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DOE OSTI2024

Tailoring electrophotonic capabilities of atomically thin GeS through controlled organometallic intercalation

The unique structure of van der Waals materials facilitates a robust mechanism for precise control of physical properties. In this study, we present a comprehensive analysis based on the intercalation of organometallics to modulate the optoelectronic behavior of two-dimensional germanium sulfide (GeS). Advanced computational exploration reveals significant and tunable features in the intercalated material. Additionally, the weak chemical interactions between organometallics and GeS support the electric-field-mediated drift and charge–discharge processes in intercalants. Controlling the concentration of organometallics in this manner enables the dynamic emergence of novel characteristics post-intercalation. These include flatbands near the Fermi level, significant enhancement of carrier mobility, and a magnetic ground state that is atypical for pristine GeS. Our findings demonstrate that organometallic intercalation offers a powerful strategy for tailoring the optoelectronic and magnetic characteristics of GeS, paving the way for harnessing emerging features for applications in next-generation devices.

Physics↗

DOE OSTI2015

High-resolution spectroscopic study of extremely metal-poor star candidates from the SkyMapper survey

The SkyMapper Southern Sky Survey is carrying out a search for the most metal-poor stars in the Galaxy. It identifies candidates by way of its unique filter set which allows for estimation of stellar atmospheric parameters. The set includes a narrow filter centered on the Ca ii K 3933 Å line, enabling a robust estimate of stellar metallicity. Promising candidates are then confirmed with spectroscopy. We present the analysis of Magellan Inamori Kyocera Echelle high-resolution spectroscopy of 122 metal-poor stars found by SkyMapper in the first two years of commissioning observations. Forty-one stars have [Fe/H]⩽−3.0. Nine have [Fe/H]⩽−3.5, with three at [Fe/H]∼−4. A 1D LTE abundance analysis of the elements Li, C, Na, Mg, Al, Si, Ca, Sc, Ti, Cr, Mn, Co, Ni, Zn, Sr, Ba, and Eu shows these stars have [X/Fe] ratios typical of other halo stars. One star with low [X/Fe] values appears to be “Fe-enhanced,” while another star has an extremely large [Sr/Ba] ratio: >2. Only one other star is known to have a comparable value. Seven stars are “CEMP-no” stars ([C/Fe]>0.7, [Ba/Fe]<0). 21 stars exhibit mild r-process element enhancements (0.3⩽[Eu/Fe]<1.0), while four stars have [Eu/Fe]⩾1.0. These results demonstrate the ability to identify extremely metal-poor stars from SkyMapper photometry, pointing to increased sample sizes and a better characterization of the metal-poor tail of the halo metallicity distribution function in the future.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Error field measurements with rotating RMP fields for DIII-D H-mode

3D magnetic sensors are employed to identify the amplitude and toroidal phase of error fields (EF) by analyzing the torque balance for magnetic islands entrained by rotating resonant magnetic perturbations (RMPs) in DIII-D H-mode plasmas. This technique of torque balance allows for efficient error field identification, offering a valuable tool for scenario-specific and optimized error field compensation (EFC) and requires only magnetic diagnostics. The torque balance used in this work includes the contribution from electromagnetic torque due to error fields, wall response, RMP fields, and viscous. Results show that viscous torque plays a crucial role, particularly during locked modes and H-mode plasmas, ensuring accurate data fits with lower residuals. The torque balance technique reveals that the L- and H-mode plasmas have distinct EF configurations, and consistent with a model-based EF analysis including MHD response in IPEC and the SURFMN EF simulation. This technique shows great robustness in measuring the intrinsic EF amplitude regardless of its amplitude or toroidal phase. Repeated discharges with EFC disparities exhibit consistent results of intrinsic error field within a reasonable range near the “standard” error field compensation. Additionally, the use of a rotating n = 1 resonant magnetic perturbation offers the advantage of reducing disruption risks by entraining saturated magnetic islands. These findings are instrumental for optimizing EF correction in fusion devices, thereby enhancing tearing mode suppression and overall plasma stability.

