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At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Surface-Functionalized Cellulose Nanocrystals as Nanofillers for Crosslinking Processes: Implications for Thermosetting Resins

Understanding the response of fillers in the epoxy resin crosslinking process and characterizing polymer–filler dynamics are the key features that guide the engineering of new thermosetting resin composites. Here, in this work, X-ray photon correlation spectroscopy (XPCS) is used as a thermal analysis tool to track the microscopic changes occurring during the cure of a functionalized cellulose nanocrystal (mCNC)–epoxy composite. In contrast, traditional methods such as differential scanning calorimetry (DSC) and curing rheology are used to understand the kinetics and properties on macroscopic length scales. Of interest is the influence of the mCNC on the curing kinetics and properties of the thermosetting resin. Two levels of modification (increasing hydrophobicity) were chosen to observe the effect of functionalization. Before cure, the highly functionalized CNC (mCNC3) shows a 44% increase in complex viscosity (η*), while the less functionalized CNC (mCNC2) shows a η* value similar to that of the neat resin. As the cure cycle progresses, results from DSC, rheology, and XPCS further show the enhancement in dispersion for mCNC3. The results show a clear difference in the maximum drift velocity, maximum heat flow, and complex viscosity during the ramp to the isothermal cure temperature (T cure ). Such results suggest that mCNC3 contains a well-dispersed network of particles due to the higher level of functionalization. During T cure , a transition in elastic modulus (G') occurs only for the highly functionalized CNC particle system. We believe that heat-induced aggregation occurs, and the crosslinked resin ultimately dominates the macroscopic properties of the final cured system for all samples. The results from the three techniques are in good agreement and showcase XPCS as a beneficial experimental tool for characterizing the microscopic dynamics of particulate-filled thermosetting resins. Hence, we envision this to be a fundamental curing study for the design of thermosetting resin composites.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Increasing Branching and Functionalization Decreases Crystallinity and Crystallization Rate in Linear EVOH

Here, we report the crystallization behavior of a linear poly(ethylene-co-vinyl alcohol) (LEVOH) under isothermal crystallization as a function of both OH incorporation and undercooling, and compare the results to conventional branched EVOH. This LEVOH is synthesized by post-polymerization functionalization of polycyclooctene, and it exhibits a half-crystallization time and primary crystallization rate nearly an order of magnitude faster than branched EVOH at ~ 6 mol% OH incorporation. While the LEVOH obtains approximately twice the extent of crystallization compared to the branched equivalent, as OH incorporation increases, the crystallization kinetics and crystallinity of LEVOH decrease. The crystal structure of LEVOH is orthorhombic at low functionalization (≤ 11 mol% OH), a mixture of orthorhombic and hexagonal at moderate functionalization (17 - 21 mol%), and hexagonal at high functionalization (23 %). The LEVOH crystallizes into plates, with crystallite widths ~ 20 - 60 times the crystallite thickness. Ultimately, we show LEVOH crystallizes faster and to a greater extent than commercial branched EVOH, a potential advantage of post-polymerization functionalization as part of polymer-to-polymer upcycling.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Increasing Functional Diversity in a Global Land Surface Model Illustrates Uncertainties Related to Parameter Simplification

Abstract Simulations of the land surface carbon cycle typically compress functional diversity into a small set of plant functional types (PFT), with parameters defined by the average value of measurements of functional traits. In most earth system models, all wild plant life is represented by between five and 14 PFTs and a typical grid cell (≈100 × 100 km) may contain a single PFT. Model logic applied to this coarse representation of ecological functional diversity provides a reasonable proxy for the carbon cycle, but does not capture the non‐linear influence of functional traits on productivity. Here we show through simulations using the Energy Exascale Land Surface Model in 15 diverse terrestrial landscapes, that better accounting for functional diversity markedly alters predicted total carbon uptake. The shift in carbon uptake is as great as 30% and 10% in boreal and tropical regions, respectively, when compared to a single PFT parameterized with the trait means. The traits that best predict gross primary production vary based on vegetation phenology, which broadly determines where traits fall within the global distribution. Carbon uptake is more closely associated with specific leaf area for evergreen PFTs and the leaf carbon to nitrogen ratio in deciduous PFTs.

