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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Data Mining Scientific Literature Demonstrates Use of Biological and Medical Data Across Scientific Disciplines

The Protein Data Bank (PDB) was established as the 1st open access digital data resource in biology and medicine. Today, the PDB archive contains over 140,000 atomic‐level biomolecular structures determined by crystallography, NMR spectroscopy, and 3D electron microscopy. About 20 new structures are deposited daily. PDB data is used in basic and applied research, patent applications, discovery of lifesaving drugs, product innovation, and education. About 80% of all PDB structures deposited have a “primary citation,” which is the first paper to describe the molecule and its structure and function. In turn, these primary citations have contributed to more than 1 million publications. An initial study by Clarivate Analytics on the Nucleic Acids Research publication demonstrated that PDB data drive high‐impact research in diverse scientific fields. To build on this study, we used Python programming to perform several data mining studies to understand the impact of these structures in fundamental biology, biomedicine, and energy in the scientific literature. The scientific literature database, Web of Science, tracks scientific article metrics such as the number of times cited, subject category, year published, funding source, and keywords. Web of Science data for PDB primary citations was compiled as used as the data set. Two main investigations were performed. In the first, we examined the number of citations per article (data overall and by individual subject categories) to develop “top 10 cited structures” lists and analyzed for trends. In the second investigation, we extended our data mining analysis to consider for each main subject category, the papers with the most citations and the structures they cite, and the most frequently occuring keywords. We have observed different aspects of biological data utility in various subject areas, at times in ways unanticipated from the structures' primary citation. This research demonstrates the value of biological data from the PDB by showing the diverse ways in which the data are being used. Support or Funding Information RCSB PDB is funded by a grant (DBI‐1338415) from the National Science Foundation, the National Institutes of Health, and the US Department of Energy. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Verdiguel, Natalie↗
DOE OSTI2012

Code Qualification of Structural Materials for AFCI Advanced Recycling Reactors

This report summarizes the further findings from the assessments of current status and future needs in code qualification and licensing of reference structural materials and new advanced alloys for advanced recycling reactors (ARRs) in support of Advanced Fuel Cycle Initiative (AFCI). The work is a combined effort between Argonne National Laboratory (ANL) and Oak Ridge National Laboratory (ORNL) with ANL as the technical lead, as part of Advanced Structural Materials Program for AFCI Reactor Campaign. The report is the second deliverable in FY08 (M505011401) under the work package 'Advanced Materials Code Qualification'. The overall objective of the Advanced Materials Code Qualification project is to evaluate key requirements for the ASME Code qualification and the Nuclear Regulatory Commission (NRC) approval of structural materials in support of the design and licensing of the ARR. Advanced materials are a critical element in the development of sodium reactor technologies. Enhanced materials performance not only improves safety margins and provides design flexibility, but also is essential for the economics of future advanced sodium reactors. Code qualification and licensing of advanced materials are prominent needs for developing and implementing advanced sodium reactor technologies. Nuclear structural component design in the U.S. must comply with the ASME Boiler and Pressure Vessel Code Section III (Rules for Construction of Nuclear Facility Components) and the NRC grants the operational license. As the ARR will operate at higher temperatures than the current light water reactors (LWRs), the design of elevated-temperature components must comply with ASME Subsection NH (Class 1 Components in Elevated Temperature Service). However, the NRC has not approved the use of Subsection NH for reactor components, and this puts additional burdens on materials qualification of the ARR. In the past licensing review for the Clinch River Breeder Reactor Project (CRBRP) and the Power Reactor Innovative Small Module (PRISM), the NRC/Advisory Committee on Reactor Safeguards (ACRS) raised numerous safety-related issues regarding elevated-temperature structural integrity criteria. Most of these issues remained unresolved today. These critical licensing reviews provide a basis for the evaluation of underlying technical issues for future advanced sodium-cooled reactors. Major materials performance issues and high temperature design methodology issues pertinent to the ARR are addressed in the report. The report is organized as follows: the ARR reference design concepts proposed by the Argonne National Laboratory and four industrial consortia were reviewed first, followed by a summary of the major code qualification and licensing issues for the ARR structural materials. The available database is presented for the ASME Code-qualified structural alloys (e.g. 304, 316 stainless steels, 2.25Cr-1Mo, and mod.9Cr-1Mo), including physical properties, tensile properties, impact properties and fracture toughness, creep, fatigue, creep-fatigue interaction, microstructural stability during long-term thermal aging, material degradation in sodium environments and effects of neutron irradiation for both base metals and weld metals. An assessment of modified versions of Type 316 SS, i.e. Type 316LN and its Japanese version, 316FR, was conducted to provide a perspective for codification of 316LN or 316FR in Subsection NH. Current status and data availability of four new advanced alloys, i.e. NF616, NF616+TMT, NF709, and HT-UPS, are also addressed to identify the R&D needs for their code qualification for ARR applications. For both conventional and new alloys, issues related to high temperature design methodology are described to address the needs for improvements for the ARR design and licensing. Assessments have shown that there are significant data gaps for the full qualification and licensing of the ARR structural materials. Development and evaluation of structural materials require a variety of experimental facilities that have been seriously degraded in the past. The availability and additional needs for the key experimental facilities are summarized at the end of the report. Detailed information covered in each Chapter is given.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRSDate not supplied

