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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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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Static Subspace Approximation for Random Phase Approximation Correlation Energies: Applications to Materials for Catalysis and Electrochemistry

Modeling complex materials using high-fidelity, ab initio methods at low cost is a fundamental goal for quantum chemical software packages. The GW approximation and random phase approximation (RPA) provide a unified description of both electronic structure and total energies using the same physics in a many-body perturbative approach that can be more accurate than generalized-gradient density functional theory (DFT) methods. However, GW/RPA implementations have historically been limited to either specific materials classes or application toward small chemical systems. Here, the static subspace approximation allows for reduced cost full-frequency GW/RPA calculations and has previously been benchmarked thoroughly for GW calculations. Here, we describe our approach to including partial occupations of electronic orbitals in full-frequency GW and RPA calculations for the study of electrocatalysts. We benchmarked RPA total energy calculations using the subspace approximation across a diverse test suite of materials for a variety of computational parameters. The benchmarking quantifies the impact of different extrapolation procedures for representing the static polarizability at infinite screened cutoff, and shows that using screened cutoffs above 20-25 Ryd result in diminishing accuracy returns for predicting RPA total energies. Additionally, for moderately sized electrocatalytic models, 2-3 times fewer computational resources are used to compute RPA total energies by representing the static polarizability with 20-30% of the static subspace basis, with an error of approximately 0.01 eV or better in RPA adsorption energy calculations. Finally, we show that for these electrochemical models RPA can shift DFT adsorption energy shifts by up to 0.5 eV and that GW can frequently shift DFT eigenvalues of surface and adsorbate states by approximately 0.5-1 eV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The impacts of charge transfer, localization, and metallicity on hydrogen retention and transport capacity

Solid state hydrides such as early transition metal hydrides are of inestimable importance for the future of hydrogen energy and are actively being investigated for energy conversion and storage applications such as fuel cells, solid-state batteries and neutron moderators. The retention and transport behavior of hydrogen in these hydrides has a huge role on the extended performance of components. While early transition-metal-based compounds exhibit many peculiar properties due to their unique correlated electronic signatures arising from -orbital electrons, the fundamental chemistry and transport behavior of hydrogen in such hydrides is not well understood. In the present work, using density functional theory, a highly intricate bonding feature is revealed through the theoretical investigation of the electronic structure of early transition metal hydrides YH 2 and ZrH 2 . In particular, a pronounced charge transfer from the transition element to H, results in localized electron densities at deep energy levels. The interplay between intrinsic charge transfer, charge localization, and metallicity in YH 2 and ZrH 2 leads to strong chemical bonding between metal and hydrogen atoms and large energy barriers for the migration of hydrogen vacancies. Specifically, hydrogen vacancies are found to be stable in the neutral state due to electron screening effects, accompanied by substantially high migration barriers between 0.8–1.2 eV along different crystallographic directions. In contrast, recent literature shows the migration barrier for charged H vacancies in insulating s-block metal hydrides lie between 0.1–0.4 eV, which is suitable for fast conduction applications. This pivotal electron structure difference exploited between early transition metal hydrides and alkali/alkaline earth metal hydrides determines extended hydrogen retention in these early transition metal hydrides. Finally, this work explains fundamental differences between the electronic structure of s-block and d-block metal hydrides, and its impact on the mobility of hydrogen vacancies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Machine learning prediction on the fractional free volume of polymer membranes

Fractional free volume (FFV) characterizes the microstructural level features of polymers and affects their properties including thermal, mechanical, and separation performance. Experimental measurements and theoretical analyses have been used to quantify the FFV of polymers, but challenges remain because of their limitations. Experimental measurements are laborious and based on semi empirical equations, while Bondi’s group contribution theory involves ambiguities like the determination of van der Waals volume and the choice of factor values in the theoretical equation. To efficiently evaluate the FFV of polymers, this study utilizes high-throughput molecular dynamics (MD) simulations to build a large dataset regarding polymer’s FFV. Based on this large dataset, we further build machine learning (ML) models to establish the composition-structure relation. Inspired by group contribution theory which correlates polymer’s functional groups to FFV, our ML models correlate polymer’s substructures or physico-chemical indexes to FFV. Here, our study first benchmarks the MD simulation protocol to obtain reliable FFV of polymers and then carries out high-throughput MD simulations for more than 6,500 homopolymers and 1,400 polyamides. Such a large and diverse dataset makes the well-trained ML models more generalizable, compared with the group contribution theory. The efficiency of a feed forward neural network model is further demonstrated by applying it to a hypothetical polyimide dataset of more than 8 million chemical structures. The predicted FFVs of hypothetical polyimides are further validated by MD simulations. The obtained FFVs of the 8 million polymers, plus their previously reported gas separation performances, demonstrate the promising capability of ML virtual screening for the discovery of polymer membranes with exceptional permeability/selectivity.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Phenotypically anchored transcriptomics across diverse agrichemicals reveals conserved pathways and unique gene expression signatures in zebrafish

