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At least 127 records · Page 7

An Assessment of Cumulative Axial and Torsional Fatigue in a Cobalt-Base Superalloy

Cumulative fatigue under axial and torsional loading conditions can include both load-order (higMow and low/high) as well as load-type sequence (axial/torsional and torsional/axial) effects. Previously reported experimental studies on a cobalt-base superalloy, Haynes 188 at 538 C, addressed these effects. These studies characterized the cumulative axial and torsional fatigue behavior under high amplitude followed by low amplitude (Kalluri, S. and Bonacuse, P. J., "Cumulative Axial and Torsional Fatigue: An Investigation of Load-Type Sequance Effects," in Multiaxial Fatigue and Deformation: Testing and Prediction, ASTM STP 1387, S. Kalluri, and P. J. Bonacuse, Eds., American Society for Testing and Materials, West Conshohocken, PA, 2000, pp. 281-301) and low amplitude followed by high amplitude (Bonacuse, P. and Kalluri, S. "Sequenced Axial and Torsional Cumulative Fatigue: Low Amplitude Followed by High Amplitude Loading," Biaxial/Multiaxial Fatigue and Fracture, ESIS Publication 31, A. Carpinteri, M. De Freitas, and A. Spagnoli, Eds., Elsevier, New York, 2003, pp. 165-182) conditions. In both studies, experiments with the following four load-type sequences were performed: (a) axial/axial, (b) torsional/torsional, (c) axial/torsional, and (d) torsional/axial. In this paper, the cumulative axial and torsional fatigue data generated in the two previous studies are combined to generate a comprehensive cumulative fatigue database on both the load-order and load-type sequence effects. This comprehensive database is used to examine applicability of the Palmgren-langer-Miner linear damage rule and a nonlinear damage curve approach for Haynes 188 subjected to the load-order and load-type sequencing described above. Summations of life fractions from the experiments are compared to the predictions from both the linear and nonlinear cumulative fatigue damage approaches. The significance of load-order versus load-type sequence effects for axial and torsional loading conditions is discussed. Possible reasons for the observed differences between the computed and observed summations of cycle fractions are rationalized in terms of the observed ever lutions of cyclic axial and shear stress ranges in the cumulative fatigue tests.

Kalluri, Sreeramesh↗

Electrospray Collection of Lunar Dust

A report describes ElectroSpray Ionization based Electrostatic Precipitation (ESIEP) for collecting lunar dust particles. While some HEPA filtration processes may remove a higher fraction (>99.9 percent) of the particles, the high efficiency may not be appropriate from an overall system standpoint, especially in light of the relatively large power requirement that such systems demand. The new electrospray particle capture technology is described as a variant of electrostatic precipitation that eliminates the current drawbacks of electrostatic precipitation. The new approach replaces corona prone field with a mist of highly charged micro-droplets generated by electrospray ionization (ESI) as the mechanism by which incoming particles are attracted and captured. In electrospray, a miniscule flow rate (microliters/minute) of liquid (typically water and a small amount of salt to enhance conductivity) is fed from the tip of a needle held at a high voltage potential relative to an opposite counter electrode. At sufficient field strength, a sharp liquid meniscus forms , which emits a jet of highly charged droplets that drift through the surrounding gas and are collected on the walls of a conductive tube. Particles in the gas have a high probability of contact with the droplets either by adhering to the droplets or otherwise acquiring a high level of charge, causing them to be captured on the collecting electrode as well. The spray acts as a filtration material that is continuously introduced and removed from the gas flow, and thus can never become clogged.

Dziekan, Michael↗

OASIS: Organics Analyzer for Sampling Icy Surfaces

Liquid chromatography mass spectrometry (LC-MS) is a well established laboratory technique for detecting and analyzing organic molecules. This approach has been especially fruitful in the analysis of nucleobases, amino acids, and establishing chirol ratios [1 -3]. We are developing OASIS, Organics Analyzer for Sampling Icy Surfaces, for future in situ landed missions to astrochemically important icy bodies, such as asteroids, comets, and icy moons. The OASIS design employs a microfabricated, on-chip analytical column to chromatographically separate liquid ana1ytes using known LC stationary phase chemistries. The elution products are then interfaced through electrospray ionization (ESI) and analyzed by a time-of-flight mass spectrometer (TOF-MS). A particular advantage of this design is its suitability for microgravity environments, such as for a primitive small body.