Lunar Impact Melt Crystallization Produces Reflectance Spectra Dominated By Clinopyroxene Signatures: Implications for the Origin of Pink Spinel Anorthosite

Magma-wallrock interaction and impact melt crystallization are the two leading hypotheses for the formation of orbitally detected lunar “pink” spinel anorthosite (PSA) [1-3]. Distinguishing among hypotheses is complicated because both require mixing of anorthositic crust and MgO-rich ultramafic components. Models for PSA formation need to account for either the thermodynamic hurdles of crustal assimilation, or the size of impactor and composition of target material needed to generate spinel during crater and basin formation. Determining whether the energy source is endogenic or exogenic is important for understanding the thermal and chemical evolution of the lunar crust. Here we test the impact melt hypothesis by performing controlled cooling experiments on two hypothetical impact melt compositions. The compositions represent mixing of ultramafic magma and anorthositic crust in molar ratios of approximately 50:50 and 25:75. Synthetic crystallized assemblages were prepared for chemical analysis and bidirectional reflectance spectroscopy in the visible to near-infrared wavelengths. All crystallization experiments contained plagioclase, olivine, and clinopyroxene, but trace amounts of spinel were only observed in the 50:50 mix. The experimental spinel is similar to the compositions inferred from remote observations. However, the high-Ca pyroxene in our experimental assemblages (9 – 18 wt.%) resulted in 1 and 2 µm absorption band center positions consistent with synthetic clinopyroxene. The clinopyroxene absorptions are present regardless of specific mineral modes and the presence of either olivine or spinel. These results suggest that impact melt crystallization will produce clinopyroxene-bearing lithologies, the presence of which masks spectral contributions from coexisting spinel and olivine. Assuming that the trace amounts of spinel observed in our experiments could be concentrated and isolated from the mafic silicates by convection or density settling in the impact melt sheet, the spinel-rich areas would still be proximally associated with the remaining silicate-dominated assemblage exhibiting strong clinopyroxene spectral signatures. We conclude that impact melting of the lunar crust can explain rare cases of PSA in association with clinopyroxene. Previous investigations of magma-wallrock interactions [2] demonstrate that small plagioclase-contaminated regions of an ultramafic intrusion can concentrate spinel whereas larger portions of the same intrusion remain relatively uncontaminated and yield olivine and orthopyroxene, consistent with the more common occurrence of PSAs in association with orthopyroxene ±olivine in the remote sensing database (e.g., Moscoviense Basin) [4].

petrology↗
DOE OSTI2026

The Stability of Nd Hydroxyl Complexes at Near Neutral to Alkaline pH from 25 to 75 °C: Implications for Monazite Solubility in Hydrothermal Aqueous Fluids

