Search NASA⌕ Search

SEARCH · Search NASA

Results for “Core characterization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Multifrequency observations of the flaring quasar 1156+295

A report is presented on the optically violent variable quasar 1156+295, known also as 4C 29.45 and Ton 599. A large outburst of this quasar was discovered in April 1981 in the course of a program to obtain simultaneous multifrequency spectra of variable quasars. Ultraviolet observations taken with the International Ultraviolet Explorer satellite were coordinated with ground-based observations at radio, infrared, and optical wavelengths. Measurements were made at four epochs starting immediately after the outburst was discovered, when the B-magnitude was 14.0, and at intervals of 4 days, 60 days and 1 year. The luminosity integrated only over observed wavelength bands was approximately 3 x 10 to the 48th ergs/sec on the first epoch of observation. Modeling of the source with a synchrotron self-Compton model suggests that the core of the source has a linear dimension of 0.01 pc, a magnetic field strength in the range 0.1-30 gauss, and a bulk relativistic motion in the quasar rest frame characterized by a Lorentz factor in the range 2-8.

Glassgold, A. E.↗
NASA NTRS1989

Titanium carbide and titania phases on Antarctic ice particles of probable extraterrrestrial origin

Two unique titania-rich particles, found within ancient Antarctic ice have been discovered and characterized, and are believed to be of extraterrestrial origin. Both particles contain abundant submicron-sized crystals of Magneli phases (Ti(n)O(2n-1). In addition, one particle contains a core of TiC. Whereas the Magneli phases would have been stable in the early solar nebula, and so probably formed there, the TiC is more likely to have condensed in the cool, dusty, carbon-rich outer shell of a red giant star. It is suggested that both particles are interplanetary dust particles whose Magneli phases carry a record of the PO2-T conditions of the early solar nebula. It is further suggested that the TiC grain in particle 705 is remnant interstellar dust.

Zolensky, M. E.↗
NASA NTRS1993

The giant impact produced a precipitated Moon

The author's current simulations of Giant Impacts on the protoearth show the development of large hot rock vapor atmospheres. The Balbus-Hawley mechanism will pump mass and angular momentum outwards in the equatorial plane; upon cooling and expansion the rock vapor will condense refractory material beyond the Roche distance, where it is available for lunar formation. During the last seven years, the author together with several colleagues has carried out a series of numerical investigations of the Giant Impact theory for the origin of the Moon. These involved three-dimensional simulations of the impact and its aftermath using Smooth Particle Hydrodynamics (SPH), in which the matter in the system is divided into discrete particles whose motions and internal energies are determined as a result of the imposed initial conditions. Densities and pressures are determined from the combined overlaps of the particles, which have a bell-shaped density distribution characterized by a smoothing length. In the original series of runs all particle masses and smoothing lengths had the same values; the matter in the colliding bodies consisted of initial iron cores and rock (dunite) mantles. Each of 41 runs used 3,008 particles, took several weeks of continuous computation, and gave fairly good representations of the ultimate state of the post-collision body or bodies but at best crude and qualitative information about individual particles in orbit. During the last two years an improved SPH program was used in which the masses and smoothing lengths of the particles are variable, and the intent of the current series of computations is to investigate the behavior of the matter exterior to the main parts of the body or bodies subsequent to the collisions. These runs are taking times comparable to a year of continuous computation in each case; they use 10,000 particles with 5,000 particles in the target and 5,000 in the impactor, and the particles thus have variable masses and smoothing lengths (the latter are dynamically adjusted so that a particle typically overlaps a few tens of its neighbors). Since the matter in the impactor provides the majority of the mass left in orbit after the collision, and since the masses of the particles that originated in the impactor are smaller than those in the target, the mass resolution in the exterior parts of the problem is greatly improved and the exterior particles properly simulate atmospheres in hydrostatic equilibrium.

Cameron, A. G. W.↗
NASA NTRS1991

Optical fiber sensors for materials and structures characterization

The final technical report on Optical Fiber Sensors for Materials and Structures Characterization, covering the period August 1990 through August 1991 is presented. Research programs in the following technical areas are described; sapphire optical fiber sensors; vibration analysis using two-mode elliptical core fibers and sensors; extrinsic Fabry-Perot interferometer development; and coatings for fluorescent-based sensor. Research progress in each of these areas was substantial, as evidenced by the technical publications which are included as appendices.