3D magnetic sensors↗

DOE OSTI2018

Dark Energy Survey Year 1 Results: Cosmological Constraints from Cosmic Shear

Here, we use 26 million galaxies from the Dark Energy Survey (DES) Year 1 shape catalogs over 1321 deg 2 of the sky to produce the most significant measurement of cosmic shear in a galaxy survey to date. We constrain cosmological parameters in both the flat CDM and wCDM models, while also varying the neutrino mass density. These results are shown to be robust using two independent shape catalogs, two independent photo- z calibration methods, and two independent analysis pipelines in a blind analysis. We find a 3% fractional uncertainty on σ 8 ( Ω m =0.3)0.5 = 0.789$+0.024\atop{0.026}$ at 68% CL, which is a factor of three improvement over the fractional constraining power of our DES Science Verification results and a factor 1.5 tighter than the previous state-of-the-art cosmic shear results. In wCDM, we find a 5% fractional uncertainty on 8( m=0:3)0:5 = 0.789$+0.036\atop{0.038}$ and a dark energy equation-of-state w = -0.82$+0.26\atop{-0.48}$. Though we find results that are consistent with previous cosmic shear constraints in 8 – m, we nevertheless see no evidence for disagreement of our weak lensing data with data from the CMB. Finally, we find no evidence preferring a wCDM model allowing w≠ -1. Finally, we expect further significant improvements with subsequent years of DES data, which will more than triple the sky coverage of our shape catalogs and double the effective integrated exposure time per galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Quantifying and Controlling Entanglement in the Quantum Magnet Cs 2 CoCl 4

The lack of methods to experimentally detect and quantify entanglement in quantum matter impedes our ability to identify materials hosting highly entangled phases, such as quantum spin liquids. We thus investigate the feasibility of using inelastic neutron scattering (INS) to implement a model-independent measurement protocol for entanglement based on three entanglement witnesses: one-tangle, two-tangle, and quantum Fisher information (QFI). We perform high-resolution INS measurements on Cs 2 CoCl 4 , a close realization of the S = 1/2 transverse-field XXZ spin chain, where we can control entanglement using the magnetic field, and compare with density-matrix renormalization group calculations for validation. The three witnesses allow us to infer entanglement properties and make deductions about the quantum state in the material. Overall, we find QFI to be a particularly robust experimental probe of entanglement, whereas the one and two-tangles require more careful analysis. Our results lay the foundation for a general entanglement detection protocol for quantum spin systems.

1-dimensional spin chains↗

DOE OSTI2025

Model for the curvature response of the CDF II drift chamber

The CDF II experiment at the Fermilab Tevatron used a drift chamber to measure the momenta of charged particles. We present a model for the response of the drift chamber to the curvature of a charged particle's trajectory. Constraints on the model parameters are obtained from cosmic-ray data and from information published by CDF in the context of the W boson mass measurement. Implications for the calibration of the drift chamber measurement of momentum are discussed. The robustness of the CDF calibration procedure is demonstrated. The model provides a framework for the analysis of precision magnetic trackers of high-momentum particles. Published by the American Physical Society 2025

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Design and Evaluation of a Ring Tension Test Grip for Remote Mechanical Testing of Irradiated Tubular Specimens

Here, the ring tension test (RTT) is a mechanical testing method for determining bulk mechanical behavior in the circumferential or hoop direction for tubular materials. The test is especially useful for testing materials with anisotropic mechanical properties, such as zirconium alloys, which are commonly used as nuclear fuel cladding. Anisotropy requires direction-specific testing to determine the hoop strength. Historically, several RTT methods and grips have been used, each method has its strengths and weaknesses, and, in all cases, the measured strength is subject to uncertainty due to variations of the testing geometry and experimental tolerances. Recent analysis has shown that grips with a hemicylindrical mandrel configuration are recommended as the most robust configuration. The two strictest aspects to be controlled are the ability to determine gage region orientation and closely matching the size of the mandrels to the test specimen. This last requirement is particularly challenging when the dimensions of the specimen vary because of environmental effects such as dimensional changes due to irradiation. This paper presents a new RTT grip designed to incorporate this mandrel shape, hold the gage at the desired orientation, be suitable for remote operation in a hot-cell environment, and be adaptable for different sizes or variations in the specimen size. The general description and the unique design features of the test specimen and grips are given in detail. The performance of the grips in mechanical testing, including in a remote hot-cell environment, is also provided.

