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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Rotational excitations in rare-earth nuclei: A comparative study within three cranking models with different mean fields and treatments of pairing correlations

High-spin rotational bands in rare-earth Er (Z = 68), Tm (Z = 69), and Yb (Z = 70) isotopes are investigated by three different nuclear models. These are (i) the cranked relativistic Hartree-Bogoliubov (CRHB) approach with approximate particle number projection by means of the Lipkin-Nogami (LN) method, (ii) the cranking covariant density functional theory (CDFT) with pairing correlations treated by a shell-model-like approach (SLAP) or the so-called particle-number conserving (PNC) method, and (iii) cranked shell model (CSM) based on the Nilsson potential with pairing correlations treated by the PNC method. A detailed comparison between these three models in the description of the ground-state rotational bands of even-even Er and Yb isotopes is performed. The similarities and differences between these models in the description of the moments of inertia, the features of band crossings, and equilibrium deformations and pairing energies of the even-even nuclei under study are discussed. These quantities are considered as a function of rotational frequency and proton and neutron numbers. The changes in the properties of the first band crossings with increasing neutron number in this mass region are investigated. On average, a comparable accuracy of the description of available experimental data is achieved in these models. However, the differences between model predictions become larger above the first band crossings. Because of the time-consuming nature of numerical calculations in the CDFT-based models, a systematic study of the rotational properties of both ground-state and excited-state bands in odd-mass Tm nuclei is carried out only by the PNC-SCM. With few exceptions, the rotational properties of experimental 1-quasiparticle and 3-quasiparticle bands in 165,167,169,171 Tm are reproduced reasonably well. As a result, the appearance of backbendings or upbendings in these nuclei is well understood from the analysis of the variations of the occupation probabilities of the single-particle states and their contributions to total angular momentum alignment with rotational frequency.

150 ≤ A ≤ 189↗
DOE OSTI2024

An Empirical Model For Intrinsic Alignments: Insights From Cosmological Simulations

We extend current models of the halo occupation distribution (HOD) to include a flexible, empirical framework for the forward modeling of the intrinsic alignment (IA) of galaxies. A primary goal of this work is to produce mock galaxy catalogs for the purpose of validating existing models and methods for the mitigation of IA in weak lensing measurements. This technique can also be used to produce new, simulation-based predictions for IA and galaxy clustering. Our model is probabilistically formulated, and rests upon the assumption that the orientations of galaxies exhibit a correlation with their host dark matter (sub)halo orientation or with their position within the halo. We examine the necessary components and phenomenology of such a model by considering the alignments between (sub)halos in a cosmological dark matter only simulation. We then validate this model for a realistic galaxy population in a set of simulations in the Illustris-TNG suite. We create an HOD mock with Illustris-like correlations using our method, constraining the associated IA model parameters, with the $\mathcal{X}$$^{2}_{dof}$ between our model’s correlations and those of Illustris matching as closely as 1.4 and 1.1 for orientation–position and orientation–orientation correlation functions, respectively. By modeling the misalignment between galaxies and their host halo, we show that the 3-dimensional two-point position and orientation correlation functions of simulated (sub)halos and galaxies can be accurately reproduced from quasi-linear scales down to 0.1 $\mathcal{h}$ –1 Mpc. We also find evidence for environmental influence on IA within a halo. Our publicly-available software provides a key component enabling efficient determination of Bayesian posteriors on IA model parameters using observational measurements of galaxy-orientation correlation functions in the highly nonlinear regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Predicting Antimicrobial Resistance Using Partial Genome Alignments

