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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Constraints on simulated past Arctic amplification and lapse rate feedback from observations

The Arctic has warmed more rapidly than the global mean during the past few decades. The lapse rate feedback (LRF) has been identified as being a large contributor to the Arctic amplification (AA) of climate change. This particular feedback arises from the vertically non-uniform warming of the troposphere, which in the Arctic emerges as strong near-surface and muted free-tropospheric warming. Stable stratification and meridional energy transport are two characteristic processes that are evoked as causes for this vertical warming structure. Our aim is to constrain these governing processes by making use of detailed observations in combination with the large climate model ensemble of the sixth Coupled Model Intercomparison Project (CMIP6). We build on the result that CMIP6 models show a large spread in AA and Arctic LRF, which are positively correlated for the historical period of 1951–2014. Thus, we present process-oriented constraints by linking characteristics of the current climate to historical climate simulations. In particular, we compare a large consortium of present-day observations to co-located model data from subsets that show a weak and strong simulated AA and Arctic LRF in the past. Our analyses suggest that the vertical temperature structure of the Arctic boundary layer is more realistically depicted in climate models with weak (w) AA and Arctic LRF (CMIP6/w) in the past. In particular, CMIP6/w models show stronger inversions in the present climate for boreal autumn and winter and over sea ice, which is more consistent with the observations. These results are based on observations from the year-long Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic, long-term measurements at the Utqiagvik site in Alaska, USA, and dropsonde temperature profiling from aircraft campaigns in the Fram Strait. In addition, the atmospheric energy transport from lower latitudes that can further mediate the warming structure in the free troposphere is more realistically represented by CMIP6/w models. In particular, CMIP6/w models systemically simulate a weaker Arctic atmospheric energy transport convergence in the present climate for boreal autumn and winter, which is more consistent with fifth generation reanalysis of the European Centre for Medium-Range Weather Forecasts (ERA5). We further show a positive relationship between the magnitude of the present-day transport convergence and the strength of past AA. With respect to the Arctic LRF, we find links between the changes in transport pathways that drive vertical warming structures and local differences in the LRF. This highlights the mediating influence of advection on the Arctic LRF and motivates deeper studies to explicitly link spatial patterns of Arctic feedbacks to changes in the large-scale circulation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Isomer-Selective Detection of Keto-Hydroperoxides in the Low-Temperature Oxidation of Tetrahydrofuran

Keto-hydroperoxides (KHPs) are reactive, partially oxidized intermediates that play a central role in chain-branching reactions during the gas-phase low-temperature oxidation of hydrocarbons and oxygenated species. Although multiple isomeric forms of the KHP intermediate are possible in complex oxidation environments when multiple reactant radicals exist that contain nonequivalent O 2 addition sites, isomer-resolved data of KHPs have not been reported. In this work, we provide partially isomer-resolved detection and quantification of the KHPs that form during the low-temperature oxidation of tetrahydrofuran (THF, cycl. -O–CH 2 CH 2 CH 2 CH 2 –). We describe how these short-lived KHPs were detected, identified, and quantified using integrated experimental and theoretical approaches. The experimental approaches were based on direct molecular-beam sampling from a jet-stirred reactor operated at near-atmospheric pressure and at temperatures between 500 and 700 K, followed by mass spectrometry with single-photon ionization via tunable synchrotron-generated vacuum-ultraviolet radiation, and the identification of fragmentation patterns. The interpretation of the experiments was guided by theoretical calculations of ionization thresholds, fragment appearance energies, and photoionization cross sections. On the basis of the experimentally observed and theoretically calculated ionization and fragment appearance energies, KHP isomers could be distinguished as originating from H-abstraction reactions from either the α-C adjacent to the O atom or the β-C atoms. Temperature-dependent concentration profiles of the partially resolved isomeric KHP intermediates were determined in the range of 500–700 K, and the results indicate that the observed KHP isomers are formed overwhelmingly (~99%) from the α-C THF radical. Furthermore, the comparisons of the partially isomer-resolved quantification of the KHPs to up-to-date kinetic modeling results reveal new opportunities for the development of a next-generation THF oxidation mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Metaphenomic Responses of a Native Prairie Soil Microbiome to Moisture Perturbations

