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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
NASA NTRS2008

Fluid control structures in microfluidic devices

Methods and apparatus for implementing microfluidic analysis devices are provided. A monolithic elastomer membrane associated with an integrated pneumatic manifold allows the placement and actuation of a variety of fluid control structures, such as structures for pumping, isolating, mixing, routing, merging, splitting, preparing, and storing volumes of fluid. The fluid control structures can be used to implement a variety of sample introduction, preparation, processing, and storage techniques.

Mathies, Richard A.↗
DOE OSTI2021

Fractionation of Oxygen Isotopes in Uranium Oxides during Peroxide Precipitation and Dry Air Calcination

The interaction between uranium and oxygen-containing substrates is nearly ubiquitous within the nuclear fuel cycle. Given the well-known and predictable oxygen stable isotope compositions of atmospheric oxygen and meteoric waters around the world, the use of these isotopes as a potential geolocation or processing signature of uranium compounds has been of interest within the nuclear safeguards community. This study focuses on measuring the oxygen-stable isotope composition of synthetically produced uranium oxides to determine the mechanism and extent of fractionation during materials processing relevant to the nuclear fuel cycle. Here, metastudtite [UO 2 O 2 (H 2 O) 2 ] samples were first produced using water and hydrogen peroxide of a known oxygen isotope composition. This starting material was calcined in dry air at temperatures ranging from 300 °C to 1000 °C for 20 h producing oxides ranging in composition from UO 3 +x (0 ≤ x ≤ 0.5) to U 3 O 8 . In addition, calcinations between 500 and 800 °C were performed at different time intervals to evaluate the rate of isotopic equilibration. The δ 18 O values of water bound to metastudtite were measured by thermogravimetric analysis coupled to isotope ratio infrared spectroscopy (TGA–IRIS). A redesigned fluorination manifold was constructed at the University of Utah and was used to extract the bulk oxygen from precipitated and calcined products using bromine pentafluoride (BrF 5 ). Mineralization water on metastudtite (measured by TGA–IRIS) was closely associated with the aqueous environment of precipitation with a fractionation of +3.5 ± 0.6‰. In contrast, bulk oxygen from metastudtite (measured by fluorination and gas chromatography combined with isotope ratio mass spectrometry) was found to have an inconsistent fractionation with precipitation water. Samples calcined in dry air exhibited a wide range of oxygen isotope compositions which increased from δ 18 O = +1.4 ± 0.9‰ at 300 °C to +17.3 ± 0.9‰ at 1000 °C. This variation in δ 18 O values was a result of oxygen exchange with atmospheric O 2 and was found to be rapid at calcination temperatures greater than 600°C—with equilibration occurring in less than 2 h. These results provide insights into the incorporation and exchange of oxygen isotopes during precipitation and calcination processes comparable to those employed within the nuclear fuel cycle and establish a foundation for future investigations to build upon.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS1993

Technical Update: Johnson Space Center system using a solid electrolytic cell in a remote location to measure oxygen fugacities in CO/CO2 controlled-atmosphere furnaces

Details are given for the design and application of a (one atmosphere) redox-control system. This system differs from that given in NASA Technical Memorandum 58234 in that it uses a single solid-electrolytic cell in a remote location to measure the oxygen fugacities of multiple CO/CO2 controlled-atmosphere furnaces. This remote measurement extends the range of sample-furnace conditions that can be measured using a solid-electrolytic cell, and cuts costs by extending the life of the sensors and by minimizing the number of sensors in use. The system consists of a reference furnace and an exhaust-gas manifold. The reference furnace is designed according to the redox control system of NASA Technical Memorandum 58234, and any number of CO/CO2 controlled-atmosphere furnaces can be attached to the exhaust-gas manifold. Using the manifold, the exhaust gas from individual CO/CO2 controlled atmosphere furnaces can be diverted through the reference furnace, where a solid-electrolyte cell is used to read the ambient oxygen fugacity. The oxygen fugacity measured in the reference furnace can then be used to calculate the oxygen fugacity in the individual CO/CO2 controlled-atmosphere furnace. A BASIC computer program was developed to expedite this calculation.