Antimicrobial resistance (AMR) is an important global health threat that impacts millions of people worldwide each year. Developing methods that can detect and predict AMR phenotypes can help to mitigate the spread of AMR by informing clinical decision making and appropriate mitigation strategies. Many bioinformatic methods have been developed for predicting AMR phenotypes from whole-genome sequences and AMR genes, but recent studies have indicated that predictions can be made from incomplete genome sequence data. In order to more systematically understand this, we built random forest-based machine learning classifiers for predicting susceptible and resistant phenotypes for Klebsiella pneumoniae (1,640 strains), Mycobacterium tuberculosis (2,497 strains), and Salmonella enterica (1,981 strains). We started by building models from alignments that were based on a reference chromosome for each species. We then subsampled each chromosomal alignment and built models for the resulting subalignments, finding that very small regions, representing approximately 0.1 to 0.2% of the chromosome, are predictive. In K. pneumoniae, M. tuberculosis, and S. enterica, the subalignments are able to predict multiple AMR phenotypes with at least 70% accuracy, even though most do not encode an AMR-related function. We used these models to identify regions of the chromosome with high and low predictive signals. Finally, subalignments that retain high accuracy across larger phylogenetic distances were examined in greater detail, revealing genes and intergenic regions with potential links to AMR, virulence, transport, and survival under stress conditions. IMPORTANCE Antimicrobial resistance causes thousands of deaths annually worldwide. Understanding the regions of the genome that are involved in antimicrobial resistance is important for developing mitigation strategies and preventing transmission. Machine learning models are capable of predicting antimicrobial resistance phenotypes from bacterial genome sequence data by identifying resistance genes, mutations, and other correlated features. They are also capable of implicating regions of the genome that have not been previously characterized as being involved in resistance. In this study, we generated global chromosomal alignments for Klebsiella pneumoniae, Mycobacterium tuberculosis, and Salmonella enterica and systematically searched them for small conserved regions of the genome that enable the prediction of antimicrobial resistance phenotypes. In addition to known antimicrobial resistance genes, this analysis identified genes involved in virulence and transport functions, as well as many genes with no previous implication in antimicrobial resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Bipolar Membrane Electrodialyzers as Flexible Demand Response Resources: Co-Optimization of Cost Savings and Product Formation

Bipolar membrane electro dialyzers (BPMED) are widely used for chemical production and processing, including in the emerging ocean alkalinity enhancement (OAE) industry. In this paper, we explore the potential of BPMED devices as flexible electrochemical loads within power system operations. Using a multi-objective optimization framework, we evaluate BPMED operation across 24-hour and monthly horizons to examine how dispatch strategies respond to electricity price and grid conditions. Simulation results show that altering the relative weights of the choices in the objective function strongly shape the operating patterns, with cost-focused strategies that suppress the operation during peak prices. Furthermore, we propose alternative formulations that optimize operations to achieve both cost savings and alignment with periods of lower grid-side carbon intensity (CI), as low grid-side CI is key to maximize OAE efficiency. Additionally, a detailed sensitivity analysis highlights the importance of device properties, where low area-specific resistance (ASR) of membrane and high current efficiency (CE) are observed to jointly unlock cost-effective operation. However, even modest shunt efficiency losses are observed to erode performance and decrease system value. Importantly, the analysis demonstrates that BPMED can serve as a controllable and flexible demand response resource, shifting load to support multiple grid-side objectives, including (but not limited to) renewable integration, alleviate peak demand, and provide co-benefits for system reliability. These findings underscore BPMED’s dual role as a process technology and a grid-supporting asset, pointing to promising pathways for operational optimization of multiple objectives.

Bhattacharya, Saptarshi (ORCID:0000000308902060)↗
DOE OSTI2025

Photochemistry of Hypervalent Iodoazide Derivatives

The photochemical properties and reaction mechanisms of a series of hypervalent iodoazide compounds (R–IN3) were investigated, with substituents (−CH 3 , −H, −CF 3 ) tuning the electronic density of the phenyl ring. With the help of UV irradiation, ultrafast time-resolved spectroscopy, and density functional theory (DFT) calculations, we elucidated the mechanisms of azide radical (N 3 • ) release and its subsequent reactivity. UV–vis spectroscopy reveals that the photoconversion rates follow the trend CH3 > H > CF3, aligning with DFT-calculated ΔG values for ring-opening transitions. Homolytic cleavage of the I–N bond is identified as the dominant pathway for N3• generation upon UV irradiation, occurring within 400 fs. The released azide radicals react with the solvent molecules, while the iodo radical R–I C • fragments undergo a thermodynamically uphill lactone ring-opening (RO) reaction and subsequent hydrogen atom abstraction from the solvent to form carboxylic acids R–I–COOH, as validated by NMR and IR spectroscopy. The study also highlights the role of substituents in influencing reaction kinetics and intermediate stability, with electron-donating groups accelerating the release of the N 3 • species. This work bridges experimental observations with computational predictions, offering a foundation for future advancements in azide-based reactions and materials.