Climate change is causing shifts in precipitation patterns in the central grasslands of the United States, with largely unknown consequences on the collective physiological responses of the soil microbial community, i.e., the metaphenome. Here, we used an untargeted omics approach to determine the soil microbial community’s metaphenomic response to soil moisture and to define specific metabolic signatures of the response. Specifically, we aimed to develop the technical approaches and metabolic mapping framework necessary for future systematic ecological studies. We collected soil from three locations at the Konza Long-Term Ecological Research (LTER) field station in Kansas, and the soils were incubated for 15 days under dry or wet conditions and compared to field-moist controls. The microbiome response to wetting or drying was determined by 16S rRNA amplicon sequencing, metatranscriptomics, and metabolomics, and the resulting shifts in taxa, gene expression, and metabolites were assessed. Soil drying resulted in significant shifts in both the composition and function of the soil microbiome. In contrast, there were few changes following wetting. The combined metabolic and metatranscriptomic data were used to generate reaction networks to determine the metaphenomic response to soil moisture transitions. Site location was a strong determinant of the response of the soil microbiome to moisture perturbations. However, some specific metabolic pathways changed consistently across sites, including an increase in pathways and metabolites for production of sugars and other osmolytes as a response to drying. Using this approach, we demonstrate that despite the high complexity of the soil habitat, it is possible to generate insight into the effect of environmental change on the soil microbiome and its physiology and functions, thus laying the groundwork for future, targeted studies. Climate change is predicted to result in increased drought extent and intensity in the highly productive, former tallgrass prairie region of the continental United States. These soils store large reserves of carbon. The decrease in soil moisture due to drought has largely unknown consequences on soil carbon cycling and other key biogeochemical cycles carried out by soil microbiomes. In this study, we found that soil drying had a significant impact on the structure and function of soil microbial communities, including shifts in expression of specific metabolic pathways, such as those leading toward production of osmoprotectant compounds. This study demonstrates the application of an untargeted multi-omics approach to decipher details of the soil microbial community’s metaphenotypic response to environmental perturbations and should be applicable to studies of other complex microbial systems as well.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Materials characterization: Can artificial intelligence be used to address reproducibility challenges?

Material characterization techniques are widely used to characterize the physical and chemical properties of materials at the nanoscale and, thus, play central roles in material scientific discoveries. However, the large and complex datasets generated by these techniques often require significant human effort to interpret and extract meaningful physicochemical insights. Artificial intelligence (AI) techniques such as machine learning (ML) have the potential to improve the efficiency and accuracy of surface analysis by automating data analysis and interpretation. In this perspective paper, we review the current role of AI in surface analysis and discuss its future potential to accelerate discoveries in surface science, materials science, and interface science. We highlight several applications where AI has already been used to analyze surface analysis data, including the identification of crystal structures from XRD data, analysis of XPS spectra for surface composition, and the interpretation of TEM and SEM images for particle morphology and size. We also discuss the challenges and opportunities associated with the integration of AI into surface analysis workflows. These include the need for large and diverse datasets for training ML models, the importance of feature selection and representation, and the potential for ML to enable new insights and discoveries by identifying patterns and relationships in complex datasets. Most importantly, AI analyzed data must not just find the best mathematical description of the data, but it must find the most physical and chemically meaningful results. In addition, the need for reproducibility in scientific research has become increasingly important in recent years. The advancement of AI, including both conventional and the increasing popular deep learning, is showing promise in addressing those challenges by enabling the execution and verification of scientific progress. By training models on large experimental datasets and providing automated analysis and data interpretation, AI can help to ensure that scientific results are reproducible and reliable. Although integration of knowledge and AI models must be considered for the transparency and interpretability of models, the incorporation of AI into the data collection and processing workflow will significantly enhance the efficiency and accuracy of various surface analysis techniques and deepen our understanding at an accelerated pace.

Materials Science↗
DOE OSTI2026

Search for the chiral magnetic effect through beam energy dependence of charge separation using event shape selection

High-energy, heavy-ion collisions can create local domains of chirality-imbalanced quarks, reflecting the topological features of quantum chromodynamics. The chiral magnetic effect (CME) predicts an electric charge separation of quarks in such topological domains along the magnetic field ($\vec{B}$) generated by the passing of two high-Z nuclei. Here, we use a correlation observable Δ⁢𝛾$^{112}$ between charged meson pairs to detect the CME-induced charge separation and a novel event shape selection (ESS) method to mitigate the background effects related to elliptic flow (𝑣 2 ). The ESS method classifies events based on the emission pattern of final-state particles and determines Δ⁢𝛾$^{112}_{ESS}$ from the zero-flow limit. We reconstruct the $\vec{B}$ field direction from the spectator nucleons, which minimizes backgrounds unrelated to the collective motion of the system. In this work, we report the measurements of Δ⁢𝛾$^{112}$ and a background indicator Δ⁢𝛾$^{132}$ in Au+Au collisions from the Brookhaven National Laboratory Relativistic Heavy Ion Collider (RHIC) Beam Energy Scan phase II and at the top RHIC energy. After background suppression, Δ⁢𝛾$^{132}_{ESS}$ aligns with zero, and Δ⁢𝛾$^{112}_{ESS}$ is reduced to no more than 20% of Δ⁢𝛾$^{112}$. We observe a finite residual charge separation with 2.5⁢𝜎, 3⁢𝜎, and 3.2⁢𝜎 significance in the 20–50% centrality range of Au + Au collisions at 11.5, 14.6, and 19.6 GeV. The results at 17.3 and 27 GeV also show positive values but with a lower significance of 1.3⁢𝜎 and 1.1⁢𝜎, respectively. The corresponding Δ⁢𝛾$^{112}_{ESS}$ values at 7.7, 9.2, and 200 GeV are consistent with zero within uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Real-Time Ammonia and Humidity Monitoring with Ultra-Fast Conductometric Sensors Based on Porphyrin and Phthalocyanine Complexes

