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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 OSTI2015

Excitonic couplings between molecular crystal pairs by a multistate approximation

In this paper, we present a diabatization scheme to compute the excitonic couplings between an arbitrary number of states in molecular pairs. The method is based on an algebraic procedure to find the diabatic states with a desired property as close as possible to that of some reference states. In common with other diabatization schemes, this method captures the physics of the important short-range contributions (exchange, overlap, and charge-transfer mediated terms) but it becomes particularly suitable in presence of more than two states of interest. The method is formulated to be usable with any level of electronic structure calculations and to diabatize different types of states by selecting different molecular properties. These features make the diabatization scheme presented here especially appropriate in the context of organic crystals, where several excitons localized on the same molecular pair may be found close in energy. In this paper, the method is validated on the tetracene crystal dimer, a well characterized case where the charge transfer (CT) states are closer in energy to the Frenkel excitons (FE). The test system was studied as a function of an external electric field (to explore the effect of changing the relative energy of the CT excited state) and as a function of different intermolecular distances (to probe the strength of the coupling between FE and CT states). Additionally, we illustrate how the approximation can be used to include the environment polarization effect.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Alternative Fuel Vehicle Usage and Owner Demographics in New York State

With mounting concerns over climate change and the environmental impact of fossil fuels, the United States has witnessed a growing interest in alternative fuel vehicles (AFVs). In 2021, approximately 1.5 million battery EVs (BEVs), 0.8 million plug-in hybrid EVs (PHEVs), and 5.5 million hybrid EVs (HEVs) were registered in the United States. In the state of New York, a total of 51,900 BEVs, 44,600 PHEVs, and 221,600 HEVs were registered in 2021. The current report presents the results of an analysis of AFV adoption patterns in New York State and the rest of the United States based on data from the 2017 National Household Travel Survey (NHTS). Overall, the report reveals the demographics and mobility factors (e.g., household income, homeownership, and trip length) that contribute to the adoption of AFVs. This study provides insights that can inform policy decisions aimed at promoting sustainable transportation solutions.The 2017 NHTS data showed that the percentage of households owning at least one AFV is lower in New York City compared with that in other regions of New York State. From the NHTS samples, of the 25 households that owned at least one BEV in New York State, 15 households (60%) lived within a 5-mile radius, based on the great circle distance, of the nearest charging station, and 23 households (92%) lived within a 10-mile radius of the nearest charging station. Furthermore, among the 40 households in New York State that own at least one PHEV, 48% (19 households) lived within a 5-mile radius of the closest EV charging station, and 83% (33 households) lived within a 10-mile radius of the nearest charging station. The rest of the United States had a higher percentage of households that own at least one AFV compared with that of New York State. A comparison was made between EV adoption levels using NHTS and EValuateNY, which is a tool that gathers statistics on the electric car market in New York State. The estimates obtained from New York State household samples in NHTS were slightly lower than the data provided by EValuateNY. In New York State and the rest of the United States, households with higher incomes tended to have a higher proportion of AFV ownership compared with those with lower incomes. For example, households in New York State earning $\$ $150,000 or more had an approximately 6% share of owning at least one AFV, which was markedly higher than those earning less than $\$ $100,000 (less than 3%). Additionally, homeowners in New York State and the rest of the United States also exhibited a significantly higher share of AFV ownership compared with that of renters. In New York State, households that own at least one AFV tended to travel farther and had longer travel times compared with their counterparts without an AFV. In terms of households with at least one AFV, households with HEVs tended to have more person trips, longer person miles of travel, and more vehicle miles traveled, resulting in longer travel times than that of households with BEVs or PHEVs. Notably, households with AFVs had a slightly lower share of family and personal business trips but a higher share of social and recreational trips compared with households without AFVs. Additionally, households with at least one AFV tended to have a slightly higher share of walking trips than their counterparts without an AFV. However, the comparisons were not statistically significant. These travel patterns observed in New York State were consistent with those observed in other regions of the United States.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Monopole antenna in quantitative near-field microwave microscopy of planar structures

