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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SPRUCE Porewater Chemistry Data for Experimental Plots, Beginning in 2013, Version 4

This data set includes the chemistry of porewater in the SPRUCE experiment plots located in the S1 bog of the USDA Forest Service Marcell Experimental Forest (MEF) in northern Minnesota, 40 km north of Grand Rapids. Data are presented from June 2013 through September 2020 (2013-06-28 to 2020-09-28). Data will continue to be collected until 2025 and will be appended to this dataset periodically. These data are the pre- and post-treatment data from the warming and elevated carbon dioxide (CO2) treatments associated with the SPRUCE experiment. There are 10 experimental plots in SPRUCE: 5 temperature treatments (+0, +2.25, +4.5, +6.75, +9°C) at ambient CO2, and the same 5 temperature treatments at elevated CO2 (+500 ppm). There are 7 additional ambient plots without experimental enclosures, and thus a total of 17 plots. Water samples were analyzed for pH, specific conductivity, nutrient concentrations (ammonium, nitrate, soluble reactive phosphorus, total nitrogen, total phosphorus), cation concentrations (calcium, potassium, magnesium, sodium, aluminum, iron, manganese, silicon, strontium), anion concentrations (chloride, sulfate), and TOC concentrations. Subsets of the samples were analyzed for natural-abundance stable isotopes of water (δ18O-H2O and δD-H2O) and THg and MeHg concentrations. User note: Results will be added to this data set and released to the public periodically as quality assurance and publication of results are accomplished. This June 2024 release (Version 4) is an updated and expanded version that supersedes and replaces the previous release. See the Data Release History table below for additional release notes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantifying molecular deformation in polymer melts by a generalized Zimm plot approach

The Zimm plot has been widely used to characterize the molecular dimensions of polymers from small-angle scattering experiments, where the reciprocal intensity is analyzed as a function of the square of the magnitude of the scattering wavevector Q. Here, this work explores the benefits of analyzing the reciprocal scattering intensity from deformed polymers, extending the original Zimm plot to anisotropic materials. In the small-angle limit, a tensorial extension of the Guinier law is found for the gyration tensor and the reciprocal single-chain structure factor. In the high-Q limit, application of the spherical harmonic expansion technique to the reciprocal structure factor permits direct model-independent analysis of spatially dependent molecular deformation of polymers. Additionally, the contributions from high-order spherical harmonics become insignificant in the reciprocal-intensity representation. The proposed generalized Zimm plot approach is demonstrated computationally with the affine deformation model and the Rouse model, and experimentally with small-angle neutron scattering measurements of deformed polystyrene melts.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Measurement of Convective Heat Transfer Coefficients With Supercritical CO 2 Using the Wilson-Plot Technique

This paper describes the measurement of convective heat transfer coefficients and friction factors for sCO 2 flowing in a smooth tube and compares the results with published correlations for validation. The paper also describes the Heat Exchange and Experimental Testing (HEET) rig recently designed and built at the U.S. Department of Energy’s (DoE’s) National Energy Technology Laboratory (NETL) in Morgantown, WV. Here, the Wilson-plot technique used for measuring the heat transfer coefficients is described along with the data reduction process. The Wilson-plot technique was chosen as the basis for the design of NETL’s HEET rig. Advantages of the Wilson-plot technique include the (1) ability to measure high convective heat transfer coefficients accurately, (2) ability to measure average heat transfer coefficient for complicated heat exchange geometries like those produced using additive manufacturing, (3) ability to measure heat transfer coefficients on both sides of a heat exchanger independently, and (4) simplicity of experimental setup. Capabilities of the HEET rig include pressure to 24 MPa (3500 psig), temperature to 538 °C (1000 °F), mass flow rate to 1.5 kg/s (3 lb/s), and Re to 500,000. The rig is designed to operate with pure CO 2 or a mixture of CO 2 and up to 10% N2 by volume to study the impact of gas mixtures typical of direct-fired sCO 2 power cycles on the convective heat transfer and pressure drop. Preliminary tests in the HEET rig were performed with smooth stainless-steel tube and pure CO 2 , and the results were compared with published correlations for Nusselt number (Nu) and friction factor. Over a Reynolds number (Re) range from 58,000 to 228,000, measured Nu was compared to predictions using the Dittus and Boelter equation (Kreith and Bohn, 1993, “Principles of Heat Transfer, West Publishing Company”) within 5% and measured friction factors were compared to predictions using the McAdams correlation (“McAdams, 1954, “Heat Transmission,” 3rd ed., McGraw Hill, New York)” for smooth tube to be within 5%.