Organic semiconductors like porphyrins and phthalocyanines are attracting a wide range of researchers due to their versatile electrical properties and sensing performances in conductometric sensors. In this study, we investigate two types of π-extended porphyrins, which share the same macrocyclic structure but differ in their central metal. These porphyrins are employed as sublayers in bilayer heterojunction devices, with the lutetium bisphthalocyanine complex, LuPc 2 , serving as the common top layer. Remarkably, the central metal in the porphyrin macrocycle significantly influences the solubility of the materials and, consequently, the surface topography of the resulting bilayer heterojunction devices. This structural variation translates into distinct electrical and sensing performances. The device incorporating nickel as metal centre (AM2) demonstrates superior sensitivity towards NH3, with a relative response (RR) of ca. -7% at 90 ppm, an ultra-fast response time of about 9 s, and an impressive limit of detection (LOD) of 250 ppb, whereas, the device that has zinc as metal centre in sublayer (AM3) exhibits RR value of ca. -0.9% at 90 ppm with t 90 of ca. 120 s and LOD of 2 ppm. Both devices are evaluated under randomly varying NH 3 concentration and RH value. The results shows that the AM2-based sensor allows following NH 3 in real-time, while the AM3-based sensor delivers an average concentration over time. On the other hand, the AM2-based sensor exhibits slow kinetics under RH exposure, while the AM3-based sensor precisely mirrors the pattern of random RH changes generated by the software, demonstrating its exceptional responsiveness and accuracy in tracking humidity fluctuations. In conclusion, these findings underscore the critical role of the metal centre in tuning the electrical and sensing properties of the heterojunction devices.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Efficient Thermal Energy Storage with Radial Flow in Packed Beds

Thermal energy storage (TES) is a way to store excess heat in order to generate power later. These types of systems are valuable in the solar industry, where power production can still occur when sunlight is not available. This not only increases system flexibility, it drives down the cost of electricity. One option to store thermal energy is with a packed bed where the storage media resides in a cylindrical container. Flow from one end of the cylinder to the other deposits or recovers heat (axial flow). While a promising technology in terms of energy storage, it exhibits a high pressure drop that lowers overall system efficiency. This project seeks to flow the heat transfer fluid through the storage media in the radial direction. This system offers the potential to retain reasonable thermal performance while substantially lowering the pressure drop. The overall goal was to assess the performance of radial flow experimentally and numerically. Three main designs were considered in this work. The first system utilized a central pipe and four receiving pipes near the wall. The second system utilized a central pipe and an annulus with holes near the wall. The last approach considered segmenting the bed so only select zones would receive flow in the radial direction. In a high-aspect ratio system, the hole patterns in the piping are important for ensuring even flow into the bed, and a major design effort was testing holes patterns to promote even flow. The four pipe system was shown to be not feasible, as preferential flow paths occur that do not allow even and full heating of the packed bed. The annular system can lead to even flow, but the results show this is better accomplished through larger piping instead of considering variations in the hole pattern along the axial length of the pipe. Segmenting the bed can lead to similar exergetic performance when compared to axial or radial flow. However, the pressure drop in the segmented design is likely too high for practical implementation. A baseline commercial design showed exergetic efficiencies for axial, radial, and radial segments of 81.6%, 82.8%, and 80.2%, respectively. Pressure drop for the axial and radial results were 2.36 psi and 2.45 psi, respectively, with segments being nearly an order of magnitude higher. At these large scales, the aspect ratio of the system is important. From a baseline of 0.64, an aspect ratio of 0.32 for radial flow showed an exergetic efficiency of 86% but a pressure drop of 5.39 psi. All of these results provide new insights into packed bed thermal energy storage with radial flow. Competing effects must be considered when designing a radial system, and results show a radial design can show strong thermal results at the expense of system efficiencies from pressure drop. The COMSOL models used in this analysis are available to the public and other researchers. Public benefits include a potential increase in the efficiency of packed bed thermal energy storage. Higher efficiency in storage promotes green energy technologies while reducing costs.

