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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

The Influence of Redox Conditions on the Seismic Properties of Polycrystalline Olivine

Eight olivine specimens were fabricated by use of a solgel method and hot-pressing at 1200 degrees Centigrade and 300 megapascals (MPa) inside of welded Pt capsules. Each hot-pressed specimen was then recovered, precision ground, and wrapped in Pt, Ni or NiFe foil to vary oxygen fugacity (fO2) during the subsequent forced torsional oscillation measurements. Mechanical testing was conducted at 10 oscillation periods between 1 and 1000 seconds, at a confining pressure of 200 MPa, during a slow staged-cooling from a maximum temperature of 1200 degrees Centigrade down to room temperature. After mechanical testing, each specimen was axially sectioned and EBSD (Electron BackScatter Diffraction) was used for the determination of the representative grain size, and grain size distribution of each sample. In addition, each longitudinal section was mapped via FTIR (Fourier Transform Infrared Spectroscopy) to determine the spatial distribution and concentrations of chemically bound and molecular water. Amongst these eight specimens, chemically bound ‘water’ contents were observed to vary between 0 and 1150 atom parts per million (ppm) H/Si, and molecular water concentrations varied between 0 and 245 atom ppm H/Si. Our forced-oscillation results demonstrate that the measured magnitude of anelastic relaxation within the experimental ‘window’ of oscillation periods is unrelated to the water content. Rather, a relationship was observed between the magnitude of anelastic relaxation and the prevailing redox conditions, which is influenced by the choice of metal sleeving used during the mechanical test. Further, regardless of water content or metal sleeving, each specimen exhibits coupled variations in shear modulus and dissipation within the observational window, indicative of ‘high-temperature background’ behavior, that can be described by a Burgers-type model. During initial fitting of the Burgers models, the unrelaxed shear modulus at a reference temperature of 900°C (elastic unloading/reloading shear modulus G (sub UR)) and the temperature derivative of the unrelaxed shear modulus (dGU/dT), were treated as adjustable parameters. For all Fe-bearing olivine samples we observe deficits of G (sub UR) and increased values of dGU/dT, relative to the expected elastic (anharmonic) behavior for Fo (Forsterite content percentage) (sub 90) olivine. This behavior is indicative of anelastic relaxation occurring at shorter periods than observable within the ‘window’ of oscillation periods used in the mechanical test. Moving towards a comprehensive and seismologically applicable Burgers model, which includes this newly observed effect of redox conditions on anelastic relaxation, we will present our progress on reconciling truly anharmonic and elastic behavior of Fo (sub 90) olivine with our observed forced-oscillation data.

Cline, C. J., II↗
NASA NTRS2022

Comparison of U.S. and Russian Slow Crack Growth Data and Models

Both the US and Russian space programs use similar predictive models for design of fused silica windows on the International space station. The Russian model can be derived from the power expression for slow crack growth (SCG) or “static fatigue.” The US uses both power and exponential models. Despite the similarity of models and data fitting approach (linear regression and right censoring), different SCG parameters have been derived by US and Russian parties for the same material (Russian fused silica) tested in a similar manner. The difference appears to be related to the use of short-term strength data along with the longer-term static fatigue data, with the power law parameter n being very sensitive to the conversion of strength data into equivalent static data. This hybrid approach is feasible if strength data is measured with a constant stress rate and is appropriately converted to a static equivalent. More research into the approach is needed. However, because of the nonlinear behavior of fused silica in log(v) – log(K(I) ) space and the sensitivity of parameter estimation to fit range, the exponential model is a better choice regardless of test method. Functions are given to convert parameters from the Russian model to those in the US model. However, accurate conversion is hampered by the lack of inert strength data. When the same test technique is used, US and Russian materials exhibit very similar parameters.

