the go. There are various ML approaches that have been applied to IMS data over the last decade. Here, in this review, we discuss recent examples of the common unsupervised (principal component analysis, non-negative matrix factorization, k-means clustering, uniform manifold approximation and projection), supervised (random forest, logistic regression, XGboost, support vector machine), and other methods applied to various IMS datasets in the past five years. The information from this review will be useful for specialists from both IMS and ML fields since it summarizes current and representative studies of computational ML-based exploratory methods for IMS.

47 OTHER INSTRUMENTATION↗

Gamma ray spectrometer experiment

The transearth coast period of the Apollo 16 mission provided an opportunity to study the astronomical sources of gamma radiation. This experiment was used to aid compositional identification for geochemical mapping of the lunar surface.

Arnold, J. R.↗

Techniques for using diazo materials in remote sensor data analysis

The use of data derived from LANDSAT is facilitated when special products or computer enhanced images can be analyzed. However, the facilities required to produce and analyze such products prevent many users from taking full advantages of the LANDSAT data. A simple, low-cost method is presented by which users can make their own specially enhanced composite images from the four band black and white LANDSAT images by using the diazo process. The diazo process is described and a detailed procedure for making various color composites, such as color infrared, false natural color, and false color, is provided. The advantages and limitations of the diazo process are discussed. A brief discussion interpretation of diazo composites for land use mapping with some typical examples is included.

Whitebay, L. E.↗

Compositional analysis of silicon

The use of surface analysis methods in the detection and evaluation of elemental and impurity species in Si is presented. Examples are provided from polycrystalline Si and high-efficiency MINP cells. Auger electron spectroscopy and secondary ion mass spectrometry are used to complement microelectrical data obtained by electron-beam induced-current measurements. A new method is discussed which utilizes the volume indexing of digital secondary ion mass spectroscopy signals, providing compositional information and impurity maps on internal materials/device interfaces.

Kazmerski, L. L.↗

The use of dc-probe measurements in the middle atmosphere program

The middle atmosphere is weakly ionized, collision dominated plasma. Rocket-borne dc probes have proven effective in measuring conductivity and electron and ion concentrations in this plasma, and in some cases electron temperatures and ion composition were observed. During MAP, dc probes were also used successfully to study turbulence in the middle atmosphere, using the plasma as a passive tracer for the dynamical processes in the nonionized gas. Basic principles are reviewed of the dc-probe technique and examples are presented of results obtained during MAP.

Thrane, E. V.↗

Novae as distance indicators

Nova shells are characteristically prolate with equatorial bands and polar caps. Failure to account for the geometry can lead to large errors in expansion parallaxes for individual novae. When simple prescriptions are used for deriving expansion parallaxes from an ensemble of randomly oriented prolate spheroids, the average distance will be too small by factors of 10 to 15 percent. The absolute magnitudes of the novae will be underestimated and the resulting distance scale will be too small by the same factors. If observations of partially resolved nova shells select for large inclinations, the systematic error in the resulting distance scale could easily be 20 to 30 percent. Extinction by dust in the bulge of M31 may broaden and shift the intrinsic distribution of maximum nova magnitudes versus decay rates. We investigated this possibility by projecting Arp's and Rosino's novae onto a composite B - 6200A color map of M31's bulge. Thirty two of the 86 novae projected onto a smooth background with no underlying structure due to the presence of a dust cloud along the line of sight. The distribution of maximum magnitudes versus fade rates for these unreddened novae is indistinguishable from the distribution for the entire set of novae. It is concluded that novae suffer very little extinction from the filamentary and patchy distribution of dust seen in the bulge of M31. Time average B and H alpha nova luminosity functions are potentially powerful new ways to use novae as standard candles. Modern CCD observations and the photographic light curves of M31 novae found during the last 60 years were analyzed to show that these functions are power laws. Consequently, unless the eruption times for novae are known, the data cannot be used to obtain distances.

