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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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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Synergistic Multisites Fe 2 Mo 6 S 8 Electrocatalysts for Ambient Nitrogen Conversion to Ammonia

Electrochemical hydrogenation of N 2 under ambient conditions is attractive for sustainable and distributable NH 3 production but is limited by the lack of selective electrocatalysts. In this work, we describe active site motifs based on the Chevrel phase chalcogenide Fe 2 Mo 6 S 8 that exhibit intrinsic activities for converting N 2 to NH 3 in aqueous electrolytes. Despite having a very low specific surface area of ~2 m 2 /g, this catalyst exhibited a Faradaic efficiency of 12.5% and an average rate of 70 μg h –1 mg cat –1 for NH 3 production at -0.20 V vs RHE. Such activities were attributed to the unique composition and structure of Fe 2 Mo 6 S 8 that provide synergistic multisites for activating and associating key reaction intermediates. Specifically, Fe/Mo sites assist adsorption and activation of N 2 , whereas S sites stabilize hydrogen intermediate H ad * for N 2 hydrogenation. Fe in Fe 2 Mo 6 S 8 enhances binding of S with H ad * and thus inhibits the competing hydrogen evolution reaction. The spatial geometry of Fe, Mo, and S sites in Fe 2 Mo 6 S 8 promotes conversion of N 2 –H ad * association intermediates, reaching a turnover frequency of ~0.23 s –1 for NH 3 production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Bond Selective Photochemistry at Metal Nanoparticle Surfaces: CO Desorption from Pt and Pd

The use of visible photon fluxes to influence catalytic reactions on metal nanoparticle surfaces has attracted attention based on observations of reaction mechanisms and selectivity not observed under equilibrium heating. These observations suggest that photon fluxes can selectively impact the rates of certain elementary steps, creating nonequilibrium energy distributions among various reaction pathways. However, quantitative studies validating these hypotheses on metal nanoparticle surfaces are lacking. Here, we examine the influence of continuous wave visible photon fluxes on the CO desorption rates from 1 to 2 nm diameter Pt and Pd nanoparticle surfaces supported on γ-Al 2 O 3 . Temperature-programmed desorption measurements quantified via diffuse reflectance infrared Fourier transform spectroscopy demonstrate that visible photon fluxes significantly enhanced the rate of CO desorption from Pt nanoparticles in a wavelength-dependent manner. 440 nm photons most efficiently promoted CO desorption from Pt nanoparticle surfaces, aligning with the excitation energy for the interfacial electronic transition within the Pt–CO bond. Conversely, visible photon fluxes had no measurable influence on CO desorption rates from Pd nanoparticle surfaces after accounting for photon-induced heating. Density functional theory calculations demonstrate that the Pt–CO bond exhibits a narrower LUMO resonance, stronger coupling between the photoexcitation and forces induced on the metal–C bond, and vibrational energy dissipation that more effectively couples to desorption as compared to Pd–CO. These results demonstrate the specificity photons provide in facilitating chemical reactions on metal nanoparticle surfaces and substantiate the idea that photon fluxes can steer processes and outcomes of catalytic reactions in ways not achievable by equilibrium heating.

desorption↗
DOE OSTI2026

Sequential Fracture Activation and Stress Evolution During EGS Stimulation at Utah FORGE Revealed by Waveform Cross‐Correlation

Mapping fracture networks in Enhanced Geothermal Systems (EGS) is essential for optimizing reservoir performance, yet complex fracture evolution during stimulation remains difficult to resolve. This study examines the evolution of microseismicity and fracture networks during stage 3 of the 2022 EGS stimulation at the Utah Frontier Observatory for Research in Geothermal Energy site. We map the fracture network represented by 20 clusters of seismic events identified by waveform similarities with cross-correlation. We characterize their geometric properties such as strike, dip, length, and width, and analyze the time evolution of activated fractures. The results reveal a systematic fracture evolution: early activation of pre-existing natural fractures, complex network development during peak injection, and continued activation of less favorably oriented fractures post-injection. Magnitude calibration using the Principal Component Analysis of cross-correlated waveforms improves relative amplitude measurements, refining estimations of the Gutenberg-Richter b-values with spatial variations in b-values suggesting stress re-distribution across the stimulated area. Analysis of the stress state of selected fractures further shows that fractures requiring higher excess pore pressure primarily activate at the end of injection and post-injection, highlighting stress transfer due to pore pressure as a dominant triggering mechanism. These findings provide insights into fracture propagation, stress evolution, and seismic hazard assessment in EGS reservoirs.

