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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Molecular detection of per- and polyfluoroalkyl substances in water using time-of-flight secondary ion mass spectrometry

Detection of per- and polyfluoroalkyl substances (PFASs) is crucial in environmental mitigation and remediation of these persistent pollutants. We demonstrate that time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a viable technique to analyze and identify these substances at parts per trillion (ppt) level in real field samples without complicated sample preparation due to its superior surface sensitivity. Several representative PFAS compounds, such as perfluorooctanesulfonic acid (PFOS), perfluorobutanoic acid (PFBA), perfluoropentanoic acid (PFPeA), perfluoheptanoic acid (PFHpA), and perfluorononanoic acid (PFNA), and real-world groundwater samples collected from monitoring wells installed around at a municipal wastewater treatment plant located in Southern California were analyzed in this work. ToF-SIMS spectral comparison depicts sensitive identification of pseudo-molecular ions, characteristic of reference PFASs. Additionally, principal component analysis (PCA) shows clear discrimination among real samples and reference compounds. Our results show that characteristic molecular ion and fragments peaks can be used to identify PFASs. Furthermore, SIMS two-dimensional (2D) images directly exhibit the distribution of perfluorocarboxylic acid (PFCA) and PFOS in simulated mixtures and real wastewater samples. Such findings indicate that ToF-SIMS is useable to determine PFAS compounds in complex environmental water samples. In conclusion, ToF-SIMS provides simple sample preparation and high sensitivity in mass spectral imaging, offering an alternative solution for environmental forensic analysis of PFASs in wastewater in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

The scientific case for concurrent neutron and X-ray scattering and spectroscopy

The interrogation of materials with X-rays or neutrons to determine structure, energetics, and dynamics is fundamental to advancing physical and chemical materials science and enabling innovative material technologies. A persistent challenge in materials development is that progress depends on understanding structure and dynamics across multiple length and time scales in increasingly complex, multicomponent systems featuring interfaces, heterogeneity, and hierarchical organization. Despite rapidly growing demands on materials characterization, current experimental approaches are almost exclusively based on isolated X-ray or neutron scattering and spectroscopy, reflecting a paradigm largely unchanged for decades. To assess the scientific need for a new experimental paradigm, a 3-day workshop sponsored by the U.S. National Science Foundation (NSF) was held at the SpringHill Suites, San Jose, California, from June 2 to 4, 2022. The workshop brought together 70 national and international experts who critically evaluated opportunities enabled by concurrent neutron and X-ray (NeX) scattering, spectroscopy, and imaging experiments. The participants reached a clear consensus that establishing NeX capabilities is crucial for advancing the science of complex materials in the United States. This report illustrates the scientific drivers for NeX experiments through representative examples spanning biomaterials, energy materials, soft matter, nanomaterials, quantum materials, geoscience, and applied materials research. The complementarity of neutrons and X-rays is essential for robust model development and refinement, particularly in multiphase and multicomponent systems. While joint refinement of data from separate experiments is valuable, concurrent measurements uniquely eliminate uncertainties arising from sample evolution, environmental drift, and irreproducibility associated with experiments performed at different locations and times. Realizing NeX capabilities will require the development of new instrumentation, data analysis frameworks, and robust sample environments compatible with both neutron and X-ray probes. Addressing these challenges will enable unambiguous interpretation of complex materials behavior and open new frontiers in materials research.

X-ray↗
DOE OSTI2021

The Completed SDSS-IV Extended Baryon Oscillation Spectroscopic Survey: N-body Mock Challenge for Galaxy Clustering Measurements

