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At least 235 records · Page 13

The XMM Cluster Survey analysis of the SDSS DR8 redMaPPer catalogue: implications for scatter, selection bias, and isotropy in cluster scaling relations

ABSTRACT In this paper, we present the X-ray analysis of Sloan Digital Sky Survey DR8 redMaPPer (SDSSRM) clusters using data products from the XMM Cluster Survey (XCS). In total, 1189 SDSSRM clusters fall within the XMM–Newton footprint. This has yielded 456 confirmed detections accompanied by X-ray luminosity (LX) measurements. Of these clusters, 381 have an associated X-ray temperature measurement (TX). This represents one of the largest samples of coherently derived cluster TX values to date. Our analysis of the X-ray observable to richness scaling relations has demonstrated that scatter in the TX–λ relation is roughly a third of that in the LX–λ relation, and that the LX–λ scatter is intrinsic, i.e. will not be significantly reduced with larger sample sizes. Analysis of the scaling relation between LX and TX has shown that the fits are sensitive to the selection method of the sample, i.e. whether the sample is made up of clusters detected ‘serendipitously’ compared to those deliberately targeted by XMM. These differences are also seen in the LX–λ relation and, to a lesser extent, in the TX–λ relation. Exclusion of the emission from the cluster core does not make a significant impact on the findings. A combination of selection biases is a likely, but yet unproven, reason for these differences. Finally, we have also used our data to probe recent claims of anisotropy in the LX–TX relation across the sky. We find no evidence of anistropy, but stress this may be masked in our analysis by the incomplete declination coverage of the SDSS.

79 ASTRONOMY AND ASTROPHYSICS↗

Yarkovsky Drift Detections for 247 Near-Earth Asteroids

The Yarkovsky effect is a thermal process acting upon the orbits of small celestial bodies, which can cause these orbits to slowly expand or contract with time. The effect is subtle (〈da/dt〉∼10{sup −4} au My{sup −1} for a 1 km diameter object) and is thus generally difficult to measure. We analyzed both optical and radar astrometry for 600 Near-Earth Asteroids (NEAs) for the purpose of detecting and quantifying the Yarkovsky effect. We present 247 NEAs with measured drift rates, which is the largest published set of Yarkovsky detections. This large sample size provides an opportunity to examine the Yarkovsky effect in a statistical manner. In particular, we describe two independent population-based tests that verify the measurement of Yarkovsky orbital drift. First, we provide observational confirmation for the Yarkovsky effect’s theoretical size dependence of 1/D, where D is diameter. Second, we find that the observed ratio of negative to positive drift rates in our sample is 2.34, which, accounting for bias and sampling uncertainty, implies an actual ratio of 2.7{sub −0.7}{sup +0.3}. This ratio has a vanishingly small probability of occurring due to chance or statistical noise. The observed ratio of retrograde to prograde rotators is two times lower than the ratio expected from numerical predictions from NEA population studies and traditional assumptions about the sense of rotation of NEAs originating from various main belt escape routes. We also examine the efficiency with which solar energy is converted into orbital energy and find a median efficiency in our sample of 12%. We interpret this efficiency in terms of NEA spin and thermal properties.

79 ASTRONOMY AND ASTROPHYSICS↗

Euromet Ureilite Consortium: A preliminary report on carbon and nitrogen geochemistry

The first Euromet expedition to the Frontier Mountain in Antarctica in December 1990 recovered two ureilites, FRO 90036 (34.6g) and FRO 90054 (17.5g). Preliminary classification indicated that the specimens had very different textures and mineral chemistries, and hence were not paired. A third ureilite, Acfer 277 (41.0 g), has also recently been returned from the Sahara. Due to the small sample sizes of the meteorites, and the unusual mineralogy of FRO 90054, a consortium was established to ensure the most effective study of these samples; this abstract reports on the carbon and nitrogen stable isotope geochemistry of two of the three ureilites issued to the consortium.