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

Missing components in ΛCDM from DESI Y1 baryonic acoustic oscillation measurements: Insights from redshift remapping

We explore transformations of the Friedman-Lemaître-Robertson-Walker (FLRW) metric and cosmological parameters that align with observational data while aiming to gain insights into potential extensions of standard cosmological models. We modified the FLRW metric by introducing a scaling factor, e 2Θ(a) –the cosmological scaling function (CSF), which alters the standard relationship between cosmological redshift and the cosmic scale factor without affecting angular measurements or cosmic microwave background (CMB) anisotropies. Using data from DESI Year 1, Pantheon+ supernovae, and the Planck CMB temperature power spectrum, we constrained both the CSF and cosmological parameters through a Markov chain Monte Carlo approach. Our results indicate that the CSF model fits observational data with a lower Hubble constant (although it is compatible with the value given by Planck 2018 within 1σ) and is predominantly dark matter dominated. Additionally, the CSF model produces temperature and lensing power spectra similar to those predicted by the standard model, though with lower values in the CSF model at large scales. We also checked that when fitting a CSF model without dark energy to the data, we obtain a more negative conformal function. This suggests that the CSF model may offer hints about missing elements and opens up a new avenue for exploring physical interpretations of cosmic acceleration.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

pnnl/mlxrd

A multi-task neural network for the simultaneous identification of multiple compounds from XRD data obtained in a synchrotron-based hydrothermal fluid system. To enhance the alignment between the training and test datasets, random noise is introduced into the synthetic training dataset, and minor labeled experimental data is incorporated. Additionally, we employ a weighted cross-entropy loss function to address data imbalances and ensure smoother model training.

Li, Ang↗
DOE OSTI2021

Selectivity of enzymes involved in the formation of opposite enantiomeric series of p -menthane monoterpenoids in peppermint and Japanese catnip

Peppermint (Mentha x piperita L.) and Japanese catnip (Schizonepeta tenuifolia (Benth.) Briq.) accumulate p-menthane monoterpenoids with identical functionalization patterns but opposite stereochemistry. In the present study, we investigate the enantioselectivity of multiple enzymes involved in monoterpenoid biosynthesis in these species. Based on kinetic assays, mint limonene synthase, limonene 3-hydroxylase, isopiperitenol dehydrogenase, isopiperitenone reductase, and menthone reductase exhibited significant enantioselectivity toward intermediates of the pathway that proceeds through (-)-4S-limonene. Limonene synthase, isopiperitenol dehydrogenase and isopiperitenone reductase of Japanese catnip preferred intermediates of the pathway that involves (+)-4R-limonene, whereas limonene 3-hydroxylase was not enantioselective, and the activities of pulegone reductase and menthone reductase were too low to acquire meaningful kinetic data. Molecular modeling studies with docked ligands generally supported the experimental data obtained with peppermint enzymes, indicating that the preferred enantiomer was aligned well with the requisite cofactor and amino acid residues implicated in catalysis. A striking example for enantioselectivity was peppermint (-)-menthone reductase, which binds (-)-menthone with exquisite affinity but was predicted to bind (+)-menthone in a non-productive orientation that positions its carbonyl functional group at considerable distance to the NADPH cofactor. Here, the work presented here lays the groundwork for structure-function studies aimed at unraveling how enantioselectivity evolved in closely related species of the Lamiaceae and beyond.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Cosmic shear cosmology beyond two-point statistics: a combined peak count and correlation function analysis of DES-Y1

ABSTRACT We constrain cosmological parameters from a joint cosmic shear analysis of peak-counts and the two-point shear correlation functions, as measured from the Dark Energy Survey (DES-Y1). We find the structure growth parameter $S_8\equiv \sigma _8\sqrt{\Omega _{\rm m}/0.3} = 0.766^{+0.033}_{-0.038}$ which, at 4.8 per cent precision, provides one of the tightest constraints on S8 from the DES-Y1 weak lensing data. In our simulation-based method we determine the expected DES-Y1 peak-count signal for a range of cosmologies sampled in four w cold dark matter parameters (Ωm, σ8, h, w0). We also determine the joint covariance matrix with over 1000 realizations at our fiducial cosmology. With mock DES-Y1 data we calibrate the impact of photometric redshift and shear calibration uncertainty on the peak-count, marginalizing over these uncertainties in our cosmological analysis. Using dedicated training samples we show that our measurements are unaffected by mass resolution limits in the simulation, and that our constraints are robust against uncertainty in the effect of baryon feedback. Accurate modelling for the impact of intrinsic alignments on the tomographic peak-count remains a challenge, currently limiting our exploitation of cross-correlated peak counts between high and low redshift bins. We demonstrate that once calibrated, a fully tomographic joint peak-count and correlation functions analysis has the potential to reach a 3 per cent precision on S8 for DES-Y1. Our methodology can be adopted to model any statistic that is sensitive to the non-Gaussian information encoded in the shear field. In order to accelerate the development of these beyond-two-point cosmic shear studies, our simulations are made available to the community upon request.