42 ENGINEERING↗

DOE OSTI2016

On the Path to SunShot. The Role of Advancements in Solar Photovoltaic Efficiency, Reliability, and Costs

This report examines the remaining challenges to achieving the competitive photovoltaic (PV) costs and large-scale deployment envisioned under the U.S. Department of Energy's SunShot Initiative. Solar-energy cost reductions can be realized through lower PV module and balance-of-system (BOS) costs as well as improved system efficiency and reliability. Numerous combinations of PV improvements could help achieve the levelized cost of electricity (LCOE) goals because of the tradeoffs among key metrics like module price, efficiency, and degradation rate as well as system price and lifetime. Using LCOE modeling based on bottom-up cost analysis, two specific pathways are mapped to exemplify the many possible approaches to module cost reductions of 29%-38% between 2015 and 2020. BOS hardware and soft cost reductions, ranging from 54%-77% of total cost reductions, are also modeled. The residential sector's high supply-chain costs, labor requirements, and customer-acquisition costs give it the greatest BOS cost-reduction opportunities, followed by the commercial sector, although opportunities are available to the utility-scale sector as well. Finally, a future scenario is considered in which very high PV penetration requires additional costs to facilitate grid integration and increased power-system flexibility--which might necessitate even lower solar LCOEs. The analysis of a pathway to 3-5 cents/kWh PV systems underscores the importance of combining robust improvements in PV module and BOS costs as well as PV system efficiency and reliability if such aggressive long-term targets are to be achieved.

14 SOLAR ENERGY↗

DOE OSTI2016

Environmentally Friendly Economical Sequestration of Rare Earth Metals from Geothermal Waters

The purpose of this work was to complete a proof of concept study to apply and validate a novel method developed by Tusaar for the capture and recovery of rare earth elements (known as REEs) and other critical and valuable elements from geothermal waters produced from deep within the earth. Geothermal water provides heat for power production at many geothermal power plants in the western United States. The target elements, the REEs, are vital to modern day electronics, batteries, motors, automobiles and many other consumer favorites and necessities. Currently there are no domestic sources of REEs while domestic and international demand for the products they are used in continues to rise. Many of the REEs are considered “strategically” important. A secure supply of REEs in the USA would benefit consumers and the country at large. A new method to recover these REEs from geothermal waters used at existing geothermal power plants around the country is a high priority and would benefit consumers and the USA. The result of this project was the successful development and demonstration of an integrated process for removal and recovery of the REEs from synthetic geothermal brines on a small laboratory scale. The work included preparation of model geothermal brines to test, selection of the most effective proprietary sorbent media to capture the REEs and testing of the media under a variety of potential operating conditions. Geothermal brines are generally very high in salt content and contain a wide range of elements and anions associated with the rock layers from which they are produced. Processing the geothermal water is difficult because it is corrosive and the dissolved minerals in the water precipitate easily once the temperature and pressure change. No commercial technologies have been shown to be effective or robust enough under these geothermal brine conditions to be commercially viable for removal of REEs. Technologies including ion exchange, traditional sorptive media and membrane concentration are too expensive, difficult or impossible to regenerate and easily rendered ineffective under these working conditions. The work completed during this project has demonstrated that a selective media that is robust and durable under the conditions associated with geothermal brines is possible. The initial economic analysis indicates that the process would not be financially viable at current market prices for REEs. The world market price for REEs has been turbulent over the past several years and are currently near historical lows. Historical trends and market forces suggest that the world price is stabilizing and will rise. At the same time, further development has the potential to reduce the costs associated with the technology. This work opened the door to the idea that a large scale process for removal and recovery of REEs from geothermal brines is possible. Upward price pressures coupled with technology improvements suggest that this process has the opportunity to be commercially successful at a point in the future.

15 GEOTHERMAL ENERGY↗

DOE OSTI2018

Deploy production sliding mesh capability with linear solver benchmarking.