Jurewicz, A. J. G.↗
DOE OSTI2020

Machine Learning Calabi–Yau Metrics

We apply machine learning to the problem of finding numerical Calabi–Yau metrics. Building on Donaldson's algorithm for calculating balanced metrics on Kähler manifolds, we combine conventional curve fitting and machine-learning techniques to numerically approximate Ricci-flat metrics. We show that machine learning is able to predict the Calabi–Yau metric and quantities associated with it, such as its determinant, having seen only a small sample of training data. Using this in conjunction with a straightforward curve fitting routine, we demonstrate that it is possible to find highly accurate numerical metrics much more quickly than by using Donaldson's algorithm alone, with our new machine-learning algorithm decreasing the time required by between one and two orders of magnitude.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2010

Cryogenic Absorption Cells Operating Inside a Bruker IFS-125HR: First Results for 13CH4 at 7 Micrometers

New absorption cells designed specifically to achieve stable temperatures down to 66 K inside the sample compartment of an evacuated Bruker IFS-125HR Fourier transform spectrometer (FTS) were developed at Connecticut College and tested at the Jet Propulsion Laboratory (JPL). The temperature stabilized cryogenic cells with path lengths of 24.29 and 20.38 cm were constructed of oxygen free high conductivity (OFHC) copper and fitted with wedged ZnSe windows using vacuum tight indium seals. In operation, the temperature-controlled cooling by a closed-cycle helium refrigerator achieved stability of 0.01 K. The unwanted absorption features arising from cryodeposits on the cell windows at low temperatures were eliminated by building an internal vacuum shroud box around the cell which significantly minimized the growth of cryodeposits. The effects of vibrations from the closed-cycle helium refrigerator on the FTS spectra were characterized. Using this set up, several high-resolution spectra of methane isotopologues broadened with nitrogen were recorded in the 1200-1800 per centimeter spectral region at various sample temperatures between 79.5 and 296 K. Such data are needed to characterize the temperature dependence of spectral line shapes at low temperatures for remote sensing of outer planets and their moons. Initial analysis of a limited number of spectra in the region of the R(2) manifold of the v4 fundamental band of 13CH4 indicated that an empirical power law used for the temperature dependence of the N2-broadened line widths would fail to fit the observed data in the entire temperature range from 80 to 296 K; instead, it follows a temperature-dependence similar to that reported by Mondelain et al. [17,18]. The initial test was very successful proving that a high precision Fourier transform spectrometer with a completely evacuated optical path can be configured for spectroscopic studies at low temperatures relevant to the planetary atmospheres.

Sung, K.↗
DOE OSTI2024

VpROM: a novel variational autoencoder-boosted reduced order model for the treatment of parametric dependencies in nonlinear systems

Reduced Order Models (ROMs) are of considerable importance in many areas of engineering in which computational time presents difficulties. Established approaches employ projection-based reduction, such as Proper Orthogonal Decomposition. The limitation of the linear nature of such operators is typically tackled via a library of local reduction subspaces, which requires the assembly of numerous local ROMs to address parametric dependencies. Our work attempts to define a more generalisable mapping between parametric inputs and reduced bases for the purpose of generative modeling. We propose the use of Variational Autoencoders (VAEs) in place of the typically utilised clustering or interpolation operations, for inferring the fundamental vectors, termed as modes, which approximate the manifold of the model response for any and each parametric input state. The derived ROM still relies on projection bases, built on the basis of full-order model simulations, thus retaining the imprinted physical connotation. However, it additionally exploits a matrix of coefficients that relates each local sample response and dynamics to the global phenomena across the parametric input domain. The VAE scheme is utilised for approximating these coefficients for any input state. This coupling leads to a high-precision low-order representation, which is particularly suited for problems where model dependencies or excitation traits cause the dynamic behavior to span multiple response regimes. Moreover, the probabilistic treatment of the VAE representation allows for uncertainty quantification on the reduction bases, which may then be propagated to the ROM response. The performance of the proposed approach is validated on an open-source simulation benchmark featuring hysteresis and multi-parametric dependencies, and on a large-scale wind turbine tower characterised by nonlinear material behavior and model uncertainty.