Harnois-Déraps, Joachim↗
DOE OSTI2021

Barriers to carriers: faults and recombination in non-stoichiometric perovskite scintillators

Abstract Tuning the efficiency and speed of charge carrier recombination in inorganic scintillators can potentially improve their performance in diverse applications. Recent work suggests that this maybe be achieved via a two-phase scintillator AB that naturally phase separates into A -rich and B -rich domains. In addition, a favorable electronic structure and band-edge alignment such that the charge carriers are confined or are thermodynamically driven to preferentially accumulate in one of the two domains, might lead to an improved radiative recombination rate. Here, we use density functional theory computations and ab initio molecular dynamics (AIMD), including non-adiabatic molecular dynamics (NAMD) simulations, to examine an alternative phase structure and its potential impact on recombination. Using a model perovskite SrTiO $$_3$$ 3 system with one-, two- and three-dimensional Ruddlesden–Popper (RP) phases, we demonstrate that RP faults induce band structure changes in the material that can act as barriers to carrier transport. Our AIMD/NAMD simulations indicate competing effects of a lower mean free path (potentially enhancing the desired radiative recombination and overall scintillating efficiency) and faster non-radiative recombination (undesired) due to enhanced electron–phonon coupling in the faulted system. Full exploitation of such a rational design approach would require tuning of the effective scintillation efficiency by varying the perovskite chemistry using appropriate arrangements of RP faults in the bulk material. Finally, other effects, such as the tendency of point defects to segregate at the interface, that might affect the overall performance, are briefly discussed. We expect the basic results found here to apply to other nanostructured scintillators. Graphical Abstract

36 MATERIALS SCIENCE↗
DOE OSTI2021

Optimal toolpath design of additive manufactured composite cylindrical structures

Structural design optimization for additive manufacturing is primarily focused on planar layer-by-layer processes and design of composite cylindrical structures does not often accommodate manufacturing constraints. In this study, we propose to optimize the toolpath trajectory of additively manufactured composite cylinders comprised of multiple thin cylindrical annuli. Additionally, our printing process is based on direct ink writing in which short carbon fibers in a thermoset resin are extruded through a moving nozzle to build up a structure. Since the fibers are primarily aligned in the flow direction of the extrudate, the printing trajectory influences the material properties of the composite structure. To accommodate this, we define the toolpaths as contours of parameterized level-set functions. This parameterization allows us to optimize the material properties and impose manufacturing constraints such as no-overlap, no-sag, minimum radius of curvature, and continuity of the toolpaths. Several examples illustrate the optimization procedure.

42 ENGINEERING↗
DOE OSTI2021

Tunneling current modulation in atomically precise graphene nanoribbon heterojunctions

Lateral heterojunctions of atomically precise graphene nanoribbons (GNRs) hold promise for applications in nanotechnology, yet their charge transport and most of the spectroscopic properties have not been investigated. Here, we synthesize a monolayer of multiple aligned heterojunctions consisting of quasi-metallic and wide-bandgap GNRs, and report characterization by scanning tunneling microscopy, angle-resolved photoemission, Raman spectroscopy, and charge transport. Comprehensive transport measurements as a function of bias and gate voltages, channel length, and temperature reveal that charge transport is dictated by tunneling through the potential barriers formed by wide-bandgap GNR segments. The current-voltage characteristics are in agreement with calculations of tunneling conductance through asymmetric barriers. We fabricate a GNR heterojunctions based sensor and demonstrate greatly improved sensitivity to adsorbates compared to graphene based sensors. This is achieved via modulation of the GNR heterojunction tunneling barriers by adsorbates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Directing the far-from-equilibrium assembly of nanoparticles in confined liquid crystals by hydrodynamic fields

