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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Prediction of nonlinear optical properties of organic materials. General theoretical considerations

The prediction of nonlinear optical properties of organic materials is geared to assist materials scientists in the selection of good candidate molecules. A brief summary of the quantum mechanical methods used for estimating hyperpolarizabilities will be presented. The advantages and limitations of each technique will be discussed. Particular attention will be given to the finite-field method for calculating first and second order hyperpolarizabilities, since this method is better suited for large molecules. Corrections for dynamic fields and bulk effects will be discussed in detail, focusing on solvent effects, conformational isomerization, core effects, dispersion, and hydrogen bonding. Several results will be compared with data obtained from third-harmonic-generation (THG) and dc-induced second harmonic generation (EFISH) measurements. These comparisons will demonstrate the qualitative ability of the method to predict the relative strengths of hyperpolarizabilities of a class of compounds. The future application of molecular mechanics, as well as other techniques, in the study of bulk properties and solid state defects will be addressed. The relationship between large values for nonlinear optical properties and large conjugation lengths is well known, and is particularly important for third-order processes. For this reason, the materials with the largest observed nonresonant third-order properties are conjugated polymers. An example of this type of polymer is polydiacetylene. One of the problems in dealing with polydiacetylene is that substituents which may enhance its nonlinear properties may ultimately prevent it from polymerizing. A model which attempts to predict the likelihood of solid-state polymerization is considered, along with the implications of the assumptions that are used. Calculations of the third-order optical properties and their relationship to first-order properties and energy gaps will be discussed. The relationship between monomeric and polymeric third-order optical properties will also be considered.

Cardelino, B.↗
DOE OSTI2025

Across the Scales of the Nucleus: Understanding Short Range Correlations from Medium Modification to Probe Independence

The atomic nucleus presents an intricate system due to the non-linear forces described by Quantum Chromodynamics (QCD) that govern its structure. The range of scales involved is remarkable; the most massive nuclei weigh approximately five orders of magnitude more than the quarks that compose them. The nucleus can be analyzed at various levels, from quarks to hadrons to the nucleus as a whole. Short-Range Correlations (SRCs) within the nucleus play a significant role that spans these diverse scales. At the most fundamental level, SRCs influence the interaction between nucleons. The nucleon-nucleon (NN) interaction, arising from QCD, is crucial in determining nuclear properties. SRCs serve as valuable probes for measuring this NN interaction, as the nucleons within SRCs become effectively decoupled from the rest of the nucleus. Multiple experimental techniques, including electron scattering, have been employed to investigate the NN interaction through SRCs. However, our first project demonstrates that inclusive measurements alone are inadequate to constrain this interaction fully. Moving to the scale of the nucleus, SRCs contribute to the high-momentum tail of the nuclear spectral function. While the low-momentum region is characterized by nucleons exhibiting bulk properties, nucleons begin to pair into SRCs at higher momenta. Our research aims to bridge the understanding between the mean-field portion of the nucleus and its high-momentum SRC components. Additionally, SRCs affect the quark structure of protons, as evidenced by the EMC effect, which indicates that quarks behave differently when protons are embedded within a nucleus—an effect referred to as medium modification. This thesis explores the correlation between SRCs and medium modification across various experimental setups. Finally, we seek to establish an interpretation of the nuclear ground state. Accomplishing this requires demonstrating that our SRC observables are independent of the probe’s scale and scheme. The concluding project of this thesis illustrates how we utilize triple coincidence quasi-elastic scattering across a range of (Q2) values to develop a model-dependent framework for understanding SRC distributions within the nucleus’s ground-state wavefunction.