We have developed an analytical model of a near-field microwave microscope based on a coaxial resonator with a sharpened tip probe. The probe interacts with a layered sample that features an arbitrary depth distribution of permittivity. The microscopic tip end with the accumulated charge is regarded as a monopole antenna radiating an electric field in near zone. The impedance of such an antenna is determined within a quasi-static approximation. The proposed model is used for calculating the sample-sensitive parameters of the microscope, specifically, resonance frequency f{sub 0} and quality factor Q{sub 0}, as a function of probe-sample distance h. The theory has been verified experimentally in studies of semiconductor structures, both bulk and thin films. For measurements, we built a ∼2.1 GHz microscope with an effective tip radius of about 100 μm. The theoretical and experimental dependences f{sub 0}(h) and Q{sub 0}(h) were found to be in a good agreement. The developed theory underlies the method for determining sheet resistance R{sub sh} of a semiconductor film on a dielectric substrate proposed in this article. Studies were performed on doped n-GaN films on an Al{sub 2}O{sub 3} substrate. The effective radius and height of the probe determined from calibration measurements of etalon samples were used as the model fitting parameters. For etalon samples, we employed homogeneous sapphire and doped silicon plates. We also performed four-probe dc measurements of R{sub sh}. The corresponding values for samples with R{sub sh} > 1 kΩ were found to be 50% to 100% higher than the microwave results, which are attributed to the presence of microdefects in semiconductor films.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
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 OSTI2016

Systematic errors in low-latency gravitational wave parameter estimation impact electromagnetic follow-up observations

Among the most eagerly anticipated opportunities made possible by Advanced LIGO/Virgo are multimessenger observations of compact mergers. Optical counterparts may be short-lived so rapid characterization of gravitational wave (GW) events is paramount for discovering electromagnetic signatures. One way to meet the demand for rapid GW parameter estimation is to trade off accuracy for speed, using waveform models with simplified treatment of the compact objects’ spin. We report on the systematic errors in GW parameter estimation suffered when using different spin approximations to recover generic signals. Component mass measurements can be biased by >5σ using simple-precession waveforms and in excess of 20σ when non-spinning templates are employed. This suggests that electromagnetic observing campaigns should not take a strict approach to selecting which LIGO/Virgo candidates warrant follow-up observations based on low-latency mass estimates. For sky localization, we find that searched areas are up to a factor of ∼2 larger for non-spinning analyses, and are systematically larger for any of the simplified waveforms considered in our analysis. Distance biases for the non-precessing waveforms can be in excess of 100% and are largest when the spin angular momenta are in the orbital plane of the binary. We confirm that spin-aligned waveforms should be used for low-latency parameter estimation at the minimum. Including simple precession, though more computationally costly, mitigates biases except for signals with extreme precession effects. Our results shine a spotlight on the critical need for development of computationally inexpensive precessing waveforms and/or massively parallel algorithms for parameter estimation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Planetary population synthesis coupled with atmospheric escape: a statistical view of evaporation

We apply hydrodynamic evaporation models to different synthetic planet populations that were obtained from a planet formation code based on the core-accretion paradigm. We investigated the evolution of the planet populations using several evaporation models, which are distinguished by the driving force of the escape flow (X-ray or EUV), the heating efficiency in energy-limited evaporation regimes, or both. Although the mass distribution of the planet populations is barely affected by evaporation, the radius distribution clearly shows a break at approximately 2 R {sub ⊕}. We find that evaporation can lead to a bimodal distribution of planetary sizes and to an 'evaporation valley' running diagonally downward in the orbital distance—planetary radius plane, separating bare cores from low-mass planets that have kept some primordial H/He. Furthermore, this bimodal distribution is related to the initial characteristics of the planetary populations because low-mass planetary cores can only accrete small primordial H/He envelopes and their envelope masses are proportional to their core masses. We also find that the population-wide effect of evaporation is not sensitive to the heating efficiency of energy-limited description. However, in two extreme cases, namely without evaporation or with a 100% heating efficiency in an evaporation model, the final size distributions show significant differences; these two scenarios can be ruled out from the size distribution of Kepler candidates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Data Center Waste Heat as an Emerging Urban Thermal Hazard: First Field Measurements of Neighborhood-Scale Air Temperature Impacts

Data centers are among the fastest-growing sources of concentrated anthropogenic heat in urban environments. Despite heat flux densities that exceed peak solar irradiance by a factor of 2–6, their thermal impacts on adjacent communities have never been directly measured or reported in the peer-reviewed literature. This short communication addresses that gap by presenting the first vehicle-based traverse measurements of air temperature in residential neighborhoods downwind of operational data centers. Five traverses at four facilities in the Phoenix, Arizona metropolitan area, ranging from a 36 MW single-building data center in Mesa to a 169 MW colocation campus in Chandler, reveal downwind air temperature warming as high as 2.2 °C, with average downwind air temperatures 0.7–0.9 °C warmer than corresponding upwind areas. Thermal signatures were detectable at distances up to 500 m from facility perimeters. The 36 MW Mesa facility rejects waste heat equivalent to the electricity consumption of approximately 40,000 households, while the 169 MW Chandler campus is equivalent to over 180,000 households, both concentrated into footprints smaller than a single residential subdivision. With U.S. data center capacity projected to more than double by 2030, these findings establish data center anthropogenic waste heat as a previously undocumented urban thermal hazard demanding attention from the data center and urban planning communities.

