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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Soil Environmental Conditions in the East River Watershed, CO

This dataset contains depth-resolved soil environmental variables collected between June 2016 and October 2018 from the Bradley Meadow site in the East River watershed. Datalogger output from 7 Campbell CS655 12 cm Soil Moisture and Temperature Sensors including depth, temperature, volumetric water content, and electrical conductivity are included in ‘BM_Merged_T_VWC_0616_10_18.csv’. Sensors were installed in June 2016. Data have been processed to merge raw sensor data and to remove additional variables. No additional QA/QC was performed. Measured pCO2 and depth are contained in ‘BM_EGM_WELL_CO2.csv’. These data represent gas well samples measured via injection using a PP Systems EGM-5 infra-red gas analyzer as described in the methods section. Measured CO2 surface flux values are contained in 'BM_EGM_Surface_Flux.csv'. These were measured using the PP Systems EGM-5 with the Soil Respiration Chamber attachment. Multiple reps are reported for each measurement including CO2 flux rate calculations using built-in linear and quadratic function methods, and average and standard deviations are taken across all reps and calculation methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Soil Water Retention and Hydraulic Conductivity Data and Model at Trail Creek in Taylor River Watershed, Colorado 2024-2025

This data package includes soil water retention and hydraulic conductivity data and model fitting results from measurements of ex-situ soil samples and in-situ soil sensors near Trail Creek. Soil water retention curves (SWRC) characterize soil water content as a function of soil water potential. SWRC depends on soil texture and pore structure and can be used to describe the constraints on biogeochemical processes in terms of soil water availability. In this data package, the sample identification follows the format TR-X-Y, where TR refers to Trail Creek, X is the treatment block identifier, and Y is the location identifier. Specifically, TR-ASCC1 is the control treatment block under the Adaptive Silviculture for Climate Change (ASCC) project, and TR-ASCC2 is the clear-cut treatment block. TR-ASCC-EHSn is associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and TR-ASCC-ERTn (upslope n=1) are ecohydrology sites along the electrical resistivity tomography transects. The sample and location information can be found in metadata.csv, and the data from the soil sensors will be included in a future data version when the observation period becomes sufficiently long for data analysis. Sampling and Measurements Each sample falls into one of the two sampling methods – (1) intact cores or (2) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. The intact cores were measured using the laboratory methods, which include measurements of soil water potential (HYPROP & WP4C, METER), saturated (KSAT, METER) and unsaturated hydraulic conductivity (HYPROP). The in-situ method uses a pair of co-located soil sensors to measure volumetric water content (TEROS12, METER) and soil water potential (TEROS21, METER), and the hydraulic conductivity was not measured. In comparison, the laboratory methods progress from full saturation to dry conditions, and the in-situ method includes both dry-to-wet and wet-to-dry cycles. The sampling and measurement methods for each sample can be found in metadata.csv, and more information about the measurements is detailed in the Methods section below. Models Retention and hydraulic conductivity data were fitted with four van-Genuchten-type models (specified by “model_name” column in the files): (1) traditional constrained van Genuchten model (“vG_constrained”), (2) traditional unconstrained van Genuchten model (“vG_unconstrained”), (3) PDI-variant of the constrained van Genuchten model (“vG_constrained_PDI”), and (4) PDI-variant of the unconstrained van Genuchten model (“vG_unconstrained_PDI”). The difference between the constrained (1: n) and the unconstrained (2: n, m) van Genuchten models is the number of pore-size distribution parameters in the model equations, giving the unconstrained model more degrees of freedom when fitting the data. Between the traditional and the PDI-variant models, model fitting differs the most at the dry end of the measurements. The traditional models allow infinite suction at the residual water content (water content does not drop below residual water content), and the PDI-variant models enforce a soil water potential value of pF=6.8 (~ -630 MPa) at oven-dryness (water content reaches 0). The inclusion of the van-Genuchten-type models is due to their common application. If other