42 ENGINEERING↗
DOE OSTI2018

Review of PBX 9502 Pop Plot data

Pop plot data (distance of run and time to detonation as a function of shock pressure) is a simple characterization of shock initiation of a high explosive. It is used, along with other data, to calibrate reactive burn models. For the insensitive TATB based explosive PBX 9502, there are data at 5 initial temperatures (77 K, -55 C, 23 C, 76 C, 130 C) and for several lots. Here we review the dependence of the Pop plot on temperature and the variation with lot. There is a significant increase in shock sensitivity with temperature.Since the Pop plot is important for modeling, fit parameters are interpolated to cover the temperature range –55 < T < 76 C. The scatter in the data and variation with lot is important for assessing the accuracy to which a model can be calibrated.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2018

Hill Plot Focusing on Ce Compounds with High Magnetic Ordering Temperatures and Consequent Study of Ce{sub 2}AuP{sub 3}

The Hill plot is a well-known criterion of the f-electron element interatomic threshold distance separating the nonmagnetic state from the magnetic state in actinides and lanthanides. We have reinvestigated the Hill plot of Ce compounds using the commercial crystallographic database CRYSTMET, focusing on a relationship between the Ce-Ce distance and the magnetic ordering temperature because a Ce compound with no other magnetic elements rarely has a magnetic ordering temperature that is higher than 20 K. The Hill plot of approximately 730 compounds has revealed that a Ce compound, particularly a ferromagnet, showing a high magnetic ordering temperature would require a short Ce-Ce distance with a suppression of the valence instability of the Ce ion. From the study, we developed interest in Ce{sub 2}AuP{sub 3} with a Curie temperature of 31 K. The ferromagnetic nature of this material has been examined in terms of a doping effect, which suggests a possible increase in magnetic anisotropy energy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Plot-level rapid screening for photosynthetic parameters using proximal hyperspectral imaging

Abstract Photosynthesis is currently measured using time-laborious and/or destructive methods which slows research and breeding efforts to identify crop germplasm with higher photosynthetic capacities. We present a plot-level screening tool for quantification of photosynthetic parameters and pigment contents that utilizes hyperspectral reflectance from sunlit leaf pixels collected from a plot (~2 m×2 m) in <1 min. Using field-grown Nicotiana tabacum with genetically altered photosynthetic pathways over two growing seasons (2017 and 2018), we built predictive models for eight photosynthetic parameters and pigment traits. Using partial least squares regression (PLSR) analysis of plot-level sunlit vegetative reflectance pixels from a single visible near infra-red (VNIR) (400–900 nm) hyperspectral camera, we predict maximum carboxylation rate of Rubisco (Vc,max, R2=0.79) maximum electron transport rate in given conditions (J1800, R2=0.59), maximal light-saturated photosynthesis (Pmax, R2=0.54), chlorophyll content (R2=0.87), the Chl a/b ratio (R2=0.63), carbon content (R2=0.47), and nitrogen content (R2=0.49). Model predictions did not improve when using two cameras spanning 400–1800 nm, suggesting a robust, widely applicable and more ‘cost-effective’ pipeline requiring only a single VNIR camera. The analysis pipeline and methods can be used in any cropping system with modified species-specific PLSR analysis to offer a high-throughput field phenotyping screening for germplasm with improved photosynthetic performance in field trials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from soil samples in control and warming plots in Blodgett Forest, CA (2014-2021)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of LBNL (Lawrence Berkeley National Laboratory) TES (Terrestrial Ecosystem Science) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization.Here, we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community from soil depth profiles collected from 2014 to 2021 from three paired control and warming plots. We collected soil samples across a range of depth profiles (spanning surface to 90 cm deep) from three paired control and warming plots from a temperate mixed forest in Northern California. Each paired plot had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. 101 soil metagenomes were sequenced at JGI (Joint Genome Institute) and UCSF (University of California San Francisco) Center for Advanced Technology and can be found under the JGI (Joint Genome Institute) GOLD (Genomes Online Database) Sequencing project Gs0151586 and NCBI (National Center for Biotechnology Information) Projects PRJNA1225762 and PRJEB39497. Metagenomes were assembled using JGI (Joint Genome Institute) Metagenome Workflow (10.1128/mSystems.00804-20). For each metagenome, the assembled contigs were binned into genomes using 3 binning algorithms (cocacola, metabat, and maxbin) and the resulting bins were consolidated using dastool. The consolidated bins from all metagenomes were pooled, filtered by completeness (>50%) and contamination (<25%), and dereplicated at 99% ANI (average nucleotide identity) using dRep (https://github.com/MrOlm/drep).The dataset includes a zip file of 2321 MAG (Metagenome Assembled Genome) fasta files, the accession numbers for the underlying metagenomes, and a csv file with MAG (Metagenome Assembled Genome) quality metrics and taxonomic classification (GTDB -Genome Taxonomy Database-RS220). This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. A sample metadata file (samples.csv) that contains site information has also been included.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