Agrichemicals such as herbicides, fungicides, insecticides, and biocides are widely used in agriculture, yet some are associated with adverse effects in humans and the environment. While many of these chemicals have been extensively studied in vitro and are included in the EPA’s ToxCast program, comprehensive in vivo comparisons using RNA sequencing across structurally diverse agrichemicals, in a single screening platform, are lacking. In this study, we examined structurally diverse agrichemicals found in the U.S. Environmental Protection Agency’s (EPA) Toxcast Phase I and II library by statically exposing early life stage zebrafish at 6 h post fertilization (hpf) until 120 hpf at concentrations ranging from 0.25 to 100 µM. Morphological outcomes were assessed at 120 hpf across 10 endpoints, including yolk sac edema, craniofacial malformations, and axis abnormalities. Chemicals that produced robust concentration-response relationships were selected for transcriptomic profiling. For transcriptomic analysis, zebrafish were statically exposed to each chemical and sampled at 48 hpf, prior to the onset of morphological effects observed at 120 hpf. Differential expression analysis identified between 0 and 4,538 differentially expressed genes (DEGs) per chemical, with no clear correlation to morphological severity. Both DEG and co-expression network analyses revealed chemical-specific expression patterns that converged on shared biological pathways, including neurodevelopment and cytoskeletal organization. Key regulatory genes such as mylpfa and krt4 were identified within co-expression modules, suggesting their potential role in conserved toxicity mechanisms. Semantic similarity analysis of enriched gene ontology (GO) terms, when compared to existing datasets, highlighted gaps in the annotation of neurodevelopmental processes, indicating that some in vivo effects may not be fully captured by current curated resources. The results provide new insights into the modes of action of diverse agrichemicals and establish a framework for understanding how agrichemical structure relates to biological function in a vertebrate model.

agrichemical↗
DOE OSTI2021

Evaluating causal‐based feature selection for fuel property prediction models

Abstract In‐silico screening of novel biofuel molecules based on chemical and fuel properties is a critical first step in the biofuel evaluation process due to the significant volumes of samples required for experimental testing, the destructive nature of engine tests, and the costs associated with bench‐scale synthesis of novel fuels. Predictive models are limited by training sets of few existing measurements, often containing similar classes of molecules that represent just a subset of the potential molecular fuel space. Software tools can be used to generate every possible molecular descriptor for use as input features, but most of these features are largely irrelevant and training models on datasets with higher dimensionality than size tends to yield poor predictive performance. Feature selection has been shown to improve machine learning models, but correlation‐based feature selection fails to provide scientific insight into the underlying mechanisms that determine structure–property relationships. The implementation of causal discovery in feature selection could potentially inform the biofuel design process while also improving model prediction accuracy and robustness to new data. In this study, we investigate the benefits causal‐based feature selection might have on both model performance and identification of key molecular substructures. We found that causal‐based feature selection performed on par with alternative filtration methods, and that a structural causal model provides valuable scientific insights into the relationships between molecular substructures and fuel properties.