The assembly of nematic colloids relies on long-range elastic interactions that can be manipulated through external stimuli. Confinement and the presence of a hydrodynamic field alter the defect structures and the energetic interactions between the particles. Here, the assembly landscape of nanoparticles embedded in a nematic liquid crystal confined in a nanochannel under a pressure-driven flow is determined. The dynamics of the liquid crystal tensor alignment field is determined through a Poisson-Bracket framework, namely the Stark–Lubensky equations, coupled with the zero-Reynolds momentum equations and the liquid crystal Landau-de Gennes free energy functional. A second order semi-implicit time integration and a three-dimensional Galerkin finite element method are used to resolve flow and nematic fields under several conditions. In general, the zero Reynolds flow displaces the defects around the particles in the upstream direction and renders the surface anchoring ineffective when the flow strength dominates over the nematic elasticity. More importantly, the potential of mean force for particle assembly is non-monotonic independent of surface anchoring. Our results show that the confinement length scale determines the repulsion/attraction transition between colloids, while the flow strength modifies the static defect structure surrounding the particles and determines the magnitude of the energetic barrier for successful assembly. In the attractive regime, the particles move at different rates through the nematic until one particle eventually catches up with the other. This process occurs against or along the direction of flow depending on the flow strength. Ultimately, these results provide a template for engineering and controlling the transport and assembly of nanoparticles under far-from equilibrium conditions in anisotropic media.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Solid structure of Li 2 BeF 4 (FLiBe) from room temperature to melting studied by neutron and X-ray diffraction

Molten fluoride salts such as Li 2 BeF 4 (FLiBe) are used in molten salt reactors, fluoride-salt-cooled high-temperature reactors and fusion reactors as a fuel solvent, coolant and/or tritium breeding medium. In engineered systems that use molten salt, solid-state material will be present during melting and freezing scenarios, and therefore the temperature-dependent properties of the solid and solid/liquid phase transition merit investigation. To observe the behavior of the solid state of Li 2 BeF 4 from room temperature to melting, this work used neutron and X-ray diffraction to measure the changes in the lattice parameters and volume of the crystalline unit cell and compared the results with prior low-temperature data for solid Li 2 BeF 4 . From neutron diffraction data it is also possible to identify anisotropy: centimetre-scaled crystals align preferentially with the a axes parallel to the direction of freezing front propagation, and the c axes expand 54% more than the a axes. This work provides the lattice constants as a function of temperature, quantifies the thermal expansion, and determines the equation describing the change in density for solid Li 2 BeF 4 from room temperature to 459°C to be ρ solid (kg m −3 ) = 2182 (3) − 0.115 (2) T (°C) and the volume expansion upon melting to be less than 5%. This density changes depending on molecular weight and enrichment.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Toward three-dimensional DNA industrial nanorobots

Nanoscale industrial robots have potential as manufacturing platforms and are capable of automatically performing repetitive tasks to handle and produce nanomaterials with consistent precision and accuracy. We demonstrate a DNA industrial nanorobot that fabricates a three-dimensional (3D), optically active chiral structure from optically inactive parts. By making use of externally controlled temperature and ultraviolet (UV) light, our programmable robot, ~100 nanometers in size, grabs different parts, positions and aligns them so that they can be welded, releases the construct, and returns to its original configuration ready for its next operation. Our robot can also self-replicate its 3D structure and functions, surpassing single-step templating (restricted to two dimensions) by using folding to access the third dimension and more degrees of freedom. Our introduction of multiple-axis precise folding and positioning as a tool/technology for nanomanufacturing will open the door to more complex and useful nano- and microdevices.

Robotics↗
DOE OSTI2026

Distinguishing Leptothrix and Sphaerotilus genera by an integrated genomic-phenotypic analysis supported by new Leptothrix genomes