SPRUCE Aboveground Vegetation Coverage in Root Ingrowth Core Plots, Marcell Experimental Forest, Minnesota, August 2022

This dataset contains vegetation survey measurements from root ingrowth core plots (Määttä et al. 2025) inside SPRUCE Experiment plots at the Marcell Experimental Forest in northern Minnesota. Vegetation surveys were conducted in 0.25 meter2 plots containing root ingrowth cores on August 8th and 9th, 2022 (2022-08-08 to 2022-08-09). The warming and elevated carbon dioxide (CO2) treatments in the dataset include the full treatment gradient: +0 degrees Celsius (C) (+0 and +500 parts per million (ppm) elevated CO2), +2.25 degrees C (+0 and +500 ppm), +4.5 degrees C (+0 and +500 ppm elevated CO2), +6.75 degrees C (+0 and +500 ppm) and +9 degrees C (+0 and +500 ppm elevated CO2) for both hummocks and hollows. This dataset includes measurements of the height and absolute coverage (%) for each vascular plant and moss species, as well as organic litter and dead overstory vascular plants, and the distance from the grid center to the nearest tree and the species of the nearest tree. These data were used as species-specific aboveground plant metadata for assessing the warming and elevated CO2 response of fine roots across different peatland microtopographical features (hummocks and hollows) and plant functional types (shrub, spruce and larch). This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗
DOE OSTI2022

Automation of Plot Generation for Strategic Petroleum Reserve Cavern Leaching Monitoring

Monitoring cavern leaching after each calendar year of oil sales is necessary to support cavern stability efforts and long-term availability for oil drawdowns in the U.S. Strategic Petroleum Reserve. Modeling results from the SANSMIC code and recent sonars are compared to show projected changes in the cavern’s geometry due to leaching from raw-water injections. This report aims to give background on the importance of monitoring cavern leaching and provide a detailed explanation of the process used to create the leaching plots used to monitor cavern leaching. In the past, generating leaching plots for each cavern in a given leaching year was done manually, and every cavern had to be processed individually. A Python script, compatible with Earth Volumetric Studio, was created to automate most of the process. The script makes a total of 26 plots per cavern to show leaching history, axisymmetric representation of leaching, and SANSMIC modeling of future leaching. The current run time for the script is one hour, replacing 40-50 hours of the monitoring cavern leaching process.

02 PETROLEUM↗
DOE OSTI2019

SPRUCE Tritium in Porewater of SPRUCE Experimental Plots and Neighboring Peatlands, and in Groundwater, Stream Water, and Precipitation of the S1 Bog, 2014-2016

This data set reports the tritium concentrations in (1) porewater from selected SPRUCE experimental plots located in the S1 bog and in (2) groundwater, streamwater, and precipitation in the S1 bog watershed, and (3) in porewater from the S2 bog, S3 fen, and Bog Lake fen. All sites are located at the USDA Forest Service, Marcell Experimental Forest (MEF) near Grand Rapids, MN. Samples were collected between June of 2014 and August of 2016. These data include samples collected pre- and post-belowground warming treatments associated with the SPRUCE Experiment. There are 10 experimental plots in SPRUCE: 5 temperature treatments (+0, +2.25, +4.5, +6.75, +9°C) at ambient CO2, and the same 5 temperature treatments at elevated CO2 (+500 ppm). Porewater samples in this dataset were collected from three of the warming treatment plots (+0, +4.5, +9°C) at ambient CO2.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2022

