Search NASA⌕ Search

SEARCH · Search NASA

Results for “Distributed Sensing”

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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Inter-digital capacitive sensor for evaluating cable jacket and insulation aging

An inter-digital capacitive (TDC) sensor has previously been used to measure dielectric properties of cable insulation polymer material when placed in direct contact with the insulation. Often cable insulation is covered by a polymer jacket. The dielectric properties of many cable jacket and insulation polymers are known to change due to thermal and radiation exposure-related damage. These dielectric properties frequently track with other measures of cable aging, such as tensile elongation-at-break and indenter modulus that have been broadly established as cable insulation polymer assessment methods. The external jacket of a cable is likely to have a different permittivity from the underlying insulation, and frequently the jacket material exhibits more severe damage than the insulation material due to environmental exposure. Because the jacket serves primarily to guard the cable during installation, as long as the underlying insulation condition is acceptable, the jacket condition is relatively unimportant in service. As part of a continuing program to develop and evaluate nondestructive examination methods that may be applied to cable condition assessment, a set of tools has been developed including (1) a parallel-plate sensor to directly measure the permittivity spectrum of flat sheet material and (2) an TDC and fixture to measure the effect of cable polymer dielectric property change on the sensor response. The TDC consists of two fork-like electrodes facing each other with the fork tines interspersed and separated by a small gap. The electrodes are printed on one side of a flexible substrate that can be conformed to the surface of a cylindrical cable, with tines parallel to the cable axis. The electrodes are connected to a broad-frequency-spectral impedance meter that senses the capacitance between the narrowly gapped electrode tines. This capacitance is known to vary as a function of the permittivity of any material in close proximity to the electrodes. By finite element modeling (FEM) and experimentation, this study investigates the effect of tine spacing and other design parameters associated with the TDC on the voltage (potential) distribution and electric field depth of penetration. The TDC measurement of an unshielded ethylene-propylene rubber (EPR)-insulated cable is shown to track with the degree of aging and quantities obtained by established methods. For jacketed cable systems, the TDC response is dominated by the jacket but, by analyzing measurements from TDC sensors with different depths-of-field penetration into the cable under test, the influence of the chlorinated polyethylene (CPE) cable jacket material degradation can be separated from an assessment of the cable insulation thereby enabling assessment of the insulation beneath/through the jacket.

Cable NDE, Interdigital Capacitance, Cable test↗
DOE OSTI2025

Coupling magnons to an opto-electronic parametric oscillator

Hybrid magnonic systems have emerged as versatile modular components for quantum signal transduction and sensing applications owing to their capability of connecting distinct quantum platforms. To date, the majority of the magnonic systems have been explored in a local, near-field scheme, due to the close proximity required for realizing a strong coupling between magnons and other excitations. This constraint greatly limits the applicability of magnons in developing remotely coupled, distributed quantum network systems. On the contrary, opto-electronic architectures hosting self-sustained oscillations have been a unique platform for long-haul signal transmission and processing. Here, we integrated an opto-electronic oscillator with a magnonic oscillator consisting of a microwave waveguide and a Y 3 Fe 5 O 12 (YIG) sphere, and demonstrated strong and coherent coupling between YIG’s magnon modes and the opto-electronic oscillator’s characteristic photon modes—revealing the hallmark anti-crossing gap in the measured spectrum. In particular, the photon mode is produced on-demand via a nonlinear, parametric process as stipulated by an external seed pump. Both the internal cavity phase and the external pump phase can be precisely tuned to stabilize either degenerate or nondegenerate auto-oscillations. Our result lays out a new, hybrid platform for investigating the long-distance coupling and nonlinearity in coherent magnonic phenomena, which may be found useful in constructing the future “distributed hybrid magnonic systems.”