Speciation of rare earth elements (REE) in aqueous fluids controls their mobilization during fluid-rock interaction. Thermodynamic modeling provides important insights into the factors controlling REE mobility and fractionation in aqueous fluids, in which aqueous REE hydroxyl complexes are particularly important across a broad pH range. However, the stability of these REE hydroxyl complexes remains poorly determined due to limited experimental data above ambient temperature. In this work, UV–vis spectrophotometry experiments were conducted to determine the cumulative hydrolysis constants for neodymium (Nd) from 25 to 75 °C in near-neutral to alkaline solutions. The color indicator m -cresol purple was used to determine in situ pH. Alkaline NaOH-bearing aqueous solutions were doped with varying initial Nd concentrations (0 to ∼0.155 mmol/kg), which resulted in the release of protons (H + ) and pH decrease during hydrolysis of Nd 3+ according to Nd 3+ + n H 2 O = Nd(OH) n 3– n + H + . The average OH – ligand number coordinated to Nd 3+ was found to increase from 1.0 to 1.6 at 25 °C and from 1.2 to 2.8 at 75 °C over a pH range from 6.3 to 9.0. The measured speciation shows an increased predominance of Nd(OH) 3 0 over the Nd(OH) 2 + and Nd(OH) 2+ species with increased temperature and pH. The increasing cumulative formation constants (log*β° n , n = 1 to 3) retrieved from 25 to 75 °C differ by 0.1 to 1.9 logarithmic units in comparison to existing thermodynamic databases. These updated thermodynamic data have important implications for geochemical modeling of the speciation of Nd hydroxyl complexes and the solubility of monazite as a function of pH.

58 GEOSCIENCES↗
NASA NTRS1995

Mississippi State University Center for Air Sea Technology FY95 Research Program

The Mississippi State University (MSU) Center for Air Sea Technology (CAST) evolved from the Institute for Naval Oceanography's (INO) Experimental Center for Mesoscale Ocean Prediction (ECMOP) which was started in 1989. MSU CAST subsequently began operation on 1 October 1992 under an Office of Naval Research (ONR) two-year grant which ended on 30 September 1994. In FY95 MSU CAST was successful in obtaining five additional research grants from ONR, as well as several other research contracts from the Naval Oceanographic Office via NASA, the Naval Research Laboratory, the Army Corps of Engineers, and private industry. In the past, MSU CAST technical research and development has produced tools, systems, techniques, and procedures that improve efficiency and overcome deficiency for both the operational and research communities residing with the Department of Defense, private industry, and university ocean modeling community. We continued this effort with the following thrust areas: to develop advanced methodologies and tools for model evaluation, validation and visualization, both oceanographic and atmospheric; to develop a system-level capability for conducting temporally and ; spatially scaled ocean simulations driven by or are responsive to ocean models, and take into consideration coupling to atmospheric models; to continue the existing oceanographic/atmospheric data management task with emphasis on distributed databases in a network environment, with database optimization and standardization, including use of Mosaic and World Wide Web (WWW) access; and to implement a high performance parallel computing technology for CAST ocean models

Yeske, Lanny↗
NASA NTRS2012

Finite Element Models for Electron Beam Freeform Fabrication Process

Electron beam freeform fabrication (EBF3) is a member of an emerging class of direct manufacturing processes known as solid freeform fabrication (SFF); another member of the class is the laser deposition process. Successful application of the EBF3 process requires precise control of a number of process parameters such as the EB power, speed, and metal feed rate in order to ensure thermal management; good fusion between the substrate and the first layer and between successive layers; minimize part distortion and residual stresses; and control the microstructure of the finished product. This is the only effort thus far that has addressed computer simulation of the EBF3 process. The models developed in this effort can assist in reducing the number of trials in the laboratory or on the shop floor while making high-quality parts. With some modifications, their use can be further extended to the simulation of laser, TIG (tungsten inert gas), and other deposition processes. A solid mechanics-based finite element code, ABAQUS, was chosen as the primary engine in developing these models whereas a computational fluid dynamics (CFD) code, Fluent, was used in a support role. Several innovative concepts were developed, some of which are highlighted below. These concepts were implemented in a number of new computer models either in the form of stand-alone programs or as user subroutines for ABAQUS and Fluent codes. A database of thermo-physical, mechanical, fluid, and metallurgical properties of stainless steel 304 was developed. Computing models for Gaussian and raster modes of the electron beam heat input were developed. Also, new schemes were devised to account for the heat sink effect during the deposition process. These innovations, and others, lead to improved models for thermal management and prediction of transient/residual stresses and distortions. Two approaches for the prediction of microstructure were pursued. The first was an empirical approach involving the computation of thermal gradient, solidification rate, and velocity (G,R,V) coupled with the use of a solidification map that should be known a priori. The second approach relies completely on computer simulation. For this purpose a criterion for the prediction of morphology was proposed, which was combined with three alternative models for the prediction of microstructure; one based on solidification kinetics, the second on phase diagram, and the third on differential scanning calorimetry data. The last was found to be the simplest and the most versatile; it can be used with multicomponent alloys and rapid solidification without any additional difficulty. For the purpose of (limited) experimental validation, finite element models developed in this effort were applied to three different shapes made of stainless steel 304 material, designed expressly for this effort with an increasing level of complexity. These finite element models require large computation time, especially when applied to deposits with multiple adjacent beads and layers. This problem can be overcome, to some extent, by the use of fast, multi-core computers. Also, due to their numerical nature coupled with the fact that solid mechanics- based models are being used to represent the material behavior in liquid and vapor phases as well, the models have some inherent approximations that become more pronounced when dealing with multi-bead and multi-layer deposits.