The Sphaerotilus-Leptothrix group of bacteria includes one of the first described microorganisms, Leptothrix ochracea, an uncultured type strain, plus isolates of Leptothrix and Sphaerotilus. This group is unified by the ability to form sheaths and oxidize metals, although L. ochracea exhibits obvious ecological, morphological, and functional differences from the rest of Sphaerotilus-Leptothrix. Recently, there have been calls to combine the group into one genus, Sphaerotilus; however, these studies lacked adequate genomic representation of L. ochracea. Here, we present a comprehensive comparative genomic analysis of the Sphaerotilus-Leptothrix group, including expanded representation of L. ochracea, a closely related novel species, Leptothrix toolikensis, and two new isolates (Leptothrix mechoopdaensis). Analysis of 38 genomes resolves three phylogenetic and functional groups: the ochracea-type Leptothrix (Group 1), the mobilis-type Leptothrix (Group 2), and Sphaerotilus (Group 3). Group 1 genomes form a separate genus based on average nucleotide identity and alignment fraction. The genomes clearly diverge from the rest of Sphaerotilus-Leptothrix in phylogeny, size, and metabolic potential. Group 1 genomes are much smaller (2.59–3.04 Mb) than those of Groups 2 (4.55–6.06 Mb) and 3 (3.94–5.07 Mb), while encoding more metal oxidases and fewer carbohydrate-active enzymes. Group 2 clusters with Group 3 phylogenetically and is similar in organic carbon metabolisms but maintains more metal oxidation genes. Group 2 members lack homogeneity in phenotype and genotype, suggesting that additional isolates and genomes are needed for confident classification. However, Group 1 genomes (L. ochracea and L. toolikensis) show clear divergence, precluding their inclusion in Sphaerotilus and supporting the retention of the genus Leptothrix.

Leptothrix↗
DOE OSTI2024

Scalable Nanoimprint Manufacturing of Functional Multilayer Metasurface Devices

Optical metasurfaces, consisting of subwavelength-scale meta-atom arrays, hold great promise of overcoming the fundamental limitations of conventional optics. Due to their structural complexity, metasurfaces usually require high-resolution yet slow and expensive fabrication processes. Here, using a metasurface polarimetric imaging device as an example, the photonic structures and the Nanoimprint lithography (NIL) processes are designed, creating two separate NIL molds over a patterning area of > 20 mm2 with designed Moiré alignment markers by electron-beam writing, and further subsequently integrate silicon and aluminum metasurface structures on a chip. Uniquely, the silicon and aluminum metasurfaces are fabricated by using the nanolithography and 3D pattern-transfer capabilities of NIL, respectively, achieving nanometer-scale linewidth uniformity, sub-200 nm translational overlay accuracy, and <0.017 rotational alignment error while significantly reducing fabrication complexity and surface roughness. Here, the micro-sized multilayer metasurfaces have high circular polarization extinction ratios as large as ≈20 and ≈80 in blue and red wavelengths. Further, the metasurface chip-integrated CMOS imager demonstrates high accuracy in broad-band, full Stokes parameter analysis in the visible wavelength ranges and single-shot polarimetric imaging. This novel, NIL-based, multilayered nanomanufacturing approach is applicable to the scalable production of large-area functional structures for ultra-compact optic, electronic, and quantum devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Solar position confounds the relationship between ecosystem function and vegetation indices derived from solar and photosynthetically active radiation fluxes

Vegetation indices derived from solar and photosynthetically active radiation (PAR) sensors (i.e. radiation derived) have been under-utilized in inferring ecosystem function, despite measurement capability at hundreds of sites. This under-utilization may be attributed to reported mismatches among the seasonality of radiation- and satellite-derived vegetation indices and canopy photosynthesis; herein referred to as measurement biases. In this work, biases in radiation derived reflectance and vegetation indices were assessed using a decadal record of satellite and ground based spectroradiometer data, ecosystem phenology and CO 2 fluxes, and radiation derived vegetation indices (i.e. the Normalized Difference Vegetation Index [NDVI], the two band Enhanced Vegetation Index [EVI2]) from a high latitude tundra site (i.e. Imnaviat). At Imnaviat, we found poor correspondence between the three types of reflectance and vegetation indices, especially during the latter part of the growing season. Radiation derived vegetation indices resulted in incorrect estimates of phenological timing of up to a month and poor relationships with canopy photosynthesis (i.e. Gross Ecosystem Exchange (GEE)). These mismatches were attributed to solar position (i.e. solar zenith and azimuth angle) and a method, based on the diel visible and near-infrared albedo variation, was developed to improve the performance of the vegetation indices. The ability of radiation derived vegetation indices to infer GEE and phenological dates drastically improved once radiation derived vegetation indices were corrected for solar position associated biases at Imnaviat. Moreover, radiation derived vegetation indices became better aligned with MODerate resolution Imaging Spectroradiometer (MODIS) satellite estimates after solar position associated biases were corrected at Imnaviat and at 25 Fluxnet sites (~90 site years) across North America. Corrections developed here provide a way forward in understanding daily ecosystem function or filling large gaps in eddy covariance data at a significant number of Fluxnet sites.

54 ENVIRONMENTAL SCIENCES↗