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DOE OSTI2026

Linking Community‐Climate Disequilibrium to Ecosystem Function

Turnover in species composition often lags behind the pace of climate change, resulting in mismatches between climate and communities. However, the impact of these community‐climate disequilibria on ecosystem functions is rarely considered, and current methods for measuring disequilibria assume that species ranges were, until recently, in equilibrium with climate. Here, in this work, we develop a simple theoretical model to address both of these problems by linking community‐climate disequilibrium with ecosystem functioning. We show how disequilibrium can impair functioning in the near‐term even when climate change is expected to enhance functioning in the long‐term. Responses are most likely to change over time in communities where turnover is slow, the impact of disequilibrium counteracts the direct effects of climate on ecosystem function, and pre‐existing disequilibrium is large. These findings emphasise the importance of precise and unbiased estimates of community‐climate disequilibria for improving ecological forecasts. By fitting our model to time series of both climate and ecosystem function from a metacommunity simulation, we show the potential for community‐climate disequilibrium to be inferred without direct knowledge about species' distributions or climatic tolerances. We end by outlining a research agenda to apply dynamic disequilibrium concepts and test novel hypotheses across diverse ecosystems.

climate change↗

NASA NTRS2012

Use of MODIS Satellite Data to Evaluate Juniperus spp. Pollen Phenology to Support a Pollen Dispersal Model, PREAM, to Support Public Health Allergy Alerts

Juniperus spp. pollen is a significant aeroallergen that can be transported 200-600 km from the source. Local observations of Juniperus spp. phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. Methods: The Dust REgional Atmospheric Model (DREAM)is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust. We successfully modified the DREAM model to incorporate pollen transport (PREAM) and used MODIS satellite images to develop Juniperus ashei pollen input source masks. The Pollen Release Potential Source Map, also referred to as a source mask in model applications, may use different satellite platforms and sensors and a variety of data sets other than the USGS GAP data we used to map J. ashei cover type. MODIS derived percent tree cover is obtained from MODIS Vegetation Continuous Fields (VCF) product (collection 3 and 4, MOD44B, 500 and 250 m grid resolution). We use updated 2010 values to calculate pollen concentration at source (J. ashei ). The original MODIS derived values are converted from native approx. 250 m to 990m (approx. 1 km) for the calculation of a mask to fit the model (PREAM) resolution. Results: The simulation period is chosen following the information that in the last 2 weeks of December 2010. The PREAM modeled near-surface concentrations (Nm-3) shows the transport patterns of J. ashei pollen over a 5 day period (Fig. 2). Typical scales of the simulated transport process are regional.

Luvall, J. C.↗

DOE OSTI2021

Mechanistic basis of post-treatment control of SIV after anti-α4β7 antibody therapy

Treating macaques with an anti-α4β7 antibody under the umbrella of combination antiretroviral therapy (cART) during early SIV infection can lead to viral remission, with viral loads maintained at < 50 SIV RNA copies/ml after removal of all treatment in a subset of animals. Depletion of CD8+ lymphocytes in controllers resulted in transient recrudescence of viremia, suggesting that the combination of cART and anti-α4β7 antibody treatment led to a state where ongoing immune responses kept the virus undetectable in the absence of treatment. A previous mathematical model of HIV infection and cART incorporates immune effector cell responses and exhibits the property of two different viral load set-points. While the lower set-point could correspond to the attainment of long-term viral remission, attaining the higher set-point may be the result of viral rebound. Here we expand that model to include possible mechanisms of action of an anti-α4β7 antibody operating in these treated animals. We show that the model can fit the longitudinal viral load data from both IgG control and anti-α4β7 antibody treated macaques, suggesting explanations for the viral control associated with cART and an anti-α4β7 antibody treatment. This effective perturbation to the virus-host interaction can also explain observations in other nonhuman primate experiments in which cART and immunotherapy have led to post-treatment control or resetting of the viral load set-point. Interestingly, because the viral kinetics in the various treated animals differed—some animals exhibited large fluctuations in viral load after cART cessation—the model suggests that anti-α4β7 treatment could act by different primary mechanisms in different animals and still lead to post-treatment viral control. This outcome is nonetheless in accordance with a model with two stable viral load set-points, in which therapy can perturb the system from one set-point to a lower one through different biological mechanisms.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1993