Lindner, D. K.↗
NASA NTRS2003

A Gravity-Responsive Time-Keeping Protein of the Plant and Animal Cell Surface

The hypothesis under investigation was that a ubiquinol (NADH) oxidase protein of the cell surface with protein disulfide-thiol interchange activity (= NOX protein) is a plant and animal time-keeping ultradian (period of less than 24 h) driver of both cell enlargement and the biological clock that responds to gravity. Despite considerable work in a large number of laboratories spanning several decades, this is, to my knowledge, our work is the first demonstration of a time-keeping biochemical reaction that is both gravity-responsive and growth-related and that has been shown to determine circadian periodicity. As such, the NOX protein may represent both the long-sought biological gravity receptor and the core oscillator of the cellular biological clock. Completed studies have resulted in 12 publications and two issued NASA-owned patents of the clock activity. The gravity response and autoentrainment were characterized in cultured mammalian cells and in two plant systems together with entrainment by light and small molecules (melatonin). The molecular basis of the oscillatory behavior was investigated using spectroscopic methods (Fourier transform infrared and circular dichroism) and high resolution electron microscopy. We have also applied these findings to an understanding of the response to hypergravity. Statistical methods for analysis of time series phenomena were developed (Foster et al., 2003).

Morre, D. James↗
NASA NTRS1991

Regulation of phytochrome message abundance in root caps of maize

In many cultivars of maize (Zea mays L.) red light affects root development via the photomorphogenetic pigment phytochrome. The site of perception for the light is the root cap. In the maize cultivar Merit, we investigated phytochrome-mediated events in the cap. We established that the message encoded by the phyA1 gene was most abundant in dark-grown tissue and was asymmetrically distributed in the root cap, with greatest expression in the cells which make up the central columella core of the cap. Phytochrome message was negatively autoregulated in a specific region within the root cap. This autoregulation was sensitive to very-low-fluence red light, and thus was characterized as a phytochrome-mediated, very-low-fluence event. The kinetics of message reaccumulation in the dark were also examined and compared to the kinetics of the light requirement for root gravitropism in this cultivar. Similarly, the degree of autoregulation present in two other maize cultivars with different light requirements for gravitropic sensitivity was investigated. It appears that the Merit cultivar expresses a condition of hypersensitivity to phytochrome-mediated light regulation in root tissues. We conclude that phytochrome regulates many activities within the cap, but the degree to which these activities share common phytochrome-mediated steps is not known.

NASA Discipline Plant Biology↗
NASA NTRS2013

Single-Event Transient Testing of Low Dropout PNP Series Linear Voltage Regulators

As demand for high-speed, on-board, digital-processing integrated circuits on spacecraft increases (field-programmable gate arrays and digital signal processors in particular), the need for the next generation point-of-load (POL) regulator becomes a prominent design issue. Shrinking process nodes have resulted in core rails dropping to values close to 1.0 V, drastically reducing margin to standard switching converters or regulators that power digital ICs. The goal of this task is to perform SET characterization of several commercial POL converters, and provide a discussion of the impact of these results to state-of-the-art digital processing IC through laser and heavy ion testing

Adell, Philippe↗
NASA NTRS2015

Failure Predictions of Out-of-Autoclave Sandwich Joints with Delaminations Under Flexure Loads

An analysis and a test program was conducted to investigate the damage tolerance of composite sandwich joints. The joints contained a single circular delamination between the face-sheet and the doubler. The coupons were fabricated through out-of-autoclave (OOA) processes, a technology NASA is investigating for joining large composite sections. The four-point bend flexure test was used to induce compression loading into the side of the joint where the delamination was placed. The compression side was chosen since it tends to be one of the most critical loads in launch vehicles. Autoclave cure was used to manufacture the composite sandwich sections, while the doubler was co-bonded onto the sandwich face-sheet using an OOA process after sandwich panels were cured. A building block approach was adopted to characterize the mechanical properties of the joint material, including the fracture toughness between the doubler and face-sheet. Twelve four-point-bend samples were tested, six in the sandwich core ribbon orientation and six in sandwich core cross-ribbon direction. Analysis predicted failure initiation and propagation at the pre-delaminated location, consistent with experimental observations. Fracture analyses methods predicted failure loads in close agreement with tests. This investigation demonstrated a strength reduction of 10 percent due to a flaw of significant size compared to the width of the sample. Therefore, concerns of bonding an OOA material to an in-autoclave material was mitigated for the geometries, materials, and load configurations considered.