58 GEOSCIENCES↗
DOE OSTI2026

Informing Robust Functional Relationship Benchmarks: An Evaluation of the Temperature Sensitivity of Ecosystem Respiration Across the Arctic-Boreal Region

During land model development, simulated carbon dynamics are often benchmarked against observational data sets to evaluate model performance. Functional relationship benchmarks are the relationship between a driving variable (e.g., temperature) and a response variable (e.g., ecosystem respiration) and are a promising tool for assessing model performance by evaluating modeled sensitivities to changing environmental conditions. However, observed functional relationships can be influenced by choices made during data collection and throughout the benchmarking process, impacting the inferred skill of land models. To avoid misrepresenting a model's true performance, it is necessary to systematically evaluate best practices when constructing functional relationship benchmarks. We developed a set of guidelines for constructing functional relationship benchmarks, considering the choice of data set, number of daily observations, temporal extent, and temporal resolution across Alaska and Canada over a 20-year period from 2001 to 2020. The temperature sensitivity of ecosystem respiration from observations, evaluated through an apparent Q 10 , is highly variable both spatially and as a result of the data processing approach applied in the benchmark formation. When benchmarking 13 models from the Warming Permafrost Model Intercomparison Project (WrPMIP), the range in inferred model skill is substantially impacted by the choices applied in constructing functional relationship benchmarks. The inferred performance of a given model is most sensitive to the number of daily observations and temporal extent, followed by choice of benchmark data set and temporal averaging. Results from this analysis can guide the development of consistent and robust functional relationships for future model evaluation studies.

Poe, Jeralyn [Northern Arizona University, Flagsta↗
DOE OSTI2019

Dual-barcoded shotgun expression library sequencing for high-throughput characterization of functional traits in bacteria

A major challenge in genomics is the knowledge gap between sequence and its encoded function. Gain-of-function methods based on gene overexpression are attractive avenues for phenotype-based functional screens, but are not easily applied in high-throughput across many experimental conditions. Here, we present Dual Barcoded Shotgun Expression Library Sequencing (Dub-seq), a method that uses random DNA barcodes to greatly increase experimental throughput. As a demonstration of this approach, we construct a Dub-seq library with Escherichia coli genomic DNA, performed 155 genome-wide fitness assays in 52 experimental conditions, and identified overexpression phenotypes for 813 genes. We show that Dub-seq data is reproducible, accurately recapitulates known biology, and identifies hundreds of novel gain-of-function phenotypes for E. coli genes, a subset of which we verified with assays of individual strains. Dub-seq provides complementary information to loss-of-function approaches and will facilitate rapid and systematic functional characterization of microbial genomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Long-term warming in a Mediterranean-type grassland affects soil bacterial functional potential but not bacterial taxonomic composition

Abstract Climate warming is known to impact ecosystem composition and functioning. However, it remains largely unclear how soil microbial communities respond to long-term, moderate warming. In this study, we used Illumina sequencing and microarrays (GeoChip 5.0) to analyze taxonomic and functional gene compositions of the soil microbial community after 14 years of warming (at 0.8–1.0 °C for 10 years and then 1.5–2.0 °C for 4 years) in a Californian grassland. Long-term warming had no detectable effect on the taxonomic composition of soil bacterial community, nor on any plant or abiotic soil variables. In contrast, functional gene compositions differed between warming and control for bacterial, archaeal, and fungal communities. Functional genes associated with labile carbon (C) degradation increased in relative abundance in the warming treatment, whereas those associated with recalcitrant C degradation decreased. A number of functional genes associated with nitrogen (N) cycling (e.g., denitrifying genes encoding nitrate-, nitrite-, and nitrous oxidereductases) decreased, whereas nifH gene encoding nitrogenase increased in the warming treatment. These results suggest that microbial functional potentials are more sensitive to long-term moderate warming than the taxonomic composition of microbial community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Discerning the thermodynamic feasibility of the spontaneous coexistence of multiple functional vegetation groups