We develop a series of N-body data challenges, functional to the final analysis of the extended Baryon Oscillation Spectroscopic Survey (eBOSS) Data Release 16 (DR16) galaxy sample. The challenges are primarily based on high-fidelity catalogues constructed from the Outer Rim simulation - a large box size realization (3h(-1) Gpc) characterized by an unprecedented combination of volume and mass resolution, down to 1.85 x 10(9) h(-1)M(circle dot). We generate synthetic galaxy mocks by populating Outer Rim haloes with a variety of halo occupation distribution (HOD) schemes of increasing complexity, spanning different redshift intervals. We then assess the performance of three complementary redshift space distortion (RSD) models in configuration and Fourier space, adopted for the analysis of the complete DR16 eBOSS sample of Luminous Red Galaxies (LRG5). We find all the methods mutually consistent, with comparable systematic errors on the Alcock-Paczynski parameters and the growth of structure, and robust to different HOD prescriptions - thus validating the robustness of the models and the pipelines used for the baryon acoustic oscillation (BAO) and full shape clustering analysis. In particular, all the techniques are able to recover and alpha(11) to within 0.9 per cent, and f sigma(8) to within 1.5 per cent. As a by-product of our work, we are also able to gain interesting insights on the galaxy-halo connection. Our study is relevant for the final eBOSS DR16 'consensus cosmology', as the systematic error budget is informed by testing the results of analyses against these high-resolution mocks. In addition, it is also useful for future large-volume surveys, since similar mock-making techniques and systematic corrections can be readily extended to model for instance the Dark Energy Spectroscopic Instrument (DESI) galaxy sample.

cosmology: theory, large-scale structure of Univer↗
DOE OSTI2025

SPE-CZE-MS Quantifies Zeptomole Amounts of Phosphorylated Peptides

Capillary zone electrophoresis (CZE) is gaining attention in the field of single-cell proteomics for its ultralow-flow and high-resolution separation abilities. Even more sample-limited yet rich in biological information are phosphoproteomics experiments, as the phosphoproteome composes only a fraction of the whole cellular proteome. Rapid analysis, high sensitivity, and maximization of sample utilization are paramount for single-cell analysis. Some challenges of coupling CZE analysis with mass spectrometry analysis (MS) of complex mixtures include 1. sensitivity due to volume loading limitations of CZE and 2. incompatibility of MS duty cycles with electropherographic time scales. Here, we address these two challenges as applied to singlecell- equivalent phosphoproteomics experiments by interfacing a microchip-based CZE device integrated with a solid-phaseextraction (SPE) bed with the Orbitrap Astral mass spectrometer. Using 225 phosphorylated peptide standards and phosphorylated peptide-enriched mouse brain tissue, we investigate microchip-based SPE-CZE functionality, quantitative performance, and complementarity to nano-LC-MS (nLC-MS) analysis. We highlight unique SPE-CZE separation mechanisms that can empower fitfor- purpose applications in single-cell-equivalent phosphoproteomics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Measurements of three-flavor neutrino oscillations from a PISCES two-detector fit to the NOvA Experiment data

NOvA is a long-baseline neutrino oscillation experiment with two functionally identical detectors: a Near Detector (ND) at Fermilab, placed 1 km from the neutrino source, and a Far Detector (FD) located 810 km away from the ND in Minnesota. NOvA s primary physics goals are to measure the neutrino oscillation parameters $\theta_{23}$ and $\Delta m^2_{32}$ with high precision, determine the neutrino mass hierarchy, and constrain the value of $\delta_{CP}$, primarily via the study of muon neutrino to electron neutrino oscillation. Extracting values for oscillation parameters from fits to data usually relies on treating systematic uncertainties as nuisance parameters, a strategy that suffers from poor scalability as the number of uncertainties becomes larger. This work introduces PISCES (Parameter Inference with Systematic Covariance and Exact Statistics), a novel method that circumvents this scalability problem by encoding systematic uncertainties into a covariance matrix. PISCES utilizes a nested minimization in which optimal systematic pulls are first computed using the covariance matrix in an inner minimization step, then the oscillation parameters are profiled over in the outer minimization. PISCES also uses a Poisson Likelihood term, making it ideal for the inclusion of low-statistic samples in the fits. PISCES is a flexible framework that also supports complex fits, such as a joint Near and Far detector fit. In the standard NOvA analysis, oscillation parameters are extracted using an extrapolation technique in which the ND data indirectly constrain the FD prediction via a ratio method. PISCES, on the other hand, enables a simultaneous ND+FD fit, allowing the high-statistics ND data to directly constrain systematic uncertainties across all samples. This thesis presents the full PISCES joint ND+FD fit for the NOvA three-flavor analysis, details its implementation, and evaluates its performance through extensive robustness tests and fake data studies. It also provides a comparison between the PISCES joint ND+FD results and the standard NOvA extrapolation method using the full NOvA 10-year data set. The results demonstrate that PISCES can successfully fit NOvA data while incorporating the constraints from the ND detectors consistently, using physically motivated systematic uncertainties to account for data/MC discrepancies.