retention models are required, users can access the data in data.csv for further data fitting. More information about the models can be found in the Methods section below. Fitting Tasks The model fitting can be categorized into three levels of tasks (specified by “fitting_task” column in the files). Level 1 (“fit_retention”) only includes retention data fitting (the only level available for the in-situ method). Level 2 (“fit_retention_conductivity”) includes both retention and hydraulic conductivity data fitting, and the saturated hydraulic conductivity (Ks, a parameter of the hydraulic conductivity functions) is fixed by the measurements from KSAT. Level 3 (“fit_retention_conductivity_Ks”) also includes both retention and hydraulic conductivity data fitting, but Ks is a fitted parameter without the constraints from KSAT measurements. Among the same retention models (e.g. vG_constrained models of the same sample), level 1 should produce the best retention data fitting. Level 2 should have the highest misfit of the retention and hydraulic conductivity data, because the retention and hydraulic conductivity functions share common model parameters, and the unsaturated hydraulic conductivity (HYPROP) data fitting is subject to Ks measured independently by KSAT. Level 3 should have mid-level misfits of the retention and hydraulic conductivity data. While level 3 fits the hydraulic conductivity data better than level 2, the fitted Ks value might be unreasonable due to the lack of constraints at the wet end of the measurements. General recommendation when using this data package: (1) Choice of sampling methods: Intact cores might suffer from sample gaps that would lead to overestimation of Ks (sample gaps can be inferred from the “soil_sample_volume” column in metadata.csv when the value is < 249). In-situ method has higher uncertainty in characterizing the wet end of the SWRC because of sensor limitations and the difficulty in reaching full saturation under natural conditions. (2) Choice of fitting tasks: When only retention data is needed, level 1 (“fit_retention”) should be prioritized. When both retention and hydraulic conductivity data are needed, level 2 (“fit_retention_conductivity”) could be prioritized. (3) Choice of models: This could depend on what the downstream models call for. If no specific model is required, model misfit could be used as a ranking criterion. Model misfit values in terms of RMSE can be found in model_parameters.csv. The following files are included in this data package: (1) metadata.csv – This file includes the general information of each sample, including location (description, geocoordinates, elevation), sampling and measurements details (method, depth, time or period, volume, instruments), and soil physical properties (bulk density, saturated hydraulic conductivity, only applicable to physical soil samples). (2) data.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity data of each sample. Column “instrument” specifies the instrument (HYPROP, WP4C, or TEROS) used to perform the measurements. (3) model_fit.csv – This file includes soil water potential, volumetric water content, and unsaturated hydraulic conductivity fitted from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the variable does not apply to that fitting task. (4) model_parameters.csv – This file includes the fitted model parameters, model misfits, and conventional water content thresholds (field capacity and wilting point) from the four models and three fitting tasks. Column “model_name” specifies the retention model used, and “fitting_task” specifies the level of data fitting. Missing values indicate that the parameter does not apply to that model and/or that fitting task. (5) data_Ks.csv – This file includes the saturated hydraulic conductivity measurements from KSAT. (6) /figure/*.png – This folder includes three quick visualizations of the data, retention model fitting results and misfits, and hydraulic conductivity model fitting results, misfits, and parameters. The model fitting results are separated by samples and fitting tasks and colored by models. Zoom-in required. (7) /hyprop/*.bdhx – This folder includes proprietary hyprop files that require the free Labros SoilView-Analysis (METER) to open. Users can explore data fitting using other retention models (i.e. Brooks-Corey, Fredlund-Xing, Kosugi, bimodal models). Be aware that Ks value is pre-entered under “Fitting tab, Conductivity functions parameters” for level 2 fitting. If the value is lost, please refer to metadata.csv under “Ks” column. (8) Six file-level metadata that summarize file, header, column, and variable information of all files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > LAND SURFACE > SOILS↗
DOE OSTI2026