Metal abundances at z = 3.4

Echelle spectroscopy data were taken of the quasar 0000-263 on the 4m telescope at CTIO in Chile. Three nights of red and three nights of blue data were obtained (about four hours data per night). The resolution is typically 0.4 A at 5000 A (lamda/d(lamda) = 12500) and has good signal-to-noise over the wavelength range 4600 A to 8000 A. To keep the statistics manageable the data were not rebinned, although the instrument was stable enough for each night's data on the object to be co-added. Arc spectra taken between each exposure were also co-added within the nights. During profile fitting the model was convolved with a Gaussian whose width was equal to nearby arc lines, so any broadening generated by the co-adding of data will not affect the final results. Since OI and HI have the same ionization potential (13.6 eV), (O/H) is approximately (OI/HI). Unfortunately, in this data only the 1302 A OI transition is visible, and it is blended with HI in the Lyman Alpha forest. However, OI and NI coexist (the ionization potential for NI is 14.5 eV) and so the NI triplet can constrain the redshift and turbulent width of the OI. When a fit was made to the regions containing OI and NI absorption three systems were apparent with similar redshifts and velocity widths. These three systems were fitted with tied redshifts and turbulent widths, while the other lines in the region were fitted as Lyman-Alpha. The saturated Lyman-Alpha profile was then fitted with three components at the same redshifts as these observed lines, with the line widths tied. Finally, metallicity ratios for the individual lines and their totals were calculated and compared to solar values. The results for the separate clouds from low to high redshift and for the total are presented.

Cooke, Andrew↗

NASA NTRS2016

CME Flux Rope and Shock Identifications and Locations: Comparison of White Light Data, Graduated Cylindrical Shell Model, and MHD Simulations

Coronal mass ejections (CMEs) are major transient phenomena in the solar corona that are observed with ground-based and spacecraft-based coronagraphs in white light or with in situ measurements by spacecraft. CMEs transport mass and momentum and often drive shocks. In order to derive the CME and shock trajectories with high precision, we apply the graduated cylindrical shell (GCS) model to fit a flux rope to the CME directed toward STEREO A after about 19:00 UT on 29 November 2013 and check the quality of the heliocentric distance-time evaluations by carrying out a three-dimensional magnetohydrodynamic (MHD) simulation of the same CME with the Block Adaptive Tree Solar-Wind Roe Upwind Scheme (BATS-R-US) code. Heliocentric distances of the CME and shock leading edges are determined from the simulated white light images and magnetic field strength data. We find very good agreement between the predicted and observed heliocentric distances, showing that the GCS model and the BATS-R-US simulation approach work very well and are consistent. In order to assess the validity of CME and shock identification criteria in coronagraph images, we also compute synthetic white light images of the CME and shock. We find that the outer edge of a cloud-like illuminated area in the observed and predicted images in fact coincides with the leading edge of the CME flux rope and that the outer edge of a faint illuminated band in front of the CME leading edge coincides with the CME-driven shock front.

Schmidt, J. M.↗

NASA NTRS2019

Surrogate Modeling and Optimization of a Combustor with an Interdigitated Flushwall Injector

Design and Analysis of Computer Experiments (DACE) methods are applied and used to perform surrogate modeling and optimization of a simplified combustor flowpath with an interdigitated flushwall injector. The objectives of the optimization are the thrust potential and combustion efficiency, which are evaluated across a range of flight Mach numbers, duct heights, spanwise spacings, and injection angles. The focus of this work is to highlight the application of a sequential learning approach, in order to learn about the responses of the objective functions over the design space and to identify local regions of interest for further analysis. This approach is contrasted to a previous effort where only a single sampling set was used to fit surrogate models and perform optimization. The optimal solutions resulting from the previous and present approaches are different, due to surrogate model-guided local refinement of the design space allowed by the sequential learning method. The values of the global error estimates between the previous and present approaches are comparable, but the sequential method proved more computationally cost-effective. Further refinement in the optimal regions might be needed to improve predictive capability of surrogate models and to obtain the optimal solutions sets.