Asirifi, Richard [Texas A & M Univ., College Stati↗
DOE OSTI2025

Perovskite-driven solar C 2 hydrocarbon synthesis from CO 2

Photoelectrochemistry (PEC) presents a direct pathway to solar fuel synthesis by integrating light absorption and catalysis into compact electrodes. Yet, PEC hydrocarbon production remains elusive due to high catalytic overpotentials and insufficient semiconductor photovoltage. Here we demonstrate ethane and ethylene synthesis by interfacing lead halide perovskite photoabsorbers with suitable copper nanoflower electrocatalysts. The resulting perovskite photocathodes attain a 9.8% Faradaic yield towards C 2 hydrocarbon production at 0 V against the reversible hydrogen electrode. The catalyst and perovskite geometric surface areas strongly influence C 2 photocathode selectivity, which indicates a role of local current density in product distribution. The thermodynamic limitations of water oxidation are overcome by coupling the photocathodes to Si nanowire photoanodes for glycerol oxidation. These unassisted perovskite–silicon PEC devices attain partial C 2 hydrocarbon photocurrent densities of 155 µA cm -2 , 200-fold higher than conventional perovskite–BiVO 4 artificial leaves for water and CO 2 splitting. These insights establish perovskite semiconductors as a versatile platform towards PEC multicarbon synthesis.

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

Stragglers of the thick disc

Young alpha-rich (YAR) stars have been detected in the past as outliers to the local age - [α/Fe] relation. These objects are enhanced in α-elements, but they are apparently younger than typical thick disc stars. Here, we study the global kinematics and chemical properties of YAR giant stars in the APOGEE DR17 survey and show that they have properties similar to those of the standard thick disc stellar population. This leads us to conclude that YAR are rejuvenated thick disc objects, and the most likely explanation is that they are evolved blue stragglers. This is confirmed by their position in the Hertzsprung–Russel diagram (HRD). Extending our selection to dwarfs allowed us to obtain the first general straggler distribution in an HRD of field stars. We also compared the elemental abundances of our sample with those of standard thick disc stars and found that our YAR stars are shifted in oxygen, magnesium, sodium, and the slow neutron-capture element cerium. Although we detected no sign of binarity for most objects, the enhancement in cerium may be a signature of a mass transfer from an asymptotic giant branch companion. The most massive YAR stars suggest that mass transfer from an evolved star may not be the only plausible formation pathway and that other scenarios, such as collision or coalescence, should be considered.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Monolithically integrated mid-infrared sensor using narrow mode operation and temperature feedback

A method to improve the sensitivity and selectivity of a monolithically integrated mid-infrared sensor using a distributed feedback laser (DFB) is presented in this paper. The sensor is based on a quantum cascade laser/detector system built from the same epitaxial structure and with the same fabrication approach. The devices are connected via a dielectric-loaded surface plasmon polariton waveguide with a twofold function: it provides high light coupling efficiency and a strong interaction of the light with the environment (e.g., a surrounding fluid). The weakly coupled DFB quantum cascade laser emits narrow mode light with a FWHM of 2 cm{sup −1} at 1586 cm{sup −1}. The room temperature laser threshold current density is 3 kA∕cm{sup 2} and a pulsed output power of around 200 mW was measured. With the superior laser noise performance, due to narrow mode emission and the compensation of thermal fluctuations, the lower limit of detection was expanded by one order of magnitude to the 10 ppm range.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

A tight-coupling scheme sharing minimum information across a spatial interface between gyrokinetic turbulence codes