36 MATERIALS SCIENCE↗
DOE OSTI2015

Detecting anomalies in CMB maps: a new method

Ever since WMAP announced its first results, different analyses have shown that there is weak evidence for several large-scale anomalies in the CMB data. While the evidence for each anomaly appears to be weak, the fact that there are multiple seemingly unrelated anomalies makes it difficult to account for them via a single statistical fluke. So, one is led to considering a combination of these anomalies. But, if we ''hand-pick'' the anomalies (test statistics) to consider, we are making an a posteriori choice. In this article, we propose two statistics that do not suffer from this problem. The statistics are linear and quadratic combinations of the a{sub ℓ m}'s with random co-efficients, and they test the null hypothesis that the a{sub ℓ m}'s are independent, normally-distributed, zero-mean random variables with an m-independent variance. The motivation for considering multiple modes is this: because most physical models that lead to large-scale anomalies result in coupling multiple ℓ and m modes, the ''coherence'' of this coupling should get enhanced if a combination of different modes is considered. In this sense, the statistics are thus much more generic than those that have been hitherto considered in literature. Using fiducial data, we demonstrate that the method works and discuss how it can be used with actual CMB data to make quite general statements about the incompatibility of the data with the null hypothesis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Label-free molecular imaging of bacterial communities of the opportunistic pathogen Pseudomonas aeruginosa

Biofilms, such as those formed by the opportunistic human pathogen Pseudomonas aeruginosa are complex, matrix enclosed, and surface-associated communities of cells. Bacteria that are part of a biofilm community are much more resistant to antibiotics and the host immune response than their free-floating counterparts. P. aeruginosa biofilms are associated with persistent and chronic infections in diseases such as cystic fibrosis and HIV-AIDS. P. aeruginosa synthesizes and secretes signaling molecules such as the Pseudomonas quinolone signal (PQS) which are implicated in quorum sensing (QS), where bacteria regulate gene expression based on population density. Processes such as biofilms formation and virulence are regulated by QS. This manuscript describes the powerful molecular imaging capabilities of confocal Raman microscopy (CRM) and surface enhanced Raman spectroscopy (SERS) in conjunction with multivariate statistical tools such as principal component analysis (PCA) for studying the spatiotemporal distribution of signaling molecules, secondary metabolites and virulence factors in biofilm communities of P. aeruginosa. Our observations reveal that the laboratory strain PAO1C synthesizes and secretes 2-alkyl-4-hydroxyquinoline N-oxides and 2-alkyl-4-hydroxyquinolones in high abundance, while the isogenic acyl homoserine lactone QS-deficient mutant (ΔlasIΔrhlI) strain produces predominantly 2-alkyl-quinolones during biofilm formation. Furthermore, this study underscores the use of CRM, along with traditional biological tools such as genetics, for studying the behavior of microbial communities at the molecular level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

System and method for implementing a zero-sequence current filter for a three-phase power system

In a three-phase, four-wire electrical distribution system, a zig-zag transformer and at least one Cascade Multilevel Modular Inverter (CMMI) is coupled between the distribution system and the neutral. A controller modulates the states of the H-bridges in the CMMI to build an AC waveform. The voltage is chosen by the controller in order to control an equivalent impedance that draws an appropriate neutral current through the transformer. This neutral current is generally chosen to cancel the neutral current sensed in the line. The chosen neutral current may be based on a remotely sensed imbalance, rather than on a local value, determined by the power utility as a critical load point in the system. The desired injection current is then translated by the controller into a desired zero-sequence reactive impedance, based on measurement of the local terminal voltage, allowing the controller to regulate the current without generating or consuming real power.

Benavides, Nicholas↗
DOE OSTI2025

When can we detect lianas from space? Toward a mechanistic understanding of liana‐infested forest optics

Abstract Lianas, woody vines acting as structural parasites of trees, have profound effects on the composition and structure of tropical forests, impacting tree growth, mortality, and forest succession. Remote sensing could offer a powerful tool for quantifying the scale of liana infestation, provided the availability of robust detection methods. We analyze the consistency and global geographic specificity of spectral signals—reflectance across wavelengths—from liana‐infested tree crowns and forest stands, examining the underlying mechanisms of these signals. We compiled a uniquely comprehensive database, including leaf reflectance spectra from 5424 leaves, fine‐scale airborne reflectance data from 999 liana‐infested canopies, and coarse‐scale satellite reflectance data covering 775 ha of liana‐infested forest stands. To unravel the mechanisms of the liana spectral signal, we applied mechanistic radiative transfer models across scales, establishing a synthesis of the relative importance of different mechanisms, which we corroborate with field data on liana leaf chemistry and canopy structure. We find a consistent liana spectral signal at canopy and stand scales across globally distributed sites. This signature mainly arises at the canopy level due to direct effects of more horizontal leaf angles, resulting in a larger projected leaf area, and indirect effects from increased light scattering in the near and short‐wave infrared regions, linked to lianas' less costly leaf construction compared with trees on average. The existence of a consistent global spectral signal for lianas suggests that large‐scale quantification of liana infestation is feasible. However, because the traits responsible for the liana canopy‐reflectance signal are not exclusive to lianas, accurate large‐scale detection requires rigorously validated remote sensing methods. Our models highlight challenges in automated detection, such as potential misidentification due to leaf phenology, tree life history, topography, and climate, especially where the scale of liana infestation is less than a single remote sensing pixel. The observed cross‐site patterns also prompt ecological questions about lianas' adaptive similarities in optical traits across environments, indicating possible convergent evolution due to shared constraints on leaf biochemical and structural traits.