Rajiv R Shenoy↗

DOE OSTI2025

bmdrc: Python package for quantifying phenotypes from chemical exposures with benchmark dose modeling

Though chemical exposures are known to potentially have negative impacts on health, including contributing to chronic diseases such as cancer, the quantitative contribution of risk is not fully understood for every chemical. A commonly used approach to quantify levels of risk is to measure the proportion of organisms (such as a total number of zebrafish on a plate or mice in a cage) with abnormal behavioral responses or morphology at increasing concentrations of chemical exposure. A particular challenge with processing the proportional data from these assays is the appropriate estimation of chemical concentration levels that result in malformations or acute toxicity, as these values typically vary between experimental measurements. The recommended approach by the Environmental Protection Agency (EPA) is to fit benchmark dose curves with specific filters and model fitting steps, which are crucial to properly processing the proportional data. Several tools exist for the fitting of benchmark dose response curves, but none are standalone Python libraries built to process both morphological and behavioral data as proportions with all the EPA recommended filters, filter parameters, models, and model parameters. Thus, here we present the benchmark dose response curve (bmdrc) Python library, which was built to closely follow these EPA guidelines with helpful visualizations of filters and fitted model curves, and reports for reproducibility purposes. bmdrc is open-source and has demonstrated utility as a support package to an existing web portal for information on chemicals (https://srp.pnnl.gov). Our package will support any toxicology analysis where the response is a proportional value at increasing levels of a concentration of a chemical or chemical mixture.

Superfund↗

DOE OSTI2020

Probing Transit Timing Variation and Its Possible Origin with 12 New Transits of TrES-3b

We present 12 new transit light curves of the hot-Jupiter TrES-3b observed during 2012−2018 to probe the transit timing variation (TTV). By combining the midtransit times determined from these 12 transit data with those reestimated through uniform procedure from 71 transit data available in the literature, we derive new linear ephemeris and obtain the timing residuals that suggest the possibility of TTV in the TrES-3 system. However, the frequency analysis shows that the possible TTV is unlikely to be periodic, indicating the absence of an additional body in this system. To explore the other possible origins of TTV, the orbital decay and apsidal precession ephemeris models are fitted to the transit time data. We find the decay rate of TrES-3b to be P-dot {sub q}=−4.1±3.1 ms yr{sup −1}, and the corresponding estimated modified stellar tidal quality factor of Q{sub ∗}{sup ′}∼1.11×10{sup 5} is consistent with the theoretically predicted values for the stars hosting the hot-Jupiters. The shift in the transit arrival time of TrES-3b after 11 years is expected to be T {sub shift} ∼ 69.55 s, which is consistent with the rms of the timing residuals. Besides, we find that the apsidal precession ephemeris model is statistically less probable than the other considered ephemeris models. It is also discussed that despite the fact that the linear ephemeris model appears to be the most plausible model to represent the transit time data, the possibility of the orbital decay cannot be completely ruled out in the TrES-3 system. To confirm this, further high-precision and high-cadence follow-up observation of transits of TrES-3b would be important.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Mathematical modeling and parameter estimation of MFI membranes for para/ortho‐xylene separation

Abstract A mathematical model of a membrane with a thin, oriented, and selective MFI layer, which also includes contributions from defects, pore blockages, support layer, and external mass transfer, was formulated based on the Maxwell‐Stefan equations. It was validated using reported (Kim et al., Angew Chemie Int Ed, 2018, 57:480–485; Jeon et al., Nature, 2017, 543:690–694) para/ortho‐xylene separation data from five MFI membranes. The diffusivities of the xylenes were considered to be the same for all membranes, while the thickness and the density of defects and pore blockage were treated as unique properties of each membrane, and their contributions were estimated by fitting the model to the corresponding separation data. The effects of these properties and the role of permeate pressure on the separation performance were subsequently analyzed. The proposed modeling, parameter estimation, and analysis framework allow one to quantitatively interpret the variation of separation performance, to understand separation bottlenecks, and to provide guidance for designing membranes with desired performance.