Chandra, Umesh↗
DOE OSTI2022

An analysis of fluff formation in metallic fuel via data analyzes from EBR-II experiments and BISON fuel code modeling

During the operation of EBR-II, it was found that a highly porous structure (over 40% area fraction) formed at the top of several fuel columns. Previous work has shown that this structure, designated fluff in this paper, contains a significant fraction of fuel elements (e.g., U and Pu) which could potentially impact neutronics. This work aims in analyzing the formation mechanism of this microstructure so its impact can be incorporated into future metallic fuel modeling codes and algorithms. This paper details a preliminary examination into the formation mechanisms of fluff by performing qualitative and statistical analysis of EBR-II experimental data. Additionally, the operating conditions that have the greatest impact on fluff formation were determined based on this data set. Also, BISON fuel code simulations were used to help postulate potential fluff formation mechanisms. From this analysis it was found that the largest contributors to fluff formation were fuel burnup and composition, with fluff formation exhibiting a roughly linear positive correlation with increasing burnup and a negative correlation with increasing Pu content. It was also found that higher pin operating temperatures decreased fluff formation but only for U-10Zr fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

Comparison of Pre- and Post-Flight Estimations of Pitch Damping Coefficients for Unguided Entry Vehicles

Pre-flight predictions of pitch damping coefficient (C M q + C m ȧ ) curves are used in entry simulations to determine flight readiness and if any dynamic remediation strategies are required. Accurate characterization of these pitch damping coefficient curves is crucial for mission success. Historically, pre-flight estimations of these curves are derived experimentally either via ballistic range testing or with 1-degree-of-freedom (DOF) free-or forced-oscillation wind tunnel testing. With post-flight best-estimated trajectories, a fitting procedure as described in Karlgaard, et. al. is used to compare pre-and post-flight pitch damping coefficients. This technique relies on an assumed analytical form of the trajectory, a limited 3-DOF representation described in Schoenenberger and Queen, which results in an Euler-Cauchy solution form. This solution assumes constant density, thus limited amplitude multi-peak windows of the trajectory are considered to populate the pitch damping-amplitudes pace. The estimated post-flight pitch damping approximations and the pre-flight predictions shown are effective representations of pitch damping, or the integrated effect of the pitch damping coefficient over one pitch cycle at the corresponding cycle’s peak amplitude. Effective pitch damping coefficient curves provide more intuitive insights about where the vehicle is stable and permits readily processed comparisons between data-sets. It is important to note that most pitch damping curves, such as those reported in aero databases and utilized in flight mechanics trajectory simulations, are represented in instantaneous angle-of-attack space distinct from what is presented in the paper.

pitch damping coefficient↗
NASA NTRS1989

Noiseless compression using non-Markov models

Adaptive data compression techniques can be viewed as consisting of a model specified by a database common to the encoder and decoder, an encoding rule and a rule for updating the model to ensure that the encoder and decoder always agree on the interpretation of the next transmission. The techniques which fit this framework range from run-length coding, to adaptive Huffman and arithmetic coding, to the string-matching techniques of Lempel and Ziv. The compression obtained by arithmetic coding is dependent on the generality of the source model. For many sources, an independent-letter model is clearly insufficient. Unfortunately, a straightforward implementation of a Markov model requires an amount of space exponential in the number of letters remembered. The Directed Acyclic Word Graph (DAWG) can be constructed in time and space proportional to the text encoded, and can be used to estimate the probabilities required for arithmetic coding based on an amount of memory which varies naturally depending on the encoded text. The tail of that portion of the text which was encoded is the longest suffix that has occurred previously. The frequencies of letters following these previous occurrences can be used to estimate the probability distribution of the next letter. Experimental results indicate that compression is often far better than that obtained using independent-letter models, and sometimes also significantly better than other non-independent techniques.