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2023, with start- and end-of-season phenological transition dates derived through the end of autumn 2022. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step Contains 35 files in *.csv format inside a compressed (*.zip) file. Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e. vegetation type) Contains one file in *.csv format Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure Contains two files in *.csv format, one for snow on trees and one for snow on ground This data set consists of two sets of companion files: Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. Contains three files in HTML format, one for each vegetation type One additional file in HTML format with the transition dates plotted for each vegetation type, by year R files for processing Phenocam files and flags. Contains five files in R file (*.R) format in one compressed (*.zip) file User Note: All imagery is posted in near-real time to the PhenoCam Project web page (http://phenocam.sr.unh.edu/), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/y7z5mau7. The data reported here are based on the complete camera record from SPRUCE and supersedes the previously released phenocam datasets (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

SPRUCE Experiment, Marcell Experimental Forest, Sp↗
DOE OSTI2024

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2023

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2024, with start- and end-of-season phenological transition dates derived through the end of autumn 2023. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: (1) 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step • Contains 36 files in *.csv format inside a compressed (*.zip) file. (2) Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e. vegetation type) • Contains one file in *.csv format (3) Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure • Contains two files in *.csv format, one for snow on trees and one for snow on ground This data set consists of two sets of companion files: (1) Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. • Contains three files in HTML format, one for each vegetation type • One additional file in HTML format with the transition dates plotted for each vegetation type, by year (2) R files for processing Phenocam files and flags. • Contains five files in R file (*.R) format in one compressed (*.zip) file User Note: All imagery is posted in near-real time to the PhenoCam Project web page (http://phenocam.sr.unh.edu/), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/sprucecams. The data reported here are based on the complete camera record from SPRUCE and supersedes the previously released data inclusive of the 2015-2022 data (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

Spruce and Peatland Responses Under Changing Envir↗
DOE OSTI2025

SPRUCE Vegetation Phenology in Experimental Plots from PhenoCam Imagery, 2015-2024

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2025 (2015-08-24 to 2025-03-31), with start- and end-of-season phenological transition dates derived through the end of autumn 2024. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: (1) 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step. • Contains 36 files in *.csv format inside a compressed (*.zip) file. (2) Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e., vegetation type). • Contains one file in *.csv format. (3) Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure. • Contains two files in *.csv format, one for snow on trees and one for snow on ground. This data set consists of two sets of companion files: (1) Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. • Contains three files in HTML format, one for each vegetation type. • One additional file in HTML format with the transition dates plotted for each vegetation type, by year. (2) R files for processing PhenoCam files and flags. • Contains five files in R file(*.R) format and the components of the phenocamr package (Version 1.1.4) used for calculating transition dates for 2015-2024. These are contained in a compressed (*.zip) file. User Note: All imagery is posted in near-real time to the PhenoCam Project web page (https://phenocam.nau.edu), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/sprucecams. This data set is based on the complete camera record from SPRUCE and supersedes all previously released PhenoCam datasets (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

SPRUCE Deep Peat Heating (DPH) Peat Water Content and Temperature for Experimental Plot Cores, June 2014 through June 2015

This data set provides the peat water content and peat temperature at time of sampling for peat cores collected before and during the SPRUCE Deep Peat Heating (DPH) study. Cores were collected during three sampling events: 03 June 2014, 09 September 2014, and 16 June 2015. Two cores were extracted from hollow locations in each of the 10 experimental plots (4, 6, 8, 10, 11, 13, 16, 17, 19, and 20). The five ambient plots (5, 7, 14, and 21) were not included in the DPH sampling efforts. See Table 1. Cores were partitioned into samples at 11 depth increments: 0-10, 10-20, 20-30, 30-40, 40-50, 50-75, 75-100, 100-125, 125-150, 150-175, and 175-200 cm below surface of the hollow. The DPH study was undertaken to evaluate possible rapid responses of deep peat carbon (C) stocks, microbial communities, and biogeochemical cycling processes to unprecedented temperatures. In June 2014, deep soil heating was initiated at 5 warming levels (+0, +2.25, +4.5, +6.75 and +9 °C) with 2 replicate plots per level. Warming levels at depth were achieved over a 25 (+ 2.25 °C) to 60-day (+9 °C) period depending on the target treatment temperatures. Data file – There is one comma-separated (*.csv) file with peat core water content and temperature at time of sampling, plus the amount of dried archived material retained after analyses. User Note: In this third release, four variables related to extrapolations of peat core temperature were removed. See the Data Set History table for additional details. 25-150, 150-175, and 175-200 cm below surface of the hollow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Influence plots for LASSO