Silica, strength, impact, crack growth, windows, I↗
DOE OSTI2021

SANS quantification of bound water in water-soluble polymers across multiple concentration regimes

Contrast-variation small-angle neutron scattering (CV-SANS) is a widely used technique for quantifying hydration water in soft matter systems, but it is predominantly applied in the dilute regime or for systems with a well-defined structure factor. Here, CV-SANS was used to quantify the number of hydration water molecules associating with three water-soluble polymers with different critical solution temperatures and types of water–solute interactions in dilute, semidilute, and concentrated solution through the exploration of novel methods of data fitting and analysis. Multiple SANS fitting workflows with varying levels of model assumptions were evaluated and compared to give insight into SANS model selection. These fitting pathways ranged from general, model-free algorithms to more standard form and structure factor fitting. In addition, Monte Carlo bootstrapping was evaluated as a method to estimate parameter uncertainty through simulation of technical replicates. The most robust fitting workflow for dilute solutions was found to be form factor fitting without CV-SANS ( i.e. polymer in 100% D 2 O). For semidilute and concentrated solutions, while the model-free approach can be mathematically defined for CV-SANS data, the addition of a structure factor imposes physical constraints on the optimization problem, suggesting that the optimal fitting pathway should include appropriate form and structure factor models. The measured hydration numbers were consistent with the number of tightly bound water molecules associated with each monomer unit, and the concentration dependence of the hydration number was largely governed by the chemistry-specific interactions between water and polymer. Polymers with weaker water–polymer interactions ( i.e. those with fewer hydration water molecules) were found to have more bound water at higher concentrations than those with stronger water–polymer interactions due to the increase in the number of forced water–polymer contacts in the concentrated system. This SANS-based method to count hydration water molecules can be applied to polymers in any concentration regime, which will lead to improved understanding of water–polymer interactions and their impact on materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Retrospective Analysis of NIST Standard Reference Material 1450, Fibrous Glass Board, for Thermal Insulation Measurements

Thermal conductivity data acquired previously for the establishment of Standard Reference Material (SRM) 1450, Fibrous Glass Board, as well as subsequent renewals 1450a, 1450b, 1450c, and 1450d, are re-analyzed collectively and as individual data sets. Additional data sets for proto-1450 material lots are also included in the analysis. The data cover 36 years of activity by the National Institute of Standards and Technology (NIST) in developing and providing thermal insulation SRMs, specifically high-density molded fibrous-glass board, to the public. Collectively, the data sets cover two nominal thicknesses of 13 mm and 25 mm, bulk densities from 60 kg∙m -3 to 180 kg∙m -3 , and mean temperatures from 100 K to 340 K. The analysis repetitively fits six models to the individual data sets. The most general form of the nested set of multilinear models used is given in the following equation: λ(ρ, T) = α 0 + α 1 ρ +α 2 T + α 3 T 3 +α 4 e - ($\frac{T-a_{5}}{a_{6}}$) 2 = where λ(ρ,T) is the predicted thermal conductivity (W∙m -1 ∙K -1 ), ρ is the bulk density (kg∙m -3 ), T is the mean temperature (K) and $a_i$ (for i = 1, 2, … 6) are the regression coefficients. The least squares fit results for each model across all data sets are analyzed using both graphical and analytic techniques. The prevailing generic model for the majority of data sets is the bilinear model in ρ and T. λ(ρ, T) = α 0 + α 1 ρ +α 2 T One data set supports the inclusion of a cubic temperature term and two data sets with low-temperature data support the inclusion of an exponential term in T to improve the model predictions. Physical interpretations of the model function terms are described. Recommendations for future renewals of SRM 1450 are provided. An Addendum provides historical background on the origin of this SRM and the influence of the SRM on external measurement programs.

regression analysis↗
NASA NTRS1992

The anomalous extinction curve in the direction of Rho Ophiuchi from 950 to 1180 A

We report the interstellar extinction from 950 to 1180 A in the direction of Rho Oph. These data were obtained with a moderate-resolution sounding rocket observation of Ro Oph, and two lightly reddened B stars of identical spectral type. Unlike Voyager observations in this wavelength region, our spectral resolution is sufficient to directly measure the contribution of molecular hydrogen along the line of sight and unambiguously identify the dust contribution. The derived curves compare favorably with the extrapolation of functional fits to the Rho Oph derived from longer wavelengths. In addition, we have fitted a model of dust extinction to the derived curve and find that the best fits indicate that the line of sight exhibits a larger than average grain size and a preferential concentration of graphite relative to silicates. The sharp rise seen at the shortest wavelengths (below 1000 A) cannot be explained by standard silicate-graphite dust models and may be indicative of a nonstandard grain shape or a missing component in the extinction models.