A new scheme that tightly couples kinetic turbulence codes across a spatial interface is introduced. This scheme evolves from considerations of competing strategies and down-selection. It is found that the use of a composite kinetic distribution function and fields with global boundary conditions as if the coupled code were one makes the coupling problem tractable. In contrast, coupling the two solutions from each code across the overlap region is found to be more difficult due to numerical dephasing of the turbulent solutions between two solvers. Finally, another advantage of the new scheme is that the data movement can be limited to the 3D fluid quantities, instead of higher dimensional kinetic information, which is computationally more efficient for large scale simulations on leadership class computers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Interpreting the electron temperature inferred from x-ray continuum emission for direct-drive inertial confinement fusion implosions on OMEGA

In this paper, we present a theoretical framework for interpreting the hot-spot electron temperature ($T_e$) inferred from hard (10- to 20-keV) x-ray continuum emission for inertial confinement fusion implosions on OMEGA. We first show that the inferred $T_e$ represents the emission-weighted, harmonic mean of the hot-spot $T_e$ distribution, both spatially and temporally. A scheme is then provided for selecting a photon energy of which the emission weighting approximates neutron weighting. Simulations are then used to quantify the predicted relationship between the inferred T e , neutron-weighted T i , and implosion performance on OMEGA. In an ensemble of 1-D simulations, it was observed that hot-spot thermal nonequilibrium precluded a sufficiently unique mapping between the inferred $T_e$ and neutron-weighted T i . In 3-D simulations with low-harmonic-mode perturbations (i.e., laser beam power imbalance, target offset, and beam port geometry departures from spherical symmetry) and laser imprint (1 max = 200).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Implications of CMS analysis of photon-photon interactions for photon PDFs

As part of a recent analysis of exclusive two-photon production of W + W – pairs at the LHC, the CMS experiment used di-lepton data to obtain an “effective” photon-photon luminosity. We show how the CMS analysis on their 8 TeV data, along with some assumptions about the likelihood for events in which the proton breaks up to pass the selection criteria, can be used to significantly constrain the photon parton distribution functions, such as those from the CTEQ, MRST, and NNPDF collaborations. We compare the data with predictions using these photon distributions, as well as the new LUXqed photon distribution. We study the impact of including these data on the NNPDF2.3QED, NNPDF3.0QED and CT14QEDinc fits. We find that these data place a useful and complementary cross-check on the photon distribution, which is consistent with the LUXqed prediction while suggesting that the NNPDF photon error band should be significantly reduced. Additionally, we propose a simple model for describing the two-photon production of W + W – at the LHC. In conclusion, using this model, we constrain the number of inelastic photons that remain after the experimental cuts are applied.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

The impact of spectroscopic incompleteness in direct calibration of redshift distributions for weak lensing surveys

ABSTRACT Obtaining accurate distributions of galaxy redshifts is a critical aspect of weak lensing cosmology experiments. One of the methods used to estimate and validate redshift distributions is to apply weights to a spectroscopic sample, so that their weighted photometry distribution matches the target sample. In this work, we estimate the selection bias in redshift that is introduced in this procedure. We do so by simulating the process of assembling a spectroscopic sample (including observer-assigned confidence flags) and highlight the impacts of spectroscopic target selection and redshift failures. We use the first year (Y1) weak lensing analysis in Dark Energy Survey (DES) as an example data set but the implications generalize to all similar weak lensing surveys. We find that using colour cuts that are not available to the weak lensing galaxies can introduce biases of up to Δz ∼ 0.04 in the weighted mean redshift of different redshift intervals (Δz ∼ 0.015 in the case most relevant to DES). To assess the impact of incompleteness in spectroscopic samples, we select only objects with high observer-defined confidence flags and compare the weighted mean redshift with the true mean. We find that the mean redshift of the DES Y1 weak lensing sample is typically biased at the Δz = 0.005−0.05 level after the weighting is applied. The bias we uncover can have either sign, depending on the samples and redshift interval considered. For the highest redshift bin, the bias is larger than the uncertainties in the other DES Y1 redshift calibration methods, justifying the decision of not using this method for the redshift estimations. We discuss several methods to mitigate this bias.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Evidence of galaxy assembly bias in SDSS DR7 galaxy samples from count statistics