Nguyen, Bernard↗
DOE OSTI2020

Surface and grain boundary carbon heterogeneity in CH 3 NH 3 PbI 3 perovskites and its impact on optoelectronic properties

Rivaling state-of-the-art crystalline silicon, organic-inorganic hybrid perovskites have been intensely studied in recent years. Surface and interfacial engineering have been a focus for performance improvement. Even though significant progress has been made during the last decade in terms of the diversity and capability of perovskite-based devices, the structure-property relationship, particularly at the surface, which governs the real-world performance of these applications, is still unresolved. In the article, this issue was addressed by employing synchrotron-related experimental measurements, and a mechanism that correlates microstructure with surface chemistry was resolved. As a powerful and highly sensitive spectromicroscopy, soft x ray photoemission electron microscopy (X-PEEM) was used to probe the surface of perovskite films varying in post solvent annealing. Furthermore, static and in situ grazing incidence hard x ray diffraction (GIXD) was used to track the grain growth dynamics during the film formation process. It was found that the nature of the surfaces was dictated by the local chemistry that varied due to mass flow during the development of the microstructure. Combining optical and electronic characterizations, it was confirmed that a more homogenous chemistry, i.e., uniform chemical components and properties, along with reduced strain and grain boundary energies, yielded more defect-tolerant films. Grain boundaries were more favorable for screening carriers than those in the control film. Our findings underscore the importance of the uniformity in the surface for developing a chemistry-structure-property relationship in perovskite materials, as well as engineering local chemistry toward high-performance and stable devices.

42 ENGINEERING↗
NASA NTRS1973

Magnetospheric modulation effects on solar cosmic rays from simultaneous OGO 1 and 3 ion chamber data in 1968 and 1969

Simultaneous observations by identical ionization chambers aboard the satellites OGO-1 and OGO-3 are utilized to investigate spatial variations in particle intensity near and inside the magnetosphere during the solar cosmic ray events of September 1966. Cross-correlation of the absolute proton flux computed from the chamber rate during three solar particle events shows good agreement with the measurements by the IMP-F Solar Proton Monitor during the same events. The chamber has a dynamic range of over six orders of magnitude. Before launch it was calibrated in the laboratory with radiation dosages in the range 1 R/hr-6000 R/hr. The OGO-1 and OGO-3 chambers, which were normalized in the laboratory prior to the launch, are found to maintain their normalization within approximately equal to 1 per cent during their flight. The high sensitivity and absolute inter-comparability of the instruments allow small intensity differences to be detected and it is established that the observed differences can be explained by a magnetospheric screening effect when an anisotropic beam of particles is present in space. Evidence is presented to show that the screening is at times complete for a duration of as much as 110 min in the tail of the magnetosphere so that during this period the solar cosmic rays (E approximately equal to 15 MeV) have virtually no access to that region of the magnetosphere. Small intensity fluctuations of a temporal nature observed and found to be subjected to a damping effect inside the magnetosphere.

Hofmann, D. J.↗
DOE OSTI2018

Isolation and characterization of novel mutations in the pSC101 origin that increase copy number

pSC101 is a narrow host range, low-copy plasmid commonly used for genetically manipulating Escherichia coli. As a byproduct of a genetic screen for a more sensitive lactam biosensor, we identified multiple novel mutations that increase the copy number of plasmids with the pSC101 origin. All mutations identified in this study occurred on plasmids which also contained at least one mutation localized to the RepA protein encoded within the origin. Homology modelling predicts that many of these mutations occur within the dimerization interface of RepA. Mutant RepA resulted in plasmid copy numbers between ~31 and ~113 copies/cell, relative to ~5 copies/cell in wild-type pSC101 plasmids. Combining the mutations that were predicted to disrupt multiple contacts on the dimerization interface resulted in copy numbers of ~500 copies/cell, while also attenuating growth in host strains. Fluorescent protein production expressed from an arabinose-inducible promoter on mutant origin derived plasmids did correlate with copy number. Plasmids harboring RepA with one of two mutations, E83K and N99D, resulted in fluorescent protein production similar to that from p15a- (~20 copies/cell) and ColE1- (~31 copies/cell) based plasmids, respectively. The mutant copy number variants retained compatibility with p15a, pBBR, and ColE1 origins of replication. Thus, these pSC101 variants may be useful in future metabolic engineering efforts that require medium or high-copy vectors compatible with p15a- and ColE1-based plasmids.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Completed coarse-grained model for Pu hydriding that has quantum accuracy (Progress Summary)