14 SOLAR ENERGY↗
DOE OSTI2020

Analyzing the Validity of Brazilian Testing Using Digital Image Correlation and Numerical Simulation Techniques

Characterizing the mechanical behavior of rocks plays a crucial role to optimize the fracturing process in unconventional reservoirs. However, due to the intrinsic anisotropy and heterogeneity in unconventional resources, fracture process prediction remains the most significant challenge for sustainable and economic hydrocarbon production. During the deformation tracking under compression, deploying conventional methods (strain gauge, extensometer, etc.) is insufficient to measure the deformation since the physical attachment of the device is restricted to the size of the sample, monitoring limited point-wise deformation, producing difficulties in data retrieval, and a tendency to lose track in failure points, etc. Where conventional methods are limited, the application of digital image correlation (DIC) provides detailed and additional information of strain evolution and fracture patterns under loading. DIC is an image-based optical method that records an object with a camera and monitors the random contrast speckle pattern painted on the facing surface of the specimen. To overcome the existing limitations, this paper presents numerical modeling of Brazilian disc tests under quasi-static conditions to understand the full-field deformation behaviors and finally, it is validated by DIC. As the direct tensile test has limitations in sample preparation and test execution, the Brazilian testing principle is commonly used to evaluate indirectly the tensile strength of rocks. The two-dimensional numerical model was built to predict the stress distribution and full-field deformation on Brazilian disc under compression based on the assumptions of a homogenous, isotropic and linear elastic material. The uniaxial compression test was conducted using the DIC technique to determine the elastic properties of Spider Berea sandstone, which were used as inputs for the simulation model. The model was verified by the analytical solution and compared with the digital image correlation. The numerical simulation results showed that the solutions matched reasonably with the analytical solutions where the maximum deviation of stress distribution was obtained as 14.59%. The strain evolution (normal and shear strains) and displacements along the central horizontal and vertical planes were investigated in three distinguishable percentages of peak loads (20%, 40%, and 90%) to understand the deformation behaviors in rock. The simulation results demonstrated that the strain evolution contours consistently matched with DIC generated contours with a reasonable agreement. The changes in displacement along the central horizontal and vertical planes showed that numerical simulation and DIC generated experimental results were repeatable and matched closely. In terms of validation, Brazilian testing to measure the indirect tensile strength of rocks is still an issue of debate. The numerical model of fracture propagation supported by digital image correlation from this study can be used to explain the fracturing process in the homogeneous material and can be extended to non-homogeneous cases by incorporating heterogeneity, which is essential for rock mechanics field applications.

58 GEOSCIENCES↗
DOE OSTI2022

Turbulent transport and reactions of plant-emitted hydrocarbons in an Amazonian rain forest

The processes governing the temporal and spatial patterns of isoprene and monoterpenes emitted by a rainforest in the central Amazon region of Brazil is investigated using a combination of field experiments and numerical simulations. Specifically, Large Eddy Simulations (LES) were used to resolve emissions of isoprene and monoterpenes, turbulent transport, and air chemistry. The coupled chemistry-transport LES included the effects of isoprene and monoterpenes reactivity due to reactions with hydroxyl radical and ozone. The LES results are used to compute vertically resolved budgets of isoprene and monoterpenes in the rainforest canopy in response to emissions, turbulent transport, surface deposition, and air chemistry. Our results indicated that emission and dispersion dominated the isoprene budget as the gases were transported out of the canopy space. In a region limited by nitrogen oxides (with prevailing nitric oxide levels of < 0.5 parts per billion), the in-canopy chemical destruction removed approximately 10% of locally emitted monoterpenes. Hydroxyl radical production rates from the ozonolysis of monoterpenes amounted to ≈ 2 x 10 6 radicals cm -3 s -1 and had similar magnitude to the light-dependent hydroxyl radical formation. One key conclusion was that the Amazonia rainforest abundantly emitted monoterpenes whose in-canopy ozonolysis yielded hydroxyl radicals in amounts similar to the magnitude of light-dependent formation. Reactions of monoterpenes and isoprene with hydroxyl radical and ozone were necessary for the maintenance of the Amazon rainforest canopy as a photochemically active environment suitable to generate oxidants and secondary organic aerosols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Megadrought: A Series of Unfortunate La Niña Events?