We present observational constraints on the galaxy–halo connection, focusing particularly on galaxy assembly bias from a novel combination of counts-in-cylinders statistics, P(N CIC ), with the standard measurements of the projected two-point correlation function w p (r p ), and number density n gal of galaxies. We measure n gal , w p (r p ), and P(N CIC ) for volume-limited, luminosity-threshold samples of galaxies selected from SDSS DR7, and use them to constrain halo occupation distribution (HOD) models, including a model in which galaxy occupation depends upon a secondary halo property, namely halo concentration. We detect significant positive central assembly bias for the M r < -20.0 and M r <-19.5 samples. Central galaxies preferentially reside within haloes of high concentration at fixed mass. Positive central assembly bias is also favoured in the M r < -20.5 and M r < -19.0 samples. We find no evidence of central assembly bias in the M r < -21.0 sample. We observe only a marginal preference for negative satellite assembly bias in the M r < -20.0 and M r < -19.0 samples, and non-zero satellite assembly bias is not indicated in other samples. Our findings underscore the necessity of accounting for galaxy assembly bias when interpreting galaxy survey data, and demonstrate the potential of count statistics in extracting information from the spatial distribution of galaxies, which could be applied to both galaxy–halo connection studies and cosmological analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Search for gamma-ray spectral lines with the Fermi Large Area Telescope and dark matter implications

Weakly interacting massive particles (WIMPs) are a theoretical class of particles that are excellent dark matter candidates. WIMP annihilation or decay may produce essentially monochromatic γ rays detectable by the Fermi Large Area Telescope (LAT) against the astrophysical γ -ray emission of the Galaxy. We have searched for spectral lines in the energy range 5–300 GeV using 3.7 years of data, reprocessed with updated instrument calibrations and an improved energy dispersion model compared to the previous Fermi-LAT Collaboration line searches. We searched in five regions selected to optimize sensitivity to different theoretically motivated dark matter density distributions. We did not find any globally significant lines in our a priori search regions and present 95% confidence limits for annihilation cross sections of self-conjugate WIMPs and decay lifetimes. Our most significant fit occurred at 133 GeV in our smallest search region and had a local significance of 3.3 standard deviations, which translates to a global significance of 1.5 standard deviations. We discuss potential systematic effects in this search, and examine the feature at 133 GeV in detail. We find that the use both of reprocessed data and of additional information in the energy dispersion model contributes to the reduction in significance of the linelike feature near 130 GeV relative to significances reported in other works. We also find that the feature is narrower than the LAT energy resolution at the level of 2 to 3 standard deviations, which somewhat disfavors the interpretation of the 133 GeV feature as a real WIMP signal.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

An integrated integral projection model ( IPM 2 ) to disentangle size‐structured harvest and natural mortality

Abstract Body size is one of the most important traits governing individual‐level demographic rates and modulating population‐level processes. Multiple size‐dependent demographic rates can simultaneously change population structure, so distinguishing their individual contributions to overall population dynamics remains a challenge. Disentangling size‐dependent harvest rates from other demographic rates is critical for assessing the impact of removal on populations of invasive species. Inference about invasive populations can be difficult, however, as observations are often collected opportunistically as part of removal programs, rather than experimentally designed. Yet accurate inference is essential for understanding the feasibility of population suppression and optimising management decisions. We develop an integrated integral projection model (IPM 2 ) that leverages the strengths of the integrated population model and integral projection model to enable inference about complex, size‐structured demographic rates from imperfect observations. We apply the IPM 2 in the context of invasive European green crab ( Carcinus maenas ), a species for which individual body size strongly regulates both the observation‐generating process and latent, population dynamics. The IPM 2 facilitates the distinct estimation of green crab size‐structured harvest and natural mortality rates, parameters for which no explicit data is collected and that are unidentifiable in component datasets of the integrated population model. The model represents how the green crab population changes over time, providing the first estimates of size‐structured abundance of this high‐priority species. By forecasting the stable size distribution and equilibrium population size under varying removal efforts, we demonstrate that extremely high levels of removal effort can reduce the equilibrium green crab population size. Yet these high mortality rates also shift the stable size distribution and increase the equilibrium abundance of smaller crabs, since size‐selective removal alters intraspecific interactions. The ecological outcome of this shift in size structure will be variable, as green crab size modulates only some of its interactions with other species. These results highlight the value of the IPM 2 framework for inferring complex population dynamics with information needs that outpace information in individual observational datasets, providing a path forward for accurate assessment of conservation programs.