Tolerance↗
NASA NTRS2015

Failure Predictions of Out-of-Autoclave Sandwich Joints with Delaminations Under Flexure Loads

An analysis and a test program was conducted to investigate the damage tolerance of composite sandwich joints. The joints contained a single circular delamination between the face-sheet and the doubler. The coupons were fabricated through out-of-autoclave (OOA) processes, a technology NASA is investigating for joining large composite sections. The four-point bend flexure test was used to induce compression loading into the side of the joint where the delamination was placed. The compression side was chosen since it tends to be one of the most critical loads in launch vehicles. Autoclave cure was used to manufacture the composite sandwich sections, while the doubler was co-bonded onto the sandwich face-sheet using an OOA process after sandwich panels were cured. A building block approach was adopted to characterize the mechanical properties of the joint material, including the fracture toughness between the doubler and face-sheet. Twelve four-point-bend samples were tested, six in the sandwich core ribbon orientation and six in sandwich core cross-ribbon direction. Analysis predicted failure initiation and propagation at the pre-delaminated location, consistent with experimental observations. A building block approach using fracture analyses methods predicted failure loads in close agreement with tests. This investigation demonstrated a small strength reduction due to a flaw of significant size compared to the width of the sample. Therefore, concerns of bonding an OOA material to an in-autoclave material was mitigated for the geometries, materials, and load configurations considered.

Tolerance↗
NASA NTRS2013

Single-event transient testing of low dropout PNP series linear voltage regulators

As demand for high-speed, on-board, digital-processing integrated circuits on spacecraft increases (field-programmable gate arrays and digital signal processors in particular), the need for the next generation point-of-load (POL) regulator becomes a prominent design issue. Shrinking process nodes have resulted in core rails dropping to values close to 1.0 V, drastically reducing margin to standard switching converters or regulators that power digital ICs. The goal of this task is to perform SET characterization of several commercial POL converters, and provide a discussion of the impact of these results to state-of-the-art digital processing IC through laser and heavy ion testing

Allen, Gregory↗
NASA NTRSDate not supplied

Design, Instrumentation, and Data Analysis for the SLS Core Stage Green Run Test Series

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of eight mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. The actuators are powered by a Shuttle-derived hydraulic Core Auxiliary Power Unit (CAPU), and integrated with an all-new Core Stage thrust structure. The actuators are interfaced to the SLS Vehicle Management (VM) software via an all-new TVC Actuator Control (TAC) avionics subsystem. Despite the significant test and flight experience of the Shuttle hardware, the SLS Green Run ambient and hot fire test activities revealed a number of new findings associated with the dynamic response of the TVC integrated system. Test responses suggested that the TVC system did not meet its performance specifications and its step and frequency responses exhibited unexpected departures from prior lab tests and modeled behavior. This paper is the fifth installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. In this paper, the design of the TVC analyses conducted during the Core Stage Green Run test series are discussed in detail. Throughout the course of the test activities, the SLS flight control team worked diligently with the Core Stage contractor to revise test command profiles and ensure sufficient instrumentation was available to collect data. Post-test analysis combined the Green Run modal, ambient, and hot fire test data, MSFC 2- axis Core Stage TVC Inertial Load Simulator (ILS) data, Hardware-In-the-Loop (HWIL) Systems Integration Lab (SIL) results, and actuator Acceptance Testing Procedure (ATP) responses. These data were used to characterize the response, validate critical math models of the TVC subsystem, and isolate the probable cause of the unexpected responses. Through comprehensive analysis of the available test data sources, the integrated team identified the dominant contributors to the observed response and developed test-correlated rationale for vehicle flight control system performance, ultimately leading to a confident posture for the Artemis I mission.