Reconstructing Quasar Spectra and Measuring the Lyα Forest with SpenderQ

Quasar spectra carry the imprint of foreground intergalactic medium (IGM) through absorption features. In particular, absorption caused by neutral hydrogen gas, the "Lyα forest," is a key spectroscopic tracer for cosmological analyses used to measure cosmic expansion and test physics beyond the standard model. Despite their importance, current methods for measuring Lyα absorption cannot directly derive the intrinsic quasar continuum and make strong assumptions on its shape, thus distorting the measured Lyα clustering. We present SpenderQ , a ML-based approach for directly reconstructing the intrinsic quasar spectra and measuring the Lyα forest from observations. SpenderQ uses the Spender spectrum autoencoder to learn a compact and redshift-invariant latent encoding of quasar spectra, combined with an iterative procedure to identify and mask absorption regions. To demonstrate its performance, we apply SpenderQ to 400,000 synthetic quasar spectra created to validate the Dark Energy Spectroscopic Instrument Year 1 Lyα cosmological analyses. SpenderQ accurately reconstructs the true intrinsic quasar spectra, including the broad Lyβ, Lyα, SiIV, CIV, and CIII emission lines. Redward of Lyα, SpenderQ provides percent-level reconstructions of the true quasar spectra. Blueward of Lyα, SpenderQ reconstructs the true spectra to < 5%. SpenderQ reproduces the shapes of individual quasar spectra more robustly than the current state-of-the-art. We, thus, expect it will significantly reduce biases in Lyα clustering measurements and enable studies of quasars and their physical properties. SpenderQ also provides informative latent variable encodings that can be used to, e.g., classify quasars with Broad Absorption Lines. Overall, SpenderQ provides a new data-driven approach for unbiased Lyα forest measurements in cosmological, quasar, and IGM studies.

Hahn, ChangHoon [Arizona U., Astron. Dept. - Stewa↗
DOE OSTI2026

spammR: an R package designed for analysis and integration of spatial multi-omic measurements

Spatial omics is a young and evolving field and as such shows rapid development of novel technologies and analysis methods to measure transcripts, proteins, metabolites, and post-translational modifications at high spatial resolution. These advances in technology have enabled the simultaneous generation of abundance profiles for multiple different omics types and associated microscopy imaging data, as well as their analysis in a spatial context. However, most analytical tools are designed for spatial transcriptomics platforms and are challenging to use in other contexts such as mass spectrometry-based measurements or metagenomics. To this end we present spammR (spatial analysis of multi-omics measurements in R), an R package that enables end-to-end analysis with a specific focus on mass-spectrometry derived spatial omics datasets with (1) smaller sample sizes and spatial sparsity of samples, (2) considerable missingness, and (3) no a-priori knowledge about proteins or genes of interest, relying on a fully data-driven approach.

spammR↗
DOE OSTI2023

Data associated with “Different methods of estimating riverbed sediment grain size diverge at the basin scale ” (v2)

This data package is associated with the publication “Different methods of estimating riverbed sediment grain size diverge at the basin scale” published in Frontiers in Earth Science (Regier et al., 2025). The distribution of sediment grain size in streams and rivers is often quantified by the median grain size (d50), a key metric for understanding and predicting hydrologic and biogeochemical function of streams and rivers. Manual methods to measure d50 are time-consuming and ignore larger grains, while model-based methods to estimate d50 often over-generalize basin characteristics, and therefore cannot accurately represent site-scale heterogeneity. Here, we apply a machine learning-enabled photogrammetry methodology (You Only Look Once, or YOLO) for estimating d50 for grains > 2 mm based on images collected from streams and rivers throughout the Yakima River Basin (YRB). To understand how such methods may help bridge the gaps in resolution and accuracy between manual and catchment characteristics model-based d50 estimates, we compared YOLO d50 values to manual and model-based estimates across the YRB. We found distinct differences among methods for d50 averages and variability, and relationships between d50 estimates and basin characteristics. Source images can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1892052. This data package was originally published in May 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. In addition to the readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; (4) and subfolders containing data, figures, and scripts. The data folder contains datasets used for the analyses in the manuscript in image, text-delimited or geospatially-referenced formats. The figures folder contains the figures from the manuscript in different formats. The scripts folder contains all of the scripts used to complete the analyses in the manuscript. All files are .csv, .rds, .dbf, .prj, .shp, .shx, .jpg, .png, .R, .Rproj, or .pdf. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