Getty, S. A.↗

Concentration Effects and Ion Properties Controlling the Fractionation of Halides during Aerosol Formation

During the aerosolization process at the sea surface, halides are incorporated into aerosol droplets, where they may play an important role in tropospheric ozone chemistry. Although this process may significantly contribute to the formation of reactive gas phase molecular halogens, little is known about the environmental factors that control how halides selectively accumulate at the air−water interface. In this study, the production of sea spray aerosol is simulated using electrospray ionization (ESI) of 100 nM equimolar solutions of NaCl, NaBr, NaI, NaNO2, NaNO3, NaClO4, and NaIO4. The microdroplets generated are analyzed by mass spectrometry to study the comparative enrichment of anions (f (Isub x-)) and their correlation with ion properties. Although no correlation exists between f (sub x-) and the limiting equivalent ionic conductivity, the correlation coefficient of the linear fit with the size of the anions R(sub x-), dehydration free-energy ΔGdehyd, and polarizability alpha, follows the order: (R(sub x-)(exp −2)) > (R(sub x-)(exp −1)) >(R(sub x-) > delta G(sub dehyd) > alpha. The same pure physical process is observed in H2O and D2O. The factor f (sub x-) does not change with pH (6.8−8.6), counterion (Li+, Na+, K+, and Cs+) substitution effects, or solvent polarity changes in methanol − and ethanol−water mixtures (0 <= xH2O <= 1). Sodium polysorbate 20 surfactant is used to modify the structure of the interface. Despite the observed enrichment of I− on the air−water interface of equimolar solutions, our results of seawater mimic samples agree with a model in which the interfacial composition is increasingly enriched in I− < Br− < Cl− over the oceanic boundary layer due to concentration effects in sea spray aerosol formation.

iodine↗

A Simple and Sensitive LC-MS/MS Method for the Determination of Free 8-Hydroxy-2'-Deoxyguanosine in Human Urine

Urinary free 8-hydroxy-2'-deoxyguanosine (8OHdG), an oxidized product of DNA, and is frequently chosen as a biomarker of oxidative stress in humans, including studies of oxidative DNA damage during space flight. It is challenging to accurately and efficiently quantify urinary free 8OHdG in large scale human studies. LC-MS/MS is emerging as a preferable analytical technique owing its high sensitivity, selectivity and efficiency, compared to some traditional methods such as ELISA and HPLC. A simple and sensitive LC-MS/MS method has been developed for the determination of free 8OHdG in human urine. Sample preparation was done by solid phase extraction with a Waters Oasis HLB 96 well plate. A Waters Alliance 2795 HT Separation Module combined with a Quattro Micro tandem mass spectrometer was used as the LC-MS/MS system. The runtime of one injection can be less than 5 minutes using a reversed phase C18 column and an isocratic flow of methanol/water. ESI positive ions were quantified in the multiple reaction modes (MRM) using m/z 284 yields 168 for 8OHdG and m/z 289 yields173 for stable isotope labeled internal standard [(15)N5] 8OHdG. With this method for 8OHdG, a lower limit of quantitation of 1.0 nM (0.28 ng/mL) has been achieved using 100 microliter urine sample. The analytical range is between 1.0 and 100 nM with a correlation coefficient greater than or equal to 0.99. Good reproducibility can be obtained with intra-assay and inter-assay CVs less than or equal to 10% for 8OHdG spiked urine QC samples. This method can be used in high-throughput routine analysis of free 8OHdG in human urine.

Wang, Zuwei↗

OceanWATERS Lander Robotic Arm Operation

Ocean Worlds Autonomy Testbed for Exploration Research and Simulation (OceanWATERS) is an open-source simulator for developing onboard autonomy software for robotic exploration of ocean worlds, such as Europa, Enceladus, and Titan, built on the Robot Operating System (ROS) and Gazebo simulation environment. Inevitable ground communication delays increase demand for a high degree of autonomy during excavation, collection and transfer of samples to scientific instruments for in-situ analysis. This paper offers a detailed discussion of the robotic arm design and operation for such autonomous surface exploration, taking as reference the Europa Lander mission. The lander arm, which is designed primarily to acquire icy surface and subsurface samples within the arm’s workspace, is a 6-degree-of-freedom manipulator with two end effectors: a sample excavation tool and a trenching end-effector. The robotic arm’s modes and operations can be summarized as follows: stowed arm, intended as the lander arm default configuration characterized by zero-power consumption; un-stowed arm, target arm configuration after its first deployment; selection and deployment of the end-effector to use next; guarded move, to detect ground level at the desired trenching location; drill ice using the grinder; dig trench at a particular location using the scoop; deliver sample to the sample transfer dock; discard redundant samples. The motion planning tool used for the lander arm is MoveIt, a ROS package. MoveIt uses sampling-based planning and collision checking libraries to determine safe paths. The Rapidly Exploring Random Trees* (RRT*) has been chosen as default planning algorithm as it provides optimal plans with an exponential speed and is guaranteed to find a solution, if feasible solutions exist. Furthermore, this work quantifies and discusses the energy requirements for excavating and collecting samples. In OceanWATERS, force feedback from the terrain, which influences the arm dynamics, is modelled using a discrete element method (DEM) simulation. The DEM and Gazebo software run in parallel and communicate through a co-simulation plugin. This paper presents an analysis and comparison of three DEM open source software (YADE, ESyS-Particle, Project Chrono) for implementation in OceanWATERS and motivates the choice of YADE as most suitable candidate.