John H. Wall↗
NASA NTRS2022

Juno Gravity Science: Five Years of Radio Science Operations with Ka-band Uplink

Since entering orbit on July 4, 2016, the Juno spacecraft has executed 34 closest approach passes of Jupiter, completing the prime mission. During each closest approach, called perijove, the spacecraft comes within 4,000 km of the cloud tops and the motion of the spacecraft becomes perturbed by the gravitational field of Jupiter. These small changes in the motion of the spacecraft are detected using the Juno Gravity Science Instrument by measuring the Doppler shift of the radio link between the Juno spacecraft and NASA’s Deep Space Network (DSN). During a majority of these closest approach passes, the 34-meter DSS-25 antenna transmits simultaneous X-band and Ka-band uplink to the spacecraft. Juno’s onboard X-band transponder and Ka-band translator phase-coherently return the signals back to Earth for reception at the same DSS-25 antenna. The precise frequency of these signals is measured by processing open-loop recordings of the signal. These measurements, characterized by ~5-10 micron/sec accuracies (after calibration of charged particle noise and Earth troposphere), have probed the gravity field of Jupiter to unprecedented precision, allowing for discoveries of Jupiter’s core size and depth of the zonal winds. Successful operations of the instrument during perijoves requires careful planning and coordination between DSN engineers, the Juno project, and the Juno science team. This work discusses the operations of the Juno Gravity Science Instrument after five years of prime mission operations. Lessons learned are documented to be applied to future missions and the Juno extended mission. Although the Juno extended mission formally started on August 1, 2021, on June 7, 2021, the trajectory was modified with a flyby of Ganymede, the third Galilean moon of Jupiter. Gravity and radio science investigations of Jupiter and its moons will continue to play a key role in Juno’s objectives during the extended mission.

Oudrhiri, Kamal↗
NASA NTRS1995

Dense gas in high-latitude molecular clouds

The nearby molecular clouds MBM 7, 12, 30, 32, 40, 41, and 55 were surveyed for tracers of dense gas, including the (1-0), (2-1), and (3-2) rotational lines of CS and the (1-0) lines of HCO(+) and HCN. MBM 7 and MBM 12 contain dense cores, while the other clouds contain little or no traces of dense gas. Comparison of the emission from dense gas tracers to that of (13)CO reveals that the former are more compact in angular size as well as line width. An extensive CS(2-1) survey of part of MBM 12 reveals that the emission is characterized by clumps on approximately 3 min scales as well as extended emission. Observations of the CS(1-0) and (3-2) lines using telescopes with matched beam sizes reveal that the volume density must be at least approximately 10(exp 4.5)/cc within the (3-2) emitting regions, which are approximately 0.03 pc in radius. Electron excitation of the CS rotational levels is ruled out (in the cores) by comparing the (3-2)/(1-0) line ratios with models including H2 and electron collisions. The volume density in the cores is substantially larger than in the portions of the cloud traced by CO emission. The density increases into the cores as r(exp -2), suggesting dynamical collapse. The masses of the cores are close to the virial mass, suggesting they are dynamically bound. The cores in MBM 7 and MBM 12 are thus likely to form stars; they are the nearest sites of star formation.

Reach, William T.↗
DOE OSTI2026

Soil Water Retention and Hydraulic Conductivity Data and Model at Pump House in East River Watershed, Colorado 2019-2024

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 Pump House at Mount Crested Butte in the East River Watershed. 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 ER-X-Y, where ER refers to East River, X is the location identifier, and Y is the depth identifier at the same X (shallow Y=1). Specifically, ER-PHS, ER-LMC, ER-LMF, and ER-SMN are associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and ER-RBTn (upslope n=1) are sampling transects during the 2019 Rootball Campaign. The sample and location information can be found in metadata.csv. Sampling and Measurements Each sample falls into one of the three sampling methods – (1) intact cores, (2) repacked samples, or (3) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. Both intact cores and repacked samples 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 and in-situ soil sensors could be prioritized because these sampling methods are less destructive. While the repacked samples were packed to the target bulk density (estimated post-sampling, when sample volume was known), these samples had altered pore structures. Nevertheless, 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 also 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

Soil Water Retention and Hydraulic Conductivity Data and Model at Snodgrass Mountain in East River Watershed, Colorado 2020-2025

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 at Snodgrass Mountain. 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 SG-X-Y, where SG refers to Snodgrass Mountain, X is the location identifier, and Y is the depth identifier at the same X (shallow Y=1). Specifically, SG-EHS is associated with ecohydrology sites under the East-Taylor Watershed Community Observatory Sites directory, and SG-ERTn (upslope n=1) are points along the Snodgrass electrical resistivity tomography transect not associated with the existing site names in the directory. The sample and location information can be found in metadata.csv. Sampling and Measurements Each sample falls into one of the three sampling methods – (1) intact cores, (2) repacked samples, or (3) soil sensors – and one of the two measurement methods – (a) laboratory or (b) in-situ. Both intact cores and repacked samples 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 and in-situ soil sensors could be prioritized because these sampling methods are less destructive. While the repacked samples were packed to the target bulk density (estimated post-sampling, when sample volume was known), these samples had altered pore structures. Nevertheless, 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 also 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 OSTI2021