Rajaoalisoa, Miriama [Cincinnati U.]↗
NASA NTRS2014

Coordinated Mineralogical and Isotopic Analysis of a Cosmic Symplectite Identified in a Stardust Terminal Particle

Comet Wild-2 samples returned by the Stardust spacecraft contain a chemically diverse mixture of material, underscoring the complex nature of comets. Studies of entire Stardust aerogel tracks afford the opportunity to examine the fine-grained particle fragments distributed along the length of the track as well as the terminal particles. Previous TEM characterization of a terminal particle (TP) in track #147 revealed a symplectically intergrown iron sulfide and oxide assemblage. Mineralogically similar assemblages, known as cosmic symplectites (COS, formerly termed "new-PCP"), have only been identified in the primitive carbonaceous chondrite Acfer 094. Meteoritic COS have isotopically heavy O compositions (delta (sup 17), O-18 = 180per mille) that point to interactions with early solar system primordial water. In this study we report mineralogical and O isotopic measurements of the Wild-2 COS assemblage. Experimental: Track #147 is a "bulbous"-type track (4600 microns long) containing 7 terminal particles. The TPs were removed from the track, embedded in epoxy, and ultramicrotomed. A JEOL 2500SE 200 keV field-emission scanning-transmission electron microscope was used to obtain quantitative elemental maps and detailed mineralogical characterization. Following TEM analysis, two thin sections of TP4 (12 microns) were analyzed for O isotopes by raster ion imaging with the JSC NanoSIMS 50L. All three O isotopes were measured simultaneously using electron multipliers. San Carlos olivine grains were used as isotopic standards. Results and Discussion: The COS in the Wild-2 track #147 TP4 sample consists of symplectically intergrown pentlandite and nanocrystalline maghemite which coexists with high-Ca pyroxene with Na and Cr (kosmochlor component). This kosmochlor component could have a nebular origin and be precursors to type II chondrules in ordinary chondrites. Yet pentlandite is not a stable phase in the nebula. The COS in Acfer 094 also consists of pentlandite, but contains magnetite [4] rather than the more oxidized maghemite observed in the Wild-2 COS. The Acfer 094 COS display heavy O isotopic compositions that are the result of sulfidization and oxidation of Fe, Ni-metal grains and sulfides by O-17- and O-18-rich water in the solar nebula or possibly on the parent body. The O isotopic composition of the Wild-2 COS, however, is indistinguishable from terrestrial, indicating it was not altered by the same primordial aqueous reservoir as the Acfer 094 COS. The alteration could have occurred on the parent body by isotopically equilibrated ice. The mineralogy and petrography of Wild-2 samples suggests an incomplete or nascent hydration process. In future work we will analyze S isotopes in the track #147 TP4 COS and search for additional COS in Stardust samples.

Nguyen, A. N.↗
DOE OSTI2019

Development of a rapid viability polymerase chain reaction method for detection of Yersinia pestis

Due to the occurrence of natural plague outbreaks and its historical usage as a biological weapon, Yersinia pestis is considered one of the high-priority biological threat agents. It can remain viable in certain environments including water for >100 days. Because of its slow-growth characteristic, it usually takes three or more days to detect and confirm the identity of viable Y. pestis cells by PCR, serological, or biochemical assays when using the traditional microbiological plate-culture-based analysis, and that too, assuming faster growing microbes present in a water sample do not mask the Y. pestis colonies and interfere with analysis. Therefore, a rapid-viability Polymerase Chain Reaction (RV-PCR) method was developed for detection of Y. pestis . The RV-PCR method combines 24 h-incubation broth culture in a 48-well plate, and pre- and post-incubation differential PCR analyses, thereby allowing for rapid and high-throughput sample analysis compared with the current plate culture method. One chromosomal and two plasmid gene target-based real-time PCR assays were down-selected, showing ca. 10 genome equivalent detection; the chromosomal assay was then used for RV-PCR method development. A 10 1 -cell level (10–99 cells) sensitivity of detection was demonstrated even with complex sample backgrounds including known PCR inhibitors (ferrous sulfate and humic acid), as well as metal oxides and microbes present in Arizona Test Dust (ATD). The method sensitivity was maintained in the presence of dead Y. pestis cells up to 10 4 cells per sample. While affording high-throughput and rapid sample analysis, the 48-well plate format used in this method for sample enrichment significantly reduced labor requirements and generation of BioSafety Level-3 (BSL-3) laboratory waste as compared to the usual microbiological plate-culture-based methods. In conclusion, this method may serve as a model for other vegetative bacterial pathogens.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