Denniston, A. W. Denniston [University of Tel Aviv↗
NASA NTRS1995

Emissivity measurements in thin metallized membrane reflectors used for microwave radiometer sensors

This paper is concerned with electromagnetic losses in metallized films used for inflatable reflectors. An inflatable membrane is made of tough elastic material such as Kapton, and it is not electromagnetically reflective by design. A film of conducting metal is added to the membrane to enhance its reflective properties. Since the impetus for use of inflatables for spacecraft is the light weight and compact packaging, it is important that the metal film be as thin as possible. However, if the material is not conductive or thick enough, the radiation due to the emissivity of the reflector could be a significant part of the radiation gathered by the radiometer. The emissivity would be of little consequence to a radar or solar collector; but for a radiometer whose signal is composed of thermal radiation, this contribution could be severe. Bulk properties of the metal film cannot be used to predict its loss. For this reason, a program of analysis and measurement was undertaken to determine the emissivities of a number of candidate metallized film reflectors. This paper describes the three types of measurements which were performed on the metallized thin films: (1) a network analyzer system with an L-band waveguide; (2) an S-band radiometer; and (3) a network analyzer system with a C-band antenna free-space transmission system.

Schroeder, Lyle C.↗
NASA NTRS1976

The metal to metal interface and its effect on adhesion and friction

The nature of the interface, adhesion and friction properties of noble metals, platinum metals, Group IV (B) metals and transition metals were considered. The surface chemical activity of the noble and platinum metals is shown to effect metal to metal interfaces as does a valance bonding in the transition metals. With the Group IV (B) metals the degree of metallic nature of the elements is shown to effect interfacial behavior. The effect of surface segregation of alloy constituents such as silicon in iron and its influence on the metal to metal interface is discussed. In addition the effect of alloy constituents on changes in bulk properties such as transformations in tin are shown to effect interfacial adhesion and friction behavior.

Buckley, D. H.↗
NASA NTRS2023

Thermomechanical Property Prediction of Amorphous and Crystal PEKK via Molecular Dynamics

Traditionally, advanced aerospace composites have been manufactured using thermoset resins. However, recently, thermoplastics have been investigated for use in the manufacturing of composite materials due to their unique manufacturing characteristics. Thermoplastic resins can be reshaped and formed, along with the added benefit of being recyclable, which thermoset resin cannot. Thermoplastic materials undergo a crystallization process during manufacturing which affects the percent crystallinity of the material. The crystallization needs to be understood better to maximize the potential of thermoplastic resins. PEKK is a thermoplastic material with good chemical, thermal, and mechanical loading resistance. PEKK is also a material NASA is interested in for developing new bonded joint technology. The crystalline microstructure of PEKK is at the micrometer length scale, and it is of interest to model the effects of the crystallinity structure on PEKK’s bulk properties. Molecular dynamics (MD) is a simulation tool that allows for property-structure relationships between atomistic structure and nanometer-length portions of a material. This makes MD a useful tool for developing the structure-property relationship of PEKK. However, the micrometer length scale of PEKK’s crystal structure is too large for MD. Thus, a hybrid approach to modeling PEKK’s microstructure is proposed in this work where MD models are built of both the amorphous and crystalline phases of PEKK. The engineering material properties can be obtained using MD at the nanometer length scale. A micromechanics approach can then generate the micrometer length scale of the crystallinity and the effective properties can be homogenized. The objective of this paper is to show the MD model workflow and the MD-predicted properties of PEKK. The properties can then be homogenized with different crystalline percentages to build design graphs that can be used to tailor PEKK for specific composite applications.

poly ether ketone ketone↗
NASA NTRS2007

An Experimental Approach to Understanding the Optical Effects of Space Weathering

The creation and accumulation of nanophase iron (npFe(sup 0)) is the primary mechanism by which spectra of materials exposed to the space environment incur systematic changes referred to as "space weathering." The optical effects of this npFe(sup 0) on lunar soils are well documented. Space weathering though, should occur on the surface of any planetary body that is not protected by an atmosphere. There is no reason to assume that cumulative space weathering products throughout the solar system will be the same as those found in lunar soils. In fact, these products are likely to be very dependent on the specific environmental conditions under which they were produced. We have prepared a suite of analog soils to explore the optical effects of npFe(sup 0). By varying the size and concentration of npFe(sup 0) in the analogs we found significant systematic changes in the Vis/NIR spectral properties of the materials. Smaller npFe(sup 0) (<10 nm in diameter) dramatically reddens spectra in the visible wavelengths while leaving the infrared region largely unaffected. Larger npFe(sup 0) (>40 nm in diameter) lowers the albedo across the Vis/NIR range with little change in the overall shape of the continuum. Intermediate npFe(sup 0) sizes impact the spectra in a distinct pattern that changes with concentration. The products of these controlled experiments have implications for space-weathered material throughout the inner solar system. Our results indicate that the lunar soil continuum is best modeled by npFe(sup 0) particles with bulk properties in the approx.15-25 nm size range. Larger npFe0 grains result in spectra that are similar in shape to the Mercury continuum. The continuum of S-type asteroid spectra appear to be best represented by small amounts of npFe(sup 0) that is similar to, but slightly smaller on average, than the npFe(sup 0) in lunar soils (approx.10-15 nm).