Blumer, Anselm↗
DOE OSTI2015

Radiation behavior of high-entropy alloys for advanced reactors. Final report

In the first task, we have demonstrated the radiation damage and the recrystallization behaviors in multicomponent alloys through molecular-dynamics simulations. It is found that by alloying with atoms of different sizes, the atomic-level strain increases, and the propensity of the radiation-induced crystalline to amorphous transition increases as the defects cluster in the cascade body. Recrystallization of the radiation induced supercooled or glass regions show that by tuning the composition and the equilibrium temperature, the multicomponent alloys can be healed. The crystalline-amorphous-crystalline transitions predict the potential high radiation resistance in multicomponent alloys. In the second task, three types of high-entropy alloys (HEAs) were fabricated from AlCoCrFeNi and AlCuCrFeNi quinary alloys. Hardness and reduced contact modulus were measured using nanoindentation tests. Heavy ion irradiation were performed using 10 MeV gold and 5 MeV nickel to study radiation effects. Al 0.5 CrCuFeNi 2 shows phase separation upon the presence of copper. Both hardness and contact modulus exhibit the same trend as increasing the applied load, and it indicates that excessive free volume may alter the growth rate of the plastic zone. The as-cast Al 0.1 CoCrFeNi specimen undergone the hot isostatic pressing (HIP) process and steady cooling rate which mitigate the quenching effect. The swelling behavior was characterized by the atomic force microscopy (AFM), and the swelling rate is approximately 0.02% dpa. Selected area diffraction (SAD) patters show irradiation-induced amorphization throughout the ion projected range. Within the peak damage region, an amorpous ring is observed, and a mixture of amorphous/ crystalline structure at deeper depth is found. The Al 0.3 CoCrFeNi HEAs shows good radiation resistance up to 60 peak dpa. No voids or dislocations are observed. The crystal structures remain face-centered-cubic (FCC) before and after 5 MeV Ni irradiation. Higher dpa might be required to study defects formation mechanisms. In the third task, all the constituent binary and ternary systems of the Al-Co-Cr-Fe-Ni system were thermodynamically modeled within the whole composition range. Comparisons between the calculated phase diagrams and literature data are in good agreement. The multi-component thermodynamic database of the Al-Co-Cr-Fe-Ni system was then obtained via extrapolation. The current Al-Co-Cr-Fe-Ni thermodynamic database enables us to carry out the calculations of phase diagrams, which can be used as useful guidelines to identify the Al-Co-Cr-Fe-Ni HEAs with desirable microstructures. In the fourth task, we discuss how as-cast and homogenized phases can be identified, what phases are usually found in the as-cast and homogenized conditions, and what the thermodynamics and kinetics of phase transformations are in the AlCoCrFeNi HEA. The microstructure and phase composition were studied in as-cast and homogenized conditions. It showed the dendritrical structure in the as-cast condition consisting primarily of a nano-lamellar mixture of A2 [disorder body-centered-cubic (BCC)] and B2 (ordered BCC) phases, in addition to a very small amount of A1 [disorder face-centered-cubic (FCC)] phases. The homogenization heat treatment resulted in an increase in the volume fraction of the A1 phase and formation of a Sigma phase. Tensile properties in as-cast and homogenized conditions are reported at 700 °C. Thermodynamic modeling of non-equilibrium and equilibrium phase diagrams for the AlCoCrFeNi HEA gave good agreement with the experimental observations of the phase contents. The reasons for the improvement of ductility after the heat treatment are discussed.