In situ mechanical characterization of a single cell-cell adhesion interface under large strain

A method of measuring a stress-strain curve in a cell-cell adhesion interface, the method including: providing a structure including a first movable island supported by a first beam, a second movable island supported by a second beam, and a gap therebetween connected by a pair of cells forming a junction, the pair of cells comprising a cell-cell adhesion interface having an initial length defined by a distance between nuclei of the pair of cells; moving the second movable island with a defined displacement; determining a displacement of the first movable island based on moving the second movable island; calculating a difference between the displacement of the first movable island and the defined displacement of the second movable island based on moving the second movable island; determining an applied strain in the cell-cell adhesion interface between the pair of cells based on the difference divided by the initial length of the cell-cell adhesion interface; calculating a force between the cell-cell adhesion interface of the pair of cells based on the displacement of the first movable island; calculating a stress in the cell-cell adhesion interface between the pair of cells based on the force; and determining the stress-strain curve of the cell-cell adhesion interface between the pair of cells by plotting the calculated stress against the applied strain.

Yang, Ruiguo↗
DOE OSTI2020

Non-contact velocity measurement instruments and systems, and related methods

Methods for calibration of non-contact velocity measurements and systems for implementing the same are described. Generally, the method comprises inducing a shock wave into a sample at a stress intensity that varies across the sample's elastic limit, which corresponds to the elastic-plastic state transition of the sample. That transition state may be at the sample's Hugoniot elastic limit. The velocity of the sample is measured using a non-contact velocity measurement instrument such as a velocimeter. The measurement may be compared to a predicted velocity or a velocity measurement made by another system to determine calibration parameters.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Measuring Relative Energies of Ligand Binding Conformations on Nanocluster Surfaces with Temperature-Dependent FTIR Spectroscopy

We present a method to measure relative energies between binding conformations of carboxylate ligands on InP magic-sized clusters in solution. Using Markov chain Monte Carlo global fitting analysis on temperature-dependent vibrational spectra of cluster-bound ligands, we observe significantly different relative energies between various bidentate and monodentate binding motifs. Relative to the monodentate motif, the chelating conformation is 0.7 ± 0.3 kcal/mol more stable and the syn–syn bridging conformation is 1.1 ± 0.5 kcal/mol more stable, but the syn–anti bridging conformation exhibits no significant difference. Our results demonstrate that the relative energy between monodentate-bound carboxylates and unbound carboxylic acids is 4.52 ± 0.05 kcal/mol, or 1582 ± 19 cm –1 , nearly identical to the carboxylate asymmetric stretching frequency. Here, we suggest that the ligand vibrational energy may play a key role in ligand dissociation by compensating for energy differences between bound and dissociated ligand states. This approach gives important experimental insights into ligand binding and can inform future nanocrystal surface engineering.

Conformation↗
DOE OSTI2023

$S$ Hmax orientation in the Alpine region from observations of stress-induced anisotropy of nonlinear elasticity