Liu, Jingjun↗

NASA NTRS1990

Long-Term Trends in the Concentrations of SF6, CHClF2, and COF2 in the Lower Stratosphere from Analysis of High-Resolution Infrared Solar Occultation Spectra

Long-term trends in the concentrations of SF6, CHClF2 (CFC-22), and COF2 in the lower stratosphere have been derived from analysis of ca. 1980 and more recent infrared solar occultation spectra recorded near 32 deg N latitude at approx. 0.02/ cm resolution. Consistent sets of line parameters and spectral calibration methods have been used in the retrievals to minimize systematic error effects. Quoted error limits are 1 sigma estimated precisions. The SF6 and CHClF2 results are based on spectra recorded by balloon-borne interferometers in March 1981 and June 1988 and a comparison of these results with the Atmospheric Trace Molecule Spectroscopy (ATMOS) Experiment/Spacelab 3 measurements obtained in May 1985 near 30 deg N latitude. In the 13-18 km altitude range the mean measured SF6 mixing ratio in parts per trillion by volume (pptv) increased from 1.17 +/- 0.21 in March 1981 to 2.02 +/- 0.20 pptv in June 1988, and the CHClF2 mixing ratio below 15 km altitude increased from 51 +/- 8 pptv in March 1981 to 102 +/- 10 pptv in June 1988. The CHClF2 retrievals used new empirical CHClF2 line parameters derived from 0.03/cm resolution laboratory spectra recorded at six temperatures between 203 and 293 K; the derived mixing ratios are approx. 30% higher than obtained with earlier sets of line parameters, thereby removing a large discrepancy noted previously between IR and in situ measurements of CHClF2. Assuming an exponential growth model for fitting the trends, SF6 and CHClF2 mean increase rates of 7.4% +/- 1.9% and 9.4% +/- 1.3% /year, are obtained, respectively, which correspond to cumulative increases by factors of approx. 1.7 and -2.0 in the concentrations of these gases over the 7.2-year measurement period. Analysis of spectra recorded in October 1979 and April 1989 yields COF2 volume mixing ratios that are respectively 0.44 +/- 0.17 and 1.21 +/- 0.24 times the ATMOS/Spacelab 3 values, from which an average COF2 increase rate of 10.3 +/- 1.8%/ year over this time period has been estimated. The present results are compared with previously reported observations and trends and with one-dimensional model calculations. The model calculated trends are in reasonably good agreement with the observations.

Rinsland, C. P.↗

DOE OSTI2022

Connecting the Light Curves of Type IIP Supernovae to the Properties of Their Progenitors

Abstract Observations of core-collapse supernovae (CCSNe) reveal a wealth of information about the dynamics of the supernova ejecta and its composition but very little direct information about the progenitor. Constraining properties of the progenitor and the explosion requires coupling the observations with a theoretical model of the explosion. Here we begin with the CCSN simulations of Couch et al., which use a nonparametric treatment of the neutrino transport while also accounting for turbulence and convection. In this work we use the SuperNova Explosion Code to evolve the CCSN hydrodynamics to later times and compute bolometric light curves. Focusing on Type IIP SNe (SNe IIP), we then (1) directly compare the theoretical STIR explosions to observations and (2) assess how properties of the progenitor’s core can be estimated from optical photometry in the plateau phase alone. First, the distribution of plateau luminosities ( L 50 ) and ejecta velocities achieved by our simulations is similar to the observed distributions. Second, we fit our models to the light curves and velocity evolution of some well-observed SNe. Third, we recover well-known correlations, as well as the difficulty of connecting any one SN property to zero-age main-sequence mass. Finally, we show that there is a usable, linear correlation between iron core mass and L 50 such that optical photometry alone of SNe IIP can give us insights into the cores of massive stars. Illustrating this by application to a few SNe, we find iron core masses of 1.3–1.5 M ⊙ with typical errors of 0.05 M ⊙ . Data are publicly available online on Zenodo: doi: 10.5281/zenodo.6631964 .