The Proposed Mars Astrobiology Explorer - Cacher [MAX-C] Rover: First Step in a Potential Sample Return Campaign

Sample return from Mars has been advocated by numerous scientific advisory panels for over 30 years, most prominently beginning with the National Research Council s [1] strategy for the exploration of the inner solar system, and most recently by the Mars Exploration Program Analysis Group (MEPAG s) Next Decade Science Analysis Group [2]. Analysis of samples here on Earth would have enormous advantages over in situ analyses in producing the data quality needed to address many of the complex scientific questions the community has posed about Mars. Instead of a small, predetermined set of analytical techniques, state of the art preparative and instrumental resources of the entire scientific community could be applied to the samples. The analytical emphasis could shift as the meaning of each result becomes better appreciated. These arguments apply both to igneous rocks and to layered sedimentary materials, either of which could contain water and other volatile constituents. In 2009 MEPAG formed the Mid-Range Rover Science Analysis Group (MRR-SAG) to formulate a mission concept that would address two general objectives: (1) conduct high-priority in situ science and (2) make concrete steps towards the potential return of samples to Earth. This analysis resulted in a mission concept named the Mars Astrobiology Explorer-Cacher (MAX-C), which was envisioned for launch in the 2018 opportunity. After extensive discussion, this group concluded that by far the most definitive contribution to sample return by this mission would be to collect and cache, in an accessible location, a suite of compelling samples that could potentially be recovered and returned by a subsequent mission. This would have the effect of separating two of the essential functions of MSR, the acquisition of the sample collection and its delivery to martian orbit, into two missions.

Allen, Carlton C.↗
DOE OSTI2019

Randomized methods to characterize large-scale vortical flow networks

We demonstrate the effective use of randomized methods for linear algebra to perform network-based analysis of complex vortical flows. Network theoretic approaches can reveal the connectivity structures among a set of vortical elements and analyze their collective dynamics. These approaches have recently been generalized to analyze high-dimensional turbulent flows, for which network computations can become prohibitively expensive. In this work, we propose efficient methods to approximate network quantities, such as the leading eigendecomposition of the adjacency matrix, using randomized methods. Specifically, we use the Nyström method to approximate the leading eigenvalues and eigenvectors, achieving significant computational savings and reduced memory requirements. The effectiveness of the proposed technique is demonstrated on two high-dimensional flow fields: two-dimensional flow past an airfoil and two-dimensional turbulence. We find that quasi-uniform column sampling outperforms uniform column sampling, while both feature the same computational complexity.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

Validation↗
NASA NTRSDate not supplied

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

Validation↗
DOE OSTI2020

Real-time sparse-sampled Ptychographic imaging through deep neural networks

Ptychography has rapidly grown in the fields of X-ray and electron imaging for its unprecedented ability to achieve nano or atomic scale resolution while simultaneously retrieving chemical or magnetic information from a sample. A ptychographic reconstruction is achieved by means of solving a complex inverse problem that imposes constraints both on the acquisition and on the analysis of the data, which typically precludes real-time imaging due to computational cost involved in solving this inverse problem. In this work we propose PtychoNN, a novel approach to solve the ptychography reconstruction problem based on deep convolutional neural networks. We demonstrate how the proposed method can be used to predict real-space structure and phase at each scan point solely from the corresponding far-field diffraction data. The presented results demonstrate how PtychoNN can effectively be used on experimental data, being able to generate high quality reconstructions of a sample up to hundreds of times faster than state-of-the-art ptychography reconstruction solutions once trained. By surpassing the typical constraints of iterative model-based methods, we can significantly relax the data acquisition sampling conditions and produce equally satisfactory reconstructions. Besides drastically accelerating acquisition and analysis, this capability can enable new imaging scenarios that were not possible before, in cases of dose sensitive, dynamic and extremely voluminous samples.