Can the Second Law of Thermodynamics explain why ecosystems naturally organize into a complex structure composed of multiple vegetation species and functional groups? Ecosystem structure, which refers to the number and type of plant functional groups, is the result of self-organization, or the spontaneous emergence of order from random fluctuations. By considering ecosystems as open thermodynamic systems, we model and study these fluctuations of throughput signatures on short timescales to determine the drivers and characteristics of ecosystem structure. This diagnostic approach allows us to use fluxes of energy and entropy to calculate an ecosystem’s estimated work and understand the thermodynamic behavior of the system. We use a multi-layer canopy-root-soil model to calculate the energy and entropy fluxes of different scenarios for field sites across various climates. At each site, scenarios comprised of native individual plant functional groups and a coexisting multi-group composition scenario including all functional groups observed at the site are compared. Ecosystem-scale calculations demonstrate that entropy fluxes and work efficiency—the work performed for the amount of radiation entering the ecosystem—are greatest in the multi-group scenario when its leaf area is significantly larger than each of its individual functional groups. Thus, we conclude that ecosystems self-organize towards the vegetation structure with the greatest outgoing entropy flux and work efficiency, resulting in the coexistence of multiple functional groups and performing the maximum amount of work within the constraints of locally available energy, water, and nutrients.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Elevated CO 2 shifts the functional structure and metabolic potentials of soil microbial communities in a C 4 agroecosystem

Atmospheric CO 2 concentration is continuously increasing, and previous studies have shown that elevated CO 2 (eCO 2 ) significantly impacts C 3 plants and their soil microbial communities. However, little is known about effects of eCO 2 on the compositional and functional structure, and metabolic potential of soil microbial communities under C 4 plants. Here we showed that a C 4 maize agroecosystem exposed to eCO 2 for eight years shifted the functional and phylogenetic structure of soil microbial communities at both soil depths (0–5 cm and 5–15 cm) using EcoPlate and functional gene array (GeoChip 3.0) analyses. The abundances of key genes involved in carbon (C), nitrogen (N) and phosphorus (P) cycling were significantly stimulated under eCO 2 at both soil depths, although some differences in carbon utilization patterns were observed between the two soil depths. Consistently, CO 2 was found to be the dominant factor explaining 11.9% of the structural variation of functional genes, while depth and the interaction of depth and CO 2 explained 5.2% and 3.8%, respectively. This study implies that eCO 2 has profound effects on the functional structure and metabolic potential/activity of soil microbial communities associated with C 4 plants, possibly leading to changes in ecosystem functioning and feedbacks to global change in C 4 agroecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Planting increases the abundance and structure complexity of soil core functional genes relevant to carbon and nitrogen cycling

Plants have an important impact on soil microbial communities and their functions. However, how plants determine the microbial composition and network interactions is still poorly understood. During a four-year field experiment, we investigated the functional gene composition of three types of soils (Phaeozem, Cambisols and Acrisol) under maize planting and bare fallow regimes located in cold temperate, warm temperate and subtropical regions, respectively. The core genes were identified using high-throughput functional gene microarray (GeoChip 3.0) and functional molecular ecological networks (fMENs) were subsequently developed with the random matrix theory (RMT)-based conceptual framework. Our results demonstrated that planting significantly (P < 0.05) increased the gene alpha-diversity in terms of richness and Shannon – Simpson’s indexes for all three types of soils and 83.5% of microbial alpha-diversity can be explained by the plant factor. Moreover, planting had significant impacts on the microbial community structure and the network interactions of the microbial communities. The calculated network complexity was higher under maize planting than under bare fallow regimes. The increase of the functional genes led to an increase in both soil respiration and nitrification potential with maize planting, indicating that changes in the soil microbial communities and network interactions influenced ecological functioning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Exciton-dominated dielectric function of atomically thin MoS 2 films