Our team has developed a highly computationally efficient coarse-grained model for PuH 2 formation, based on high-level quantum mechanical calculations. Kohn-Sham Density Functional Theory (DFT) is a quantum mechanical approach that can be highly accurate for modeling condensed phases, including reactive materials that are subject to the breaking and forming of chemical bonds. DFT calculations, though, are extremely computationally intensive, and are generally limited to exceedingly small system sizes and time scales. This is particularly true for f-electron solids such as plutonium, where the high computational effort due to electron correlations and minimizing to specific electronic spin-states (e.g., anti-ferromagnetic vs. ferromagnetic) limits standard calculations to systems of tens of atoms and precludes the determination of time-dependent properties (e.g., chemical kinetic data). In this regard, we have created a simplified Pu + H 2 /PuH 2 equilibrium model based on a small number of interaction energies determined from DFT calculations. We have determined that Pu-H bond energetics in the bulk are largely defined by nearest-neighbor interactions, only. In other words, a hydrogen atom in a d-Pu tetrahedral interstitial site will only experience perturbations to its H-Pu bonded interactions when there is an additional hydrogen ion in a directly adjacent adsorption site. This is due to the strong electronic screening from the Pu atoms, which essentially limits the spatial extent of how hydrogen ions interact with each other within the Pu lattice. As a result, we are able to pre-tabulate all essential Pu-H interaction energies and model PuH 2 formation via a Monte Carlo simulation approach. This allows us to greatly expand the spatial and time scales of our calculations while maintaining most of the accuracy of quantum methods. Our model can thus be extended to system sizes if 100,000 atoms or greater and can be used to model hydride equilibrium processes, all of which are computationally cost prohibitive with any standard quantum code. We have used our approach to compute a two-dimensional free energy heat map and temperature dependence at sub-atmospheric pressures for PuH 2 formation. Our results compare well to the limited available experimental data, in particular for the enthalpy of formation (DH). Our goal is to extend these results to compute nucleation parameters such as the critical nucleus size and nucleation growth rates for continuum models.

36 MATERIALS SCIENCE↗
NASA NTRS2017

Carotid Intima Media Thickness in the Astronaut Corps: Association to Spacecraft

Background: Carotid Intima Media Thickness (CIMT) has been demonstrated to be predictive of future cardiovascular events. Within various populations, radiation exposure, stress, and physical confinement have all been linked to an increased CIMT. Recent research discovered CIMT was significantly increased in ten long duration astronauts from pre-flight to four days post flight. The relationship between spaceflight and CIMT is not understood and trends in CIMT within the larger astronaut population are unknown. Methods: In 2010, CIMT was offered as part of the astronaut annual exam at the JSC Flight Medicine Clinic using a standardized CIMT screening protocol and professional sonographers. Between 2010 and 2016, CIMT measurements were collected on 213 NASA astronauts and payload specialists. The values used in this retrospective chart review are the mean of the CIMT from the right and left. Spaceflight exposure was categorized based on the total number of days spent in space at the time of the ground-based ultrasound (0, 1-29, 30-100, 101-200, ≥200). Linear regression with generalized estimating equations were used to estimate the association between spaceflight exposures and CIMT. Results: 530 studies were completed among 213 astronauts with a mean of 2.5 studies (range 1-6) per astronaut over the six year period. As in other populations, CIMT was significantly associated with age; however, gender was not. While there was no significant direct correlation between total spaceflight exposure and CIMT found, astronauts with 30-100 spaceflight days and astronauts with greater than 100 spaceflight days had significantly increased CIMT over astronauts who had never flown (p=0.002 and p=<0.0001 respectively) after adjustment for age. Conclusion: Further work is needed to fully understand CIMT and its association to spaceflight. Current occupational surveillance activities are under way to study CIMT values in conjunction with other cardiovascular risk factors among astronauts as compared to the general population.