Phoenix↗
DOE OSTI2014

Basic parameter estimation of binary neutron star systems by the advanced LIGO/Vigro network

Within the next five years, it is expected that the Advanced LIGO/Virgo network will have reached a sensitivity sufficient to enable the routine detection of gravitational waves. Beyond the initial detection, the scientific promise of these instruments relies on the effectiveness of our physical parameter estimation capabilities. A major part of this effort has been toward the detection and characterization of gravitational waves from compact binary coalescence, e.g., the coalescence of binary neutron stars. While several previous studies have investigated the accuracy of parameter estimation with advanced detectors, the majority have relied on approximation techniques such as the Fisher Matrix which are insensitive to the non-Gaussian nature of the gravitational wave posterior distribution function. Here we report average statistical uncertainties that will be achievable for strong detection candidates (S/N = 20) over a comprehensive sample of source parameters. We use the Markov Chain Monte Carlo based parameter estimation software developed by the LIGO/Virgo Collaboration with the goal of updating the previously quoted Fisher Matrix bounds. We find the recovery of the individual masses to be fractionally within 9% (15%) at the 68% (95%) credible intervals for equal-mass systems, and within 1.9% (3.7%) for unequal-mass systems. We also find that the Advanced LIGO/Virgo network will constrain the locations of binary neutron star mergers to a median uncertainty of 5.1 deg{sup 2} (13.5 deg{sup 2}) on the sky. This region is improved to 2.3 deg{sup 2} (6 deg{sup 2}) with the addition of the proposed LIGO India detector to the network. We also report the average uncertainties on the luminosity distances and orbital inclinations of strong detections that can be achieved by different network configurations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

SHAPER: can you hear the shape of a jet?

The identification of interesting substructures within jets is an important tool for searching for new physics and probing the Standard Model at colliders. Many of these substructure tools have previously been shown to take the form of optimal transport problems, in particular the Energy Mover’s Distance (EMD). In this work, we show that the EMD is in fact the natural structure for comparing collider events, which accounts for its recent success in understanding event and jet substructure. We then present a Shape Hunting Algorithm using Parameterized Energy Reconstruction (SHAPER), which is a general framework for defining and computing shape-based observables. SHAPER generalizes N-jettiness from point clusters to any extended, parametrizable shape. This is accomplished by efficiently minimizing the EMD between events and parameterized manifolds of energy flows representing idealized shapes, implemented using the dual-potential Sinkhorn approximation of the Wasserstein metric. We show how the geometric language of observables as manifolds can be used to define novel observables with built-in infrared-and-collinear safety. We demonstrate the efficacy of the SHAPER framework by performing empirical jet substructure studies using several examples of new shape-based observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

TH-A-19A-04: Latent Uncertainties and Performance of a GPU-Implemented Pre-Calculated Track Monte Carlo Method

Purpose: Assessing the performance and uncertainty of a pre-calculated Monte Carlo (PMC) algorithm for proton and electron transport running on graphics processing units (GPU). While PMC methods have been described in the past, an explicit quantification of the latent uncertainty arising from recycling a limited number of tracks in the pre-generated track bank is missing from the literature. With a proper uncertainty analysis, an optimal pre-generated track bank size can be selected for a desired dose calculation uncertainty. Methods: Particle tracks were pre-generated for electrons and protons using EGSnrc and GEANT4, respectively. The PMC algorithm for track transport was implemented on the CUDA programming framework. GPU-PMC dose distributions were compared to benchmark dose distributions simulated using general-purpose MC codes in the same conditions. A latent uncertainty analysis was performed by comparing GPUPMC dose values to a “ground truth” benchmark while varying the track bank size and primary particle histories. Results: GPU-PMC dose distributions and benchmark doses were within 1% of each other in voxels with dose greater than 50% of Dmax. In proton calculations, a submillimeter distance-to-agreement error was observed at the Bragg Peak. Latent uncertainty followed a Poisson distribution with the number of tracks per energy (TPE) and a track bank of 20,000 TPE produced a latent uncertainty of approximately 1%. Efficiency analysis showed a 937× and 508× gain over a single processor core running DOSXYZnrc for 16 MeV electrons in water and bone, respectively. Conclusion: The GPU-PMC method can calculate dose distributions for electrons and protons to a statistical uncertainty below 1%. The track bank size necessary to achieve an optimal efficiency can be tuned based on the desired uncertainty. Coupled with a model to calculate dose contributions from uncharged particles, GPU-PMC is a candidate for inverse planning of modulated electron radiotherapy and scanned proton beams. This work was supported in part by FRSQ-MSSS (Grant No. 22090), NSERC RG (Grant No. 432290) and CIHR MOP (Grant No. MOP-211360)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