Damiana Catanoso↗

Overview of the Dragonfly Entry Aerosciences Measurements (DrEAM) Suite

NASA Ames and Langley arepartnering with DLR to propose acomprehensive instrumentation suite known as the Dragonfly Entry Aerosciences Meas-urements (DrEAM). DrEAM being the first competed mission to fly EDL instrumentation as part of NASA’s Engineering Science Investigation (ESI).DrEAM will provide key aerothermodynamicdata and performance analysisfor Dragonfly’s forebody and backshell therma lprotection system (TPS),and also includes a DLR-provided Data Acquisition System(DAS).Titan’s atmosphere predominantly consists of nitro-gen (~98% by mole) with small amounts of methane(~2% by mole)and other trace gases. CN is a strong ra-diator and is found in nonequilibriumconcentrationsfor Titan entry. The accurate modeling of nonequilibrium CN radiation has proven to be a difficult task. Prompted by the Huygensmission, many experimental campaigns and analyses were performed to better understand the aerothermal environments experience by the probe dur-ing Titan entry[1].However, the Huygens probe carried no heatshieldinstrumentation. Therefore,the DrEAM instrumentation suite will significantly advance the state-of-the-art not only by documenting theenviron-ment and performance of Dragonfly’sentry system but also by making keymeasurements in Titan’s atmos-phere for thefirst time, thus providing new benchmark dataapplicable to entry science more generally. Current Measurement Goals: Aerothermal envi-ronments and TPS responsewill be measured using sen-sors similarto the Mars Entry, Descent, and Landing In-strumentation2 (MEDLI2) Integrated Sensor Plug(MISP) and the COMbined Aerothermaland Radiome-ter Sensor (COMARS)suite[2], with the latter supplied by DLR.For MEDLI2, MISP usedembedded thermo-couples (TCs) todirectly measure in-depth temperature of theTPS at several locations,which can also be used to infer surface environmentsvia inverse analysis. For DrEAM, the MISPstyle plugswill be known as Drag-onfly Sensors for Aero-Thermal Reconstruction (Drag-STR)plugs. On Schiaparelli, the COMARSsuite in-cludedthree total surface-mounted heatflux sensors, three pressure sensors, and one radiometer. For DrEAM, the COMARS package will be known as COmbined Sensor System for Titan Atmosphere (COSSTA). Atmospheric density measurements and capsuleaerodynamic data will be obtained throughthe onboard Inertial Measurement Unit (IMU),supple-mented by pressure transducers similar tothose used by the MEDLI Mars Entry AtmosphericData System (MEADS).The DrEAM pressure sensors will be known as Dragonfly Atmospheric Flight Transducers(DrAFT) Both DragSTR and DrAFThave flight heritagefrom MISP and MEADS on the MSLand Mars 2020mis-sions, and the COMARS suite successfullyflew on the ESA Schiaparelli EDMlander. A preliminary layout of the sensors is shown in Fig. 1. Because Dragonflyuses the same aeroshell provider (i.e., LockheedMartin) and materials for the TPS,with what are expected to be sim-ilar thicknesses as MSL and Mars 2020on both the heat shield and backshell, theDrEAMinstrumentation will look to utilize the same techniques and processes as de-veloped byMEDLI and MEDLI2for vehicle integra-tion. This commonality alsoenables DrEAMto lever-age the extensiveground test qualifications performed forMEDLI and MEDLI2 and claim substantial heritagefor this system.

A Brandis↗

Soluble Organic Matter (SOM) analysis of the Hayabusa2 samples: The first results