Suffredini, John↗
DOE OSTI2021

Fast and Accurate Machine Learning Strategy for Calculating Partial Atomic Charges in Metal–Organic Frameworks

Computational high-throughput screening using molecular simulations is a powerful tool for identifying top-performing metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges are often required to model the electrostatic interactions between the MOF and the adsorbate, especially when the adsorption involves molecules with dipole or quadrupole moments such as water and CO 2 . Although ab initio methods can be used to calculate accurate partial atomic charges, these methods are impractical for screening large material databases because of the high computational cost. We developed a random forest machine learning model to predict the partial atomic charges in MOFs using a small yet meaningful set of features that represent both the elemental properties and the local environment of each atom. The model was trained and tested on a collection of about 320 000 density-derived electrostatic and chemical (DDEC) atomic charges calculated on a subset of the Computation-Ready Experimental Metal–Organic Framework (CoRE MOF-2019) database and separately on charge model 5 (CM5) charges. The model predicts accurate atomic charges for MOFs at a fraction of the computational cost of periodic density functional theory (DFT) and is found to be transferable to other porous molecular crystals and zeolites. In conclusion, a strong correlation is observed between the partial atomic charge and the average electronegativity difference between the central atom and its bonded neighbors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Challenges in Continuous In-Field Critical Current Testing of High-Temperature Superconducting Tapes: Thermal and Mechanical Perspectives

High-temperature superconductors (HTS) are essential for ultra-high-field applications requiring exceptional current-carrying capacity under extreme conditions. However, systematic characterization of critical current in long-length conductors remains challenging due to complex thermal, electromag netic, and mechanical interactions during continuous testing. This study reports the development of a continuous in-field magnetization testing system for position-dependent critical current measurement in HTS tapes at 20 K under 7.5 T fields applied normal to the tape plane, enabling identification of performance-limiting regions that could compromise magnet stability. Here, the system addresses two fundamental challenges inherent to cryogenic reel to-reel testing. First, thermal management requires continuous cooling of a moving conductor to 20 K, achieved through liquid nitrogen precooling combined with a 100 W@20 K Gifford McMahon cryocooler. Second, screening currents in high fields generate Lorentz forces that induce twisting, bowing, and potential delamination. To mitigate these risks, we propose mechanical reinforcement and active current density suppression strategies. Numerical simulations using the stream function formulation reveal four primary failure modes: frictional heating at guide interfaces, unstable equilibria causing deformation, transverse current-induced stresses at guide transitions, and unsupported forces in vertical spans. Our mitigation strategies include PTFE coated guides to minimize friction, spring-loaded stabilization mechanisms to maintain tape alignment, controlled pre-heating using the liquid nitrogen thermal jacket to suppress critical current at stress points, and optimized guide positioning to minimize force accumulation. The experimental system is nearing completion, with testing planned to commence within two months. Preliminary validation at 65 K under 0.5 T demonstrates strong correlation between simulation-predicted mechanical instabilities and observed critical current variations during conductor tran sitions through the measurement region. These findings establish a robust foundation for quality assurance protocols essential to next-generation superconducting magnet applications.

Chen, Siwei [Princeton Plasma Physics Laboratory (↗
NASA NTRS1992

The continuous plankton recorder survey: A long-term, basin-scale oceanic time series

In the 1920s, before the advent of echo sounders, fishery biologists were greatly concerned with assisting the fisherman to locate schools of pelagic fish. One of the approaches they developed was to relate the distribution of the planktonic food organisms to the presence of the schools of predators such as herring (Clupea harengus). The British planktologist, Alister Hardy, who had already carried out extensive studies on the feeding preferences of herring (Hardy, 1926a), initiated a program to examine the fishermen's contention that herring schools avoided 'green', i.e., phytoplankton-rich, water but could be correlated with high concentrations of zooplankton. This practical program was centered on the use of a specially developed instrument, the 'Plankton Indicator', designed to be used by the fisherman to assist in the search for suitable waters. It had limited success in its main aim but, as a collecting device, it embodied several profoundly important features. It was a simple instrument which was robust enough to be deployed and recovered by the crew of commercial vessels (in this case fishing vessels) while they were underway. The Indicator however, was no more than a high speed net which integrated the plankton over the area of sampling, but Hardy had also become interested in describing the patchiness of planktonic populations. He thus developed the Continuous Plankton Recorder (CPR) where he substituted the fixed filter screen of the Indicator by a continually moving length of silk mesh. The screen traversed at constant speed across the path of the incoming water and the trapped organisms were retained in place by sandwiching beneath an additional second mesh screen. Thus, knowing the speed of the towing vessel and the shooting and hauling positions, the spatial patterns of the plankton could be determined. Hardy took the first CPR to the Antarctic where he used it in the Southern Atlantic (Hardy, 1926b) and later deployed it in the North Sea to make some of the earliest contiguous records of plankton patchiness.