PREEMPT: Scalable Epidemic Interventions Using Submodular Optimization on Multi-GPU Systems

Preventing and slowing the spread of epidemics is achieved through techniques such as vaccination and social distancing. Given practical limitations on the number of vaccines and cost of administration, optimization becomes a necessity. Previous approaches using mathematical programming methods have shown to be effective but are limited by computational costs. In this work, we make several contributions: First, we present a new approach for intervention via maximizing the influence of vaccinated nodes on the network. We call this method \preempt. Next, we prove submodular properties associated with the objective function of our method so that it aids in construction of an efficient greedy approximation strategy. Consequently, we present a new parallel algorithm based on greedy hill climbing for \preempt, and present an efficient parallel implementation for distributed CPU-GPU heterogeneous platforms. Our results demonstrate that \preempt{} is able to achieve a significant reduction (up to 6.75$\times$) in the percentage of people infected on a city-scale network. We also show strong scaling results of \preempt{} on 128 nodes of the Summit supercomputer. Our parallel implementation is able to significantly reduce time to solution, from hours to minutes on large networks. This work represents a first-of-its-kind effort in parallelizing greedy hill climbing and applying it toward devising effective interventions for epidemics.

Minutoli, Marco↗
DOE OSTI2015

CHERENCUBE: Concept definition and implementation challenges of a Cherenkov-based detector block for PET

Purpose: A new concept for a depth-of-interaction (DOI) capable time-of-flight (TOF) PET detector is defined, based only on the detection of Cherenkov photons. The proposed “CHERENCUBE” consists of a cubic Cherenkov radiator with position-sensitive photodetectors covering each crystal face. By means of the spatial distribution of the detected photons and their time of arrival, the point of interaction of the gamma-ray in the crystal can be determined. This study analyzes through theoretical calculations and Monte Carlo simulations the potential advantages of the concept toward reaching a Cherenkov-only detector for TOF-PET with DOI capability. Furthermore, an algorithm for the DOI estimation is presented and the requirements for a practical implementation of the proposed concept are defined. Methods: The Monte Carlo simulations consisted of a cubic crystal with one photodetector coupled to each one of the faces of the cube. The sensitive area of the detector matched exactly the crystal size, which was varied in 1 mm steps between 1 × 1 × 1 mm{sup 3} and 10 × 10 × 10 mm{sup 3}. For each size, five independent simulations of ten thousand 511 keV gamma-rays were triggered at a fixed distance of 10 mm. The crystal chosen was PbWO{sub 4}. Its scintillation properties were simulated, but only Cherenkov photons were analyzed. Photodetectors were simulated having perfect photodetection efficiency and infinite time resolution. For every generated particle, the analysis considered its creation process, parent and daughter particles, energy, origin coordinates, trajectory, and time and position of detection. The DOI determination is based on the distribution of the emission time of all photons per event. These values are calculated as a function of the coordinates of detection and origin for every photon. The common origin is estimated by finding the distribution with the most similar emission time-points. Results: Detection efficiency increases with crystal size from 8.2% (1 × 1 × 1 mm{sup 3}) to 58.6% (10 × 10 × 10 mm{sup 3}) and decreases applying a photon detection threshold of 5/10/20 photons to 6.3%/4.3%/0.7% and 49.3%/30.4%/2.8%, respectively. The detection rate in the six photodetectors is uniform due to the nearly isotropic cone emission. Most cones originated after a photoelectric effect interaction, with two dominating peaks for the kinetic energy of the electron at 422.99 and 441.47 keV. The detection distance between same-event photons defines the spatial resolution of the detector required for individual photon recognition, with 20% of the detected photons having their closest neighbor within a distance of 5% of the length of the cube. Same-event photons are detected within a time window whose width is determined by the crystal size, with values of 30 and 150 ps for a 1 × 1 × 1 mm{sup 3} and a 10 × 10 × 10 mm{sup 3} cube, respectively. The DOI reconstruction has an accuracy of approximately 23% of the length of the cube, with an average value of 2.2 mm for a 10 × 10 × 10 mm{sup 3} CHERENCUBE. Conclusions: The proposed concept requires a detector with high photodetection efficiency. The structure of the sensitive surface of the detector should be a two dimensional array of microcells, able to provide individual detection coordinates and time stamps. The microcell size determines the ability to recognize individual photons, influencing detection efficiency. The 3D DOI recognition relies on the accuracy of the time stamps and detection coordinates, without the need for a recognition of the projected patterns of photons. The refractive index of the material defines a detector intrinsic energy-based rejection of scattered PET events at the cost of reduced sensitivity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Spiers Memorial Lecture : Surface-enhanced Raman spectroscopy: from single particle/molecule spectroscopy to ångstrom-scale spatial resolution and femtosecond time resolution