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d -1 (95% CI: 1.06 to 1.27 d -1 ), 0.777 d -1 (0.716 to 0.838 d -1 ), and 0.450 d -1 (0.378 to 0.522 d -1 ) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Broadband Characterization and Circuit Model Development of Transmission-Scale Transformers

This report describes broadband measurements of transmission-scale transformers typical in the electric power grid. This work was performed as part of the EMP Resilient Grid LDRD project at Sandia National Laboratories to generate circuit models that can be used for high-altitude electromagnetic pulse (HEMP) coupling simulations and response predictions. The objective of the work was to obtain characterization data of substation yard equipment across a frequency range relevant to HEMP. Vector network analyzer measurements up to 100 MHz were performed on two power transformers at ABB-Hitachi and a single ITEC potential transformer. Custom cable breakouts were designed to interface with the transformer terminals and provide ground connections to the chassis at the base of the transformer bushings. The three-phase terminals of the power transformers were measured as a common mode impedance using a parallel resistive splitter, and the single-phase terminals of the potential transformer were measured directly. A vector fitting algorithm was used to empirically fit circuit models to the resulting two-port networks and input impedances of the measured objects. Simplified circuit representations of the input impedances were also generated to assess the degree of precision needed for high-altitude electromagnetic pulse response predictions, which were performed in Sandia's XYCE circuit simulator platform. HEMP coupling simulations using the transformer models showed significant reduction in the voltage peak and broadening in the pulse width seen at the power transformer compared to the traveling wave voltage. This indicated the importance of the load condition when defining the coupled insult in an electric power substation. Simplified circuit models showed a similar voltage at the transformer with a smoothed waveform. The presence of potential transformers in the simulation did not significantly change the simulated voltage at the power transformer. Single-port input impedance models were also developed to define load conditions when transfer characteristics were not necessary.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1980

Microwave radiometric observations of snowpacks

Models for the microwave emission from snowpacks were generated on the basis of radiometric observations made at 10.7 GHz, 37 HGz, and 94 GHz at a test site near Steamboat Springs, Colorado. In addition to conducting measurements on an approximately daily basis over a six week observation period, measurements were made over several diurnal cycles during which the change in snow wetness was tracked by the microwave radiometers. Also, the variation in emissivity with snow water equivalent was examined, as was the sensitivity to changes in snow surface geometry. The microwave emissivity was observed to (1) decrease exponentially with snow water equivalent and (2) increase with snow wetness. Thus, the emission behavior is the reverse of the backscattering behavior observed by the radar. By fitting the models to the measured data, the variation of the optical depth with snow wetness was estimated.

Ulaby, F. T.↗

NASA NTRS1987

A linearized Euler analysis of unsteady flows in turbomachinery

A method for calculating unsteady flows in cascades is presented. The model, which is based on the linearized unsteady Euler equations, accounts for blade loading shock motion, wake motion, and blade geometry. The mean flow through the cascade is determined by solving the full nonlinear Euler equations. Assuming the unsteadiness in the flow is small, then the Euler equations are linearized about the mean flow to obtain a set of linear variable coefficient equations which describe the small amplitude, harmonic motion of the flow. These equations are discretized on a computational grid via a finite volume operator and solved directly subject to an appropriate set of linearized boundary conditions. The steady flow, which is calculated prior to the unsteady flow, is found via a Newton iteration procedure. An important feature of the analysis is the use of shock fitting to model steady and unsteady shocks. Use of the Euler equations with the unsteady Rankine-Hugoniot shock jump conditions correctly models the generation of steady and unsteady entropy and vorticity at shocks. In particular, the low frequency shock displacement is correctly predicted. Results of this method are presented for a variety of test cases. Predicted unsteady transonic flows in channels are compared to full nonlinear Euler solutions obtained using time-accurate, time-marching methods. The agreement between the two methods is excellent for small to moderate levels of flow unsteadiness. The method is also used to predict unsteady flows in cascades due to blade motion (flutter problem) and incoming disturbances (gust response problem).