Conditional VAEs↗
DOE OSTI2023

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

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

47 OTHER INSTRUMENTATION↗
NASA NTRS2023

Launch Complex 39B, SWMU 009 Air Sparging System Expansion Implementation Work Plan Kennedy Space Center, Florida

This Implementation Work Plan (IWP) for expansion of the Air Sparging (AS) system at Launch Complex 39B (LC39B), presents the design and coordination specifics to expand the existing AS Interim Measure (IM) at LC39B located at Kennedy Space Center (KSC), Florida. The existing AS system at LC39B was installed in 2017 and included 279 AS wells. LC39B has been designated as Solid Waste Management Unit (SWMU) 009 under the KSC Resource Conservation and Recovery Act (RCRA) Corrective Action Program. Expansion of the AS IM will include installation of an additional five AS wells to depths of approximately 13 and 17 feet below land surface (bls) to remediate contaminated groundwater identified northwest of the launch pad, near the liquid oxygen (LOX) tank. The expansion will target concentrations of cis-1,2-dichloroethene (cDCE) and vinyl chloride (VC) greater than Florida Department of Environmental Protection (FDEP) Natural Attenuation Default Concentrations (NADCs) that were identified during direct push technology (DPT) sampling events between 2019-2022 in shallow intervals between 8 and 16 feet bls. The objective for this expansion is to remediate contaminated groundwater within the treatment zone to below NADCs to support transition to monitored natural attenuation (MNA) through a long-term monitoring (LTM) program. This expansion will treat approximately 0.07-acres of residual groundwater contamination. The IWP design for this expansion will utilize the existing AS system trailer that is already onsite and operating. The five new AS expansion wells will be integrated into the existing Zone Z4 distribution manifold to deliver compressed air to the new AS wells. To deliver airflow, three existing lateral lines will be split in the field at a lateral split junction point (using 2-way or 3-way splits). Each split lateral will supply air to AS wells at the same depth interval to minimize preferential pathways. The trenching layout for the new AS wells was developed to minimize ground disturbance due to the amount of utilities in the area. One new monitoring well will also be installed and added to LC39B’s performance monitoring program to evaluate the effectiveness of the AS system expansion. This well will be sampled on a semi-annual basis for volatile organic compounds, with results evaluated to determine if system adjustments may be required. The main components of this IWP were presented to the KSC Remediation Team (KSCRT) at the October 2022 Meeting (Meeting 2210-M05). DPT delineation data from the LOX area were also presented, which included some inferred boundaries due to physical restrictions of the LOX tank and associated concrete pad and infrastructure. Planned monitoring well sampling in this area will help determine if back-diffusion may be occurring from beneath the pad. Additionally, based on potential petroleum odors and staining identified at two DPT locations during the January 2022 DPT event in the 10-16 feet bls range, a KSCRT action item was assigned during the October 2022 meeting to collect soil samples for petroleum compounds if similar odors or staining are identified during IM implementation. Construction completion and performance monitoring will be incorporated into LC39B’s groundwater monitoring reports, which are currently submitted on an annual basis to FDEP to document operation and maintenance activities and results from the AS IM.

Deborah M. Wilson↗
DOE OSTI2022

Illuminating the Photophysics of Oxygen Atom Transfer in Rare Earth Metal-Organic Complexes

Industrial separations of rare earth metals are reliant on selectivity based on ionic radii, which are time, energy, and resource consuming.1 The unique and discontinuous manifold of energy states associated with the f-electron configurations of the rare earth ions2 offer an opportunity to overcome some of these limitations by incorporating light into the separation process. Here, we use transient absorption spectroscopy to understand the differences in mechanism of light-initiated oxygen atom transfer (OAT) in yttrium (Y) and dysprosium (Dy) rare earth complexes. These metal-organic complexes are functionalized with hexfluoroacetyl-acetonate (hfac) and 4-methylmorpholine-N-oxide (NMMO). After light absorption in the presence of triphenyl phosphine (TPP), the NMMO in the Y-NMMO complex is replaced by the TPPO OAT reaction product. Because the Dy f-electron manifold is accessible to the ligand excited states, while there are no accessible states associated with f-electrons for Y, there are significant differences in reactivity. Transient absorption spectroscopy (TAS) was used to monitor changes after 340 nm photoexcitation of Dy/Y-NMMO or the product complex Dy/Y-TPPO. TAS is a pump-probe technique where a white light probe pulse is delayed relative to a visible pump pulse, which photoexcites a sample. Differences between the ground and excited states are monitored over time. With TAS, we access time scales from 100 fs-400 us to determine the photophysics of the complexes of interest. Photoexcitation of Y-NMMO (Fig. 1A) creates a broad photoinduced absorption (PIA) that evolves into a sharp positive feature over 4.2 ps centered at 450 nm. A secondary feature centered at 550 nm grows in with a 200 ps time constant and remains through the 5 ns time window of our experiment. Control experiments for Y-TPPO reveal that the feature at 450 nm is due to internal dynamics of the hfac ligand, while the 550 nm shoulder is due to the presence of the NMMO. Comparing kinetics at 550 nm for Y-NMMO and Dy-NMMO (Fig. 1B) shows that while Y exhibits a distinct growth in the NMMO feature, the Dy decays almost completely within 5 ns. Control experiments with Dy-TPPO prove that the ligand excited states centered on the hfac ligand are deactivated via energy transfer to the Dy manifold within 200 ps. This deactivation leads to significant differences in OAT reactivity between Y and Dy.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗
DOE OSTI2022