Ford, Holland C.↗

Autonomous Martian flying rover

A remotely programmable, autonomous flying rover is proposed to extensively survey the Martian surface environment. A Mach .3, solar powered, modified flying wing could cover roughly a 2000 mile range during Martian daylight hours. Multiple craft launched from an orbiting mother ship could provide near-global coverage. Each craft is envisioned to fly at about 1 km above the surface and measure atmospheric composition, pressure and temperature, map surface topography, and remotely penetrate the near subsurface looking for water (ice) and perhaps evidence of life. Data collected are relayed to Earth via the orbiting mother ship. Near surface guidance and control capability is an adaptation of current cruise missile technology. A solar powered aircraft designed to fly in the low temperature, low density, carbon dioxide Martian atmosphere near the surface appears feasible.

Source record↗

Relationships of soil, grass, and bedrock over the Kaweah serpentine melange through spectral mixture analysis of AVIRIS data

A linear mixing model is used to model the spectral variability of an AVIRIS scene from the western foothills of the Sierra Nevada and calibrate these radiance data to reflectance. Five spectral endmembers from the AVIRIS data, plus an ideal 'shade' endmember were required to model the continuum reflectance of each pixel in the image. Three of the endmembers were interpreted to model the surface constituents green vegetation, dry grass, and illumination. These are the main transient surface constituents that are expected to change with shifts in land use or climatic influences and viewing conditions ('shade' only). The spectral distinction between the other three endmembers is very small, yet the spatial distributions are coherent and interpretable. These distributions cross anthropogenic and vegetation boundaries and are best interpreted as different soil types. Comparison of the fraction images to the bedrock geology maps indicates that substrate composition must be a factor contributing to the spectral properties of these endmembers. Detailed examination of the reflectance spectra of the three soil endmembers reveals that differences in the amount of ferric and ferrous iron and/or organic constituents in the soils is largely responsible for the differences in spectral properties of these endmembers.

Mustard, John F.↗

Atmospheric electricity/meteorology analysis

This activity focuses on Lightning Imaging Sensor (LIS)/Lightning Mapper Sensor (LMS) algorithm development and applied research. Specifically we are exploring the relationships between (1) global and regional lightning activity and rainfall, and (2) storm electrical development, physics, and the role of the environment. U.S. composite radar-rainfall maps and ground strike lightning maps are used to understand lightning-rainfall relationships at the regional scale. These observations are then compared to SSM/I brightness temperatures to simulate LIS/TRMM multi-sensor algorithm data sets. These data sets are supplied to the WETNET project archive. WSR88-D (NEXRAD) data are also used as it becomes available. The results of this study allow us to examine the information content from lightning imaging sensors in low-earth and geostationary orbits. Analysis of tropical and U.S. data sets continues. A neural network/sensor fusion algorithm is being refined for objectively associating lightning and rainfall with their parent storm systems. Total lightning data from interferometers are being used in conjunction with data from the national lightning network. A 6-year lightning/rainfall climatology has been assembled for LIS sampling studies.

Goodman, Steven J.↗

Relationships of soil, grass, and bedrock over the Kaweah Serpentinite Melange through spectral mixture analysis of AVIRIS data

A linear mixing model is used to model the spectral variability of an AVIRIS scene from the western foothills of the Sierra Nevada and calibrate these radiance data to reflectance. Five spectral endmembers from the AVIRIS data, plus an ideal 'shade' endmember were required to model the continuum reflectance of each pixel in the image. Three of the endmembers were interpreted to model the surface constituents green vegetation, dry grass, and illumination. Comparison of the fraction images to the bedrock geology maps indicates that substrate composition must be a factor contributing to the spectral properties of these endmembers. Detailed examination of the reflectance spectra of the three soil endmembers reveals that differences in the amount of ferric and ferrous iron and/or organic constituents in the soils is largely responsible for the differences in spectral properties of these endmembers.