Four decades on, surface-enhanced Raman spectroscopy (SERS) continues to be a vibrant field of research that is growing (approximately) exponentially in scope and applicability while pushing at the ultimate limits of sensitivity, spatial resolution, and time resolution. This introductory paper discusses some aspects related to all four of the themes for this Faraday Discussion. First, the wavelength-scanned SERS excitation spectroscopy (WS-SERES) of single nanosphere oligomers ( viz. , dimers, trimers, etc. ), the distance dependence of SERS, the magnitude of the chemical enhancement mechanism, and the progress toward developing surface-enhanced femtosecond stimulated Raman spectroscopy (SE-FSRS) are discussed. Second, our efforts to develop a continuous, minimally invasive, in vivo glucose sensor based on SERS are highlighted. Third, some aspects of our recent work in single molecule SERS and the translation of that effort to ångstrom-scale spatial resolution in ultrahigh vacuum tip-enhanced Raman spectroscopy (UHV-TERS) and single molecule electrochemistry using electrochemical (EC)-TERS will be presented. Finally, we provide an overview of analytical SERS with our viewpoints on SERS substrates, approaches to address the analyte generality problem ( i.e. target molecules that do not spontaneously adsorb and/or have Raman cross sections <10 -29 cm 2 sr -1 ), SERS for catalysis, and deep UV-SERS.

Chemistry↗
DOE OSTI2014

A driven similarity renormalization group approach to quantum many-body problems

Applications of the similarity renormalization group (SRG) approach [F. Wegner, Ann. Phys. 506, 77 (1994) and S. D. Głazek and K. G. Wilson, Phys. Rev. D 49, 4214 (1994)] to the formulation of useful many-body theories of electron correlation are considered. In addition to presenting a production-level implementation of the SRG based on a single-reference formalism, a novel integral version of the SRG is reported, in which the flow of the Hamiltonian is driven by a source operator. It is shown that this driven SRG (DSRG) produces a Hamiltonian flow that is analogous to that of the SRG. Compared to the SRG, which requires propagating a set of ordinary differential equations, the DSRG is computationally advantageous since it consists of a set of polynomial equations. The equilibrium distances, harmonic vibrational frequencies, and vibrational anharmonicities of a series of diatomic molecules computed with the SRG and DSRG approximated with one- and two-body normal ordered operators are in good agreement with benchmark values from coupled cluster with singles, doubles, and perturbative triples. Particularly surprising results are found when the SRG and DSRG methods are applied to C{sub 2} and F{sub 2}. In the former case, both methods fail to converge, while in the latter case an unbound potential energy curve is obtained. A modified commutator approximation is shown to correct these problems in the case of the DSRG method.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2014

A stepped leader model for lightning including charge distribution in branched channels

The stepped leader process in negative cloud-to-ground lightning plays a vital role in lightning protection analysis. As lightning discharge usually presents significant branched or tortuous channels, the charge distribution along the branched channels and the stochastic feature of stepped leader propagation were investigated in this paper. The charge density along the leader channel and the charge in the leader tip for each lightning branch were approximated by introducing branch correlation coefficients. In combination with geometric characteristics of natural lightning discharge, a stochastic stepped leader propagation model was presented based on the fractal theory. By comparing simulation results with the statistics of natural lightning discharges, it was found that the fractal dimension of lightning trajectory in simulation was in the range of that observed in nature and the calculation results of electric field at ground level were in good agreement with the measurements of a negative flash, which shows the validity of this proposed model. Furthermore, a new equation to estimate the lightning striking distance to flat ground was suggested based on the present model. The striking distance obtained by this new equation is smaller than the value estimated by previous equations, which indicates that the traditional equations may somewhat overestimate the attractive effect of the ground.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Methane‐derived carbon flow through microbial communities in arctic lake sediments