Fast Characterization of Inducible Regions of Atrial Fibrillation Models With Multi-Fidelity Gaussian Process Classification

Computational models of atrial fibrillation have successfully been used to predict optimal ablation sites. A critical step to assess the effect of an ablation pattern is to pace the model from different, potentially random, locations to determine whether arrhythmias can be induced in the atria. In this work, we propose to use multi-fidelity Gaussian process classification on Riemannian manifolds to efficiently determine the regions in the atria where arrhythmias are inducible. We build a probabilistic classifier that operates directly on the atrial surface. We take advantage of lower resolution models to explore the atrial surface and combine seamlessly with high-resolution models to identify regions of inducibility. We test our methodology in 9 different cases, with different levels of fibrosis and ablation treatments, totalling 1,800 high resolution and 900 low resolution simulations of atrial fibrillation. When trained with 40 samples, our multi-fidelity classifier that combines low and high resolution models, shows a balanced accuracy that is, on average, 5.7% higher than a nearest neighbor classifier. We hope that this new technique will allow faster and more precise clinical applications of computational models for atrial fibrillation. All data and code accompanying this manuscript will be made publicly available at: https://github.com/fsahli/AtrialMFclass.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Spin skyrmion gaps as signatures of strong-coupling insulators in magic-angle twisted bilayer graphene

Abstract The flat electronic bands in magic-angle twisted bilayer graphene (MATBG) host a variety of correlated insulating ground states, many of which are predicted to support charged excitations with topologically non-trivial spin and/or valley skyrmion textures. However, it has remained challenging to experimentally address their ground state order and excitations, both because some of the proposed states do not couple directly to experimental probes, and because they are highly sensitive to spatial inhomogeneities in real samples. Here, using a scanning single-electron transistor, we observe thermodynamic gaps at even integer moiré filling factors at low magnetic fields. We find evidence of a field-tuned crossover from charged spin skyrmions to bare particle-like excitations, suggesting that the underlying ground state belongs to the manifold of strong-coupling insulators. From the spatial dependence of these states and the chemical potential variation within the flat bands, we infer a link between the stability of the correlated ground states and local twist angle and strain. Our work advances the microscopic understanding of the correlated insulators in MATBG and their unconventional excitations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Photometric redshifts from SDSS images with an interpretable deep capsule network

ABSTRACT Studies of cosmology, galaxy evolution, and astronomical transients with current and next-generation wide-field imaging surveys like the Rubin Observatory Legacy Survey of Space and Time are all critically dependent on estimates of photometric redshifts. Capsule networks are a new type of neural network architecture that is better suited for identifying morphological features of the input images than traditional convolutional neural networks. We use a deep capsule network trained on ugriz images, spectroscopic redshifts, and Galaxy Zoo spiral/elliptical classifications of ∼400 000 Sloan Digital Sky Survey galaxies to do photometric redshift estimation. We achieve a photometric redshift prediction accuracy and a fraction of catastrophic outliers that are comparable to or better than current methods for SDSS main galaxy sample-like data sets (r ≤ 17.8 and zspec ≤ 0.4) while requiring less data and fewer trainable parameters. Furthermore, the decision-making of our capsule network is much more easily interpretable as capsules act as a low-dimensional encoding of the image. When the capsules are projected on a two-dimensional manifold, they form a single redshift sequence with the fraction of spirals in a region exhibiting a gradient roughly perpendicular to the redshift sequence. We perturb encodings of real galaxy images in this low-dimensional space to create synthetic galaxy images that demonstrate the image properties (e.g. size, orientation, and surface brightness) encoded by each dimension. We also measure correlations between galaxy properties (e.g. magnitudes, colours, and stellar mass) and each capsule dimension. We publicly release our code, estimated redshifts, and additional catalogues at https://biprateep.github.io/encapZulate-1.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