The orientation of $S$ Hmax is commonly estimated from in situ borehole breakouts and earthquake focal mechanisms. Borehole measurements are expensive, and therefore sparse, and earthquake measurements can only be made in regions with many well-characterized earthquakes. Here, we derive the stress-field orientation using stress-induced anisotropy in nonlinear elasticity. In this method, we measure the strain derivative of velocity as a function of azimuth. We use a natural pump-probe (NPP) approach which consists of measuring elastic wave speed using empirical Green’s functions (probe) at different points of the earth tidal strain cycle (pump). The approach is validated using a larger data set in the Northern Alpine Foreland region where the orientation of maximum horizontal compressive stress is known from borehole breakouts and drilling-induced fractures. The technique resolves NNW-SSW to N-S directed $S$ Hmax which is in good agreement with conventional methods and the recent crustal stress model. We confirm that the NPP method can be applied to dense large-scale seismic arrays. The technique is then applied to the Southern Alps to understand the contemporary stress pattern associated with the ongoing deformation due to counterclockwise rotation of the Adriatic plate with respect to the European plate. Our results explain why the two major faults in Northeastern Italy, the Giudicarie Fault and the Periadriatic Line (Pustertal–Gailtal Fault) are currently inactive, while the currently acting stress field allows faults in Slovenia to deform actively. We have demonstrated that the pump-probe method has the potential to fill in the measurement gap left by conventional approaches, both in terms of regional coverage and in depth.

58 GEOSCIENCES↗
DOE OSTI2021

Critical and Californium Source-Driven Noise Analysis Subcritical Measurements with an Unreflected Cylindrical Tank of Mixed Uranium-Plutonium Nitrate Solution

The reported experiments were performed by Oak Ridge National Laboratory (ORNL) at the Battelle Northwest Laboratory’s (now Pacific Northwest National Laboratory) critical experiments facility at Hanford, Washington in 1981 and used 16 days of critical facility time, not including 10 days for setup and removal of ORNL equipment. These measurements were to assess the capability of the Cf source-driven noise analysis (CSDNA) method to measure the subcriticality (keff) of mixed U-Pu nitrate solutions. In addition to the CSNDA measurements, measurements were also performed near delayed criticality where CSDNA measurements cannot be performed. This report documents the experiments that were not reported at that time by presenting the ORNL experimental results and any online analysis performed during and shortly after the measurements. The mixed nitrate solution had a U concentration at 188 grams per liter (g/L), a Pu concentration of 280 g/L, free acid normality of 2.80, H ion molarity of 5.9 and a specific gravity of 1.754 g/cm 3 , a 240 Pu isotopic content of 7.981 wt. %, and a 235 U isotopic content of 0.724 wt. %. The stainless-steel tank for the solution had an inside diameter of 35.38 cm, an outside diameter of 35.53 cm, a height of 56.72 cm, and bottom thickness of 0.9525 cm. A Zircaloy pipe with a 3.1496 cm outside diameter, a 2.7788 cm inside diameter, and bottom thickness of 0.635 cm was available for insertion of the Cf source in the center of the fissile solution. The Cf source was also located at the outside surface of the tank (solution height varied from 10 to 53 cm) and in the center of the solution (solution height varied from 10 to 60.7 cm). The CSDNA measurements were not analyzed online to determine the subcritical neutron multiplication factors. At all subcritical states, the break frequency noise analysis data was fitted to obtain the prompt neutron decay constant. The neutron multiplication factors were determined for the two configurations of the measurements near delayed criticality. The subcritical neutron multiplication factors from the CNSDA measurements can be obtained with further analysis. However, the near delayed critical configuration, the prompt neutron decay constants, the count rates, and the measured cross and auto power spectral densities can be calculated directly for benchmarking. Much of data presented in this report are from ORNL notes—not in the ORNL logbooks. For the final benchmark analysis, the data from the Battelle Northwest Laboratory (which operated the critical facility in 1981) critical facility logbook should be consulted and be incorporated where appropriate. The purpose of this report is to document the experimental information for the measurements performed so that at a later date researchers could perform the required uncertainty and calculational analyses and documentation to use these data for an International Criticality Safety Benchmark Program (ICSBEP) or Nuclear Energy Agency benchmark. The data from these measurements are available from the ORNL Records Management Services Department, and the logbook is available from ICSBEP at Idaho National Laboratory. Preparation of the present report is part of a larger cooperative effort between Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) to document more than 15 undocumented critical and subcritical experiments enumerated in ORNL/TM-2019/18 and performed by ORNL at ORCEF and other USDOE critical experiments facilities using more than 500 operational days of critical facility time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Robust In-Situ Strain Measurements to Monitor CO 2 Storage