Noble, Sarah K.↗
NASA NTRS2023

Small-Scale Magnetic Flux Ropes in Stream Interaction Regions From Parker Solar Probe and Wind Spacecraft Observations

Using in situ measurements from the Parker Solar Probe and Wind spacecraft, we investigate the small-scale magnetic flux ropes (SFRs) and their properties inside stream interaction regions (SIRs). Within SIRs from ∼0.15 to 1 au, SFRs are found to exist in a wide range of solar wind speeds with more frequent occurrences after the stream interface, and the Alfvénicity of these structures decreases significantly with increasing heliocentric distances. Furthermore, we examine the variation of five corresponding SIRs from the same solar sources. The enhancements of suprathermal electrons within these SIRs persist at 1 au and are observed multiple times. An SFR appears to occur repeatedly with the recurring SIRs and is traversed by the Wind spacecraft at least twice. This set of SFRs has similarities in variations of the magnetic field components, plasma bulk properties, density ratio of solar wind alpha and proton particles, and unidirectional suprathermal electrons. We also show, through the detailed time-series plots and Grad–Shafranov reconstruction results, that they possess the same chirality and carry comparable amounts of magnetic flux. Lastly, we discuss the possibility for these recurring SFRs to be formed via interchange reconnection, maintain the connection with the Sun, and survive up to 1 au.

Solar wind↗
DOE OSTI2024

Bioblendstocks to Optimize Mixing Controlled Compression Ignition (MCCI) Engines

In this project, a team of researchers from the University of Massachusetts Lowell, the University of Maine, and Mainstream Engineering developed an integrated process for the product of bioblendstocks to optimize mixing controlled compression ignition (MCCI) engines. The objective was to improve the energy density, sooting propensity, and cetane number of base diesel fuel while maintaining cold weather behavior. The process converts woody biomass (e.g. sawmill residues) into bio-oil through selective fast pyrolysis; the bio-oil is then selectively upgraded to form selectively oxygenated, minimally-branched hydrocarbons using non-noble metal catalysts in combination with metal-catalyzed hydrogenation. Advanced predictive models, in conjunction with existing property databases, and experimental testing are used to evaluate overall bioblendstock properties and their impact on base diesel fuel. An iterative, targeted upgrading approach was implemented to optimize the proposed bioblendstock’s properties. Assessment methodologies included techno-economic analysis, life-cycle assessment, property testing, and engine testing. Ultimately, the project team successfully produced a viable bioblendstock while identifying critical process points related to scale-up efforts. It was found that producing pyrolysis oils at 500 degrees C and with pine particle sizes of 1-2 mm led to bio-oil with a higher yield (of approximately 45 wt%) and rich amounts of aromatic alcohols. The resultant pyrolysis oil was then upgraded using a sequence of mild hydrotreating, followed by catalytic etherification and esterification, followed by another final mild hydrotreating to produce a blendstock containing saturated species with a limited, but non-zero, amount of oxygen. The aromatic alcohols produced by pyrolysis were especially helpful in this regard, as the resulting bicycloethers and derivatives exhibited high cetane numbers. While most bulk properties of the bioblendstock met or exceeded targeted thresholds, viscosity and cloud point notably fell outside the expected range; this could be addressed by blending limits and/or through the use of additives that are commonplace in current refinding practices. Identification of a bioblendstock that can be produced economically at scale while improving the performance and emissions characteristics of internal combustion engines positively affects the economy by boosting domestic fuel production and the environment by decreasing harmful emissions and increasing efficiency.