Green, James C.↗
DOE OSTI2019

Radiogenic backgrounds in the NEXT double beta decay experiment

Natural radioactivity represents one of the main backgrounds in the search for neutrinoless double beta decay. Within the NEXT physics program, the radioactivity-induced backgrounds are measured with the NEXT-White detector. Data from 37.9 days of low-background operations at the Laboratorio Subterr\'aneo de Canfranc with xenon depleted in $^{136}$Xe are analyzed to derive a total background rate of (0.84$\pm$0.02) mHz above 1000 keV. The comparison of data samples with and without the use of the radon abatement system demonstrates that the contribution of airborne-Rn is negligible. A radiogenic background model is built upon the extensive radiopurity screening campaign conducted by the NEXT Collaboration. A spectral fit to this model yields the specific contributions of $^{60}$Co, $^{40}$K, $^{214}$Bi and $^{208}$Tl to the total background rate, as well as their location in the detector volumes. The results are used to evaluate the impact of the radiogenic backgrounds in the double beta decay analyses, after the application of topological cuts that reduce the total rate to (0.25$\pm$0.01) mHz. Based on the best-fit background model, the NEXT-White median sensitivity to the two-neutrino double beta decay is found to be 3.5$\sigma$ after 1 year of data taking. The background measurement in a Q$_{\beta\beta}\pm$100 keV energy window validates the best-fit background model also for the neutrinoless double beta decay search with NEXT-100. Only one event is found, while the model expectation is (0.75$\pm$0.12) events.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Predicting the 5-Year Risk of Biochemical Relapse After Postprostatectomy Radiation Therapy in ≥PT2, pN0 Patients With a Comprehensive Tumor Control Probability Model

Purpose: To fit the individual biochemical recurrence-free survival (bRFS) data from patients treated with postprostatectomy radiation therapy (RT) with a comprehensive tumor control probability (TCP) model. Methods and Materials: Considering pre-RT prostate-specific antigen (PSA) as a surrogate of the number of clonogens, bRFS may be expressed as a function of dose-per-fraction–dependent radiosensitivity (α{sub eff}), the number of clonogens for pre-RT PSA = 1 ng/mL (C), and the fraction of patients who relapse because of clonogens outside the treated volume (K), assumed to depend (linearly or exponentially) on pre-RT PSA and Gleason score (GS). Data from 894 node-negative, ≥pT2, pN0 hormone-naive patients treated with adjuvant (n=331) or salvage (n=563) intent were available: 5-year bRFS data were fitted grouping patients according to GS (<7:392, =7:383, >7:119). Results: The median follow-up time, pre-RT PSA, and dose were 72 months, 0.25 ng/mL, and 66.6 Gy (range 59.4-77.4 Gy), respectively. The best-fit values were 0.23 to 0.26 Gy{sup −1} and 10{sup 7} for α{sub eff} and C for the model considering a linear dependence between K and PSA. Calibration plots showed good agreement between expected and observed incidences (slope: 0.90-0.93) and moderately high discriminative power (area under the curve [AUC]: 0.68-0.69). Cross-validation showed satisfactory results (average AUCs in the training/validation groups: 0.66-0.70). The resulting dose-effect curves strongly depend on pre-RT PSA and GS. bRFS rapidly decreases with PSA: the maximum obtainable bRFS (defined as 95% of the maximum) declined by about 2.7% and 4.5% for each increment of 0.1 ng/mL for GS <7 and ≥7, respectively. Conclusions: Individual data were fitted by a TCP model, and the resulting best-fit parameters were radiobiologically consistent. The model suggests that relapses frequently result from clonogens outside the irradiated volume, supporting the choice of lymph-node irradiation, systemic therapy, or both for specific subgroups (GS <7: PSA >0.8-1.0 ng/mL; GS ≥7: PSA >0.3 ng/mL). Early RT should be preferred over delayed RT; the detrimental effect of PSA increase can never be fully compensated by increasing the dose, especially for patients with GS ≥7.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1995

The FU Orionis outburst as a thermal accretion event: Observational constraints for protostellar disk models

The results of the time-dependent disk models developed in Bell & Lin are compared with observed properties of FU Orionis variables. Specific models are fit to the light curves of Fu Ori, V1515 Cyg, and V1057 Cyg. The slow risetime of V1515 Cyg can be matched by a self-regulated outburst model. The rapid risetimes of FU Ori and V1057 Cyg can be fitted with the application of modest perturbations to the disk surface density. Model disks display spectral features characteristic of observed objects. The color evolution of V1057 Cyg is naturally explained if mass flux drops in the inner disk (r less than 1/4 AU) while remaining steady in the outer disk. The decrease in optical line width (rotational velocity) observed during the decay of V1057 Cyg may be accounted for by an outward-propagating ionization front. We predict that before final decay to the quiescent phase, short-wavelength line widths (lambda less than 1.5 microns) will again increase. It is suggested that FU Orionis outbursts primarily occur to systems during the embedded phase with ages less than several times 10(exp 5) yr.