Grady, Monica M.↗

Using X-Ray Computed Tomography as a Tool for Preliminary Examination Tool of Current and Future Extraterrestrial Sample Return Missions

The Astromaterials Acquisition and Curation Office at the Johnson Space Center is the past, present, and future home of all of NASA’s astromaterials sample collections. The primary goals of the curation office are to maintain the long-term integrity of the samples and ensure that the samples are distributed for scientific study in a fair, timely, and responsible manner, thus maximizing the return on each sample. Part of the curation process is planning for the future. To this end, we perform fundamental research in advanced curation initiatives to better prepared for future sample return missions. Advanced Curation is tasked with developing procedures, technology, and data sets necessary for curating new sample collections, or getting new results from existing sample collections. As part of these advanced curation efforts, we have installed and are operating a Nikon XTH 320 X-ray Computed Tomography(XCT) system in the JSC curation office with four interchangeable X-ray sources, a large-area detector, and a heavy-duty stage. These instrument characteristics allow us exceptional flexibility to analyze a wide range of sample sizes, from sub-mm soil particles to rocks >10 cm in diameter. The penetrative nature of the XCT scans allows for astromaterials samples to be analyzed within sealed low-density containers (e.g., Teflon bags), preserving the pristinity of the samples. We have begun scanning of the Apollo and Antarctic Meteorite sample suites in order to non-destructively map out lithic clasts (and other features) within the samples. The data from these scans will be made available to scientists via the JSC curation website and the Astromaterials Curation Newsletter. We anticipate sample requests from these “new” lithic clasts identified in these “old” samples. We also anticipate that XCT analyses like these would be useful for future sample return missions, like the OSIRIS REx mission, as well as future sample return missions.

Zeigler, Ryan↗

Microscale Thermophoresis (MST) as a Tool to Study Binding Interactions of Oxygen-Sensitive Biohybrids

Microscale thermophoresis (MST) is a technique used to measure the strength of molecular interactions. MST is a thermophoretic-based technique that monitors the change in fluorescence associated with the movement of fluorescent-labeled molecules in response to a temperature gradient triggered by an IR LASER. MST has advantages over other approaches for examining molecular interactions, such as isothermal titration calorimetry, nuclear magnetic resonance, biolayer interferometry, and surface plasmon resonance, requiring a small sample size that does not need to be immobilized and a high-sensitivity fluorescence detection. In addition, since the approach involves the loading of samples into capillaries that can be easily sealed, it can be adapted to analyze oxygen-sensitive samples. In this Bio-protocol, we describe the troubleshooting and optimization we have done to enable the use of MST to examine protein–protein interactions, protein–ligand interactions, and protein–nanocrystal interactions. The salient elements in the developed procedures include 1) loading and sealing capabilities in an anaerobic chamber for analysis using a NanoTemper MST located on the benchtop in air, 2) identification of the optimal reducing agents compatible with data acquisition with effective protection against trace oxygen, and 3) the optimization of data acquisition and analysis procedures. The procedures lay the groundwork to define the determinants of molecular interactions in these technically demanding systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improved measurement of thermal effects on microstructure

The objectives were to introduce a simple methodology which could be used to replace the time-consuming and expensive conventional methods of metallographic and quantitative analysis of thermal treatment effect on microstructure. Metallurgical analysis continually calls for the evaluation of thermal treatment effects on microstructure. This commonly demands metallographic sample preparation and microscopic examination, which are time absorbing and costly. These drawbacks are burdensome when large numbers of samples must be levied fast. Mechanical testing can sometimes be substituted, but sample size and shape frequently make these methods impractical. The experiment described here is ideal for the microstructural evaluation of lamp filaments and other wire samples such as copper wire which can be conveniently coiled.

Rastani, Mansur↗

Lithium Inventory of 2 Solar Mass Red Clump Stars in Open Clusters: A Test of the Helium Flash Mechanism

The temperature distribution of field Li-rich red giants suggests the presence of a population of Li-rich red clump (RC) stars. One proposed explanation for this population is that all stars with masses near 2 solar mass experience a shortlived phase of Li-richness at the onset of core He-burning. Many of these stars have low C-12/C-13, a signature of deep mixing that is presumably associated with the Li regeneration. To test this purported mechanism of Li enrichment, we measured abundances in 38 RC stars and 6 red giant branch (RGB) stars in four open clusters selected to have RC masses near 2 solar mass. We find six Li-rich stars (A(Li) greater than or equal to 1.50 dex) of which only two may be RC stars. None of the RC stars have Li exceeding the levels observed in the RGB stars, but given the brevity of the suggested Li-rich phase and the modest sample size, it is probable that stars with larger Li-enrichments were missed simply by chance. However, we find very few stars in our sample with low C-12/C-13. Such low C-12/C-13, seen in many field Li-rich stars, should persist even after lithium has returned to normal low levels. Thus, if Li synthesis during the He flash occurs, it is a rare, but potentially long-lived occurrence rather than a short-lived phase for all stars. We estimate a conservative upper limit of the fraction of stars going through a Li-rich phase to be less than 47%, based on stars that have low C-12/C-13 for their observed A(Li).