09 BIOMASS FUELS↗
NASA NTRSDate not supplied

Multiscale Modeling of Thermoplastics Using Atomistic-informed Micromechanics

A multiscale model was developed for predicting the thermoelastic behavior of semi-crystalline thermoplastic materials for composite aerospace applications. At the highest scale containing the semi-crystalline spherulite in an amorphous matrix, the generalized method of cells, or high fidelity method of cells, was used to perform the homogenization calculations to obtain the effective properties. Models were developed assuming a cubic, or spherical shape, for the spherulite to understand if the morphology of the spherulite affects the effective thermoelastic properties. The generalized method of cells was used to model at the repeating unit cells at the subscales of the microstructure including the lamellae stacks and granular crystal blocks. The scales are integrated using the multiscale micromechanics method in the NASA Multiscale Analysis Tool. Data from molecular dynamics simulations were used as inputs for the amorphous and crystalline constituents. Convergence studies were performed to determine the best level of discretization for the repeating unit cell at the highest scale. Effective Young’s modulus, shear modulus, Poisson’s ratio, coefficient of thermal expansion, and thermal conductivity were predicted for polyether ether ketone and polyether ketone ketone, and very good agreement between the model utilizing the cubic spherulite and the experimental data, where available, was observed for polyether ketone ketone. Normalization of the data for the bulk polyether ketone ketone, against amorphous data, improved the predictions as compared to experimental data. Overall, the high fidelity method of cells predicted a stiffer response then the generalized method of cells as the crystallinity was increased. The shape of the spherulite had a minimal effect on the predicted bulk properties of the polymers.

thermoplastics↗
NASA NTRS2007

Protective Skins for Aerogel Monoliths

A method of imparting relatively hard protective outer skins to aerogel monoliths has been developed. Even more than aerogel beads, aerogel monoliths are attractive as thermal-insulation materials, but the commercial utilization of aerogel monoliths in thermal-insulation panels has been inhibited by their fragility and the consequent difficulty of handling them. Therefore, there is a need to afford sufficient protection to aerogel monoliths to facilitate handling, without compromising the attractive bulk properties (low density, high porosity, low thermal conductivity, high surface area, and low permittivity) of aerogel materials. The present method was devised to satisfy this need. The essence of the present method is to coat an aerogel monolith with an outer polymeric skin, by painting or spraying. Apparently, the reason spraying and painting were not attempted until now is that it is well known in the aerogel industry that aerogels collapse in contact with liquids. In the present method, one prevents such collapse through the proper choice of coating liquid and process conditions: In particular, one uses a viscous polymer precursor liquid and (a) carefully controls the amount of liquid applied and/or (b) causes the liquid to become cured to the desired hard polymeric layer rapidly enough that there is not sufficient time for the liquid to percolate into the aerogel bulk. The method has been demonstrated by use of isocyanates, which, upon exposure to atmospheric moisture, become cured to polyurethane/polyurea-type coats. The method has also been demonstrated by use of commercial epoxy resins. The method could also be implemented by use of a variety of other resins, including polyimide precursors (for forming high-temperature-resistant protective skins) or perfluorinated monomers (for forming coats that impart hydrophobicity and some increase in strength).

Leventis, Nicholas↗
NASA NTRS2002

Observations and Parameterizations of Particle Size Distributions in Deep Tropical Cirrus and Stratiform Precipitation Clouds: Results from In-Situ Observations in TRMM Field Campaigns