Bell, K. R.↗
NASA NTRS1989

Soft X-ray emission lines from low-mass X-ray binaries. I - Collision-dominated models

The soft X-ray line emission from five low-mass X-ray binaries observed by the Einstein Observatory (HEAO 2) Objective Grating Spectrometer is examined. Observed spectra are fitted to model spectra consisting of emission from an optically thin plasma. Fits are performed using a variety of different assumptions for elemental abundances, heating and ionization mechanisms, and the distribution of gas temperature and ionization parameter. The results are discussed in the context of current models for the accretion flow in low-mass X-ray binaries.

Kallman, T. R.↗
DOE OSTI2020

Mechanistic modelling of SARS-CoV-2 and other infectious diseases and the effects of therapeutics

Modern viral kinetic modeling and its application to therapeutics is a field that attracted the attention of the medical, pharmaceutical and modeling communities during the early days of the AIDS epidemic. Its successes lead to applications of modeling methods not only to HIV but a plethora of other viruses, such as hepatitis C virus (HCV), hepatitis B virus (HBV) and cytomegalovirus (CMV), which along with HIV cause chronic diseases, and viruses such as influenza, respiratory syncytial virus (RSV), West Nile virus (WNV), Zika virus, and SAR-CoV-2, which generally cause acute infections. Here we first review the historical development of mathematical models to understand HIV and HCV infections and the effects of treatment by fitting the models to clinical data. Furthermore, we then focus on recent efforts and contributions of applying these models towards understanding SARS-CoV-2 infection and highlight outstanding questions where modeling can provide crucial insights and help to optimize non-pharmaceutical and pharmaceutical interventions of the COVID-19 pandemic. The review is written from our personal perspective emphasizing the power of simple target cell limited models that provided important insights and then their evolution into more complex models that captured more of the virology and immunology. To quote Albert Einstein “Everything should be made as simple as possible, but not simpler”, and this idea underlies the modeling we describe below.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Does the leaf economic spectrum hold within plant functional types? A Bayesian multivariate trait meta-analysis

The leaf economic spectrum is a widely-studied axis of plant trait variability that defines a trade-off between leaf longevity and productivity. While this has been investigated at the global scale, where it is robust, and at local scales, where deviations from it are common, it has received less attention at the intermediate scale of PFTs. We investigated whether global leaf economic relationships are also present within the scale of plant functional types (PFTs) commonly used by Earth System models, and the extent to which this global-PFT hierarchy can be used to constrain trait estimates. We developed a hierarchical multivariate Bayesian model that assumes separate means and covariance structures within and across PFTs and fit this model to seven leaf traits from the TRY database related to leaf longevity, morphology, biochemistry, and photosynthetic metabolism. Although patterns of trait covariation were generally consistent with the leaf economic spectrum, we found three approximate tiers to this consistency. Relationships among morphological and biochemical traits (SLA, N, P) were the most robust within and across PFTs, suggesting that covariation in these traits is driven by universal leaf construction trade-offs and stoichiometry. Relationships among metabolic traits (R_d, V_{c,max}, J_max) were slightly less consistent, reflecting in part their much sparser sampling (especially for high-latitude PFTs), but also pointing to more flexible plasticity in plant metabolistm. Finally, relationships involving leaf lifespan were the least consistent, indicating that leaf economic relationships related to leaf lifespan are dominated by across-PFT differences and that within-PFT variation in leaf lifespan is more complex and idiosyncratic. Across all traits, these covariance were an important source of information, as evidenced by the improved imputation accuracy and reduced predictive uncertainty in multivariate models compared to univariate models. Ultimately, our study reaffirms the value of studying not just individual traits but the multivariate trait space and the utility of hierarchical modeling for studying the scale dependence of trait relationships.