Li-rich red giants↗

Estimating the Concentration of Large Raindrops from Polarimetric Radar and Disdrometer Observations

Estimation of rainfall integral parameters, including radar observables, and empirical relations between them are sensitive to the truncation of the drop size distribution (DSD), particularly at the large drop end. The sensitivity of rainfall integral parameters to the maximum drop diameter (D(sub max)) is exacerbated at C‐band since resonance effects are pronounced for large drops in excess of 5 mm diameter (D). Due to sampling limitations, it is often difficult to reliably estimate D(sub max) with disdrometers. The resulting uncertainties in D(sub max0 potentially increase errors in radar retrieval methods, particularly at C‐band, that rely on disdrometer observations for DSD input to radar models. In fact, D(sub max) is typically an assumed DSD parameter in the development of radar retrieval methods. Because of these very uncertainties, it is difficult to independently confirm disdrometer estimates of D(sub max) with polarimetric radar observations. A couple of approaches can be taken to reduce uncertainty in large drop measurement. Longer integration times can be used for the collection of larger disdrometer samples. However, integration periods must be consistent with a radar resolution volume (RRV) and the temporal and spatial scales of the physical processes affecting the DSD therein. Multiple co‐located disdrometers can be combined into a network to increase the sample size within a RRV. However, over a reasonable integration period, a single disdrometer sample volume is many orders of magnitudes less than a RRV so it is not practical to devise a network of disdrometers that has an equivalent volume to a typical RRV. Since knowledge of DSD heterogeneity and large drop occurrence in time and space is lacking, the specific accuracy or even general representativeness of disdrometer based D(sub max) and large drop concentration estimates within a RRV are currently unknown. To address this complex issue, we begin with a simpler question. Is the frequency of occurrence of large rain drops (D > 5 mm) in disdrometer observations, either stand alone or networked, generally representative and consistent with polarimetric radar observations? We first show from simulations that the concentration of large (D > 5 mm) rain drops (N(sub T5)) can be estimated from polarimetric observations of specific differential phase (K(sub dp)) and differential reflectivity (Z(sub dr)), N(sub T5)=F(K(sub dp),Z(sub dr)), or horizontal reflectivity (Z(sub h)) and Z(sub dr), N(sub T5)=(Z(sub h),Z(sub dr)). We assess the error associated with polarimetric retrieval of N(sub T5), including sensitivity to D(sub max) parameterization assumptions and measurement error in the radar simulations. Polarimetric measurements at S‐band and C‐band will then be used to retrieve estimates of N(sub T5) and compared to disdrometer estimates of N(sub T5). After careful consideration of retrieval error, we will check consistency between disdrometer and polarimetric radar estimates of N(sub T5) and the frequency of occurrence of large rain drops in a variety of precipitating regimes using data from NASA's Global Precipitation Measurement (GPM) Ground Validation (GV) program, including field campaigns such as MC3E (Oklahoma) and IFloodS (Iowa) and extended measurements over Huntsville, Alabama and NASA Wallops Flight Facility in coastal Virginia.

Carey, Lawrence D.↗

Terrestrial Ages and Pairing of Howardites, Eucrites and Diogenites From the Miller Range Icefields, Antarctica