36 MATERIALS SCIENCE↗
NASA NTRS2019

Nonmodal Growth of TravelingWaves on Blunt Cones at Hypersonic Speeds

The existing database of transition measurements in hypersonic ground facilities has established that, as the nosetip bluntness is increased, the onset of boundary layer transition over a circular cone at zero angle of attack shifts downstream. However, this trend is reversed at sufficiently large values of the nose Reynolds number, so that the transition onset location eventually moves upstream with a further increase in nose-tip bluntness. Because modal amplification is too weak to initiate transition at moderate-to-large bluntness values, nonmodal growth has been investigated as the potential basis for a physics-based model for the frustum transition. The present analysis investigates the nonmodal growth of traveling disturbances initiated within the nose-tip vicinity that peak within the entropy layer. Results show that, with increasing nose bluntness, both planar and oblique traveling disturbances experience appreciable energy amplification up to successively higher frequencies. For moderately blunt cones, the initial nonmmodal growth is followed by a partial decay that is more than overcome by an eventual, modal growth as Mack-mode waves. For larger bluntness values, the Mack-mode waves are not amplified anywhere upstream of the experimentally measured transition location, but the traveling modes still undergo a significant amount of nonmodal growth. This finding does not provide a definitive link between optimal growth and the onset of transition, but it is qualitatively consistent with the experimental observations that frustum transition in the absence of sufficient Mack-mode amplification implies a double peak in disturbance amplification and the appearance of transitional events above the boundary-layer edge.

Hypersonic speed↗
DOE OSTI2016

Insights into cellulase-lignin non-specific binding revealed by computational redesign of the surface of green fluorescent protein

Biological-mediated conversion of pretreated lignocellulosic biomass to biofuels and biochemicals is a promising avenue towards energy sustainability. However, a critical impediment to the commercialization of cellulosic biofuel production is the high cost of cellulase enzymes needed to deconstruct biomass into fermentable sugars. One major factor driving cost is cellulase adsorption and inactivation in the presence of lignin, yet we currently have a poor understanding of the protein structure-function relationships driving this adsorption. In this work, we have systematically investigated the role of protein surface potential on lignin adsorption using a model monomeric fluorescent protein. We have designed and experimentally characterized 16 model protein variants spanning the physiological range of net charge (-24 to +16 total charges) and total charge density (0.28 to 0.40 charges per sequence length) typical for natural proteins. Protein designs were expressed, purified, and subjected to in silico and in vitro biophysical measurements to evaluate the relationship between protein surface potential and lignin adsorption properties. The designs were comparable to model fluorescent protein in terms of thermostability and heterologous expression yield, although the majority of the designs unexpectedly formed homodimers. Protein adsorption to lignin was studied at two different temperatures using Quartz Crystal Microbalance with Dissipation Monitoring and a subtractive mass balance assay. We found a weak correlation between protein net charge and protein-binding capacity to lignin. No other single characteristic, including apparent melting temperature and 2nd virial coefficient, showed correlation with lignin binding. Analysis of an unrelated cellulase dataset with mutations localized to a family I carbohydrate-binding module showed a similar correlation between net charge and lignin binding capacity. Altogether, our study provides strategies to identify highly active, low lignin-binding cellulases by either rational design or by computational screening genomic databases.