Environmental Sciences & Ecology↗
DOE OSTI2013

A direct dynamical measurement of the Milky Way's disk surface density profile, disk scale length, and dark matter profile at 4 kpc ≲ R ≲ 9 kpc

We present and apply rigorous dynamical modeling with which we infer unprecedented constraints on the stellar and dark matter mass distribution within our Milky Way (MW), based on large sets of phase-space data on individual stars. Specifically, we model the dynamics of 16,269 G-type dwarfs from SEGUE, which sample 5 kpc < R{sub GC} < 12 kpc and 0.3 kpc ≲ |Z| ≲ 3 kpc. We independently fit a parameterized MW potential and a three-integral, action-based distribution function (DF) to the phase-space data of 43 separate abundance-selected sub-populations (MAPs), accounting for the complex selection effects affecting the data. We robustly measure the total surface density within 1.1 kpc of the mid-plane to 5% over 4.5 kpc < R{sub GC} < 9 kpc. Using metal-poor MAPs with small radial scale lengths as dynamical tracers probes 4.5 kpc ≲ R{sub GC} ≲ 7 kpc, while MAPs with longer radial scale lengths sample 7 kpc ≲ R{sub GC} ≲ 9 kpc. We measure the mass-weighted Galactic disk scale length to be R{sub d} = 2.15 ± 0.14 kpc, in agreement with the photometrically inferred spatial distribution of stellar mass. We thereby measure dynamically the mass of the Galactic stellar disk to unprecedented accuracy: M {sub *} = 4.6 ± 0.3 + 3.0 (R {sub 0}/ kpc – 8) × 10{sup 10} M {sub ☉} and a total local surface density of Σ{sub R{sub 0}}(Z=1.1 kpc)=68 ± 4 M{sub ⊙} pc{sup −2} of which 38 ± 4 M {sub ☉} pc{sup –2} is contributed by stars and stellar remnants. By combining our surface density measurements with the terminal velocity curve, we find that the MW's disk is maximal in the sense that V {sub c,} {sub disk}/V {sub c,} {sub total} = 0.83 ± 0.04 at R = 2.2 R{sub d} . We also constrain for the first time the radial profile of the dark halo at such small Galactocentric radii, finding that ρ{sub DM}(r; ≈R {sub 0})∝1/r {sup α} with α < 1.53 at 95% confidence. Our results show that action-based DF modeling of complex stellar data sets is now a feasible approach that will be fruitful for interpreting Gaia data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Sizing ice hydrometeor populations using the dual-wavelength radar ratio

Dual-wavelength (3.2 and 0.32 cm, i.e., X- and W-radar bands) radar ratio (DWR) measurements in ice clouds and precipitation using Canada's National Research Council Institute for Aerospace Research airborne radar are compared to closely collocated particle microphysical in situ sampling data in order to develop relations between DWR and characteristic hydrometeor size. This study uses the radar and in situ data sets collected during the In-Cloud ICing and Large-drop Experiment (ICICLE) campaign in midlatitude frontal clouds. Since atmospheric particle scattering at X band is predominantly in the Rayleigh regime and the W-band frequency is the highest frequency usually used for hydrometeor remote sensing, the X–W-band combination provides a relatively strong dual-wavelength reflectivity difference. This study considers radar and in situ measurements conducted in relatively homogeneous cloud and precipitation conditions. Measurements show that under these conditions, the difference between the X-band radar reflectivities observed with vertical and horizontal pointing of the radar beam are generally small and often negligible. However, W-band reflectivities at vertical beam pointing are, on average, larger than those for horizontal beam pointing by about 4 dB, which is a non-Rayleigh scattering effect from preferentially oriented non-spherical particles. A horizontal radar beam DWR–mean volume particle size relation, D v , provides robust estimates of this characteristic size for populations of particles with different habits. Uncertainties of D v retrievals using DWR are around 0.6 mm when D v is greater than approximately 1 mm. Size estimates using vertical radar beam DWRs have larger uncertainties due to smaller dual-wavelength signals and stronger influences of hydrometeor habits and orientations at this geometry of beam pointing. Mean relations among different characteristic sizes, which describe the entire particle size distribution (PSD), such as D v , and other sizes used in various applications (e.g., the mean, effective, and median sizes) are derived, so the results of this study can be used for estimating different PSD characteristic sizes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Learning Provably Stable Local Volt/Var Controllers for Efficient Network Operation