We systematically measure the dielectric function of atomically thin MoS 2 films with different layer numbers and demonstrate that excitonic effects play a dominant role in the dielectric function when the films are less than 5–7 layers thick. The dielectric function shows an anomalous dependence on the layer number. It decreases with the layer number increasing when the films are less than 5–7 layers thick but turns to increase with the layer number for thicker films. We show that this is because the excitonic effect is very strong in the thin MoS 2 films and its contribution to the dielectric function may dominate over the contribution of the band structure. We also extract the value of layer-dependent exciton binding energy and Bohr radius in the films by fitting the experimental results with an intuitive model. The dominance of excitonic effects is in stark contrast with what reported at conventional materials whose dielectric functions are usually dictated by band structures. Lastly, the knowledge of the dielectric function may enable capabilities to engineer the light-matter interactions of atomically thin MoS 2 films for the development of novel photonic devices, such as metamaterials, waveguides, light absorbers, and light emitters.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Effects of Atomic Scale Roughness at Metal/insulator Interfaces on Metal Work Function

We evaluate the performance of different van der Waals (vdW) corrected density functional theory (DFT) methods in predicting the structure of perfect interfaces between the LiF(001), MgO(001), NiO(001) films on the Ag(001) surface and the resulting work function shift of Ag(001). The results demonstrate that including the van der Waals interaction is important for obtaining accurate interface structures and the metal work function shift. The work function shift results from a subtle interplay of several effects strongly affected by even small changes in the interface geometry. This makes the accuracy of theoretical methods insufficient for predicting the shift values better than within 0.2 eV. Most of the existing van der Waals corrected functionals are not particularly suited for studying metal/insulator interfaces. The lack of accurate experimental data on the interface geometries and surface rumpling of insulators hampers the calibration of existing and novel density functionals.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2013

ωB97X-V: A 10-parameter, range-separated hybrid, generalized gradient approximation density functional with nonlocal correlation, designed by a survival-of-the-fittest strategy

A 10-parameter, range-separated hybrid (RSH), generalized gradient approximation (GGA) density functional with nonlocal correlation (VV10) is presented in this paper. Instead of truncating the B97-type power series inhomogeneity correction factors (ICF) for the exchange, same-spin correlation, and opposite-spin correlation functionals uniformly, all 16 383 combinations of the linear parameters up to fourth order (m = 4) are considered. These functionals are individually fit to a training set and the resulting parameters are validated on a primary test set in order to identify the 3 optimal ICF expansions. Through this procedure, it is discovered that the functional that performs best on the training and primary test sets has 7 linear parameters, with 3 additional nonlinear parameters from range-separation and nonlocal correlation. The resulting density functional, ωB97X-V, is further assessed on a secondary test set, the parallel-displaced coronene dimer, as well as several geometry datasets. Finally and furthermore, the basis set dependence and integration grid sensitivity of ωB97X-V are analyzed and documented in order to facilitate the use of the functional.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Negative thermal expansion in functional materials: controllable thermal expansion by chemical modifications

Negative thermal expansion (NTE) is an intriguing physical property of solids, which is a consequence of a complex interplay among the lattice, phonons, and electrons. Interestingly, a large number of NTE materials have been found in various types of functional materials. In the last two decades good progress has been achieved to discover new phenomena and mechanisms of NTE. In the present review article, NTE is reviewed in functional materials of ferroelectrics, magnetics, multiferroics, superconductors, temperature-induced electron configuration change and so forth. Zero thermal expansion (ZTE) of functional materials is emphasized due to the importance for practical applications. The NTE functional materials present a general physical picture to reveal a strong coupling role between physical properties and NTE. There is a general nature of NTE for both ferroelectrics and magnetics, in which NTE is determined by either ferroelectric order or magnetic one. In NTE functional materials, a multi-way to control thermal expansion can be established through the coupling roles of ferroelectricity-NTE, magnetism-NTE, change of electron configuration-NTE, open-framework-NTE, and so on. Chemical modification has been proved to be an effective method to control thermal expansion. Finally, challenges and questions are discussed for the development of NTE materials. There remains a challenge to discover a “perfect” NTE material for each specific application for chemists. The future studies on NTE functional materials will definitely promote the development of NTE materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Benchmarking density functional theory predictions of framework structures and properties in a chemically diverse test set of metal-organic frameworks