In-operando surface-sensitive probing of electrochemical reactions on nanoparticle electrocatalysts: Spectroscopic characterization of reaction intermediates and elementary steps of oxygen reduction reaction on Pt

In this paper we present an in-operando spectroscopic study of the reaction intermediates involved in ORR on electrified Pt nanoparticle electrocatalysts. To accomplish this, we have synthesized Ag-Pt core–shell nanoparticles, that contain a thin shell of Pt (~1 nm) uniformly deposited on a larger Ag core (~60 nm). We show that these nanostructures are ideal platforms for in-operando Plasmon Enhanced Raman Spectroscopy (PERS) of ORR on Pt. We combined these PERS studies with DFT calculations to assign the measured vibrational spectra to relevant surface intermediates as a function of electrocatalyst potential. Overall, these vibrational assignments were further verified and validated by performing PERS measurements using de-oxygenated and heavy oxygen (O 2 -18) saturated electrolyte. These studies allowed us to identity the presence of critical reaction intermediates (OH, O 2 , OOH, and H 2 O) as the function of operating voltage on the Pt surface and derive voltage-dependent elementary step mechanisms of the reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Community Input on the Need, Scope, and Development Roadmap of a Proposed National Virtual Biosecurity for Bioenergy Crops Center (NVBBCC)

Brookhaven National Laboratory (BNL) was awarded a pilot project in FY22 under the U.S. Department of Energy (DOE) Office of Science Biopreparedness Research Virtual Environment (BRaVE) initiative, to define research priorities, needs, and requirements for a national virtual center devoted to the biosecurity of bioenergy crops. The mission of the proposed center, referred to as the National Virtual Biosecurity for Bioenergy Crop Center (NVBBCC), would be to provide the scientific basis and tools to detect, characterize, model, and mitigate biothreats to bioenergy crops. This function will be essential to ensure the projected increased US reliance over the next few decades on key plant-based energy products, such as biojet fuel. The NVBBCC is envisioned as a distributed, virtual center with multiple national laboratories at its core to maximize the use of existing unique facilities and expertise across the DOE complex. A major goal of the pilot project was to develop a roadmap for establishing NVBBCC through a series of meetings to gather community input. A total of about 150 individuals, drawn from DOE laboratories, the USDA, academia, NIH, DHS and the private sector participated in six planning meetings held in FY23. Four of the meetings were focused on specific research topics (disease detection, dispersion and disease propagation, biomolecular characterization of plant-pathogen interaction, and mitigation strategies). These four meetings were followed by a meeting that focused on computational needs to support collaborative, data-intensive research within a distributed center as well as workforce development. A final meeting focused on establishing and maintaining preparedness within NVBBCC to respond to an emerging disease within bioenergy crops and how it would collaborate and coordinate with USDA and DHS.

09 BIOMASS FUELS↗
DOE OSTI2019

Graphitic‐Shell Encapsulation of Metal Electrocatalysts for Oxygen Evolution, Oxygen Reduction, and Hydrogen Evolution in Alkaline Solution

Abstract Developing highly efficient, cost effective, and environmentally friendly electrocatalysts for the oxygen evolution reaction (OER), oxygen reduction reaction (ORR), and hydrogen evolution reaction (HER) is of interest for sustainable and clean energy technologies, including metal–air batteries and fuel cells. In this work, the screening of electrocatalytic activities of a series of single metallic iron, cobalt, and nickel nanoparticles and their binary and ternary alloys encapsulated in a graphitic carbon shell toward the OER, ORR, and HER in alkaline media is reported. Synthesis of these compounds proceeds by a two‐step sol–gel and carbothermal reduction procedure. Various ex situ characterizations show that with harsh electrochemical activation, the graphitic shell undergoes an electrochemical exfoliation. The modified electronic properties of the remaining graphene layers prevent their exfoliation, protect the bulk of the metallic cores, and participate in the electrocatalysis. The amount of near‐surface, higher‐oxidation‐state metals in the as‐prepared samples increases with electrochemical cycling, indicating that some metallic nanoparticles are not adequately encased within the graphite shell. Such surface oxide species provide secondary active sites for the electrocatalytic activities. The Ni–Fe binary system gives the most promising results for the OER, and the Co–Fe binary system shows the most promise for the ORR and HER.

Khani, Hadi↗