Megadroughts are multidecadal periods of aridity more persistent than most droughts during the instrumental period. Paleoclimate evidence suggests that megadroughts occur in many parts of the world, including North America, Central America, western Europe, eastern Asia, and northern Africa. It remains unclear to what extent such megadroughts require external forcing or whether they can arise from internal climate variability alone. A novel statistical–dynamical approach is used to evaluate the possibility that such events arise solely as a function of interannual tropical sea surface temperature (SST) variations. A statistical emulator of tropical SST variations is constructed by using an empirical moving-blocks bootstrap approach that randomly samples multiyear sequences of the observational SST record. This approach preserves the power spectrum, seasonal cycle, and spatial pattern of El Niño-Southern Oscillation (ENSO) but removes longer timescale fluctuations embedded in the observational record. These resampled SST anomalies are then used to force an atmospheric model (the Community Atmosphere Model Version 5). As megadroughts emerge in this run, they should, therefore, be solely a consequence of La Niña sequences combined with internal atmospheric variability and persistence driven by soil moisture storage and other land-surface processes. We indeed find that megadroughts in this simulation have an amplitude-duration rate that is generally indistinguishable from the rate documented in paleoclimate records of the western United States. Our findings support the idea that megadroughts may occur randomly when the unforced climate system evolves freely over a sufficiently long period of time, implying that an unforced unusual but statistically plausible series of La Niña events may be sufficient to generate megadrought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Development of Thin Gap GEM-µRWELL Hybrid Detectors at Jefferson Lab

Over the past few decades, Micro Pattern Gaseous Detector (MPGD) technologies have been increasingly adopted as tracking detector options in High Energy and Nuclear Physics experiments thanks to their good spatial resolution, high-rate capability, stability and more importantly their ability for large area coverage at a relatively low cost compared to the alternative. The thin gap GEM-µRWELL hybrid detector is the latest addition to the MPGD family, that was introduced to vastly improve the spatial resolution capability of gaseous trackers when deployed in the barrel region to cover large angular acceptance of the central tracker in a collider experiment. In this talk, I will re-introduce the concept and motivation for the development of thin gap GEM-µRWELL hybrid technology with an emphasis on the initial studies that establish the proof-of-concept of the technology. I will then discuss the more recent results from latest beam test campaign at Jefferson Lab in May 2025 to study detector efficiency performance with various gas mixtures. I will also briefly present the ongoing activities to develop large area thin gap GEM-µRWELL tracking detectors for the ePIC experiment of the future Electron Ion Collider as well as the exploration of the technology to provide large area tracking options to the muon system of experiments at a future Higgs Factory Collider such as the FCC-ee for example. Finally, I will conclude with some perspectives on new ideas under exploration to develop the next generation of thin gap MPGD technologies with enhanced timing and spatial resolution capabilities

Gnanvo, Kondo [Thomas Jefferson National Accelerat↗
DOE OSTI2021

Shape-Selective Synthesis of Alkylcyclopentenyl Cations in Zeolites and Spectroscopic Distinction of Constitutional Isomers

Alkylcyclopentenyl cations belong to the long-lived intermediates that make up the “hydrocarbon pool” during the catalytic conversion of methanol on zeolites, and recent works show that such cations contribute to olefin and aromatics formation. From liquid phase chemistry, two types of alkylcyclopentenyl cations are known and distinguished by the substituent at the central carbon (C-2) of the allylic system: a more stable type with a methyl group at the C-2 and a less stable type with hydrogen at the C-2. The following three linked objectives are pursued: (i) IR spectroscopic distinction of the different substitution patterns at the allylic system of alkylcyclopentenyl cations, (ii) the role of the zeolite framework in determining the substitution pattern, and (iii) identification of alkylcyclopentenyl cations from precursors relevant to methanol-to-olefins conversion. UV–vis and IR spectroscopy are applied in situ to characterize alkylcyclopentenyl cations produced by adsorption of a pentaalkylcyclopentadiene or by adsorption and thermally induced cyclization of 2,6-dimethyl-2,4,6-octatriene. Prior knowledge of electronic spectra is combined with DFT-computed and experimental IR spectra to establish the frequency of the C–H vibration of the C-2 hydrogen-substituted type, and a characteristic red shift of the asymmetric allylic stretching vibration (Δν ≈ -20 to -30 cm –1 ) after replacing hydrogen by methyl at the central carbon of the allylic system. Although DFT demonstrates that both types of ions fit into medium- and large-pore zeolites and that the C-2 methyl-substituted type is thermodynamically favored even in the pores of the considered zeolites, formation of alkylcyclopentenyl cations is found by UV–vis and IR spectra to be shape-selective. The bulkier C-2 methyl-substituted type is detected in large-pore zeolites (MOR, BEA) and in the intersections of medium-pore zeolites (MFI), whereas in channels of medium size (TON), the less bulky C-2 hydrogen-substituted type is exclusively formed. Finally, the type of ion formed and its overall size are dictated by the zeolite framework and are independent of the precursor; the same type of alkylcyclopentenyl cation as found through cyclization of dimethyloctatriene could be generated from ethene.