09 BIOMASS FUELS↗
DOE OSTI2016

Tritium Decay Helium-3 Effects in Tungsten

A critical challenge for long-term operation of ITER and beyond to a Demonstration reactor (DEMO) and future fusion reactor will be the development of plasma-facing components (PFCs) that demonstrate erosion resistance to steady-state/transient heat fluxes and intense neutral/ion particle fluxes under the extreme fusion nuclear environment, while at the same time minimizing in-vessel tritium inventories and permeation fluxes into the PFC’s coolant. Tritium will diffuse in bulk tungsten at elevated temperatures, and can be trapped in radiation-induced trap site (up to 1 at. % T/W) in tungsten [1,2]. Tritium decay into helium-3 may also play a major role in microstructural evolution (e.g. helium embrittlement) in tungsten due to relatively low helium-4 production (e.g. He/dpa ratio of 0.4-0.7 appm [3]) in tungsten. Tritium-decay helium-3 effect on tungsten is hardly understood, and its database is very limited. Two tungsten samples (99.99 at. % purity from A.L.M.T. Co., Japan) were exposed to high flux (ion flux of 1.0x1022 m-2s-1 and ion fluence of 1.0x1026 m-2) 0.5%T2/D2 plasma at two different temperatures (200, and 500°C) in Tritium Plasma Experiment (TPE) at Idaho National Laboratory. Tritium implanted samples were stored at ambient temperature in air for more than 3 years to investigate tritium decay helium-3 effect in tungsten. The tritium distributions on plasma-exposed was monitored by a tritium imaging plate technique during storage period [4]. Thermal desorption spectroscopy was performed with a ramp rate of 10°C/min up to 900°C to outgas residual deuterium and tritium but keep helium-3 in tungsten. These helium-3 implanted samples were exposed to deuterium plasma in TPE to investigate helium-3 effect on deuterium behavior in tungsten. The results show that tritium surface concentration in 200°C sample decreased to 30 %, but tritium surface concentration in 500°C sample did not alter over the 3 years storage period, indicating possible tritium retention in helium-3 bubble. This paper reports the initial experimental observation of tritium-decay helium-3 in tungsten exposed to deuterium/tritium plasma along with electron microscope analysis and also discusses a Tritium Migration Analysis Program (TMAP) analysis of tritium-decay helium-3 effects on tritium retention in tungsten for DEMO and future fusion reactor. [1] Y. Hatano, et.al., Nucl. Fusion 53 (2013) 073006 [2] M. Shimada, et.al., Nucl. Fusion 55 (2015) 013008 [3] M. Sawan, Fus. Sci. Technol. 66 (2014) 272 [4] T. Otsuka, Fus. Sci. Technol. 60 (2011) 1539 This work was prepared for the U.S. Department of Energy, Office of Fusion Energy Sciences, under the DOE Idaho Field Office contract number DE-AC07-05ID14517.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

*-DCC: A platform to collect, annotate, and explore a large variety of sequencing experiments

Background: Over the past few years the variety of experimental designs and protocols for sequencing experiments increased greatly. To ensure the wide usability of the produced data beyond an individual project, rich and systematic annotation of the underlying experiments is crucial. Findings: We first developed an annotation structure that captures the overall experimental design as well as the relevant details of the steps from the biological sample to the library preparation, the sequencing procedure, and the sequencing and processed files. Through various design features, such as controlled vocabularies and different field requirements, we ensured a high annotation quality, comparability, and ease of annotation. The structure can be easily adapted to a large variety of species. We then implemented the annotation strategy in a user-hosted web platform with data import, query, and export functionality. Conclusions: We present here an annotation structure and user-hosted platform for sequencing experiment data, suitable for lab-internal documentation, collaborations, and large-scale annotation efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

An ensemble model of QSAR tools for regulatory risk assessment

Quantitative structure activity relationships (QSARs) are theoretical models that relate a quantitative measure of chemical structure to a physical property or a biological effect. QSAR predictions can be used for chemical risk assessment for protection of human and environmental health, which makes them interesting to regulators, especially in the absence of experimental data. For compatibility with regulatory use, QSAR models should be transparent, reproducible and optimized to minimize the number of false negatives. In silico QSAR tools are gaining wide acceptance as a faster alternative to otherwise time-consuming clinical and animal testing methods. However, different QSAR tools often make conflicting predictions for a given chemical and may also vary in their predictive performance across different chemical datasets. In a regulatory context, conflicting predictions raise interpretation, validation and adequacy concerns. To address these concerns, ensemble learning techniques in the machine learning paradigm can be used to integrate predictions from multiple tools. By leveraging various underlying QSAR algorithms and training datasets, the resulting consensus prediction should yield better overall predictive ability. We present a novel ensemble QSAR model using Bayesian classification. The model allows for varying a cut-off parameter that allows for a selection in the desirable trade-off between model sensitivity and specificity. The predictive performance of the ensemble model is compared with four in silico tools (Toxtree, Lazar, OECD Toolbox, and Danish QSAR) to predict carcinogenicity for a dataset of air toxins (332 chemicals) and a subset of the gold carcinogenic potency database (480 chemicals). Leave-one-out cross validation results show that the ensemble model achieves the best trade-off between sensitivity and specificity (accuracy: 83.8 % and 80.4 %, and balanced accuracy: 80.6 % and 80.8 %) and highest inter-rater agreement [kappa (κ): 0.63 and 0.62] for both the datasets. The ROC curves demonstrate the utility of the cut-off feature in the predictive ability of the ensemble model. In conclusion, this feature provides an additional control to the regulators in grading a chemical based on the severity of the toxic endpoint under study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