In the past 45 years, the US Antarctic Meteorite (ANSMET) program has recovered more than 22,000 meteorites from more than 50 individual meteorite stranding areas. Although the Antarctic meteorite collection is dominated by ordinary chondrites which represent 80-90% of the recovered samples, it also contains many achondrites, including howardites, eucrites and diogenites, which are collectively known as HED meteorites. A challenge for the Antarctic meteorite collection is to identify paired fragments that belong to the same fall. Eight ANSMET field sea-sons at the Miller Range Icefields (MIL), a series of blue ice fields about 40 km long and 10-20 km wide, have yielded more than 3000 meteorites including 56 HEDs. At least three possible pairing groups (with 3-10 members each) were initially identified among the MIL diogenites and one each among the howardites and eucrites. Since many HED meteorites are heterogeneous breccias, pairing identifications based on cm-sized samples is difficult and other independent evidence is needed to verify these proposed pairings, as was shown for several Antarctic howardite pairing-groups. Here we re-examine pairings of HED’s from the Miller Range Icefields, using multiple lines of evidence, including texture/petrography, chemical composition, cosmogenic radionuclides and find locations. Due to the heterogeneous nature of HED meteorites, we will not only consider pairings strictly among the three HED groups, but will also consider pairing of howardites with brecciated eucrites or brecciated diogenites if the cosmogenic nuclides, texture and chemical compositions support this. The concentrations of cosmogenic radionuclides in meteorites are a function of the cosmic-ray exposure (CRE) age, shielding conditions (size and irradiation depth), chemical composition, as well the terrestrial age of the meteorite sample. Since the production rates of cosmogenic nuclides as a function of meteoroid size, depth and composition are well understood [6], their measured concentrations can be used to determine which meteorites belong to the same fall even if the chemical composition of the samples show significant variations. We selected 28 of the 56 HED samples from the MIL collection, including 12 diogenites, 8 howardites and 8 brecciated eucrites to investigate pairing relationships.

howardite↗

Brain‐age prediction: Systematic evaluation of site effects, and sample age range and size

Abstract Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain‐age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain‐age has highlighted the need for robust and publicly available brain‐age models pre‐trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain‐age model. Here we expand this work to develop, empirically validate, and disseminate a pre‐trained brain‐age model to cover most of the human lifespan. To achieve this, we selected the best‐performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain‐age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5–90 years; 53.59% female). The pre‐trained models were tested for cross‐dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8–80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9–25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age‐bins (5–40 and 40–90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain‐age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain ( https://centilebrain.org/#/brainAGE2 ), an open‐science, web‐based platform for individualized neuroimaging metrics.

60 APPLIED LIFE SCIENCES↗

Beyond microbial abundance: metadata integration enhances disease prediction in human microbiome studies

Multiple studies have highlighted the interaction of the human microbiome with physiological systems such as the gut, immune, liver, and skin, via key axes. Advances in sequencing technologies and high-performance computing have enabled the analysis of large-scale metagenomic data, facilitating the use of machine learning to predict disease likelihood from microbiome profiles. However, challenges such as compositionality, high dimensionality, sparsity, and limited sample sizes have hindered the development of actionable models. One strategy to improve these models is by incorporating key metadata from both the human host and sample collection/processing protocols. This remains challenging due to sparsity and inconsistency in metadata annotation and availability. In this paper, we introduce a machine learning-based pipeline for predicting human disease states by integrating host and protocol metadata with microbiome abundance profiles from 68 different studies, processed through a consistent pipeline. Our findings indicate that metadata can enhance machine learning predictions, particularly at higher taxonomic ranks like Kingdom and Phylum, though this effect diminishes at lower ranks. Our study leverages a large collection of microbiome datasets comprising 11,208 samples, therefore enhancing the robustness and statistical confidence of our findings. This work is a critical step toward utilizing microbiome and metadata for predicting diseases such as gastrointestinal infections, diabetes, cancer, and neurological disorders.

Mathematics and Computing↗

Convergence of oscillator spectral estimators for counted-frequency measurements.

A common intermediary connecting frequency-noise calibration or testing of an oscillator to useful applications is the spectral density of the frequency-deviating process. In attempting to turn test data into predicts of performance characteristics, one is naturally led to estimation of statistical values by sample-mean and sample-variance techniques. However, sample means and sample variances themselves are statistical quantities that do not necessarily converge (in the mean-square sense) to actual ensemble-average means and variances, except perhaps for excessively large sample sizes. This is especially true for the flicker noise component of oscillators. This article shows, for the various types of noises found in oscillators, how sample averages converge (or do not converge) to their statistical counterparts. The convergence rate is shown to be the same for all oscillators of a given spectral type.