With many predictors in regression, fitting the full model can induce multicollinearity problems. Least Absolute Shrinkage and Selection Operation (LASSO) is useful when the effects of many explanatory variables are sparse in a high-dimensional dataset. Influential points can have a disproportionate impact on the estimated values of model parameters. Here, this paper describes a new influence plot that can be used to increase understanding of the contributions of individual observations and the robustness of results. This can serve as a complement to other regression diagnostics techniques in the LASSO regression setting. Using this influence plot, we can find influential points and their impact on shrinkage of model parameters and model selection. Lastly, we provide two examples to illustrate the methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

SPRUCE Hollow Elevation Data for Experimental Plots Beginning in 2015

This data set provides hollow elevation data for the 17 SPRUCE experimental plots in the S1 bog on the Marcell Experimental Forest. Hollows were selected for measurement by walking along each octagonal boardwalk segment in a plot and identifying where a hollow intersected the boardwalk. The vertical distance between the surface of the boardwalk (with a known elevation) and the surface of the hollow was measured and the absolute elevation (in meters amsl) of the hollow surface was calculated. The hollow elevation measurements were carried out in October 2015, May 2016, October 2016, April 2017, and August 2018. These measurements will be repeated annually or more frequently.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Qualitative and quantitative estimation of comprehensive synaptic connectivity in short- and long-term cultured rat hippocampal neurons with new analytical methods inspired by Scatchard and Hill plots

To investigate comprehensive synaptic connectivity, we examined Ca{sup 2+} responses with quantitative electric current stimulation by indium-tin-oxide (ITO) glass electrode with transparent and high electro-conductivity. The number of neurons with Ca{sup 2+} responses was low during the application of stepwise increase of electric current in short-term cultured neurons (less than 17 days in-vitro (DIV)). The neurons cultured over 17 DIV showed two-type responses: S-shaped (sigmoid) and monotonous saturated responses, and Scatchard plots well illustrated the difference of these two responses. Furthermore, sigmoid like neural network responses over 17 DIV were altered to the monotonous saturated ones by the application of the mixture of AP5 and CNQX, specific blockers of NMDA and AMPA receptors, respectively. This alternation was also characterized by the change of Hill coefficients. These findings indicate that the neural network with sigmoid-like responses has strong synergetic or cooperative synaptic connectivity via excitatory glutamate synapses. - Highlights: • We succeed to evaluate the maturation of neural network by Scathard and Hill Plots. • Long-term cultured neurons showed two-type responses: sigmoid and monotonous. • The sigmoid-like increase indicates the cooperatevity of neural networks. • Excitatory glutamate synapses cause the cooperatevity of neural networks.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Pyrolysis reaction models of waste tires: Application of Master-Plots method for energy conversion via devolatilization

Highlights: • Pyrolysis kinetics of waste tire was studied. • Activation energy was obtained using model free methods. • Master Plots were used to predict pyrolysis reaction model. • Reaction model was in a good agreement with experimental data. - Abstract: Land applied disposal of waste tires has far-reaching environmental, economic, and human health consequences. Pyrolysis represents a potential waste management solution, whereby the solid carbonaceous residue is heated in the absence of oxygen to produce liquid and gaseous fuels, and a solid char. The design of an efficient conversion unit requires information on the reaction kinetics of pyrolysis. This work is the first to probe the appropriate reaction model of waste tire pyrolysis. The average activation energy of pyrolysis was determined via iso-conversional methods over a mass fraction conversion range between 0.20 and 0.80 to be 162.8 ± 23.2 kJ mol{sup −1}. Using the Master Plots method, a reaction order of three was found to be the most suitable model to describe the pyrolytic decomposition. This suggests that the chemical reactions themselves (cracking, depolymerization, etc.), not diffusion or boundary layer interactions common with carbonaceous biomasses, are the rate-limiting steps in the pyrolytic decomposition of waste tires.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