Keller, Abigail G. [Department of Environment Scie↗
DOE OSTI2023

Continental Scale Hydrostratigraphy: Basin‐Scale Testing of Alternative Data‐Driven Approaches

Abstract Integrated hydrological modeling is an effective method for understanding interactions between parts of the hydrologic cycle, quantifying water resources, and furthering knowledge of hydrologic processes. However, these models are dependent on robust and accurate datasets that physically represent spatial characteristics as model inputs. This study evaluates multiple data‐driven approaches for estimating hydraulic conductivity and subsurface properties at the continental‐scale, constructed from existing subsurface dataset components. Each subsurface configuration represents upper (unconfined) hydrogeology, lower (confined) hydrogeology, and the presence of a vertical flow barrier. Configurations are tested in two large‐scale U.S. watersheds using an integrated model. Model results are compared to observed streamflow and steady state water table depth (WTD). We provide model results for a range of configurations and show that both WTD and surface water partitioning are important indicators of performance. We also show that geology data source, total subsurface depth, anisotropy, and inclusion of a vertical flow barrier are the most important considerations for subsurface configurations. While a range of configurations proved viable, we provide a recommended Selected National Configuration 1 km resolution subsurface dataset for use in distributed large‐and continental‐scale hydrologic modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

SU-E-T-20: A Correlation Study of 2D and 3D Gamma Passing Rates for Prostate IMRT Plans

Purpose: To investigate the correlation between the two-dimensional gamma passing rate (2D %GP) and three-dimensional gamma passing rate (3D %GP) in prostate IMRT quality assurance. Methods: Eleven prostate IMRT plans were randomly selected from the clinical database and were used to obtain dose distributions in the phantom and patient. Three types of delivery errors (MLC bank sag errors, central MLC errors and monitor unit errors) were intentionally introduced to modify the clinical plans through an in-house Matlab program. This resulted in 187 modified plans. The 2D %GP and 3D %GP were analyzed using different dose-difference and distance-toagreement (1%-1mm, 2%-2mm and 3%-3mm) and 20% dose threshold. The 2D %GP and 3D %GP were then compared not only for the whole region, but also for the PTVs and critical structures using the statistical Pearson’s correlation coefficient (γ). Results: For different delivery errors, the average comparison of 2D %GP and 3D %GP showed different conclusions. The statistical correlation coefficients between 2D %GP and 3D %GP for the whole dose distribution showed that except for 3%/3mm criterion, 2D %GP and 3D %GP of 1%/1mm criterion and 2%/2mm criterion had strong correlations (Pearson’s γ value >0.8). Compared with the whole region, the correlations of 2D %GP and 3D %GP for PTV were better (the γ value for 1%/1mm, 2%/2mm and 3%/3mm criterion was 0.959, 0.931 and 0.855, respectively). However for the rectum, there was no correlation between 2D %GP and 3D %GP. Conclusion: For prostate IMRT, the correlation between 2D %GP and 3D %GP for the PTV is better than that for normal structures. The lower dose-difference and DTA criterion shows less difference between 2D %GP and 3D %GP. Other factors such as the dosimeter characteristics and TPS algorithm bias may also influence the correlation between 2D %GP and 3D %GP.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Luminescence imaging of water during proton-beam irradiation for range estimation