Here this paper develops a data-driven framework to synthesize local Volt/Var control strategies for distributed energy resources (DERs) in power distribution grids (DGs). Aiming to improve DG operational efficiency, as quantified by a generic optimal reactive power flow (ORPF) problem, we propose a two-stage approach. The first stage involves learning the manifold of optimal operating points determined by an ORPF instance. To synthesize local Volt/Var controllers, the learning task is partitioned into learning local surrogates (one per DER) of the optimal manifold with voltage input and reactive power output. Since these surrogates characterize efficient DG operating points, in the second stage, we develop local control schemes that steer the DG to these operating points. We identify the conditions on the surrogates and control parameters to ensure that the locally acting controllers collectively converge, in a global asymptotic sense, to a DG operating point agreeing with the local surrogates. We use neural networks to model the surrogates and enforce the identified conditions in the training phase. AC power flow simulations on the IEEE 37-bus network empirically bolster the theoretical stability guarantees obtained under linearized power flow assumptions. The tests further highlight the optimality improvement compared to prevalent benchmark methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2011

Dancing bunches as Van Kampen modes

Van Kampen modes are eigen-modes of Jeans-Vlasov equation [1-3]. Their spectrum consists of continuous and, possibly, discrete parts. Onset of a discrete van Kampen mode means emergence of a coherent mode without any Landau damping; thus, even a tiny couple-bunch wake is sufficient to drive instability. Longitudinal instabilities observed at Tevatron [4], RHIC [5] and SPS [6] can be explained as loss of Landau damping (LLD), which is shown here to happen at fairly low impedances. For repulsive wakes and single-harmonic RF, LLD is found to be extremely sensitive to steepness of the bunch distribution function at small amplitudes. Based on that, a method of beam stabilization is suggested. Emergence of a discrete van Kampen mode means either loss of Landau damping or instability. Longitudinal bunch stability is analysed in weak head-tail approximation for inductive impedance and single-harmonic RF. The LLD threshold intensities are found to be rather low: for cases under study all of them do not exceed a few percent of the zero-amplitude incoherent synchrotron frequency shift, strongly decreasing for shorter bunches. Because of that, LLD can explain longitudinal instabilities happened at fairly low impedances at Tevatron [4], and possibly for RHIC [5] and SPS [6], being in that sense an alternative to the soliton explanation [5, 20]. Although LLD itself results in many cases in emergence of a mode with zero growth rate, any couple-bunch (and sometimes multi-turn) wake would drive instability for that mode, however small this wake is. LLD is similar to a loss of immune system of a living cell, when any microbe becomes fatal for it. The emerging discrete mode is normally very different from the rigid-bunch motion; thus the rigid-mode model significantly overestimates the LLD threshold. The power low of LLD predicted in Ref. [17] agrees with results of this paper. However, the numerical factor in that scaling low strongly depends on the bunch distribution function. Particularly, for inductive impedance above transition and three examined distributions, the highest LLD threshold intensity exceeds the lowest one by a factor of {approx}100. Based on that observation, proper RF phase shaking as a method of beam stabilization is suggested.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Determining the Drivers of Redox Sensitive Biogeochemistry in Humid Tropical Forests

Our objectives were to determine the spatial and temporal dynamics and drivers of soil O 2 availability and redox-sensitive biogeochemical processes using easily measured and modeled parameters. We used automated soil O 2 sensing coupled with measurements of soil chemical and physical properties, climate, and greenhouse gas concentrations and fluxes. These results are being used to derive quantitative relationships linking climate and soil physical properties to redox sensitive biogeochemical processes in tropical forests. We tested the hypothesis that hot spots and hot moments are driven primarily by high substrate availability using distributed sampling and field and lab fertilization experiments. To better model C and nutrient cycling and greenhouse gas fluxes in Earth system models we need to develop a more mechanistic understanding of the spatial and temporal dynamics and drivers of soil O 2 availability in tropical forest soils. In this study we used field and laboratory experiments to help develop a mechanistically derived redox component for the Community Land Model (CLM) module of the Community Earth System Model (CESM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Integrating Overhead Camera Imagery with Reinforcement Learning to Improve Fuel Economy Through Adaptive Traffic Control