Mustard, John F.↗

Twenty-fourth Lunar and Planetary Science Conference. Part 1: A-F

The topics covered include the following: petrology, petrography, meteoritic composition, planetary geology, atmospheric composition, astronomical spectroscopy, lunar geology, Mars (planet), Mars composition, Mars surface, volcanology, Mars volcanoes, Mars craters, lunar craters, mineralogy, mineral deposits, lithology, asteroids, impact melts, planetary composition, planetary atmospheres, planetary mapping, cosmic dust, photogeology, stratigraphy, lunar craters, lunar exploration, space exploration, geochronology, tectonics, atmospheric chemistry, astronomical models, and geochemistry.

Source record↗

Scientific Objectives of the Mars Surveyor 2001 Gamma-Ray Spectrometer

The Gamma-Ray Spectrometer (GRS) is one of the instruments on the Mars Surveyor 2001 Orbiter, which is part of NASA's Mars-Surveyor program. The GRS is really an instrument suite consisting of the GRS, a neutron spectrometer (NS), and a high-energy neutron detector (FIEND). Each of these instruments/sensors are remotely mounted at different locations on the spacecraft and connect to a central electronics box. The GRS will achieve global mapping of the elemental composition of the surface and the abundance of hydrogen in the shallow subsurface. It is an updated design using the same technology as the lost Mars Observer mission. The Martian surface is continuously bombarded by cosmic ray particles; their interactions with the constituents of the soil produces nuclear reaction cascades with fast neutrons being the main secondaries. Those neutrons interact in turn with the nuclei of the elements that make up the soil and they eventually get slowed to thermal energies. In this process they leave the nuclei in an excited state that decays via the emission of characteristic gamma rays. All these processes are precisely known and have been simulated by means of numerical models. Thus, remote gamma-ray spectroscopy is a useful method for quantitatively measuring the geochemical composition of the surface down to a few tens of g/sq cm. Additional information is contained in original extended abstract.

Boynton, W. V.↗

Exploring Asteroid Interiors: The Deep Interior Mission Concept

Deep Interior is a mission to determine the geophysical properties of near-Earth objects, including the first volumetric image of the interior of an asteroid. Radio reflection tomography will image the 3D distribution of complex dielectric properties within the ~1 km rendezvous target and hence map structural, density or compositional variations. Laser altimetry and visible imaging will provide high-resolution surface topography. Smart surface pods culminating in blast experiments, imaged by the high frame rate camera and scanned by lidar, will characterize active mechanical behavior and structure of surface materials, expose unweathered surface for NIR analysis, and may enable some characterization of bulk seismic response. Multiple flybys en route to this target will characterize a diversity of asteroids, probing their interiors with non-tomographic radar reflectance experiments. Deep Interior is a natural follow-up to the NEARShoemaker mission and will provide essential guidance for future in situ asteroid and comet exploration. While our goal is to learn the interior geology of small bodies and how their surfaces behave, the resulting science will enable pragmatic technologies required of hazard mitigation and resource utilization.

Asphaug, E.↗

Applications of Sea-Ice Motion and Deformation Derived from Satellite Data

QuikSCAT backscatter, AMSR and DMSP SSM/I radiance data have been used to derive sea ice motion for both the Arctic and Antarctic region using the wavelet analysis tracking method. All results from QuikSCAT, AMSR and SSM5 are compatible with buoys and can then be merged by data fusion method to generate composite sea ice motion maps for more complete coverage. Furthermore, based on this merged data set daily sea-ice deformation (shear, and convergence) maps have been produced and show consistent spatial and temporal patterns. Temporal correlation maps between ice deformation and SSM/II ice concentration show interesting results in the Arctic, especially the coast area. In this study, principal component analysis for both the merged ice tracking result from satellite data and pressure field from buoy have also been examined for the relationship between the principal components and eigenvectors from these two data sets. While the result shows that principal components of modes 1 and 2 from two data sets are highly correlated which confirms that wind forcing is a major factor driving the ice drift, it also reveals that other high energy modes are not highly correlated which maybe caused by coastal effects. Principal component analysis of Arctic sea-ice motion during fall/winter period in different years shows the reverse of dominant modes or patterns is related to the Arctic Oscillation.

Liu, Antony K.↗