Hall, Kenneth C.↗

NASA NTRS1989

Calculation of unsteady flows in turbomachinery using the linearized Euler equations

Hall, Kenneth C.↗

NASA NTRS2005

The Abundance of Interstellar Fluorine

The primary objective of this program was to obtain FUSE observations of the interstellar absorption lines of F I at 951 and 954 Angstroms to derive the abundance of fluorine toward the star HD 164816. The nucleosynthetic source(s) of fluorine are still a matter of debate - the present day abundance of fluorine can potentially constrain models for pulsationally driven dredge-up in asymptotic giant branch stars. An accurate measure for the depletion behavior of fluorine will determine whether it may be detectable in QSO absorption line systems - an unambiguous detection of fluorine at suitably high redshifts would provide the best evidence to date for the neutrino process in massive stars. Furthermore, due to its extreme reactivity, measurement of the gas-phase interstellar fluorine abundance is important for models of grain chemistry. Despite the importance of measuring the interstellar fluorine abundance, at the time of our proposal only one previous detection has been made due to the low relative abundance of fluorine, the lack of lines outside the far-UV, and the blending of the available F I transitions with lines of Hz. The star HD 164816 is associated with the Lagoon nebula (M8), and at a distance of approximately 1.5 kpc probes both distant and local gas. Beginning April 8th, 2004 FUSE FP-Split observations of the star HD 164816 were obtained for this program. This data became available in the FUSE data archive May 21, 2004, and these observations were then downloaded and we began our analysis. Our analysis procedure has involved (1) fitting stellar models to the FUSE spectra, (2) using the multiple lines of Hz and N I at other wavelengths in the FUSE bandpass to derive column densities for the lines of H2 and N I which are blended with the F I features at 951 and 954 angstroms (3) the measurement of the column densities of F I and the species O I and C1 I which are important species for the dis-entangling of dust and nucleosynthetic effects. As discussed in our poster paper presented at the Winter 2005 American Astronomical Society meeting (Lauroesch et al. 2004, AAS, 205, 57.06), our analysis of the data taken for this star suggests that the observed fluorine gas-phase abundance (and hence inferred depletion onto dust grains) are consistent with previous measures toward delta Sco (Copernicus) and two recent measures toward stars in Cep OB2 obtained by others with FUSE. We are currently revising the draft a paper for submission to the Astrophysical Journal which presents the results of these observations and in addition our recently obtained FUSE observations of another star (HD 103779, FUSE GO program D073) which shows an apparent slight enhancement in the gas-phase fluorine abundance.

Lauroesch, James T.↗

DOE OSTI2022

Practical guide to understanding goodness-of-fit metrics used in chemical state modeling of x-ray photoelectron spectroscopy data by synthetic line shapes using nylon as an example

Chemical state analysis of a sample surface through fitting bell-shaped curves to x-ray photoelectron spectroscopic polymer data is reviewed using nylon to introduce and discuss aspects of data analysis. Different strategies for modeling chemistry in nylon spectra are presented and in so doing, a case is made to include in published science the design logic and implementation in terms of line shapes and optimization parameter constraints between components in a peak model. Imperfections in line shape relative to the true shape for photoemission lines, when compensated for using constraints to optimization parameters, are shown to provide chemical state information about a sample that justify, for peak models constructed with these limitations, metrics for goodness-of-fit different from those expected for pulse-counted data.

Materials Science↗