biodiversity, ecological modeling, ecology, leaf b↗
DOE OSTI2018

Chemical modelling of Delayed Ettringite Formation for assessment of affected concrete structures

Delayed Ettringite Formation (DEF) modelling is addressed in the context of structural analysis. First, a chemical model is specified to simulate the effects of the heating of concrete in terms of reactions involving sulfates, aluminates and alkalis. It can be decomposed into: dissolution of primary sulfoaluminates at high temperature, fixation of aluminates in hydrogarnet or carboaluminates, and formation of delayed ettringite at low temperature. The influences of alkalis, temperature and water saturation on these reactions are taken into account. The main result of this model is the amount of delayed ettringite. The parameters of the proposed chemical model are fitted on a large number of experiments taken from the literature. The chemical model is then coupled with a nonlinear mechanical model based on poro-mechanics modelling. An application of chemo-mechanical coupling shows the features and benefits of such modelling to help practitioners in the management of structures affected by DEF.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Enhanced Jahn-Teller response induced by low-dose 10 MeV I{sup +} irradiation of La{sub 0.7}Ca{sub 0.3}MnO{sub 3−δ} films

The structural response of pulsed laser deposited La{sub 0.7}Ca{sub 0.3}Mn0{sub 3−δ} films to low-level 10 MeV I{sup +} irradiation is correlated with magnetic and electronic properties. A series of annealed pulsed laser deposited films were subjected to ion irradiation at doses of 0.5–2.0 × 10{sup 13} 10 MeV iodine ions/cm{sup 2}. X-ray diffraction measurements show no measurable increase in the full width at half maximum values of major reflections before and after irradiation. Extended x-ray absorption fine structure analyses (EXAFS), employing both a model independent fitting using expanded cumulants as well as a nonlinear least squares multiple scattering model based on FEFF generated theoretical EXAFS data, were employed to measure local properties relative to the Mn ions. Increasing irradiation doses lead to an unambiguous evolution of MnO{sub 6} octahedra from highly symmetric (i.e., undistorted) to a clear bimodal structure in which the MnO{sub 6} octahedra are measured to undergo a c-axis stretching bearing resemblance to a Jahn-Teller distortion. Concomitantly, the metal to insulator transition temperature decreases more than 270 K and the magnetoresistance increases from 10{sup 2}% to 10{sup 6}%.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Optical shielding of nickel nanoparticle by a bubble: Optical limiting gets limited

We have demonstrated that in a nickel nanoparticle colloid, the optical limiting action reduces if a vapor bubble forms around the nanoparticle. The energy-dependent transmission and z-scan measurements on nickel nanoparticles in toluene show the onset of an additional process. At high fluence excitation, the particle becomes less visible to the later part of the incoming pulse due to the heat generated bubble formed around it. We have proposed a simple “particle-in-bubble” model which fits the optical limiting and z-scan curves quite well. Using this model, we have also estimated that the bubble radius increases at a rate of 4.5 m/s.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

THE FERMI GBM GAMMA-RAY BURST SPECTRAL CATALOG: FOUR YEARS OF DATA

In this catalog we present the updated set of spectral analyses of gamma-ray bursts (GRBs) detected by the Fermi Gamma-Ray Burst Monitor during its first four years of operation. It contains two types of spectra, time-integrated spectral fits and spectral fits at the brightest time bin, from 943 triggered GRBs. Four different spectral models were fitted to the data, resulting in a compendium of more than 7500 spectra. The analysis was performed similarly but not identically to Goldstein et al. All 487 GRBs from the first two years have been re-fitted using the same methodology as that of the 456 GRBs in years three and four. We describe, in detail, our procedure and criteria for the analysis and present the results in the form of parameter distributions both for the observer-frame and rest-frame quantities. The data files containing the complete results are available from the High-Energy Astrophysics Science Archive Research Center.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Analysis of the theoretical bias in dark matter direct detection