In this study, we report on the evolution of particle size distributions (PSDs) and habits as measured during slow, Lagrangian-type spiral descents through deep subtropical and tropical cloud layers in Florida, Brazil, and Kwajalein, Marshall Islands, most of which were precipitating. The objective of the flight patterns was to learn more about how the PSDs evolved in the vertical and to obtain information of the vertical structure of microphysical properties. New instrumentation yielding better information on the concentrations of particles in the size (D) range between 0.2 and 2 cm, as well as improved particle imagery, produced more comprehensive observations for tropical stratiform precipitation regions and anvils than have been available previously. Collocated radar observations provided additional information on the vertical structure of the cloud layers sampled. Most of the spirals began at cloud top, with temperatures (T) as low as -50 C, and ended at cloud base or below the melting layer (ML). The PSDs broadened from cloud top towards cloud base, with the largest particles increasing in size from several millimeters at cloud top to one centimeter or larger towards cloud base. Some continued growth was noted in the upper part of the ML. Concentrations of particles less than 1 mm in size decreased with decreasing height. The result was a consistent change in the PSDs in the vertical. Similarly, systematic changes in the size dependence of the particle cross-sectional area was noted with decreasing height. Aggregation-as ascertained from both the changes in the PSDs and evolution of particle habits as observed in high detail with the cloud particle imager (CPI) probe-was responsible for these trends. The PSDs were generally well-represented by gamma distributions of the form N = N0 gamma D microns e- lambda gamma D that were fitted to the PSDs over 1-km horizontal intervals throughout the spirals. The intercept (N0 gamma), slope (lambda gamma), and dispersion (microns) values were derived for each PSD. Exponential curves (N = N0e- lambdaD; micron = 0) were also fitted to the distributions. The lambda gamma values for given spirals varied systematically with temperature as did the values of lambda (exponential), and the data generally conformed to values found in previous studies involving exponential fits to size distributions in mid-latitude frontal and cirrus layers. Considerable variability often noted in the PSD properties during the loops of individual spirals was manifested primarily in large changes in N0 gamma and N0, but micron, lambda gamma and lambda remained fairly stable. Temperature is not found to be the sole factor controlling lambda gamma or lambda but is a primary one. Direct relationships were found between lambda gamma and N0 gamma or lambda gamma and micron for the gamma distributions and lambda and N0 for the exponential. The latter relationship was not found as distinctly in earlier studies; observed PSDs in this study had better fidelity with less scatter. The micron values changed monotonically with T over the range of temperatures and were directly related to N0 gamma or lambda gamma, thereby reducing the number of variables in the PSD functional equation to two. In the upper part of the ML, N0 and lambda continued to decrease, and in the lower part these values began to increase as the largest particles melted. We developed general expressions relating various bulk microphysical, radar, and radiative transfer-related variables to N0 gamma and lambda gamma, useful for both tropical and mid-latitude clouds. These relationships facilitate the specification of a number of bulk properties in cloud and climate models. The results presented in this paper apply best to temperatures between 0 and -40 C, for which the measured radar reflectivities fall in the range of 0 to 25 dBZe.

Heymsfield, Andrew J.↗
NASA NTRS2018

An IR Sounding-Based Analysis of the Saharan Air Layer in North Africa

Intense daytime surface heating over barren-to-sparsely vegetated surfaces results in dry convective mixing. In the absence of external forcing such as mountain waves, the dry convection can produce a deep, well-mixed, nearly isentropic boundary layer that becomes a well-mixed residual layer in the evening. These well-mixed layers (WML) retain their unique mid-tropospheric thermal and humidity structure for several days. To detect the SAL and characterize its properties, AIRS Level 2 Ver. 6 temperature and humidity products (2003-Present) are evaluated against rawinsondes and compared to model analysis at each of the 55 rawinsonde stations in northern Africa. To distinguish WML from Saharan air layers (WMLs of Saharan origin), the detection involved a two-step process: 1) algorithm-based detection of WMLs in dry environments (less than 7 g per kilogram mixing ratio) 2) identification of Sahara air layers (SAL) by applying Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) back trajectories to determine the history of each WML. WML occurrence rates from AIRS closely resemble that from rawinsondes, yet rates from model analysis were up to 30% higher than observations in the Sahara due to model errors. Despite the overly frequent occurrence of WMLs from model analysis, HYSPLIT trajectory analysis showed that SAL occurrence rates (given a WML exists) from rawinsondes, AIRS, and model analysis were nearly identical. Although the number of WMLs varied among the data sources, the proportion of WMLs which were classified as SAL was nearly the same. The analysis of SAL bulk properties showed that AIRS and model analysis exhibited a slight warm and moist bias relative to rawinsondes in non-Saharan locations, but model analysis was notably warmer than rawinsondes and AIRS within the Sahara. The latter result is likely associated with the dearth of available data assimilated by model analysis in the Sahara. The variability of SAL thicknesses was reasonably captured by both AIRS and model analysis, but the former favor layers than are thinner than observations. Finally, further analysis of HYSPLIT trajectories revealed that fewer than 10% and 33% of all SAL back trajectories passed through regions with notable precipitation (>100 mm accumulated along the trajectory path) or Aerosol Optical Depth (AOD greater than 0.4, 75th percentile of AOD) on average, respectively. Trajectory analysis indicated that only 57% of Saharan and 24% of non-Saharan WMLs are definitively of Saharan origin (Saharan requirement: Two consecutive days in Sahara and 24 or more of those hours within 72 hours of detection). Non-SAL WMLs either originate from local-to-regionally generated residual layers or from mid-latitude air streams that do not linger over the Sahara for a sufficient time period. Initial analysis shows these non-SAL WMLs tend to be both notably cooler and slightly moister than their SAL counter parts. Continuing analysis will address what role Saharan and non-Saharan air masses characteristics may play on local and regional environmental conditions.