Overhead cameras have been deployed for some time as a sensor for traffic control, with many advantages over conventional inductive loop sensors in terms of robustness, ease of installation, and simplicity with respect to maintenance. We explore the utility of such imagery (in particular, fisheye lens cameras) for intelligent traffic control in real-time using reinforcement learning, with a goal of improving fuel economy for the overall intersection and grid of intersections. We summarize our initial work in data collection and approach to ascertain the ability to visually sense vehicular fuel consumption using real-world data. We then describe our deep reinforcement learning topology to test adaptive control informed by the camera capabilities. Next, we tested the proof-of-concept through a variety of simulation scenarios using the Simulation of Urban Mobility (SUMO) traffic simulator, which included different estimates on vehicle classifications, different traffic distributions, and different traffic densities. Six different control policies were tested ranging from simple timing, to heuristic visual-based methods, to actual policies learned via the reinforcement learning approach. Our results demonstrate the feasibility of the approach for controlling traffic lights for better fuel efficiency based on visual vehicle estimates from commercial, fisheye lens cameras.

Karnowski, Thomas↗
DOE OSTI2010

Strong-field ionization of a heteronuclear diatomic molecule

We theoretically study strong-field ionization of a heteronuclear diatomic molecule, CO, by calculating the photoelectron angular distributions (PADs) and the total ionization rates using linearly and circularly polarized laser fields. We find that, although the PADs of CO generally do not have inversion symmetry, they become more inversion symmetric as the photoelectron energy increases. Heteronuclear features of CO upon ionization are better understood by comparing the results with those of a representative of homonuclear molecules, N{sub 2}, in that, although there are some similarities between CO and N{sub 2} due to the same orbital symmetry, {sigma}{sub g}, there are some differences between them in terms of the ionization suppression and orientation dependence of the total ionization yield. Namely, CO behaves more like an atom in the low-intensity range in a sense that ionization takes place mainly from the neighborhood of the C core, while it behaves more like a double-core molecule in the high-intensity range since ionization takes place from the neighborhood of both C and O cores. This explains why ionization suppression of CO is not seen at the low intensity but it becomes more visible at the high intensity range.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Sea Ice Detection Using GNSS-R Data From TechDemoSat-1

A new method for the detection of sea ice using GNSS-R (Global Navigation Satellite Systems Reflectometry) is presented and applied to 33 months of data from the U.K. TechDemoSat-1 mission. This method of sea ice detection shows the potential for a future GNSS-R polar mission, attaining an agreement of over 98% and 96% in the Antarctic and Arctic, respectively, when compared to the European Space Agency's Climate Change Initiative sea ice concentration product. The algorithm uses a combination of two parameters derived from the delay-Doppler Maps to quantify the spread of power in delay and Doppler. Application of thresholds then allows sea ice to be distinguished from open water. Differences between the TechDemoSat-1 sea ice detection and comparison data sets are explored. The results provide information on the seasonal and multiyear changes in sea ice distribution of the Arctic and Antarctic. Future potential and applications of this technique are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A review of coarse mineral dust in the Earth system