Cherukara, Mathew J↗
NASA NTRS2013

Community Supported Stardust Compendia

The Stardust cometary and interstellar collections present unprecedented challenges in sample preparation and analysis. The ensemble of approx.80 tracks and dozens of foil craters from the cometary collection for which we have analyses exhibits a bewildering complexity and diversity of materials. The interstellar collection is even more challenging, because of the extremely low fluence of interstellar dust, a relatively large background of secondary ejecta from impacts on the spacecraft, and the small size of interstellar dust, approximately three orders of magnitude smaller in mass than typical cometary particles. Unlike with the other returned sample collections, characterization of these samples beyond basic photo-documentation is not generally practical at JSC. Even among the other small-particle collections, currently the cosmic dust and Hayabusa samples, SEM/EDX can provide basic chemistry. This is not possible with Stardust particles without destructive and invasive sample preparation. Furthermore, SEM/EDX requires isolating small grains from adhering aerogel. A reliable technique to carry out this task does not exist. Complete characterization of particles requires coordinated analyses using synchrotron and electron-beam microprobes, which do not exist at any one lab. Thus, it was recognized since the Stardust Preliminary Examination in 2006 that characterization of the samples would rely on the worldwide community of Stardust Investigators. Here we announce the development of community-editable, wiki-style Stardust compendia that will support this effort. Our intention is that this will facilitate sample requests by providing basic characterization of tracks. We expect that this will also support comprehensive meta-analyses (global syntheses of analyses) of the collections.

Westphal, Andrew J.↗
DOE OSTI2019

Investigation of Compatibility Between M-Cr-Al-X Thermal Spray Coatings and Third Generation γ-TiAl Alloys

In this work, the physical and chemical compatibility of cast Ti-Al-Nb-Cr-Zr and Ti-Al-Nb-Cr-Zr-B-La alloys was investigated with oxidation-resistant M-Cr-Al-X thermal spray coatings. Ti and Al are main alloy elements to form γ-TiAl and α{sub 2}-Ti{sub 3}Al phases. To obtain coatings, we used air plasma spray and high-velocity oxygen fuel equipment. Four commercially available M-Cr-Al-X powders, including Ta-containing, were used as starting materials. Our investigation of compatibility between M-Cr-Al-X thermal spray coatings and γ-TiAl alloys consists of isothermal annealing in air muffle furnace during 100 h at 920 °C, followed by samples investigation. Oxidation products formed at coatings surface were studied by XRD analysis with Rietveld refinement. Interdiffusion between coatings and alloys was studied by means of cross-sectional SEM with EDX analysis. Plots were made to show concentration of each main element at the end of experiments. Samples were subjected to dynamic mechanical thermal analysis in order to determine the effect of high-temperature exposure on complex elastic modulus. Finally, burner rig cycling test was performed to estimate the thermal shock resistance of M-Cr-Al-X coatings.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Fundamental Studies on Poly(2-oxazoline) Side Chain Isomers Using Tandem Mass Spectrometry and Ion Mobility-Mass Spectrometry