The Hayabusa2 spacecraft successfully collected the surface and possible sub-surface materials of the asteroid 162173 Ryugu. Ryugu is a C-type asteroid characterized by a low-albedo surface probably consisting of hydrous minerals and carbonaceous materials. [1] The direct optical and spectral analysis of the returned samples indicates that Ryugu material is dominated by hydrous carbonaceous chondrite-like matter (similar to CI chondrites) [2]. Since carbonaceous chondrites have generally yielded various types of organic matter, the collected Ryugu grains are expected to contain diverse types of organic compounds including bio-related molecules. The occurrence of organic compounds in the Ryugu surface will provide clues to the evolution of prebiotic molecules and their preservations associated with aqueous alteration of the primitive asteroid. The initial analysis of soluble organic matter (SOM) of the Hayabusa2-returned samples has been performed by an international team consisting of 32 members. Because the sample amount available for comprehensive SOM analyses is limited, and because the SOM is expected to be present as a complex mixture of various types of organic compounds with very small concentrations of each compound, high-sensitivity and high-resolution analytical techniques have been developed using carbonaceous meteorites [e.g. 3]. Two aggregate samples of the Ryugu grains (A106 and C107) were allocated for the solvent extractions and bulk carbon (C), hydrogen (H), nitrogen (N), sulfur (S) and oxygen (O) measurements. The A106 sample was collected during the 1st sampling in February 2019 and the C107 sample was collected during the 2nd sampling in July 2019 after the Small Carry Impactor (SCI) operation. They consist mainly of particles smaller than 1 mm in diameter, and each sample mass was 38-39 mg. They were firstly investigated spectroscopically in the near infrared wavelength range by the Stone Team prior to the solvent extractions. Other small grains (A0080 and C0057) were also allocated for this study to investigate the spatial distribution of organic compounds on the sample surface. The extraction and analytical measurements implemented by the SOM Team are summarized in Figure 1. Each powder sample was extracted sequentially with non-polar to polar solvents, i.e., hexane, dichloromethane (DCM), methanol (MeOH) and H2O, for non-targeted analysis to reveal the compound composition. Each solvent extract was analyzed by solution state nuclear magnetic resonance (NMR) spectroscopy [4], Fourier transform- ion cyclotron resonance/mass spectrometry (FT-ICR/MS) with ESI and APPI ionization [5] and by high-resolution mass spectroscopy using Orbitrap MS coupled with nano-liquid chromatography (nanoLC/Orbitrap MS) [6], and using two dimensional gas chromatography/mass spectrometry (GC×GC/MS). The extracted residues were passed to the Chemistry Team for further inorganic element analysis. The other powder sample was subjected to the hot water extraction for amino acid analyses including chiral isomer separation, which was performed by three-dimensional (3D) high-performance liquid chromatography (HPLC) with high-sensitivity fluorescence detection (FD) [7] and by HPLC/FD coupled with quadrupole-time of flight/mass spectrometry (QToF/MS) [8]. After the hot water extraction, the residue was split into two halves. One half was further extracted with hydrochloric acid (HCl) to analyze for amino acids in bound-form. The other half was sequentially extracted with DCM/MeOH (1/1) to analyze semi-polar compounds such as polycyclic aromatic hydrocarbons (PAHs) by GC/MS, followed by further extraction with formic acid to analyze polar heterocyclic compounds, and subsequent extraction with HCl to detect bound-form polar compounds. The extracted residues were passed to the IOM Team for the analysis of insoluble organic matter (IOM). Compound-specific stable isotope analyses will be performed using GC/combustion/isotope ratio mass spectrometry (GC/C/IRMS) if the compound concentration is high enough to enable such an isotopic measurement. All extraction procedures were performed on an ISO 6 (Class 100) clean bench inside an ISO 5 (Class 1000) clean room. Baked serpentine powder was also analyzed as a procedural blank. In situ organic compound analysis with the molecular imaging was performed using desorption electrospray ionization (DESI) equipped with Orbitrap MS [9, 10], followed by spatial imaging of organic compounds using ToF/secondary ion mass spectrometry (ToF/SIMS) [11]. The bulk chemical and isotopic compositions of CNS and HO were determined using nano-elemental analysis/isotope ratio mass spectrometry (nanoEA/IRMS) [12] and EA/pyrolysis/IRMS, respectively. We have identified a variety of indigenous organic compounds in the extracts of both A106 and C107 samples. The Ryugu grains host organic molecules under the high-vacuum and cosmic-ray irradiation environment of the asteroid surface. The analysis of extracted molecules is in progress, and the first results will be presented at the symposium.

Hiroshi Naraoka↗

Dust Mitigation Technology to Enable Survive the Night Capabilities

Introduction: As we return to the Moon, the lunar regolith (i.e. lunar dust) covering the surface will be an obstacle to nominal operations. Accounts from Apollo astronauts and analysis of hardware returned from the surface illustrate just how deleterious the dust can be [1]. During Apollo missions, the lunar dust adhered to hardware mechanically and electrostatically [2]. Surviving the Night: Mitigating the lunar dust will be critical to surviving the night. Going hand-in-hand with other extreme environment considerations, dust mitigation is critical to mission success. Dust Impacts on Other Systems: The lunar dust can have negative implications for power, thermal, mechanisms, and several other systems or sub-systems. For example, Apollo encountered marked degradation of performance in heat rejection systems for the lunar roving vehicle, science packages, and other components because of the lunar dust [1]. For power alone, dust can cause internal clogging for power connectors, heat rejection issues, excessive dust on reflective surfaces, reduced power output for solar arrays, and so on. Dust Mitigation Strategy: In addition to considering technology solutions, it is important for hardware, systems, and or components to have a dust mitigation strategy. At a high level, hardware that will encounter the lunar dust should consider these things when defining a dust mitigation strategy: • Understand Natural Environment • Understand Induced Environment • Understand Tolerance to Dust • Write Dust Requirements • Select Dust Mitigation Solutions • Test Hardware in Dusty Environment More information on each of these can be provided to hardware owners. Dust Mitigation Technology Development: NASA has a series of technologies that may be available for hardware that needs to survive the lunar night. Many of these solutions are leveraging dust mitigation technology development efforts from NASA’s Space Technology Mission Directorate (STMD), as well as efforts from ESDMD programs, industry, and academia. Through a series of STMD programs (both internal to NASA and through partnerships), there are several technologies in development as considerations as dust mitigation solutions for hardware. Within STMD, the Game Changing Development Program (GCD) has funded several internal dust mitigation projects including low to mid TRL development, demonstrations on CLPS landers of high TRL solutions, and creating standards and best practices for dust mitigation. STMD dust mitigation efforts also include a series of partnerships for developing technologies and advancing the state of dust mitigation at NASA. This includes the Lunar Surface Innovation Consortium (LSIC), Small Business Innovation Research, Early Stage Innovations (ESI), Space Technology Research Grants (STRG), Announcement of Collaboration Opportunities (ACOs) and Tipping Points (TPs), and Challenges and Crowdsourcing, among others. There are also a series of dust mitigation solutions that have been widely used terrestrially, or during Apollo. In recent years, several studies have produced more data on the efficacy of these potential solutions in the lunar environment. Dust Mitigation Solutions: Dust mitigation solutions generally fall into four categories: • Dust Tolerant Mechanisms • Passive Dust Mitigation Capabilities • Active Dust Mitigation Capabilities • Dust Measurement Capabilities There are a series of solutions that may prove beneficial for hardware that needs to survive the lunar night, including new technology development as well as proven, terrestrial solutions. This presentation will discuss in more detail what some of these solutions are for payloads going to the surface. References: [1] J. R. Gaier, NASA/TM—2005-213610, The Effects of Lunar Dust on EVA Systems During the Apollo Missions [2] T. J. Stubbs, et al. Impact of Dust on Lunar Exploration, 2005