On the Importance of Producing and Characterizing Laboratory Analogs of Cosmic Grains, Planetary Atmospheric Aerosols, and Surface Materials

Carbonaceous dust and aerosols have been observed in interstellar/circumstellar and planetary environments. Dedicated laboratory experiments have been developed to produce analogs of these solid materials under different experimental conditions (molecular precursors, temperature, pressure, energy source…). These experimental studies are key to investigating the physical and chemical processes that drive the formation of solid particles from gas and solid phase molecular precursors in astrophysical and planetary environments. They also allow the characterization of the physical, optical, and chemical properties of these laboratory-generated analogs, hence providing critical information that can be used as input parameters in models for the analysis and interpretation of observational data. Here, as an example of these laboratory efforts, we will present various studies that combined (1) experiments performed with the NASA Ames COSmIC facility to produce analogs of Titan’s atmospheric aerosols and cosmic grains from gas phase molecular precursors, and (2) the characterization of these analogs with the NASA Ames Optical Constants Facility (OCF) to provide the real and imaginary parts of their refractive indices, n + ik, to the community, from the visible to the far-infrared (0.59–200 µm, 16,950–50 per cm). We will also discuss the importance of the wavelength and spectral range coverage of these optical constants, n and k, for their use in radiative transfer, atmospheric and reflectance models, and present a new effort to develop an Optical Constant database (OCdb) to provide this critical data to the scientific community.

Cosmic Grains↗
DOE OSTI2025

Developing predictive models for µ opioid receptor binding using machine learning and deep learning techniques

Opioids exert their analgesic effect by binding to the µ opioid receptor (MOR), which initiates a downstream signaling pathway, eventually inhibiting pain transmission in the spinal cord. However, current opioids are addictive, often leading to overdose contributing to the opioid crisis in the United States. Therefore, understanding the structure-activity relationship between MOR and its ligands is essential for predicting MOR binding of chemicals, which could assist in the development of non-addictive or less-addictive opioid analgesics. This study aimed to develop machine learning and deep learning models for predicting MOR binding activity of chemicals. Chemicals with MOR binding activity data were first curated from public databases and the literature. Molecular descriptors of the curated chemicals were calculated using software Mold2. The chemicals were then split into training and external validation datasets. Random forest, k-nearest neighbors, support vector machine, multi-layer perceptron, and long short-term memory models were developed and evaluated using 5-fold cross-validations and external validations, resulting in Matthews correlation coefficients of 0.528–0.654 and 0.408, respectively. Furthermore, prediction confidence and applicability domain analyses highlighted their importance to the models’ applicability. Our results suggest that the developed models could be useful for identifying MOR binders, potentially aiding in the development of non-addictive or less-addictive drugs targeting MOR.

Research & Experimental Medicine↗
DOE OSTI2017

Accurate Theoretical Methane Line Lists in the Infrared up to 3000 K and Quasi-continuum Absorption/Emission Modeling for Astrophysical Applications

Modeling atmospheres of hot exoplanets and brown dwarfs requires high- T databases that include methane as the major hydrocarbon. We report a complete theoretical line list of {sup 12}CH{sub 4} in the infrared range 0–13,400 cm{sup −1} up to T {sub max} = 3000 K computed via a full quantum-mechanical method from ab initio potential energy and dipole moment surfaces. Over 150 billion transitions were generated with the lower rovibrational energy cutoff 33,000 cm{sup −1} and intensity cutoff down to 10{sup −33} cm/molecule to ensure convergent opacity predictions. Empirical corrections for 3.7 million of the strongest transitions permitted line position accuracies of 0.001–0.01 cm{sup −1}. Full data are partitioned into two sets. “Light lists” contain strong and medium transitions necessary for an accurate description of sharp features in absorption/emission spectra. For a fast and efficient modeling of quasi-continuum cross sections, billions of tiny lines are compressed in “super-line” libraries according to Rey et al. These combined data will be freely accessible via the TheoReTS information system (http://theorets.univ-reims.fr, http://theorets.tsu.ru), which provides a user-friendly interface for simulations of absorption coefficients, cross-sectional transmittance, and radiance. Comparisons with cold, room, and high- T experimental data show that the data reported here represent the first global theoretical methane lists suitable for high-resolution astrophysical applications.

79 ASTRONOMY AND ASTROPHYSICS↗