Summary Aerobic methane ( CH 4 ) oxidation mitigates CH 4 release and is a significant pathway for carbon and energy flow into aquatic food webs. Arctic lakes are responsible for an increasing proportion of global CH 4 emissions, but CH 4 assimilation into the aquatic food web in arctic lakes is poorly understood. Using stable isotope probing ( SIP ) based on phospholipid fatty acids ( PLFA‐SIP ) and DNA ( DNA‐SIP ), we tracked carbon flow quantitatively from CH 4 into sediment microorganisms from an arctic lake with an active CH 4 seepage. When 0.025 mmol CH 4 g −1 wet sediment was oxidized, approximately 15.8–32.8% of the CH 4 ‐derived carbon had been incorporated into microorganisms. This CH 4 ‐derived carbon equated to up to 5.7% of total primary production estimates for Alaskan arctic lakes. Type I methanotrophs, including Methylomonas , Methylobacter and unclassified Methylococcaceae , were most active at CH 4 oxidation in this arctic lake. With increasing distance from the active CH 4 seepage, a greater diversity of bacteria incorporated CH 4 ‐derived carbon. Actinomycetes were the most quantitatively important microorganisms involved in secondary feeding on CH 4 ‐derived carbon. These results showed that CH 4 flows through methanotrophs into the broader microbial community and that type I methanotrophs, methylotrophs and actinomycetes are important organisms involved in using CH 4 ‐derived carbon in arctic freshwater ecosystems.

He, Ruo↗
DOE OSTI2016

SU-F-T-671: Effects of Collimator Material On Proton Minibeams

Purpose: To investigate the dosimetric effects of collimator material on spatially modulated proton minibeams (pMBRT). Methods: pMBRT holds promise to exhibit shallow depth normal-tissue sparing effects similar to synchrotron based microbeams while also retaining potential for uniform dose distributions for tumor targets. TOPAS Monte Carlo simulations were performed for a 5cm thick multislit collimator with 0.3mm slits and 1mm center-to-center spacing for a 50.5MeV proton minibeam while varying collimator material between brass, tungsten, and iron. The collimator was placed both “flush” at the water phantom surface and at 5cm distance to investigate the effects on surface dose, peak-to-valley-dose-ratio (PVDR) and neutron contribution. Results: For flush placement, the neutron dose at the phantom surface for the tungsten collimator was approximately 20% higher than for brass and iron. This was not reflected in the overall surface dose, which was comparable for all materials due to the relatively low neutron contribution of <0.1%. When the collimator was retracted, the overall neutron contribution was essentially identical for all three collimators. Surface dose dropped by ∼40% for all collimator materials with air gap compared to being flush with the phantom surface. This surface dose reduction was at the cost of increase in valley dose for all collimator materials due to increased angular divergence of the mini-beams at the surface and their consequent geometric penumbra at depth. When the collimator was placed at distance from the phantom surface the PVDR decreased. The peak-to-entrance-dose ratio was highest for the iron collimator with 5cm air gap. Conclusion: The dosimetric difference between the collimator materials is minimal despite the relatively higher neutron contribution at the phantom surface for the tungsten collimator when placed flush. The air gap between the collimator and phantom surface strongly influences all dosimetry parameters due to the influence of scatter on the narrow spatial modulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

The LPM effect in sequential bremsstrahlung 2: factorization

The splitting processes of bremsstrahlung and pair production in a medium are coherent over large distances in the very high energy limit, which leads to a suppression known as the Landau-Pomeranchuk-Migdal (LPM) effect. In this paper, we continue analysis of the case when the coherence lengths of two consecutive splitting processes overlap (which is important for understanding corrections to standard treatments of the LPM effect in QCD), avoiding soft-gluon approximations. In particular, this paper analyzes the subtle problem of how to precisely separate overlapping double splitting (e.g. overlapping double bremsstrahlung) from the case of consecutive, independent bremsstrahlung (which is the case that would be implemented in a Monte Carlo simulation based solely on single splitting rates). As an example of the method, we consider the rate of real double gluon bremsstrahlung from an initial gluon with various simplifying assumptions (thick media; q approximation; large N c ; and neglect for the moment of processes involving 4-gluon ver-tices) and explicitly compute the correction Δ dΓ/dx dy due to overlapping formation times.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