Nicholls, Stephen D.↗
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↗
NASA NTRS1995

Long-wavelength Radar Studies of the Lunar Maria

Radar measurements at 70 cm and 7.5 m wavelengths provide insight into the structure and chemical properties of the upper 5-100 m of the lunar regolith and crust. Past work has identified a number of anomalous regions and changes in echo strength, some attributed to differences in titanium content. There has been little opportunity, however, to compare calibrated long-wavelength backscatter among different units or to theoretical model results. We combine recent high-resolution (3-5 km) 70-cm radar data for the nearside with earlier calibrated full-disk observations to provide a reasonable estimate of the true lunar backscatter coefficient. These data are tested against models for quasi-specular scattering from the surface, echoes from a buried substrate, and Mie scattering from surface and buried rocks. We find that 70 cm echoes likely arise from Mie scattering by distributed rocks within the soil, consistent with earlier hypotheses. Returns from a buried substrate would provide a plausible fit to the observations only if the regolith depth were ~3 m or less and varied little across the maria. Depolarized echoes are due to some combination of single and multiple scattering events, but it appears that single scattering alone could account for the observed echo power, based on comparisons with terrestrial rocky surfaces. Backscatter strength from the regolith is most strongly affected by the loss tangent, whose variation with mineral content is still poorly defined. We compared the backscatter values for the mare deposits to the oxide contents inferred from spectral ratio methods, and found that in general the unit boundaries evident in radar images closely follow those seen in color difference images. The 70-cm data are not well correlated with TiO2 values found using the Charette relationship nor with Fe abundances derived from Clementine observations. The lack of a relationship between radar echo and Fe content is reasonable given the distribution of iron among various mineral phases, but ilmenite content (FeTiO3) has typically been cited as the dominant cause of changes in loss tangent (and thus the radar absorption). The lack of correlation between the radar data and TiO2 estimates may arise from uncertainties in the Charette technique, subtle differences in the upper surface and bulk properties of the regolith, mineralogic effects on the radar not linked to titanium content, or to some combination of these factors. Dark crater haloes in the mare and highlands, and low radar returns from apparent cryptomare regions, are used to illustrate the role radar data can play in identifying changes in regolith composition; low-return haloes around craters such as Petavius may indicate 5-25% contamination of the highlands soil by excavated mare material or a layer of rock-poor ejecta at least several meters deep. The 7.5-m data were shown to correlate to a reasonable degree with estimates of Fe abundance, suggesting that this component of the mare basalts is primarily responsible for attenuation losses at very long wavelengths. The different sensitivities of the two radar wavelengths and multispectral data offers the potential for future deep mapping of the mare lava flows and regolith.