dust mitigation↗

Survive the Dust: Dust Mitigation Technology to Enable Survive the Night Capabilities

Introduction: As we return to the Moon, the lunar regolith (i.e. lunar dust) covering the surface will be an obstacle to nominal operations. Accounts from Apollo astronauts and analysis of hardware returned from the surface illustrate just how deleterious the dust can be [1]. During Apollo missions, the lunar dust adhered to hardware mechanically and electrostatically [2]. Surviving the Night: Mitigating the lunar dust will be critical to surviving the night. Going hand-in-hand with other extreme environment considerations, dust mitigation is critical to mission success. Dust Impacts on Other Systems: The lunar dust can have negative implications for power, thermal, mechanisms, and several other systems or sub-systems. For example, Apollo encountered marked degradation of performance in heat rejection systems for the lunar roving vehicle, science packages, and other components because of the lunar dust [1]. For power alone, dust can cause internal clogging for power connectors, heat rejection issues, excessive dust on reflective surfaces, reduced power output for solar arrays, and so on. Dust Mitigation Strategy: In addition to considering technology solutions, it is important for hardware, systems, and or components to have a dust mitigation strategy. At a high level, hardware that will encounter the lunar dust should consider these things when defining a dust mitigation strategy: • Understand Natural Environment • Understand Induced Environment • Understand Tolerance to Dust • Write Dust Requirements • Select Dust Mitigation Solutions • Test Hardware in Dusty Environment More information on each of these can be provided to hardware owners. Dust Mitigation Technology Development: NASA has a series of technologies that may be available for hardware that needs to survive the lunar night. Many of these solutions are leveraging dust mitigation technology development efforts from NASA’s Space Technology Mission Directorate (STMD), as well as efforts from ESDMD programs, industry, and academia. Through a series of STMD programs (both internal to NASA and through partnerships), there are several technologies in development as considerations as dust mitigation solutions for hardware. Within STMD, the Game Changing Development Program (GCD) has funded several internal dust mitigation projects including low to mid TRL development, demonstrations on CLPS landers of high TRL solutions, and creating standards and best practices for dust mitigation. STMD dust mitigation efforts also include a series of partnerships for developing technologies and advancing the state of dust mitigation at NASA. This includes the Lunar Surface Innovation Consortium (LSIC), Small Business Innovation Research, Early Stage Innovations (ESI), Space Technology Research Grants (STRG), Announcement of Collaboration Opportunities (ACOs) and Tipping Points (TPs), and Challenges and Crowdsourcing, among others. There are also a series of dust mitigation solutions that have been widely used terrestrially, or during Apollo. In recent years, several studies have produced more data on the efficacy of these potential solutions in the lunar environment. Dust Mitigation Solutions: Dust mitigation solutions generally fall into four categories: • Dust Tolerant Mechanisms • Passive Dust Mitigation Capabilities • Active Dust Mitigation Capabilities • Dust Measurement Capabilities There are a series of solutions that may prove beneficial for hardware that needs to survive the lunar night, including new technology development as well as proven, terrestrial solutions. This presentation will discuss in more detail what some of these solutions are for payloads going to the surface. References: [1] J. R. Gaier, NASA/TM—2005-213610, The Effects of Lunar Dust on EVA Systems During the Apollo Missions [2] T. J. Stubbs, et al. Impact of Dust on Lunar Exploration, 2005

dust mitigation↗

Role of Antecedent Soil Moisture and Vegetation Stress in Lightning-Initiated Wildfires

Lightning-caused wildfires are a small percentage of all wildfire events within the Conterminous U.S. (CONUS), but they account for over 56% of the acreage burned. The atmospheric conditions favoring wildfire and rapid growth are well understood: large dewpoint depressions, unstable planetary boundary layer, strong winds, etc. However, antecedent land surface conditions affecting dead and live fuel moisture is more difficult to quantify. This study examines over 20 years of antecedent land surface, vegetation stress, and wildfire characteristic data associated with nearly 77,000 lightning-initiated wildfires from the U.S. Forest Service Wildfire Database. We will invoke two in-house databases generated by the NASA Short-term Prediction Research and Transition (SPoRT) Center: an observations-driven, climatological run of the Noah land surface model within the NASA Land Information System (i.e., SPoRT-LIS) to depict soil moisture deficits / anomalies, and a satellite-constrained Evaporative Stress Index (ESI) product to denote areas of stressed vegetation. We will mine these datasets associated with lightning-caused (and null) events to determine important relationships, distributions, and delineators that correspond to elevated threat areas for lightning-initiated wildfires.