Purpose: Proton therapy has the ability to selectively deliver a dose to the target tumor, so the dose distribution should be accurately measured by a precise and efficient method. The authors found that luminescence was emitted from water during proton irradiation and conjectured that this phenomenon could be used for estimating the dose distribution. Methods: To achieve more accurate dose distribution, the authors set water phantoms on a table with a spot scanning proton therapy system and measured the luminescence images of these phantoms with a high-sensitivity, cooled charge coupled device camera during proton-beam irradiation. The authors imaged the phantoms of pure water, fluorescein solution, and an acrylic block. Results: The luminescence images of water phantoms taken during proton-beam irradiation showed clear Bragg peaks, and the measured proton ranges from the images were almost the same as those obtained with an ionization chamber. Furthermore, the image of the pure-water phantom showed almost the same distribution as the tap-water phantom, indicating that the luminescence image was not related to impurities in the water. The luminescence image of the fluorescein solution had ∼3 times higher intensity than water, with the same proton range as that of water. The luminescence image of the acrylic phantom had a 14.5% shorter proton range than that of water; the proton range in the acrylic phantom generally matched the calculated value. The luminescence images of the tap-water phantom during proton irradiation could be obtained in less than 2 s. Conclusions: Luminescence imaging during proton-beam irradiation is promising as an effective method for range estimation in proton therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-C-BRB-06: Dosimetric Impact of Breast Contour Reconstruction Errors in GammaPod Stereotactic Radiotherapy

Purpose: The first GammaPod™ unit, a dedicated prone stereotactic treatment device for early stage breast cancer, has been installed and commissioned at University of Maryland School of Medicine. The objective of this study was to investigate potential dosimetric impact of inaccurate breast contour. Methods: In GammaPod treatments, patient’s beast is immobilized by a breast cup device (BCID) throughout the entire same-day imaging and treatment procedure. 28 different BICD sizes are available to accommodate patients with varying breast sizes. A mild suction helps breast tissue to conform to the shape of the cup with selected size. In treatment planning, dose calculation utilizes previously calculated dose distributions for available cup geometry rather than the breast shape from CT image. Patient CT images with breast cups indicate minor geometric discrepancy between the matched shape of the cup and the breast contour, i.e., the contour size is larger or smaller. In order to investigate the dosimetric impact of these discrepancies, we simulated such discrepancies and reassessed the dose to target as well as skin. Results: In vicinity of skin, hot/cold spots were found when matched cup size was smaller/larger than patient’s breast after comparing the corrected dose profiles from Monte Carlo simulation with the planned dose from TPS. The overdosing/underdosing of target could yield point dose differences as large as 5% due to these setup errors (D95 changes within 2.5%). Maximal skin dose was overestimated/underestimated up to 25%/45% when matched cup size was larger/smaller than real breast contour. Conclusion: The dosimetric evaluation suggests substantial underdosing/overdosing with inaccurate cup geometry during planning, which is acceptable for current clinical trial. Further studies are needed to evaluate such impact to treating small volume close to skin.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Novel covariance-based neutrality test of time-series data reveals asymmetries in ecological and economic systems

Systems as diverse as the interacting species in a community, alleles at a genetic locus, and companies in a market are characterized by competition (over resources, space, capital, etc) and adaptation. Neutral theory, built around the hypothesis that individual performance is independent of group membership, has found utility across the disciplines of ecology, population genetics, and economics, both because of the success of the neutral hypothesis in predicting system properties and because deviations from these predictions provide information about the underlying dynamics. However, most tests of neutrality are weak, based on static system properties such as species-abundance distributions or the number of singletons in a sample. Time-series data provide a window onto a system’s dynamics, and should furnish tests of the neutral hypothesis that are more powerful to detect deviations from neutrality and more informative about to the type of competitive asymmetry that drives the deviation. Here, we present a neutrality test for time-series data. We apply this test to several microbial time-series and financial time-series and find that most of these systems are not neutral. Our test isolates the covariance structure of neutral competition, thus facilitating further exploration of the nature of asymmetry in the covariance structure of competitive systems. Much like neutrality tests from population genetics that use relative abundance distributions have enabled researchers to scan entire genomes for genes under selection, we anticipate our time-series test will be useful for quick significance tests of neutrality across a range of ecological, economic, and sociological systems for which time-series data are available. Here, future work can use our test to categorize and compare the dynamic fingerprints of particular competitive asymmetries (frequency dependence, volatility smiles, etc) to improve forecasting and management of complex adaptive systems.

59 BASIC BIOLOGICAL SCIENCES↗