When polymer mixtures become increasingly complex, the conventional analysis techniques become insufficient for complete characterization. Mass spectrometric techniques can satisfy this increasing demand for detailed sample characterization. Even though isobaric polymers are indistinguishable using simple mass spectrometry (MS) analyses, more advanced techniques such as tandem MS (MS/MS) or ion mobility (IM) can be used. Here, we report proof of concept for characterizing isomeric polymers, namely poly(2-n-propyl-2-oxazoline) (Pn-PrOx) and poly(2-isopropyl-2-oxazoline) (Pi-PrOx), using MS/MS and IM-MS. Pi-PrOx ions lose in intensity at higher accelerating voltages than Pn-PrOx ions during collision-induced dissociation (CID) MS/MS experiments. A Pn/i-PrOx mixture could also be titrated using survival yield calculations of either precursor ions or cation ejection species. IM-MS yielded shape differences in the degree of polymerization (DP) regions showing the structural rearrangements. Combined MS techniques are thus able to identify and deconvolute the molar mass distributions of the two isomers in a mixture. Finally, the MS/MS and IM-MS behaviors are compared for interpretation. .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Identification of Porphyrin-Silica Composite Nanoparticles using Atmospheric Solids Analysis Probe Mass Spectrometry

Porphyrins are critical pigments involved in biological energy transduction processes. Their abilities to absorb light, then convert it to energy, have raised the interest of using porphyrin nanoparticles as photosensitizers in photodynamic therapy. A current study showed that self- assembled porphyrin-silica composite nanoparticles can selectively destroy tumor cells, but detection of the cellular uptake of porphyrin-silica composite nanoparticles was limited to imaging microscopy. In this work, we developed a novel method to rapidly identify porphyrin-silica composite nanoparticles using Atmospheric Solids Analysis Probe-Mass Spectrometry (ASAP-MS). ASAP-MS can directly analyze complex mixtures without the need for sample preparation. Porphyrin-silica composite nanoparticles were vaporized using heated nitrogen desolvation gas, and their thermo-profiles were examined to identify distinct mass- to-charge (M/Z) signatures. HeLa cells were incubated in growth media containing the nanoparticles, and after sufficient washing to remove residual nanoparticles, the cell suspension was loaded onto the end of ASAP glass capillary probe. Upon heating, HeLa cells were degraded and porphyrin-silica composite nanoparticles were released. Vaporized nanoparticles were ionized and detected by MS. Furthermore, the cellular uptake of porphyrin-silica composite nanoparticles was identified using this ASAP-MS method.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Phloem Exudate Protein Profiles during Drought and Recovery Reveal Abiotic Stress Responses in Tomato Vasculature

Drought is the leading cause of agricultural yield loss among all abiotic stresses, and the link between water deficit and phloem protein contents is relatively unexplored. Here we collected phloem exudates from Solanum lycopersicum leaves during periods of drought stress and recovery. Our analysis identified 2558 proteins, the most abundant of which were previously localized to the phloem. Independent of drought, enrichment analysis of the total phloem exudate protein profiles from all samples suggests that the protein content of phloem sap is complex, and includes proteins that function in chaperone systems, branched-chain amino acid synthesis, trehalose metabolism, and RNA silencing. We observed 169 proteins whose abundance changed significantly within the phloem sap, either during drought or recovery. Proteins that became significantly more abundant during drought include members of lipid metabolism, chaperone-mediated protein folding, carboxylic acid metabolism, abscisic acid signaling, cytokinin biosynthesis, and amino acid metabolism. Conversely, proteins involved in lipid signaling, sphingolipid metabolism, cell wall organization, carbohydrate metabolism, and a mitogen-activated protein kinase are decreased during drought. Our experiment has achieved an in-depth profiling of phloem sap protein contents during drought stress and recovery that supports previous findings and provides new evidence that multiple biological processes are involved in drought adaptation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1988

Fine-scale traverses in cumulate rocks, Stillwater Complex: A lunar analogue study

The objective was to document finite-scale compositional variations in cumulate rocks from the Stillwater Complex in Montana and to interpret these data in the context of planetary magma fractionation processes such as those operative during the formation of the Earth's Moon. This research problem involved collecting samples in the Stillwater Complex and analyzing them by electron microprobe, X-ray fluorescence (XRF), and instrumental neutron activation analysis (INAA). The electron microprobe is used to determine the compositions of cumulus and intercumulus phases in the rocks, the XRF is used to determine the bulk-rock major element and trace element (Y, Sr, Rb, Zr, Ni, and Cr) abundances, and the INAA lab. is used to determine the trace element (Sc, Co, Cr, Ni, Ta, Hf, U, Th, and the REE) abundances of mineral separates and bulk rocks.

Elthon, Donald↗