Wildfire↗

Search for NuMI $\mu$DAR Electron Neutrinos in MicroBooNE

Muon Decay-at-Rest ($\mu$DAR) produces electron-neutrinos ($\nu_e$) in the $0$ to $53$ MeV energy range. The given range is especially interesting for its similarity to Supernovae-produced $\nu_e$. The Deep Underground Neutrino Experiment (DUNE) has as one of its main goals to measure Supernovae neutrinos on the occasion of a Galactic Supernova burst. To optimize the chances of detection, a low-energy neutrino-LAr cross-section (XS) measurement is a piece of important information to have at hand. MicroBooNE presents a good opportunity to explore the low-energy $\nu$-LAr detection and XS using the $\mu$DAR neutrinos and therefore develop the tools necessary for DUNE to in is a LArTPC that has been collecting neutrino data since October 2015 from the Booster Neutrino Beam (BNB) and off-axis to the Neutrinos at the Main Injector (NuMI) beam, both copious sources of $\mu$DAR neutrinos. esis, we present a first attempt to measure MeV-scale neutrinos in a LArTPC. To do that, we use specifi c MeV-scale reconstruction tools combined with other traditional reconstruction tools used in MicroBooNE. We discuss the tool's performance, limitations, and provide suggestions on how to improve them. zes looks for $\mu$DAR neutrino- argon charged current interactions in the NuMI Run1 data, that contains $2\times 10^{20}$ POT. We observed $9,176$ signal candidates. The number of expected background events is $8,776$, the majority from cosmic rays. We establish a XS upper limit of $<\sigma> = 1.99\times10^{-37} \textrm{cm}^2 / \textrm{Ar}$, which corresponds to $551.9$ times the nominal prediction from MARLEY, the neutrino generator used in this work. Despite the lack of sensitivity, this work is the first of its kind and sets the foundation for future similar analysis in the future. In the conclusions, we discuss how this results can be further improved in MicroBooNE.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Selective Detection of Diglycolamide Diastereomers By Metal-Ligand Cluster Formation

Introduction (120 words): Differentiation of isomers using mass spectrometry is a challenge, as these species tend to produce ions of identical mass-to-charge ratio. Therefore, separation with mass spectrometry must rely on chemical differences between isomeric species. Separation of stereoisomers is especially challenging, as these species often have very similar chemistry. However, recent investigations of the solvent extraction behavior of diastereomers of diglycolamide molecules have shown that different stereoisomers can have significantly different lanthanide extraction efficiencies. These studies showed that the R,S stereoisomer of 2,2'-oxybis(N,N-dioctylpropanamide efficiently extracts lanthanides, while the S,S stereoisomer does not. Thus, gas-phase metal complexation may provide a pathway for differentiating these species using mass spectrometry. Methods (120 words): Europium, samarium, and holmium clusters with the R,S, and the S,S diastereomers of 2,2'-oxybis(N,N-didecylpropanamide (trivially tetradecyl diglycolamide, or mTDDGA) were generated in gas-phase using the electrospray ionization source of a Bruker (Billerica, MA, USA) micrOTOF-Q II quadrupole time-of-flight mass spectrometer. Solutions of aqueous lanthanide nitrate and diglycolamide ligands in 2-propanol were added to 50%:50% by volume acetonitrile:2-propanol to generate the spray solutions. Ligand concentration was maintained at approximately 6 µM, while lanthanide concentration was maintained at either 6 µM or 30 µM . High resolution, high mass accuracy spectra were recorded using the time-of-flight. Mass accuracy was ensured using external calibration with Agilent (Santa Clara, CA, USA) ESI-L Low Concentration tuning mix. Preliminary data (300 words): Electrospray of solutions containing only R,S-mTDDGA or S,S-m-TDDGA yield abundant peaks at m/z= 721.7, corresponding to [mTDDGA+H]+1, m/z = 743.7, corresponding to [mTDDGA+Na]+1, and m/z = 1464.4, corresponding to the sodium-bound dimer, [Na(mTDDGA)2]+1. Spray of solutions containing 6 µM europium (Eu) with 3 µM R,S-mTDDGA produced an abundant cluster ion with an isotopic envelope centered at m/z=772.0, corresponding to [Eu(R,S-mTDDGA)3]3+. Europium-containing cluster ions with isotopic envelopes apexing at m/z = 1012.3 and 1189.0 correspond to the [Eu(R,S-mTDDGA)4]3+ and [Eu(R,S-mTDDGA)5]3+ cluster ions, respectively. Protonated and sodiated R,S-mTDDGA are present as well, along with the sodium-bound dimer. In contrast, spray of solutions containing 6 µM europium (Eu) with 3 µM S,S-mTDDGA diastereomer yielded only protonated and sodiated ligand ions; no Eu- S,S-mTDDGA ions were present. This mirrors the solution-phase behavior, where the S,S diestereomer extracts lanthanides with significantly less efficiency than the R,S diestereomer. Experiments with holmium and samarium yielded the same results. Increasing the lanthanide concentration to 30 µM resulted in limited formation of lanthanide-S,S-mTDDGA clusters. However, the abundance of the [Ln(S,S-mTDDGA)3]3+ clusters remained low compared to the abundance of the protonated and sodiated ligand. Additionally, the abundance of the [Ln(R,S-mTDDGA)3]3+ cluster ion was significantly higher than that of the protonated and sodiated ligand in experiments with spray solutions containing 30 µM lanthanide with R,S-mTDDA, supporting the hypothesis that R,S-mTDDGA has a higher intrinsic affinity for the lanthanides than S,S-mTDDGA. Thus, the intrinsic complexation with lanthanides appears to offer a route to differentiate diglycolamide diestereomers in the gas-phase. Novelty (20): Stereoisomers can be differentiated in the gas phase by exploitation of differences in metal complexation chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Preliminary Evidence of Gas-Phase Water Splitting on Holmium Nitrogen Oxide Clusters