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

Inclusive jet and hadron suppression in a multistage approach

We present a new study of jet interactions in the quark-gluon plasma created in high-energy heavy-ion collisions, using a multistage event generator within the jetscape framework. We focus on medium-induced modifications in the rate of inclusive jets and high transverse momentum (high-p T ) hadrons. Scattering-induced jet energy loss is calculated in two stages: a high virtuality stage based on the matter model, in which scattering of highly virtual partons modifies the vacuum radiation pattern, and a second stage at lower jet virtuality based on the LBT model, in which leading partons gain and lose virtuality by scattering and radiation. Coherence effects that reduce the medium-induced emission rate in the matter phase are also included. The TRENTO model is used for initial conditions, and the (2 + 1)dimensional VISHNU model is used for viscous hydrodynamic evolution. Jet interactions with the medium are modeled via 2-to-2 scattering with Debye screened potentials, in which the recoiling partons are tracked, hadronized, and included in the jet clustering. Holes left in the medium are also tracked and subtracted to conserve transverse momentum. Calculations of the nuclear modification factor (R AA ) for inclusive jets and high-p T hadrons are compared to experimental measurements at the BNL Relativistic Heavy Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC). Within this framework, we find that with one extra parameter which codifies the transition between stages of jet modification—along with the typical parameters such as the coupling in the medium, the start and stop criteria, etc.—we can describe these data at all energies for central and semicentral collisions without a rescaling of the jet transport coefficient q.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Mitigation of ICRF—edge plasma interaction in Alcator C-Mod

The parasitic interaction between ion cyclotron range of frequencies (ICRF) waves and the edge plasma has long limited high-power ICRF utilization in magnetically confined fusion plasmas. In this paper, we report on the successful mitigation of this interaction by power tapering a four-strap field-aligned (FA) antenna in the Alcator C-Mod tokamak. With the antenna operated in dipole phasing ($0\pi0\pi$), the ratio of the power coupled by the central two straps ($P_\mathrm {cent}$) to the power coupled by the outer two straps was varied at fixed total coupled ICRF power ($P_\mathrm {tot}$). With $P_\mathrm {cent}$/$P_\mathrm {tot} \approx 0.8-0.9$, no enhancement of the plasma potential was measured despite 1 MW of coupled ICRF power. When the antenna is powered, energy deposition increases on its four corners and on neighboring limiter tiles magnetically connected to some of those corners. The energy deposited on the antenna and limiter is minimized together with near-field plasma potentials. Additionally, we show that deviation from $P_\mathrm {cent}$/$P_\mathrm {tot} \approx 0.8$ enhances wave-plasma interactions in places not magnetically connected to the antenna. These far-field effects are correlated with changes in the antenna spectrum. Hence, on C-Mod, near-field and far-field interactions were minimized for about the same range of $P_\mathrm {cent}$/$P_\mathrm {tot}$. Optimal power tapering was also found to improve ICRF heating efficiency and facilitate H-mode access. Finally, we show that the heat flux pattern on the toroidally aligned antennas reverses with the direction of the RF-induced E×B flow in front of the antenna, a correlation not observed for the FA antenna. We argue that the RF-induced E×B flow, which carries high-density plasma from the near-SOL, is aligned with the FA antenna and does not intercept its corners, where the plasma potential is large. This could explain the previously reported smaller impurity generation by the FA antenna (Wukitch et al 2013 Phys. Plasmas 20 056117).

Alcator C-Mod↗
DOE OSTI2019

Understanding the Response of Photosynthetic Metabolism in Tropical Forests to Seasonal Climate Variations

We propose a study focused on the basic question: What controls the response of photosynthesis in Amazonian forests to seasonal variations in climate? This question, despite its apparent simplicity, remains difficult for modern earth system models to answer, and is also the subject of continuing controversy in the remote-sensing literature. For example, in the modeling arena, four cutting-edge earth system models (ESM’s) show significant divergence in their seasonal patterns of photosynthesis from observed whole-system photosynthetic fluxes at two sites in the central Amazon. The overall objective of the project is to guide improvements in earth system models of tropical forest photosynthesis by collecting and integrating a suite of observations to 1) test several hypotheses (three core, conceptual hypotheses for explaining observed photosynthetic seasonality and a methodological hypotheses for scaling from leaves to canopy with hyperspectral cameras), and 2) perform a synthesis activity that applies our empirical work to earth system models of terrestrial carbon cycling. The project will provide an extensive suite of new and unique datasets that enable us to fill, through advanced modeling techniques and analysis, critical knowledge gaps in current understanding of what controls the response of canopy photosynthesis and related functions in Amazonian forests to seasonal variation in climate. Three major types of datasets and data products will be delivered: (1) in situ leaf and tree-scale measurements from intensive ecophysiological and ecohydological field campaigns, (2) time-series observations of leaf-to-crown scale forest reflectance properties and atmospheric radiation from two innovative, ground-based imaging sensors (respectively, the Hyperspectral Vegetation Imaging System and the High Dynamic Range All-Sky Imaging System), and (3) results from state-of-the-art models of 3-dimensional canopy processes for radiative transfer and photosynthesis that integrate and link our observations to tropical forest processes. These data products and the improved knowledge we achieve with them will contribute to testing and improving the treatment of tropical forest processes in ESMs. They will contribute data to and leverage related data from of the GOAmazon campaign, and make significant contributions to support the overall goals of GOAmazon. This work will also help establish a foundation for the Next Generation Ecosystem Experiments (NGEE) in the Tropics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Climate-Related Trends of Within-Storm Intensities Using Dimensionless Temporal-Storm Distributions