Fitting the model ''A'' to dark matter direct detection data, when the model that underlies the data is ''B'', introduces a theoretical bias in the fit. We perform a quantitative study of the theoretical bias in dark matter direct detection, with a focus on assumptions regarding the dark matter interactions, and velocity distribution. We address this problem within the effective theory of isoscalar dark matter-nucleon interactions mediated by a heavy spin-1 or spin-0 particle. We analyze 24 benchmark points in the parameter space of the theory, using frequentist and Bayesian statistical methods. First, we simulate the data of future direct detection experiments assuming a momentum/velocity dependent dark matter-nucleon interaction, and an anisotropic dark matter velocity distribution. Then, we fit a constant scattering cross section, and an isotropic Maxwell-Boltzmann velocity distribution to the simulated data, thereby introducing a bias in the analysis. The best fit values of the dark matter particle mass differ from their benchmark values up to 2 standard deviations. The best fit values of the dark matter-nucleon coupling constant differ from their benchmark values up to several standard deviations. We conclude that common assumptions in dark matter direct detection are a source of potentially significant bias.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Molecular radiotherapy: The NUKFIT software for calculating the time-integrated activity coefficient

Purpose: Calculation of the time-integrated activity coefficient (residence time) is a crucial step in dosimetry for molecular radiotherapy. However, available software is deficient in that it is either not tailored for the use in molecular radiotherapy and/or does not include all required estimation methods. The aim of this work was therefore the development and programming of an algorithm which allows for an objective and reproducible determination of the time-integrated activity coefficient and its standard error.Methods: The algorithm includes the selection of a set of fitting functions from predefined sums of exponentials and the choice of an error model for the used data. To estimate the values of the adjustable parameters an objective function, depending on the data, the parameters of the error model, the fitting function and (if required and available) Bayesian information, is minimized. To increase reproducibility and user-friendliness the starting values are automatically determined using a combination of curve stripping and random search. Visual inspection, the coefficient of determination, the standard error of the fitted parameters, and the correlation matrix are provided to evaluate the quality of the fit. The functions which are most supported by the data are determined using the corrected Akaike information criterion. The time-integrated activity coefficient is estimated by analytically integrating the fitted functions. Its standard error is determined assuming Gaussian error propagation. The software was implemented using MATLAB.Results: To validate the proper implementation of the objective function and the fit functions, the results of NUKFIT and SAAM numerical, a commercially available software tool, were compared. The automatic search for starting values was successfully tested for reproducibility. The quality criteria applied in conjunction with the Akaike information criterion allowed the selection of suitable functions. Function fit parameters and their standard error estimated by using SAAM numerical and NUKFIT showed differences of <1%. The differences for the time-integrated activity coefficients were also <1% (standard error between 0.4% and 3%). In general, the application of the software is user-friendly and the results are mathematically correct and reproducible. An application of NUKFIT is presented for three different clinical examples.Conclusions: The software tool with its underlying methodology can be employed to objectively and reproducibly estimate the time integrated activity coefficient and its standard error for most time activity data in molecular radiotherapy.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

WE-D-BRF-05: Quantitative Dual-Energy CT Imaging for Proton Stopping Power Computation

Purpose: To extend the two-parameter separable basis-vector model (BVM) to estimation of proton stopping power from dual-energy CT (DECT) imaging. Methods: BVM assumes that the photon cross sections of any unknown material can be represented as a linear combination of the corresponding quantities for two bracketing basis materials. We show that both the electron density (ρe) and mean excitation energy (Iex) can be modeled by BVM, enabling stopping power to be estimated from the Bethe-Bloch equation. We have implemented an idealized post-processing dual energy imaging (pDECT) simulation consisting of monogenetic 45 keV and 80 keV scanning beams with polystyrene-water and water-CaCl2 solution basis pairs for soft tissues and bony tissues, respectively. The coefficients of 24 standard ICRU tissue compositions were estimated by pDECT. The corresponding ρe, Iex, and stopping power tables were evaluated via BVM and compared to tabulated ICRU 44 reference values. Results: BVM-based pDECT was found to estimate ρe and Iex with average and maximum errors of 0.5% and 2%, respectively, for the 24 tissues. Proton stopping power values at 175 MeV, show average/maximum errors of 0.8%/1.4%. For adipose, muscle and bone, these errors result range prediction accuracies less than 1%. Conclusion: A new two-parameter separable DECT model (BVM) for estimating proton stopping power was developed. Compared to competing parametric fit DECT models, BVM has the comparable prediction accuracy without necessitating iterative solution of nonlinear equations or a sample-dependent empirical relationship between effective atomic number and Iex. Based on the proton BVM, an efficient iterative statistical DECT reconstruction model is under development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