Preliminary Evidence of Gas-Phase Water Splitting on Holmium Nitrogen Oxide Clusters Christopher A. Zarzana1, Makayla R. Baxter , Introduction: Molecular hydrogen is a potential energy carrier that could be used to help implement a clean energy economy if it is generated from splitting of water. Improvements in the efficiencies of water-splitting electrolyzers relies on development of novel materials with enhanced performance. However, research in this area is slowed due to underdeveloped understanding of the mechanisms of device performance due to challenges interrogating the fundamental chemical reactions at play in bulk materials. Studies of the intrinsic reactivity of clusters that are representative of the reactive sites of these materials can increase understanding of the fundamental reaction mechanisms involved in hydrogen production, allowing for more efficient development of new water-splitting materials. Methods: Holmium tetranitrato ([Ho(NO3)4]-) clusters were generated in gas-phase using the electrospray ionization source of a Bruker (Billerica, MA, USA) micrOTOF-Q II quadrupole time-of-flight mass spectrometer. Spray solutions consisted of aqueous holmium (Ho) nitrate solutions (at nominally 3 mM) diluted to 30 µM in acetonitrile. The holmium (Ho) tetranitrato clusters were isolated using the quadrupole and were subsequently activated and allowed to react with background water in the collision cell. High resolution, high mass accuracy spectra were recorded using the time-of-flight. Mass accuracy was ensured using external calibration with Agilent (Santa Clara, CA, USA) ESI-L Low Concentration tuning mix. Preliminary data: Collisional activation of the holmium tetranitrato complexes ([Ln(NO3)4]-) resulted in an expected series of ions resulting from the loss of ·NO and ·NO2. This included an ion at m/z = 382.885 assigned as [HoO2(NO3)3]- (theoretical m/z=382.884, error=-1.2 ppm), resulting from loss of ·NO, and an ion at m/z=366.890 assigned as [HoO(NO3)3]- (theorical m/z=366.889, error=-1.8 ppm), resulting from loss of ·NO2. Additional ions were detected that would result from more complicated losses from [Ho(NO3)4]-, including ions at m/z=320.898 assigned as [HoO2(NO3)2]- (theoretical m/z=320.896, error=-4.9 ppm), at m/z=304.904 assigned as [HoO(NO3)2]- (theoretical m/z=304.901, error=-8.1 ppm, very low signal), and at m/z=288.908 assigned as [Ho(NO3)2]- (theoretical m/z=288.907, error=-3.4 ppm). This ion series would arise from loss of some combination of ·NO, ·NO2, and ·NO3, although it is not known whether these losses occur sequentially (e.g. loss of ·NO and ·NO3 to yield [HoO2(NO3)2]-) or as a single species (e.g. direct loss of N2O4). These ions were accompanied by a complementary series representing addition of a single water molecule. This included an ion at m/z=338.908 assigned as [HoO2(NO3)2H2O]- (theoretical m/z=338.907, error=-4.1 ppm), an ion at m/z=322.912 assigned as [HoO(NO3)2H2O]- (theoretical m/z=322.912, error=1.2 ppm), and an ion at m/z=306.918 assigned as [Ho(NO3)2H2O]-, (theoretical m/z=306.918, error=-3.7 ppm). An additional hydrated ion was observed at m/z=276.921 assigned as [HoO2(NO3) H2O]- (theoretical m/z=276.919, error=-7.3 ppm), although corresponding dehydrated ion was not observed. An additional ion was observed at m/z=367.898 that has been assigned as [Ho(NO3)3OH]- (theoretical m/z=367.897, error=-2.5 ppm). It is hypothesized that this ion arises from addition of water to [Ho(NO3)3]- followed by elimination of a hydrogen radical. Neither [Ho(NO3)3]- nor [Ho(NO3)3H2O]- were detected, suggesting that, if the hypothesis is correct, addition of water to [Ho(NO3)3]- and its subsequent splitting is rapid. Elimination of HNO3 from [Ho(NO3)4H2O]- could also yield [Ho(NO3)3OH]-; however, no [Ho(NO3)4H2O]- ions were observed. Novelty: Potential evidence of water splitting on gas-phase lanthanide clusters offers a way to study the intrinsic reactivity of hydrogen-generation materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