Huff curves are probabilistic time distributions of rainfall expressed as dimensionless cumulative percentages of storm depth and duration. Previous studies have documented development factors, spatial robustness, and the utility of Huff curves in practical applications. However, the effects of trending rainfall on Huff curve intensity patterns have not yet been studied. As such, the goal of this paper is to fill this gap by studying Huff curve patterns in a watershed with demonstrated increasing trends of temperature and precipitation, with the intention that it can be generalized to other areas in the US and the world. To achieve this goal, the high temporal resolution precipitation data collected from a high spatial density, 72-year precipitation-gauge network on the 4.25-km 2 North Appalachian Experimental Watershed in east-central Ohio were used. Seasonal storm pattern trends from 1939 to 2010 were investigated using dimensionless depth (with the frequency of 50%, $d_{50}$) and the curve variability $(V = d_{80} - d_{20})$ at three dimensionless within-storms time periods (three verticals). The Spearman rank correlation procedure (correlation coefficient, ρ and significance probability, p) was used to statistically determine trends over time using 8 periods of 4-season sets of Huff curves over the 72 years. Two averages of ρ and p were computed: (1) by averaging the individual ρ and p obtained from 10 gauges (AvgI); and (2) by grouped averaging of all individual gauge values of $d_{50}$ and V and then computing ρ and p (AvgG). The test results of individual gauges showed that 4 cases for $d_{50}$ and 23 cases for V were significant for all seasons and verticals (total of 120 cases for each variable). The test results of AvgI for $d_{50}$ and V and AvgG for $d_{50}$ showed no significant trends in all seasons and verticals. Only the AvgG for V led to a significant trend for V in spring and fall at different times within storm patterns. The data do not provide sufficient evidence at the p=0.05 significance level to reject the null hypothesis of unchanging position of the dimensionless depth of the 50% Huff curves for individual or averages for all seasons and verticals. Also, there is insufficient evidence to reject the null hypothesis of unchanging variability, V, using the average ρ of individual gauges (AvgI for V) for all seasons and verticals. AvgG results showed a significant trend in V; however, this analysis may be affected by the nonindependence of storm data. The results suggest that it is likely that there is little if any effect of trending climate over approximately 70 years on Huff curve patterns. The results of this study add to the robustness characteristics of Huff curves and to their potential use in hydrological practice as design storms, as the foundation of stochastic storm generation, and for storm disaggregation, and they deserve further investigation. These different forms of inputs to watershed models have the potential to improve runoff estimation. The results suggest that, if verified in other studies, they have applicability to provide useful stationary precipitation patterns across the US and other areas of the world in areas of nonstationary climate. Also, individual rain gauge data may not be representative of trends even over small areas, and seasonal differences were noticeable as found in other studies. Recommendations are provided.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A Knowledge Graph Approach for the Secondary Use of Cancer Registry Data