The goal of this project was to develop and demonstrate robust instrumentation to monitor the in-situ strain tensor in order to improve the reliability and security of CO 2 storage in geologic formations. We met the original goals of the project and the major overarching accomplishment is the advancement of strain tensor monitoring from an intriguing concept to a commercially available technology with a solid foundation of novel instruments supported by theoretical analyses and validation experiments. The main accomplishments of the project are summarized below. We designed, built and evaluated nine new optical fiber strainmeters and tiltmeters using Michelson interferometers to measure deformation with ultra-high resolution at both shallow and deep point locations in the subsurface. These are the robust strainmeters that motivated the title of the project. We designed, built and evaluated a novel method of measuring distributed strain in optical fibers with nanostrain resolution, and cm-scale location, and sampling into the seismic band. The new method is called Coherence-length-gated Microwave Photonics Interfereometry (CMPI). CMPI technology has advantages over existing commercial DAS and DSS methods. We developed and demonstrated capabilities to deploy instruments in the field and used them to measure strain caused by ambient signals like barometric pressure and tides, as well as induced signals like surface loading and pore pressure changes from pumping tests. We deployed a working strainmeter at 1,700 ft depth, slightly above an active reservoir. This is to our knowledge the greatest depth a strainmeter has been deployed and the techniques we used can readily be extended to greater depths. Optical fiber borehole tensor strainmeter techology was advanced from a TRL 4 at the start, to a TRL of 7 at the conclusion of the project. The project included advances in simulations and theoretical analyses. We developed and demonstrated a computational workflow that uses machine learning to reduce the computational requirements and make it practical to use Bayesian inversion to solve large numerical poroelastic analyses needed to interpret strain tensor field data. We evaluated the strain tensor fields and time series that would be caused by leaks of CO 2 or other fluids from reservoirs. These simulations demonstrated that signals from leaks could be measured with instruments developed for the project, opening a potentially new method for ensuring storage security. We showed that strains in caprock can be used to estimate pressure in a reservoir. This avoids the need to drill monitoring wells into the reservoir, and it expands the capabilities of monitoring in the caprock. The project includes a derivation and application of a novel analytical solution to the strains in the vicinity of a pressurized poroelastic inclusion. This solution explains field data measured during injeciton tests at the North Avant Field, and it will simplify future interpretation of strain tensor data. The project included a broad range of experiments, and of the most significant is the characterization of the strain tensor at an array three strainmeters during six injection tests at the North Avant Field, Oklahoma. This demonstrated repeatability of the strain signal measured by the new instruments developed for the project, and it showed similarities between the strain signal at shallow depths and pressure in the underlying reservoir. We also demonstrated that useful strain data can be measured at reservoir depths. This confirms that strain tensor data can be measured throughout the caprock over a reservoir. The project demonstrated the feasibility of using the strain tensor and distributed strain measured in caprock during a variety of different well tests where the pumping rate was constant, sinusoidal and positive, or a periodic square wave with zero net rate. This further strengthens the validity of using strain data to characterize reservoirs and aquifers. We also demonstrated that strain caused be fluctuations of air pressure and water pressure in the vadose zone can be measured and interpreted, suggesting that high resolution distributed strain measurements hold promise for monitoring the vadose zone. The project partially supported nine graduate students in the Environmental Engineering, Hydrogeology, Electrical Engineering programs at Clemson University. The research was described in nine journal papers, 23 talks and conference abstracts. Additional journal papers are in preparation. A new company called Tensora was started to provide strainmeter technology for commercial applications.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Apparatus and method for dynamic acousto-elasticity technique measurements at simulated subsurface pressures

An apparatus (10) and method for performing nonlinear elasticity measurements using the dynamic acousto-elasticity technique (DAET) at simulated subsurface conditions in the laboratory, are described. The current state-of-the-art for measuring nonlinear elasticity parameters using DAET is limited to ambient pressure conditions on the bench-top. The present invention permits nonlinear parameter measurements at controlled sample internal fluid pore pressures (52) and external confining stress (44), (50) conditions.