We compiled a test set of chemically and topologically diverse Metal–Organic Frameworks (MOFs) with high accuracy experimentally derived crystallographic structure data. The test set was used to benchmark the performance of Density Functional Theory (DFT) functionals (M06L, PBE, PW91, PBE-D2, PBE-D3, and vdW-DF2) for predicting lattice parameters, unit cell volume, bonded parameters and pore descriptors. On average PBE-D2, PBE-D3, and vdW-DF2 predict more accurate structures, but all functionals predicted pore diameters within 0.5 Å of the experimental diameter for every MOF in the test set. The test set was also used to assess the variance in performance of DFT functionals for elastic properties and atomic partial charges. The DFT predicted elastic properties such as minimum shear modulus and Young's modulus can differ by an average of 3 and 9 GPa for rigid MOFs such as those in the test set. Moreover, we calculated the partial charges by vdW-DF2 deviate the most from other functionals while there is no significant difference between the partial charges calculated by M06L, PBE, PW91, PBE-D2 and PBE-D3 for the MOFs in the test set. We find that while there are differences in the magnitude of the properties predicted by the various functionals, these discrepancies are small compared to the accuracy necessary for most practical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Improved spatial resolution for spot sampling in thermal desorption atomic force microscopy – mass spectrometry via rapid heating functions

The key to advancing materials is to understand and control their structure and chemistry. However, thorough chemical characterization is challenging since existing techniques characterize only a few properties of the specimen, thereby necessitating multiple measurement platforms to acquire the necessary information. The multimodal combination of atomic force microscopy (AFM) and mass spectrometry (MS) transcends existing analytical capabilities for nanometer scale spatially resolved correlation of the chemical and physical properties of a sample surface. One such hybrid system employs heated AFM cantilevers for thermal desorption (TD) sampling of molecules from a surface and subsequent gas phase ionization and detection of the liberated species by MS. Here in this paper, we report on the use of voltage pulse trains to tailor cantilever heating such that spot sampling size was reduced and mass spectral signal was improved compared to constant voltage, static heating of the cantilever. Desorption efficiency (DE), defined as the quotient of the mass spectral signal intensity and the volume of the desorption crater, was used to judge the effectiveness of a particular tailored heating function. To guide the development and optimization of the heating functions and aid in interpreting experimental results, a 1D finite element model was developed that predicted the cantilever response to different heating functions. Three tailored heating functions that used different combinations, magnitudes, and durations of rectangular voltage pulses, were used for surface spot sampling. The resultant sampling spot size and DE were compared to the same metrics obtained with the conventional method that uses a single voltage pulse. Using a model system composed of a thin film of ink containing pigment yellow 74 as a model system, desorption craters shrunk from 2 μm, using the conventional approach, to 310 nm using the optimum tailored heating function. This same pulsed heating function produced a 381× improvement in the DE and an 8× improvement in spatial resolution compared to the conventional heating approach showing that signal/amount of material sampled was improved significantly by this new cantilever heating strategy.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Evidence for non-electrostatic interactions between a pyrophosphate-functionalized uranyl peroxide nanocluster and iron (hydr)oxide minerals