Population-based central cancer registries collect valuable structured and unstructured data primarily for cancer surveillance and research, enhancing insights into clinical features associated with cancer occurrence, cancer treatment, and cancer outcomes to guide interventions which reduce the cancer burden. Cancer registries primarily collect data on (1) cancer type (case or tumor); (2) patient demographics such as age, gender, and residential address at time of diagnosis; (3) planned first course of treatment; and (4) date of last contact, vital status, and cause of death. Cancer registry data is dynamic, structured data, which is extracted from many unstructured sources such as electronic healthcare records, and consolidated for reporting and other purposes. While available advanced analytic tools such as SEER*Stat have the ability to build SAS queries, we, however, explore an innovative knowledge graph approach to organizing cancer registry data for advanced analytics and visualization, which has unique advantages over approaches of existing tools. This innovative knowledge graph approach semantically enriches the data and easily enables linkage with third-party data, which can better explain variation in outcomes. We have developed a prototype knowledge graph based on data from the Louisiana Tumor Registry and other publicly available datasets including Behavioral Risk Factor Surveillance System, Clinical Trials, DBpedia, GeoNames, Rural-Urban Continuum Codes, and Semantic MEDLINE. The resource description framework (RDF) data model was selected to represent our knowledge graph, which contains more than 25 billion triples and is ~4TB in storage size. To exhibit the benefits of the knowledge graph approach, we used scenario specific queries, which find the relationships between cancer treatment sequences and outcomes. To illustrate its ease of use in iterative analysis, the knowledge graph was linked to external datasets for performing complex queries across multiple datasets. In addition, we used knowledge graphs to identify data discrepancies and to handle schema changes. Finally, we visualized the knowledge graph to discover data patterns. Our results demonstrate this graph-based solution enables cancer researchers to execute complex queries and more easily perform iterative analyses to improve understanding of cancer registry data. In the future, we would like to use high-performance computing (HPC) resources for faster-generating hypotheses with clinical potential from our knowledge graph.

Hasan, S M Shamimul↗
DOE OSTI2018

Developing Novel Multifunctional Materials for High-Efficiency Electrical Energy Storage

This is the final report for the program “Developing Novel Multifunctional Materials for High-efficiency Electrical Energy Storage”, funded by The U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL), and performed by University of Tennessee, from September 01, 2013 to August 31, 2018. Securing a sustainable energy economy by developing affordable and clean energy from renewable energy is a central element to the mission of DOE/NETL. To further this mission, NETL funds research and development of novel multifunctional materials that can be used for high-efficiency electrical energy storage. The main objective of this research program is to conduct fundamental and applied research that lead to successful development and demonstration of novel multifunctional materials, which can improve the efficiency and reduce the cost of hydrogen production with water electrolysis. The specific objectives of this research program include: 1) Design, fabrication and demonstration of thin/well-tunable liquid/gas diffusion layer (TT-LGDLs) with different pore morphologies, including pore sizes and pore porosities. 2) Development of comprehensive computational models of proton exchange membrane water electrolyzer cell (PEMECs) for the investigation of influence of different operating conditions and physical design parameters on its performance. 3) Surface modification of TT-LGDLs for better catalyst access and product/reactant removal, and smaller interfacial contact resistance (ICR). To achieve the above challenging goals, a multidisciplinary research team was formed to work on fundamental and applied research on the following three major technical areas: 1) Design, fabrication and demonstration of thin/well-tunable LGDLs (TT-LGDLs) by using photolithography and wet etching of thin titanium (Ti) foils. During the project period, the team has successfully fabricated TT-LGDLs with different pore morphologies, including pore sizes and pore porosities. The manufacturing steps mainly include cleaning thin Ti foil, supporting the foils, applying photoresist, patterning the photoresist with designed mask, exposing and developing, etching, removing photoresist, and lift-off and cleaning. The manufactured TT-LGDLs were characterized with optical microscopies and scanning electron microscopies. Their pore morphologies, including pore size and porosity, were derived based on advanced image process. The feasibility for scale-up manufacturing has been demonstrated. The TT-LGDLs have been successfully investigated for water splitting in PEMECs, which showing better performance than their counterparts fabricated with the traditional fiber-based materials. 2) Comprehensive computational modeling of a PEMEC. A comprehensive computational model has been successfully developed, and the influence of different operating conditions and physical design parameters on its performance has been investigated, including operating temperature, pressure, exchange current density, electrode thickness, membrane thickness, and interfacial resistance. Results obtained from the present model provide a comprehensive understanding of design parameter effects and consequently improve the design/performance in a PEMEC. 3) Surface modification of TT-LGDLs. The proposed surface modifications of TT-LGDLs by sputter coating and/ electroplating have been successfully demonstrated. It has been found that the performance of PEMECs can be improved by both methods, and the thickness of the electroplated gold thin layer has limited effects on the performance. With the help of the surface modifications, the PEMECs achieved the best ever performance compared with the public literatures. In addition to completion of the proposed method, microporous layers (MPLs) with both irregular micro and sphere nano titanium particles on novel TT-LGDLs was developed for the first time. The MPLs were fabricated by a low-temperature air spraying method, which provide a better catalyst access and product/reactant removal. In summary, under the close collaborations among the research team, all the tasks have been completed and the proposed research objectives have been fulfilled. All the technical milestones have been achieved and the project has been completed successfully. The technical breakthroughs obtained under this project provide novel LGDLs with well-tunable pore morphologies that can significantly improve the performance of water splitting and energy storage. This development can be directly used in existing and next generation energy storage and fuel systems.

08 HYDROGEN↗