Lunar MariaRadarLunar Studies↗
NASA NTRS1995

Long-wavelength Radar Studies of the Lunar Maria

Radar measurements at 70 cm and 7.5 m wavelengths provide insight into the structure and chemical properties of the upper 5-100 m of the lunar regolith and crust. Past work has identified a number of anomalous regions and changes in echo strength, some attributed to differences in titanium content. There has been little opportunity, however, to compare calibrated long-wavelength backscatter among different units or to theoretical model results. We combine recent high-resolution (3-5 km) 70-cm radar data for the nearside with earlier calibrated full-disk observations to provide a reasonable estimate of the true lunar backscatter coefficient. These data are tested against models for quasi-specular scattering from the surface, echoes from a buried substrate, and Mie scattering from surface and buried rocks. We find that 70 cm echoes likely arise from Mie scattering by distributed rocks within the soil, consistent with earlier hypotheses. Returns from a buried substrate would provide a plausible fit to the observations only if the regolith depth were approx.3 m or less and varied little across the maria. Depolarized echoes are due to some combination of single and multiple scattering events, but it appears that single scattering alone could account for the observed echo power, based on comparisons with terrestrial rocky surfaces. Backscatter strength from the regolith is most strongly affected by the loss tangent, whose variation with mineral content is still poorly defined. We compared the backscatter values for the mare deposits to the oxide contents inferred from spectral ratio methods, and found that in general the unit boundaries evident in radar images closely follow those seen in color difference images. The 70-cm data are not well correlated with TiO2 values found using the Charette relationship nor with Fe abundances derived from Clementine observations. The lack of a relationship between radar echo and Fe content is reasonable given the distribution of iron among various mineral phases, but ilmenite content (FeTiO3) has typically been cited as the dominant cause of changes in loss tangent (and thus the radar absorption). The lack of correlation between the radar data and TiO2 estimates may arise from uncertainties in the Charette technique, subtle differences in the upper surface and bulk properties of the regolith, mineralogic effects on the radar not linked to titanium content, or to some combination of these factors. Dark crater haloes in the mare and highlands, and low radar returns from apparent cryptomare regions, are used to illustrate the role radar data can play in identifying changes in regolith composition; low-return haloes around craters such as Petavius may indicate 5-25% contamination of the highlands soil by excavated mare material or a layer of rock-poor ejecta at least several meters deep. The 7.5-m data were shown to correlate to a reasonable degree with estimates of Fe abundance, suggesting that this component of the mare basalts is primarily responsible for attenuation losses at very long wavelengths. The different sensitivities of the two radar wavelengths and multispectral data offers the potential for future deep mapping of the mare lava flows and regolith.

Lunar Studies↗
DOE OSTI2025

Thermodynamic Framework for Water in Deep Eutectic Solvents and Ionic Liquids

Water is widely recognized as critical to the tunability and electrochemical stability of nonaqueous solvents such as deep eutectic solvents (DESs) and ionic liquids (ILs). Traditionally, the water content of these solvents has been controlled by either drying or adding small amounts of water to control their bulk properties to meet specific application requirements. The total water content by itself, does not provide sufficient information about the chemical reactivity and molecular interactions within DES– and IL–water mixtures. In this concept article, water activity is highlighted as a thermodynamically more rigorous descriptor to quantify the influence of the co‐solvent water on DES– and IL–water mixtures. Water activity relates measurable physical properties, such as vapor pressure, density, viscosity, electrochemical stability, and conductivity of DESs and ILs to the underlying molecular interactions between their components. Furthermore, water activity of DESs and ILs correlates with changes in local solvent structures and thermodynamic excess properties, including excess molar volume, enthalpy, and Gibbs energy.

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

High-emissivity, thermally robust emitters for high power density thermophotovoltaics

Thermal radiative energy transport is essential for high-temperature energy harvesting technologies, including thermophotovoltaics (TPVs) and grid-scale thermal energy storage. However, the inherently low emissivity of conventional high-temperature materials constrains radiative energy transfer, thereby limiting system performance and technoeconomic viability. Here, in this study, we demonstrate ultrafast femtosecond laser-material interactions to transform diverse materials into near-blackbody surfaces with broadband spectral emissivity above 0.96. This enhancement arises from hierarchically engineered light-trapping microstructures enriched with nanoscale features, effectively decoupling surface optical properties from bulk thermomechanical properties. These laser-blackened surfaces (LaBS) exhibit exceptional thermal stability, retaining high emissivity for over 100 h at temperatures exceeding 1,000°C, even in oxidizing environments. When applied as TPV thermal emitters, Ta LaBS double electrical power output from 2.19 to 4.10 W cm −2 at 2,200°C while sustaining TPV conversion efficiencies above 30%. This versatile, largely material-independent technique offers a scalable and economically viable pathway to enhance emissivity for advanced thermal energy applications.

laser-blackened surfaces↗