Roberts, Peter M.↗
DOE OSTI2021

Topological Effects Near Order–Disorder Transitions in Symmetric Diblock Copolymer Melts

The effects of polymer chain topology on the order–disorder transition of symmetric AB diblock copolymer melts are studied using coarse-grained molecular dynamics simulations. Specifically, we compared chain conformations near the lamellar-disordered transition in melts of symmetric (i.e., 50–50) AB diblock copolymers of linear chains, rings, and trefoil knots at the same chain lengths. The order (lamellar)–disorder transition temperature and the domain sizes both shifted to lower values with the introduction of topological constraints, leading to the following sequence: linear chains > rings > trefoil knots. Furthermore, investigation of the polymer chain conformations in terms of their radii of gyration, their writhe values (a measure for the degree of intertwining of a chain around itself), and their Jones polynomials (a method to measure entanglement of curves) showed that linear chains and rings remained stretched, while knots were stretched and tightened in disordered melts close to the lamellar-disorder transition. This work highlights chain topology as an important factor in affecting microphase separation in block copolymers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Wavelength modulation laser-induced fluorescence for plasma characterization

Laser-Induced Fluorescence (LIF) spectroscopy is an essential tool for probing ion and atom velocity distribution functions (VDFs) in complex plasmas. VDFs carry information about the kinetic properties of species that is critical for plasma characterization. Accurate interpretation of these functions is challenging due to factors such as multicomponent distributions, broadening effects, and background emissions. Our research investigates the use of Wavelength Modulation (WM) LIF to enhance the sensitivity of VDF measurements. Unlike standard Amplitude Modulation (AM) methods, WM–LIF measures the derivative of the LIF signal. This approach makes variations in VDF shape more pronounced. VDF measurements with WM–LIF were investigated with both numerical modeling and experimental measurements. The developed model enables the generation of both WM and AM signals, facilitating comparative analysis of fitting outcomes. Experiments were conducted in a weakly collisional argon plasma with magnetized electrons and non-magnetized ions. Measurements of the argon ion VDFs employed a narrow-band tunable diode laser, which scanned the 4p 4 D 7/2 –3d 4 F 9/2 transition centered at 664.553 nm in vacuum. A lock-in amplifier detected the second harmonic WM signal, which was generated by modulating the laser wavelength with an externally controlled piezo-driven mirror of the diode laser. Finally, our findings indicate that the WM–LIF signal is more sensitive to fitting parameters, allowing for better identification of VDF parameters such as the number of distribution components, their temperatures, and velocities. In addition, WM–LIF can serve as an independent method to verify AM measurements and is particularly beneficial in environments with substantial light noise or background emissions, such as those involving thermionic cathodes and reflective surfaces.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Measuring the maximum capacity and thermal resistances in phase-change thermal storage devices

Thermal energy storage can increase the efficiency of the electric grid by adding flexibility to thermal systems. The value of thermal storage is a function of its energy and power density, which are driven by the capacity and thermal resistances in the storage device. Measuring these properties in-situ at the device level is an important step to understanding the performance and improving the design of thermal storage systems. Here, we present methods to measure the total capacity and thermal resistances in heat exchangers with integrated phase change materials. These methods are demonstrated on two thermal storage devices - a 570-kWh ice-based storage tank and a 0.35-kWh graphite-tetradecane composite device. The results show how thermal resistances evolve with the state of charge and discharge rate in these devices and quantify the impact of applied pressure on the contact resistance in composite phase change material heat exchangers. The proposed method allows for easy comparison between different systems and provides information on the thermal bottlenecks limiting performance. Ultimately, these measurements will allow designers to make robust, high-performance thermal storage devices for next-generation thermal systems.