Studies of the Virgo Cluster. I - Photometry of 109 galaxies near the cluster center to serve as standards

Attention is given to the technical aspects of photometric measurements of 109 galaxies near the center of the Virgo Cluster, noting various types of radii and surface brightness for about 50 E and dE galaxies in the sample that range in absolute magnitude from -20 to -12. These data are combined with data from the literature for giant E and dwarf E galaxies in the Local Group to study the systematic properties of E galaxies over a range of one million luminosities. The radial intensity profiles derived are fitted to the manifold of King (1978) models to derive model-dependent central surface brightness, core radii, and cutoff radii.

Sandage, A.↗
DOE OSTI2024

Finite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization

This work highlights an approach for incorporating realistic uncertainties into scientific computing workflows based on finite elements, focusing on prevalent applications in computational mechanics and design optimization. We leverage Matérn-type Gaussian random fields (GRFs) generated using the SPDE method to model aleatoric uncertainties, including environmental influences, variating material properties, and geometric ambiguities. Our focus lies on delivering practical GRF realizations that accurately capture imperfections and variations and understanding how they impact the predictions of computational models as well as the shape and topology of optimized designs. Here we describe a numerical algorithm based on solving a generalized SPDE to sample GRFs on arbitrary meshed domains. The algorithm leverages established techniques and integrates seamlessly with the open-source finite element library MFEM and associated scientific computing workflows, like those found in industrial and national laboratory settings. Our solver scales efficiently for large-scale problems and supports various domain types, including surfaces and embedded manifolds. We showcase its versatility through biomechanics and topology optimization applications, emphasizing the potential to influence these domains. The flexibility and efficiency of SPDE-based GRF generation empowers us to run large-scale optimization problems on 2D and 3D domains, including finding optimized designs on embedded surfaces, and to generate design features and topologies beyond the reach of conventional techniques. Moreover, these capabilities allow us to model and quantify geometric uncertainties on reconstructed submanifolds, such as the interpolated surfaces of cerebral aneurysms provided by postprocessing CT scans. In addition to offering benefits in these specific domains, the proposed techniques transcend specific applications and generalize to arbitrary forward and backward problems in uncertainty quantification involving finite elements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Microscale mechanical modeling of deformable geomaterials with dynamic contacts based on the numerical manifold method

Abstract Micromechanical modeling of geomaterials is challenging because of the complex geometry of discontinuities and potentially large number of deformable material bodies that contact each other dynamically. In this study, we have developed a numerical approach for micromechanical analysis of deformable geomaterials with dynamic contacts. In our approach, we detect contacts among multiple blocks with arbitrary shapes, enforce different contact constraints for three different contact states of separated, bonded, and sliding, and iterate within each time step to ensure convergence of contact states. With these features, we are able to simulate the dynamic contact evolution at the microscale for realistic geomaterials having arbitrary shapes of grains and interfaces. We demonstrate the capability with several examples, including a rough fracture with different geometric surface asperity characteristics, settling of clay aggregates, compaction of a loosely packed sand, and failure of an intact marble sample. With our model, we are able to accurately analyze (1) large displacements and/or deformation, (2) the process of high stress accumulated at contact areas, (3) the failure of a mineral cemented rock samples under high stress, and (4) post-failure fragmentation. The analysis highlights the importance of accurately capturing (1) the sequential evolution of geomaterials responding to stress as motion, deformation, and high stress; (2) large geometric features outside the norms (such as large asperities and sharp corners) as such features can dominate the micromechanical behavior; and (3) different mechanical behavior between loosely packed and tightly packed granular systems.