Tausworthe, R. C.↗

Investigation of spectral analysis techniques for randomly sampled velocimetry data

It is well known that velocimetry (LV) generates individual realization velocity data that are randomly or unevenly sampled in time. Spectral analysis of such data to obtain the turbulence spectra, and hence turbulence scales information, requires special techniques. The 'slotting' technique of Mayo et al, also described by Roberts and Ajmani, and the 'Direct Transform' method of Gaster and Roberts are well known in the LV community. The slotting technique is faster than the direct transform method in computation. There are practical limitations, however, as to how a high frequency and accurate estimate can be made for a given mean sampling rate. These high frequency estimates are important in obtaining the microscale information of turbulence structure. It was found from previous studies that reliable spectral estimates can be made up to about the mean sampling frequency (mean data rate) or less. If the data were evenly samples, the frequency range would be half the sampling frequency (i.e. up to Nyquist frequency); otherwise, aliasing problem would occur. The mean data rate and the sample size (total number of points) basically limit the frequency range. Also, there are large variabilities or errors associated with the high frequency estimates from randomly sampled signals. Roberts and Ajmani proposed certain pre-filtering techniques to reduce these variabilities, but at the cost of low frequency estimates. The prefiltering acts as a high-pass filter. Further, Shapiro and Silverman showed theoretically that, for Poisson sampled signals, it is possible to obtain alias-free spectral estimates far beyond the mean sampling frequency. But the question is, how far? During his tenure under 1993 NASA-ASEE Summer Faculty Fellowship Program, the author investigated from his studies on the spectral analysis techniques for randomly sampled signals that the spectral estimates can be enhanced or improved up to about 4-5 times the mean sampling frequency by using a suitable prefiltering technique. But, this increased bandwidth comes at the cost of the lower frequency estimates. The studies further showed that large data sets of the order of 100,000 points, or more, high data rates, and Poisson sampling are very crucial for obtaining reliable spectral estimates from randomly sampled data, such as LV data. Some of the results of the current study are presented.

Sree, Dave↗

Mineralogy of the Solar System

The coming decade will witnesses the first sample return missions from solar system bodies in 30 years. These samples will all be very small, some missions return only a few milligrams of total mass. Fortunately, the capability of modem methods to characterize ultra-small samples is well established from analysis of interplanetary dust particles (IDPs), interstellar grains recovered from meteorites, and other materials requiring ultra-sensitive analytical capabilities. Powerful analytical techniques are available that require, under favorable circumstances, single particles of only a few nanograms for entire suites of fairly comprehensive characterizations. A returned sample of greater than 1,000 particles with total mass of just one microgram permits comprehensive quantitative geochemical measurements that are impractical to can-y out in situ by flight instruments. With the Galileo flybys of Gaspra and Ida, it is now recognized that even very small airless bodies have indeed developed a particulate regolith. Acquiring a sample of the bulk regolith, a simple sampling strategy, provides two critical pieces of information about the body. Regolith samples are excellent bulk samples since they normally contain all the key components of the local environment, albeit in particulate form. Furthermore, since this fine fraction dominates remote measurements, regolith samples also provide information about surface alteration processes and are a key link to remote sensing of other bodies. Studies indicate that a statistically significant number of nanogram-sized particles should be able to characterize the regolith of a primitive asteroid, although the presence of larger components within even primitive meteorites (e.g.. Murchison), e.g. chondrules, CAI, large crystal fragments, etc., points out the limitations of using data obtained from nanogram-sized samples to characterize entire primitive asteroids. However, most important asteroidal geological processes have left their mark on the matrix, since this is the finest-grained portion and therefore most sensitive to chemical and physical changes. Thus, the following information can be learned from this fine grain size fraction alone: (1) mineral paragenesis; (2) regolith processes, (3) bulk composition; (4) conditions of thermal and aqueous alteration (if any); (5) relationships to planets, comets, meteorites (via isotopic analyses, including oxygen; (6) abundance of water and hydrated material; (7) abundance of organics; (8) history of volatile mobility, (9) presence and origin of presolar and/or interstellar material.