25 ENERGY STORAGE↗
DOE OSTI2022

A discussion on various experimental methods of impact ionization coefficient measurement in GaN

Impact ionization coefficients play a critical role in semiconductors. In addition to silicon, silicon carbide and gallium nitride are important semiconductors that are being seen more as mainstream semiconductor technologies. As a reflection of the maturity of these semiconductors, predictive modeling has become essential to device and circuit designers, and impact ionization coefficients play a key role here. Recently, several studies have measured impact ionization coefficients. We dedicated the first part of our study to comparing three experimental methods to estimate impact ionization coefficients in GaN, which are all based on photomultiplication but feature characteristic differences. The first method inserts an InGaN hole-injection layer, the accuracy of which is challenged by the dominance of ionization in InGaN, leading to possible overestimation of the coefficients. The second method utilizes the Franz–Keldysh effect for hole injection but not for electrons, where the mixed injection of induced carriers would require a margin of error. The third method uses complementary p–n and n–p structures that have been at the basis of this estimation in Si and SiC and leans on the assumption of a constant electric field, and any deviation would require a margin of error. In the second part of our study, we evaluated the models using recent experimental data from diodes demonstrating avalanche breakdown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Direct measurement and calculation of rubber bulk modulus by piston-cylinder method using conventional mechanical testing equipment

This article describes a method to directly measure the bulk modulus of rubber using a piston-cylinder type apparatus. The function of the testing apparatus is to reliably transfer load to the water inside the vessel and allow for the accurate and continuous measurement of volumetric displacement as the contents are compressed. During the test, load is applied to a piston-cylinder containing the rubber test sample and water using a conventional mechanical testing load frame. Load and the travel of the piston are recorded by a load cell and extensometer, respectfully. A brass or stainless steel plug of the same dimensions as the test sample is tested as a control sample to isolate the compliance of the system, including the compressibility of water and compliance of the piston-cylinder. The results from this control test are used to disincorporate the compliance of the system from the sample test results. Load-linear displacement data are mathematically converted to pressure-volumetric displacement data, from which bulk modulus is calculated. The test apparatus and method are validated using the known bulk modulus of water. Finally, the bulk modulus for two similar rubbers is evaluated. The validity of the results and limitations of the device are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Studies of optical and chemical properties of aged and fresh biomass burning absorbing aerosols for climate models

Particulate emissions from burning fuels from sub-Saharan Africa is currently poorly characterized. With increasing population and industrialization, emissions are expected to grow. Optical methods for measuring light absorption in the ultraviolet (UV) and visible (vis) regions of the spectrum are crucial for understanding the optical properties of BB aerosols (Bond and Bergstrom, 2006; Lack and Cappa, 2010; Moschos et al., 2021). One such instrument is the dual-spot AE33 model aethalometer is a common filter-based instrument that can be used to measure aerosol absorption properties (Hansen et al., 1984). This instrument has many figures of merit; however, the method's limitations include potential biases from scattering within the filter material, multiple scattering effects of the particles, filter loading (i.e. particle shadowing), and the need for wavelength-specific correction factors (Cλ), which depend on accurate intercomparison with other in situ techniques (Bond et al., 1999; Collaud Coen et al., 2010). This work aims to: 1. Optically characterize BB aerosol generated from African fuel 2. Correct the aethalometer at multiple wavelengths 3. Parametrize these correction factors. 4. Combusting the same fuels with two difference tube furnace systems assess the general applicability of this flexible means of producing BB aerosol. This was accomplished by conducting laboratory studies at Los Alamos National Laboratory (LANL) and North Carolina A&T State University (NCA&T), where aethalometer measurements were compared to in situ optical measurements. Mass cross sections of BB aerosol from these under-studied fuels will be determined along with their wavelength dependence.

09 BIOMASS FUELS↗