Gamble, John C.↗
DOE OSTI2020

Critical Assessment of the Thermodynamics of Vacancy Formation in Fe 2 O 3 Using Hybrid Density Functional Theory

Fe 2 O 3 hematite is a technologically important material with applications in energy storage as well as being the key phase formed in the rust of iron-based materials. Despite this central importance, there is much that is still unknown regarding the properties of defects in Fe 2 O 3 and consequently oxide growth. In this work, using screened hybrid density functional theory (HSE06), we consider the thermodynamics of vacancies in Fe 2 O 3 , considering the effects of ionic and electronic chemical potentials on both iron and oxygen vacancy formation. We find that, in the oxygen-rich limit, iron vacancies are easier to form, though the difference in formation energy between the two vacancies is only about 1 eV. In contrast, in the Fe-rich limit, oxygen vacancies have an extremely low formation energy, only 0.07 eV at mid-gap, and would spontaneously form as the Fermi level is reduced, while Fe vacancies require over 5 eV to form. Consistent with experiment, this indicates that Fe 2 O 3 is relatively easily reduced but not oxidized. However, the theoretical picture is very different when considering other exchange–correlation functionals (GGA + U or SCAN), emphasizing the critical role of the exchange–correlation functional in describing this system accurately.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

A density functional theory based approach for predicting melting points of ionic liquids

Accurate prediction of melting points of ILs is important both from the fundamental point of view and from the practical perspective for screening ILs with low melting points and broadening their utilization in a wider temperature range. In this work, we present an ab initio approach to calculating melting points of ILs with known crystal structures and illustrate its application for a series of 11 ILs containing imidazolium/pyrrolidinium cations and halide/polyatomic fluoro-containing anions. The melting point is determined as a temperature at which the Gibbs free energy of fusion is zero. The Gibbs free energy of fusion can be expressed through the use of the Born-Fajans-Haber cycle via the lattice free energy of forming a solid IL from gaseous phase ions and the sum of the solvation free energies of ions comprising IL. Dispersion-corrected density functional theory (DFT) involving (semi)local (PBE-D3) and hybrid exchange-correlation (HSE06-D3) functionals is applied to estimate the lattice enthalpy, entropy, and free energy. The ions solvation free energies are calculated with the SMD-generic-IL solvation model at the M06-2X/6-31+G(d) level of theory under standard conditions. The melting points of ILs computed with the HSE06-D3 functional are in good agreement with the experimental data, with a mean absolute error of 30.5 K and a mean relative error of 8.5%. The model is capable of accurately reproducing the trends in melting points upon variation of alkyl substituents in organic cations and replacement one anion by another. The results verify that the lattice energies of ILs containing polyatomic fluoro-containing anions can be approximated reasonably well using the volume-based thermodynamic approach. However, there is no correlation of the computed lattice energies with molecular volume for ILs containing halide anions. Moreover, entropies of solid ILs follow two different linear relationships with molecular volume for halides and polyatomic fluoro-containing anions. As a result, continuous progress in predicting crystal structures of organic salts with halide anions will be a key factor for successful prediction of melting points with no prior knowledge of the crystal structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Effect of porosity, tissue density, and mechanical properties on radial sound speed in human cortical bone