Zolensky, Michael E.↗

Gamma and Neutron Measurement and Modeling of Irradiated TRISO Fuel

Given the unique characteristics of the PBR fuel cycle, both gamma and neutron measurements are expected to play important roles in performing and maintaining nuclear material control and accounting for spent pebbles to safeguard the fuel cycle. Given the lack of irradiated pebbles in the US, a variety of irradiated TRISO fuel samples with wide ranges of burnups and cooling times available at ORNL were used in this work. A large number of gamma and neutron measurements have been performed on these samples to collect data to test the various detectors and to benchmark the computer models to simulate the depletion and decay of the fuel and the measurements themselves. Two neutron detectors, including a custom-made detector and the Very High-Performance Neutron Multiplicity Counting, were used to measure the neutrons emitted by these TRISO samples. Three gamma spectrometry detectors, including an HPGe and the M400 CZT detector, were used to measure gamma-ray emissions from these samples. The M400 was recently adopted by the IAEA for fresh uranium measurements, but it was tested for spent fuel measurements prior to this project. Detailed MCNP models were developed to simulate these neutron and gamma measurements. Some GADRAS models were also developed to cross check the MCNP models for the gamma measurements. It was found challenging to perform neutron measurements in the hot cell due to the high background counts. Close agreements were observed between the simulated and measured neutron count rates in both detectors’ measurements of californium calibration sources. Both the HPGe and M400 detectors were able to measure the 604 and 662 keV peaks from these samples, which are the two most important peaks used to infer fuel burnup. Although the M400 detector did not have nearly good energy resolution and did not detect some of the minor peaks as the HPGe detector, it was found to be capable of handling significantly higher dose rates than HPGe. Given the complexities in the TRISO samples (e.g., different samples sizes) and uncertainties in the alignments between the detector and the TRISO fuel inside the containers, large scatters were found between the peak area rates and the samples’ burnups. However, the 604/662 peak ratios were found to trend well with the samples’ burnups among most samples in both measured and simulated results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Mcgwire, K.↗

Spectroscopy-based isotopic (δ 13 C) analysis for high spatial resolution of carbon exchange in the rhizosphere

The rhizosphere is a highly dynamic zone bridging plant roots with needed nutrient resources in soil. While the rhizosphere may be small, it has a disproportionally large impact on plant success and biomass production. A suite of rhizosphere-hosted microbial and geochemical interactions facilitate nutrient acquisition by plant roots, and, in turn, the roots stimulate these processes by supplying organic carbon into the rhizosphere. The small physical dimensions of the rhizosphere, however, can constrain efforts to elucidate key carbon exchange processes and their spatial extent and localization. We present a method for spatially resolved δ 13 C analysis of rhizosphere samples by coupling laser ablation (LA) sampling with isotopic analysis using capillary absorption spectroscopy (CAS) which differs from conventional mass spectrometer (MS) approaches. The CAS system has high sensitivity (requires fewer nanomoles of CO 2 per analysis) than comparable MS systems, which enables reduced sample size requirements to thereby improve spatial resolution (from 25 μm to as low as a projected 5 μm spatial resolution). We demonstrate the utility of CAS using rhizosphere samples from switchgrass plants exposed to 13 CO 2 . As a result, this technique will provide a capability for tracking the extent and spatial distribution of root exudate into the rhizosphere at highly detailed spatial scales.

59 BASIC BIOLOGICAL SCIENCES↗

In-Situ SEM High Strain Rate Testing of Large Diameter Micropillars Followed by TEM and EBSD Postmortem Analysis

Background Dislocation dynamic simulations are intended as a tool to understand and predict the mechanical behavior of metallic materials, but its prediction has never been directly verified by experiments due to differences in specimen strain rate and size. Objective In this work, a comprehensive experimental framework is proposed to attempt direct comparison between experiments and discrete dislocation dynamics (DDD) modelling. Methods By integrating high-throughput sample fabrication and a customized testing apparatus, the sample size and strain rate typically employed in DDD simulations are explored experimentally. Constitutive properties such as stress-strain response are measured, and microstructural information is obtained from transmission electron microscopy (TEM) imaging, electron backscatter diffraction (EBSD), and TEM-based orientation mapping. Results Magnesium and copper were selected, as case studies, to demonstrate the newly developed experimental procedure. Measured stress-strain responses for Mg are consistent with those obtained with a miniaturized Hopkison bar experiments. Furthermore, by exploiting the validated workflow, the effect of strain rate on micropillar heterogeneous deformation and associated dislocation plasticity were revealed. Conclusion The work establishes a methodology for the systematic study of not only metals but also other materials and structures at the microscale and high strain rates.

42 ENGINEERING↗