2023 American Society for Mass Spectrometry (ASMS) 71st Annual Conference on Mass Spectrometry and Allied Topics

Introduction (120 words max) Understanding metal-cluster chemistry occuring at solvent boundaries in the aqueous and organic phases has applications in environments from cellular processes to nuclear fuel reprocessing. Transport of metal ions at the boundaries from aqueous to organic phases involves forming a metal-ligand complex, and wherever the initial metal coordination environment is significantly different from the final one, the metal transitions through a series of transient species in passing from one phase to another. Here an investigation of the role of coordination in the chemistry of the transient species using gas-phase measurements that are free of solvent effects to better understand the binding of complexes of metals with triphenylphosphine chalcogenide ligands, examining metal-ligand homo- and hetero-dimers to better understand transient species. Methods (120 word max) Mass spectrometry and collision induced dissociation (CID) experiments were performed with a Bruker (Billerica, MA, USA) micrOTOF-Q II quadrupole time-of-flight mass spectrometer (QTOF) and Bruker amaZon speed ETD (ion trap). High resolution/high mass accuracy spectra were generated using the QTOF. External calibration was performed with Agilent (Santa Clara, CA, USA) ESI-L Low Concentration tuning mix. Both mass spectrometers were equipped with either the electrospray ionization source or nanospray sources. Metal samples were prepared between 40 – 60 uM of the metal-ligand complex in 25% water and 75% acetonitrile. Metal-ion clusters were isolated and subjected to collision induced dissociation. Density functional theory calculations were performed. Preliminary Data or Plenary Speakers Abstract (300 words max) Metal ion clusters with triphenylphosphine chalcogenide ligands were observed for group I metals with triphenylphosphine chalcogenide samples in the mass spectrum upon electrospray ionization. For each metal ligand complex of interest, the parent ion was isolated and collision induced dissociation fragmentation spectra were acquired. We observed clusters of group I metal with triphenylphosphine oxide, triphenyl phosphine sulfide, and triphenylphosphine selenide, with homodimers and heterodimer formation. In samples where the ligands were mixed, we observed mixed sodium ligand clusters at varying amounts. These mixed ligand clusters were fragmented. Metal clusters of mixed ligand dimers containing triphenylphosphine oxide showed preferential loss of the other ligand, either triphenylphosphine sulfide or triphenyl selenide. In samples with mixed triphenylphosphine sulfide and triphenylphosphine selenium ligands, sodium bound similarly between the ligands, and losses were more evenly split, showing loss ratio upon CID with losses of triphenylphosphine sulfide:triphenylphosphine selenide 43:57 ratio observed on CID. These results suggest that the oxide binds significantly more strongly than either the selenium or sulfur triphenylphosphine ligand, and the sulfur and selenium ligands are more evenly bound. Calculations were performed using density functional theory to calculate likely structures and bond energies between the group I metal and the ligands. Novel Aspect Novel analysis of sodium bound dimers with chalcogenide triphenylphosphine ligands were investigated using mass spectrometry and theoretical calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SEAS Communication Engine: An Extensible, Flexible Wrapper for Co-Simulation Agents

When modeling and analyzing the power grid and other large scale systems, researchers often express scenarios as optimization problems and feed them into advanced software solvers. In order to allow multiple solvers to communicate with each other and share data from different domains, the National Renewable Energy Laboratory (NREL) and associated Department of Energy (DOE) labs have developed a software framework called the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). HELICS allows cosimulation via a collection of client libraries for different languages that can be called from the appropriate optimization software. However, these client libraries do not provide a higher level of abstraction beyond reading and writing data off of the shared HELICS bus. In this paper, we describe a new software library called the SEAS Communication Engine that exposes a higher-level API for running cosimulation problems. The SEAS Engine provides a class-based abstraction on top of the Python HELICS client, in order to allow users to implement their domain-specific cosimulations without needing to interact with core HELICS primitives. This will make adoption of HELICS and cosimulation in general easier, by exposing a simpler API. In the second part of the paper, we validate our library on a collection of different simulation examples, including the canonical IEEE 13 Bus Feeder. Lastly, we demonstrate using the SEAS Engine to directly call domain-specific code written in the Julia programming language. Our hope is that this will serve as a template for easily calling software in different programming languages via the SEAS Engine, thereby avoiding code duplication and complexity.

co-simulation↗