Purpose: The purpose of this study was to investigate the effect of simultaneous changes in cortical porosity, tissue mineral density, and elastic properties on radial speed of sound (SOS) in cortical bone. The authors applied quantitative pulse-echo (PE) ultrasound techniques that hold much potential especially for screening of osteoporosis at primary healthcare facilities. Currently, most PE measurements of cortical thickness, a well-known indicator of fracture risk, use a predefined estimate for SOS in bone to calculate thickness. Due to variation of cortical bone porosity, the use of a constant SOS value propagates to an unknown error in cortical thickness assessment by PE ultrasound. Methods: The authors conducted 2.25 and 5.00 MHz focused PE ultrasound time of flight measurements on femoral diaphyses of 18 cadavers in vitro. Cortical porosities of the samples were determined using microcomputed tomography and related to SOS in the samples. Additionally, the effect of cortical bone porosity and mechanical properties of the calcified matrix on SOS was investigated using numerical finite difference time domain simulations. Results: Both experimental measurements and simulations demonstrated significant negative correlation between radial SOS and cortical porosity (R{sup 2} ≥ 0.493, p < 0.01 and R{sup 2} ≥ 0.989, p < 0.01, respectively). When a constant SOS was assumed for cortical bone, the error due to variation of cortical bone porosity (4.9%–16.4%) was about 6% in the cortical thickness assessment in vitro. Conclusions: Use of a predefined, constant value for radial SOS in cortical bone, i.e., neglecting the effect of measured variation in cortical porosity, propagated to an error of 6% in cortical thickness. This error can be critical as characteristic cortical thinning of 1.10% ± 1.06% per yr decreases bending strength of the distal radius and results in increased fragility in postmenopausal women. Provided that the cortical porosity can be estimated in vivo, the relationship between radial SOS and cortical porosity can be utilized and a porosity based radial SOS estimate could be implemented to determine cortical thickness. This would constitute a step toward individualized quantitative ultrasound diagnostics of osteoporosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Iodine Waste Form Corrosion: PNNL Summary Testing Report

A test method to correlate the laboratory corrosion behavior of iodine-containing waste forms (IWFs) to a conceptual long-term corrosion models is required. Several candidate methods have been evaluated previously, and each method presents unique challenges and limitations. Dynamic leach tests have emerged as the preferred candidate test method to evaluate IWFs and parameterize an eventual long-term corrosion model. This report was prepared in support of this effort to define the test suite to evaluate the corrosion of IWFs, with the goal of defining and parameterizing a conceptual long-term corrosion model. A review was presented highlighting the high degree of variability between the IWF corrosion data that is available in the literature and the need for a standardized test suite. The targeted test suite is composed of a single interval screening test, a dynamic leach test, and post-test solid characterization of the monolithic IWF samples. The data presented serves two purposes: to expand the range of IWFs evaluated with the test suite to assess method variability and to further understand the corrosion of IWFs to best inform conceptual long-term corrosion model development. A series of IWF types were included in the testing, including hot isostatically pressed Ag-mordenite, silver functionalized silica-based aerogels, iodosodalites (hot isostatic pressing, sintered, glass bonded ceramic), iodoapatite, tellurite glass and glass composite materials.

42 ENGINEERING↗
DOE OSTI2015

Rapid estimation of sugar release from winter wheat straw during bioethanol production using FTIR-photoacoustic spectroscopy

Complexity and high cost are the main limitations for high-throughput screening methods for the estimation of the sugar release from plant materials during bioethanol production. In addition, it is important that we improve our understanding of the mechanisms by which different chemical components are affecting the degradability of plant material. In this study, Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS) was combined with advanced chemometrics to develop calibration models predicting the amount of sugars released after pretreatment and enzymatic hydrolysis of wheat straw during bioethanol production, and the spectra were analysed to identify components associated with recalcitrance. A total of 1122 wheat straw samples from nine different locations in Denmark and one location in the United Kingdom, spanning a large variation in genetic material and environmental conditions during growth, were analysed. The FTIR-PAS spectra of non-pretreated wheat straw were correlated with the measured sugar release, determined by a high-throughput pretreatment and enzymatic hydrolysis (HTPH) assay. A partial least square regression (PLSR) calibration model predicting the glucose and xylose release was developed. The interpretation of the regression coefficients revealed a positive correlation between the released glucose and xylose with easily hydrolysable compounds, such as amorphous cellulose and hemicellulose. Additionally, we observed a negative correlation with crystalline cellulose and lignin, which inhibits cellulose and hemicellulose hydrolysis. FTIR-PAS was used as a reliable method for the rapid estimation of sugar release during bioethanol production. The spectra revealed that lignin inhibited the hydrolysis of polysaccharides into monomers, while the crystallinity of cellulose retarded its hydrolysis into glucose. Amorphous cellulose and xylans were found to contribute significantly to the released amounts of glucose and xylose, respectively.

09 BIOMASS FUELS↗