58 GEOSCIENCES↗
DOE OSTI2024

Cosmic topology. Part IIa. Eigenmodes, correlation matrices, and detectability of orientable Euclidean manifolds

Abstract If the Universe has non-trivial spatial topology, observables depend on both the parameters of the spatial manifold and the position and orientation of the observer. In infinite Euclidean space, most cosmological observables arise from the amplitudes of Fourier modes of primordial scalar curvature perturbations. Topological boundary conditions replace the full set of Fourier modes with specific linear combinations of selected Fourier modes as the eigenmodes of the scalar Laplacian. We present formulas for eigenmodes in orientable Euclidean manifolds with the topologiesE 1 –E 6 ,E 11 ,E 12 ,E 16 , andE 18 that encompass the full range of manifold parameters and observer positions, generalizing previous treatments. Under the assumption that the amplitudes of primordial scalar curvature eigenmodes are independent random variables, for each topology we obtain the correlation matrices of Fourier-mode amplitudes (of scalar fields linearly related to the scalar curvature) and the correlation matrices of spherical-harmonic coefficients of such fields sampled on a sphere, such as the temperature of the cosmic microwave background (CMB). We evaluate the detectability of these correlations given the cosmic variance of the observed CMB sky. We find that topologies where the distance to our nearest clone is less than about 1.2 times the diameter of the last scattering surface of the CMB give a correlation signal that is larger than cosmic variance noise in the CMB. This implies that if cosmic topology is the explanation of large-angle anomalies in the CMB, then the distance to our nearest clone is not much larger than the diameter of the last scattering surface. We argue that the topological information is likely to be better preserved in three-dimensional data, such as will eventually be available from large-scale structure surveys.

Astronomy & Astrophysics↗
DOE OSTI2021

The Twins Embedding of Type Ia Supernovae. II. Improving Cosmological Distance Estimates

We show how spectra of Type Ia supernovae (SNe Ia) at maximum light can be used to improve cosmological distance estimates. In a companion article, we used manifold learning to build a three-dimensional parameterization of the intrinsic diversity of SNe Ia at maximum light that we call the "Twins Embedding."In this article, we discuss how the Twins Embedding can be used to improve the standardization of SNe Ia. With a single spectrophotometrically calibrated spectrum near maximum light, we can standardize our sample of SNe Ia with an rms of 0.101 0.007 mag, which corresponds to 0.084 0.009 mag if peculiar velocity contributions are removed and to 0.073 0.008 mag if a larger reference sample were obtained. Our techniques can standardize the full range of SNe Ia, including those typically labeled as peculiar and often rejected from other analyses. We find that traditional light-curve width + color standardization such as SALT2 is not sufficient. The Twins Embedding identifies a subset of SNe Ia, including, but not limited to, 91T-like SNe Ia whose SALT2 distance estimates are biased by 0.229 0.045 mag. Standardization using the Twins Embedding also significantly decreases host-galaxy correlations. We recover a host mass step of 0.040 0.020 mag compared to 0.092 0.026 mag for SALT2 standardization on the same sample of SNe Ia. These biases in traditional standardization methods could significantly impact future cosmology analyses if not properly taken into account.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2007

Measurement of the Temperature Dependence of Line Mixing and Pressure Broadening Parameters between 296 and 90 K in the v3 band of 12CH4 and their Influence on Atmospheric Methane Retrievals

We measured the temperature dependence of the nitrogen broadening, narrowing and line-mixing coefficients of four lines of the P9 manifold in the v3 band of 12CH4 for atmospheric purposes. The data were collected using our tunable diode laser (TDL) spectrometer with active wavenumber control coupled to a newly developed cold Herriott cell with a path length of 5.37 m and a temperature uniformity of better than 0.01 K along the cell. We recorded and analyzed spectra recorded at sample temperature between 90 K and room temperature. We have investigate the influence of our new results in the inversion model used to retrieve methane profiles from atmospheric spectra; our new results make it possible to retrieve significantly more precise methane profiles. The atmospheric spectra we utilized were obtained by several of us with a balloon-born Fourier Transform infrared experiment in a limb configuration. Differences up to 7% on the retrieved volume mixing ratio were found compared to an inversion model using only HITRAN04 spectroscopic parameters.

Mondelain, Didier↗