Mineral dust particles suspended in the atmosphere span more than three orders of magnitude in diameter, from <0.1 µm to more than 100 µm. This wide size range makes dust a unique aerosol species with the ability to interact with many aspects of the Earth system, including radiation, clouds, hydrology, atmospheric chemistry, and biogeochemistry. This review focuses on coarse and super-coarse dust aerosols, which we respectively define as dust particles with a diameter of 2.5–10 µm and 10–62.5 µm. We review several lines of observational evidence indicating that coarse and super-coarse dust particles are transported farther than previously expected and that the abundance of these particles is substantially underestimated in current global models. We synthesize previous studies that used observations, theories, and model simulations to highlight the impacts of coarse and super-coarse dust aerosols on the Earth system, including their effects on dust-radiation interactions, dust-cloud interactions, atmospheric chemistry, and biogeochemistry. Specifically, coarse and super-coarse dust aerosols produce a net positive direct radiative effect (warming) at the top of the atmosphere and can modify temperature and water vapor profiles, influencing the distribution of clouds and precipitation. In addition, coarse and super-coarse dust aerosols contribute a substantial fraction of ice-nucleating particles, especially at temperatures above –23 °C. They also contribute a substantial fraction to the available reactive surfaces for atmospheric processing and the dust deposition flux that impacts land and ocean biogeochemistry by supplying important nutrients such as iron and phosphorus. Furthermore, we examine several limitations in the representation of coarse and super-coarse dust aerosols in current model simulations and remote-sensing retrievals. Because these limitations substantially contribute to the uncertainties in simulating the abundance and impacts of coarse and super-coarse dust aerosols, we offer some recommendations to facilitate future studies. Overall, we conclude that an accurate representation of coarse and super-coarse properties is critical in understanding the impacts of dust aerosols on the Earth system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Blowing Snow at McMurdo Station, Antarctica During the AWARE Field Campaign: Surface and Ceilometer Observations

Blowing snow (BLSN) is an impactful process in cold climates, affecting regional thermodynamics, radiation properties, and the surface mass balance of snow. Though it has significant climatic impacts, the process is still poorly understood and not widely included in weather and climate models. In 2016, the AWARE Field Campaign saw the deployment of a large suite of in situ and remote sensing instruments to McMurdo Station, Antarctica allowing for investigation of BLSN. A ceilometer–based BLSN detection algorithm used elsewhere in Antarctica is applied to data from AWARE, yielding a BLSN frequency of 14.1% compared to 8.2% as detected by human observers. To increase confidence in detections, the algorithm is updated to have shorter temporal averaging and to include a variety of meteorological thresholds to limit false detections due to fog. Efforts to incorporate a laser disdrometer into the algorithm were unsuccessful. An unphysical dependence of particle size distributions on wind speed is found suggesting observations are problematic at wind speeds greater than 10 m s –1 . The revised algorithm detected a BLSN frequency of 7.4%, increasing agreement with human observations and confidence that the process is actively occurring at the observation site. Furthermore, these observations are put into context of a climatology of human observations of BLSN at McMurdo station from 2002–2018. An annual average of 8.0%–14.0% is estimated, with a total annual range of 3.4%–21.3%. Regardless of whether BLSN is observed by humans or instrument, the majority of cases at this location are associated with ongoing precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Validation of the Community Land Model Version 5 over the Contiguous United States (CONUS) using in situ and remote sensing data sets

The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the Contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125? during 1979-2018 over the CONUS using different configurations of CLM, namely CLM5-biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5-satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote-sensed and in-situ datasets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC-simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM-simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation datasets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially-distributed plant phenology and physiology parameters and regional-specific agricultural management practices (e.g., planting, harvest).

Cheng, Yanyan↗
DOE OSTI2016

Surface patterning of nanoparticles with polymer patches

Patterning of colloidal particles with chemically or topographically distinct surface domains (patches) has attracted intense research interest. Surface-patterned particles act as colloidal analogues of atoms and molecules serve as model systems in studies of phase transitions in liquid systems, behave as ‘colloidal surfactants’ and function as templates for the synthesis of hybrid particles. The generation of micrometre- and submicrometre-sized patchy colloids is now efficient but surface patterning of inorganic colloidal nanoparticles with dimensions of the order of tens of nanometres is uncommon. Such nanoparticles exhibit size- and shape-dependent optical, electronic and magnetic properties, and their assemblies show new collective properties. At present, nanoparticle patterning is limited to the generation of two-patch nanoparticles and nanoparticles with surface ripples or a ‘raspberry’ surface morphology. We demonstrate nanoparticle surface patterning, which utilizes thermodynamically driven segregation of polymer ligands from a uniform polymer brush into surface-pinned micelles following a change in solvent quality. Patch formation is reversible but can be permanently preserved using a photocrosslinking step. The methodology offers the ability to control the dimensions of patches, their spatial distribution and the number of patches per nanoparticle, in agreement with a theoretical model. The versatility of the strategy is demonstrated by patterning nanoparticles with different dimensions, shapes and compositions, tethered with various types of polymers and subjected to different external stimuli. Furthermore, these patchy nanocolloids have potential applications in fundamental research, the self-assembly of nanomaterials, diagnostics, sensing and colloidal stabilization.

36 MATERIALS SCIENCE↗