We report the terminal oxygen atoms of the pyrophosphate groups in the uranyl peroxide nanocluster U 24 Pp 12 ([(UO 2 ) 24 (O 2 ) 24 (P 2 O 7 ) 12 ] 48- ) are not fully satisfied by bond valence considerations and can become protonated. This functionality could allow for specific interactions with mineral surfaces, as opposed to the electrostatically-driven interactions observed between non-functionalized uranyl peroxide nanoclusters and mineral surfaces. The sorption of U 24 Pp 12 to goethite and hematite was studied using batch sorption experiments as a function of U 24 Pp 12 concentration, mineral concentration, and pH. A suite of spectroscopic techniques, scanning electron microscopy, and electrophoretic mobility measurements were used to examine the minerals before and after reaction with U 24 Pp 12 , leading to a proposed conceptual model for U 24 Pp 12 interactions with goethite. The governing rate laws were determined and compared to those previously determined for a non-functionalized uranyl peroxide nanocluster. The rate of uranyl peroxide nanocluster sorption depends on the charge density and functionalized component of the uranyl peroxide cage. Electrophoretic mobility and attenuated total reflectance Fourier transform infrared spectroscopy analyses show that an inner-sphere complex forms between the U 24 Pp 12 cluster and the goethite surface through the terminal pyrophosphate groups, leading to a proposed conceptual model in which U 24 Pp 12 interacts with the triply-coordinated reactive sites on the (110) plane of goethite. Finally, these results demonstrate that the behavior of U 24 Pp 12 at the iron (hydr)oxide-water interface is unique relative to interactions of the uranyl ion and non-functionalized uranyl peroxide nanoclusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Computational insights into the interaction of water with the UiO-66 metal–organic framework and its functionalized derivatives

The UiO-66 metal–organic framework (MOF) has been identified as a promising hydrophilic material for water harvesting. Recent studies show that its water uptake ability at low relative humidity (RH) can be improved by incorporating hydrophilic functional groups into the framework. In this work, we provide computational insights into the adsorption of water in UiO-66 and its functionalized derivatives to reveal the role played by different adsorption sites and functional groups in the adsorption mechanism. We started by developing molecular models for UiO-66, UiO-66-NH 2 , UiO-66-OH, and UiO-66-(OH) 2 compatible with the MB-pol data-driven many-body potential of water. We then benchmarked these models against ab initio data. Here we used these models to perform molecular dynamics simulations and calculate radial distribution functions, IR spectra, and two-dimensional density distribution maps for water in the MOFs. These results consistently show that the μ 3 -OH sites are the preferential interaction sites for water in UiO-66 and all its variants, and the formation of localised water clusters inside the octahedral pores is responsible for the abrupt step in the experimental adsorption isotherms. Furthermore, the presence of functional groups in the framework allows water to cluster in the octahedral pores at lower RH, thus making the MOF a more efficient water harvester. Overall, this study provides molecular-level insights into the pore filling process of UiO-66 and its functionalized derivatives, which are needed for the design of efficient water harvesting materials based on MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Planck 2013 results. IV. Low Frequency Instrument beams and window functions

This paper presents the characterization of the in-flight beams, the beam window functions, and the associated uncertainties for the Planck Low Frequency Instrument (LFI). Knowledge of the beam profiles is necessary for determining the transfer function to go from the observed to the actual sky anisotropy power spectrum. The main beam distortions affect the beam window function, complicating the reconstruction of the anisotropy power spectrum at high multipoles, whereas the sidelobes affect the low and intermediate multipoles. The in-flight assessment of the LFI main beams relies on the measurements performed during Jupiter observations. By stacking the datafrom multiple Jupiter transits, the main beam profiles are measured down to-20 dB at 30 and 44 GHz, and down to-25 dB at 70 GHz. The main beam solid angles are determined to better than 0.2% at each LFI frequency band. The Planck pre-launch optical model is conveniently tuned to characterize the main beams independently of any noise effects. This approach provides an optical model whose beams fully reproduce the measurements in the main beam region, but also allows a description of the beams at power levels lower than can be achieved by the Jupiter measurements themselves. The agreement between the simulated beams and the measured beams is better than 1% at each LFI frequency band. The simulated beams are used for the computation of the window functions for the effective beams. The error budget for the window functions is estimated from both main beam and sidelobe contributions, and accounts for the radiometer bandshapes. The total uncertainties in the effective beam window functions are: 2% and 1.2% at 30 and 44 GHz, respectively (at &ell; &approx; 600), and 0.7% at 70 GHz (at &ell; &approx; 1000).

79 ASTRONOMY AND ASTROPHYSICS↗