Wind applications require the ability to simulate rotating blades. To support this use-case, a novel design-order sliding mesh algorithm has been developed and deployed. The hybrid method combines the control volume finite element methodology (CVFEM) with concepts found within a discontinuous Galerkin (DG) finite element method (FEM) to manage a sliding mesh. The method has been demonstrated to be design-order for the tested polynomial basis (P=1 and P=2) and has been deployed to provide production simulation capability for a Vestas V27 (225 kW) wind turbine. Other stationary and canonical rotating ow simulations are also presented. As the majority of wind-energy applications are driving extensive usage of hybrid meshes, a foundational study that outlines near-wall numerical behavior for a variety of element topologies is presented. Results indicate that the proposed nonlinear stabilization operator (NSO) is an effective stabilization methodology to control Gibbs phenomena at large cell Peclet numbers. The study also provides practical mesh resolution guidelines for future analysis efforts. Application-driven performance and algorithmic improvements have been carried out to increase robustness of the scheme on hybrid production wind energy meshes. Specifically, the Kokkos-based Nalu Kernel construct outlined in the FY17/Q4 ExaWind milestone has been transitioned to the hybrid mesh regime. This code base is exercised within a full V27 production run. Simulation timings for parallel search and custom ghosting are presented. As the low-Mach application space requires implicit matrix solves, the cost of matrix reinitialization has been evaluated on a variety of production meshes. Results indicate that at low element counts, i.e., fewer than 100 million elements, matrix graph initialization and preconditioner setup times are small. However, as mesh sizes increase, e.g., 500 million elements, simulation time associated with \setup-up" costs can increase to nearly 50% of overall simulation time when using the full Tpetra solver stack and nearly 35% when using a mixed Tpetra- Hypre-based solver stack. The report also highlights the project achievement of surpassing the 1 billion element mesh scale for a production V27 hybrid mesh. A detailed timing breakdown is presented that again suggests work to be done in the setup events associated with the linear system. In order to mitigate these initialization costs, several application paths have been explored, all of which are designed to reduce the frequency of matrix reinitialization. Methods such as removing Jacobian entries on the dynamic matrix columns (in concert with increased inner equation iterations), and lagging of Jacobian entries have reduced setup times at the cost of numerical stability. Artificially increasing, or bloating, the matrix stencil to ensure that full Jacobians are included is developed with results suggesting that this methodology is useful in decreasing reinitialization events without loss of matrix contributions. With the above foundational advances in computational capability, the project is well positioned to begin scientific inquiry on a variety of wind-farm physics such as turbine/turbine wake interactions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Deploy production sliding mesh capability with linear solver benchmarking (ECP Milestone Report, Ver. 1.0)

Wind applications require the ability to simulate rotating blades. To support this use-case, a novel design-order sliding mesh algorithm has been developed and deployed. The hybrid method combines the control volume finite element methodology (CVFEM) with concepts found within a discontinuous Galerkin (DG) finite element method (FEM) to manage a sliding mesh. The method has been demonstrated to be design-order for the tested polynomial basis (P=1 and P=2) and has been deployed to provide production simulation capability for a Vestas V27 (225 kW) wind turbine. Other stationary and canonical rotating flow simulations are also presented. As the majority of wind-energy applications are driving extensive usage of hybrid meshes, a foundational study that outlines near-wall numerical behavior for a variety of element topologies is presented. Results indicate that the proposed nonlinear stabilization operator (NSO) is an effective stabilization methodology to control Gibbs phenomena at large cell Peclet numbers. The study also provides practical mesh resolution guidelines for future analysis efforts. Application-driven performance and algorithmic improvements have been carried out to increase robustness of the scheme on hybrid production wind energy meshes. Specifically, the Kokkos-based Nalu Kernel construct outlined in the FY17/Q4 ExaWind milestone has been transitioned to the hybrid mesh regime. This code base is exercised within a full V27 production run. Simulation timings for parallel search and custom ghosting are presented. As the low-Mach application space requires implicit matrix solves, the cost of matrix reinitialization has been evaluated on a variety of production meshes. Results indicate that at low element counts, i.e., fewer than 100 million elements, matrix graph initialization and preconditioner setup times are small. However, as mesh sizes increase, e.g., 500 million elements, simulation time associated with "setup-up" costs can increase to nearly 50% of overall simulation time when using the full Tpetra solver stack and nearly 35% when using a mixed Tpetra- Hypre-based solver stack. The report also highlights the project achievement of surpassing the 1 billion element mesh scale for a production V27 hybrid mesh. A detailed timing breakdown is presented that again suggests work to be done in the setup events associated with the linear system. In order to mitigate these initialization costs, several application paths have been explored, all of which are designed to reduce the frequency of matrix reinitialization. Methods such as removing Jacobian entries on the dynamic matrix columns (in concert with increased inner equation iterations), and lagging of Jacobian entries have reduced setup times at the cost of numerical stability. Artificially increasing, or bloating, the matrix stencil to ensure that full Jacobians are included is developed with results suggesting that this methodology is useful in decreasing reinitialization events without loss of matrix contributions. With the above foundational advances in computational capability, the project is well positioned to begin scientific inquiry on a variety of wind-farm physics such as turbine/turbine wake interactions.

Domino, Stefan P.↗

DOE OSTI2021

Trajectory Optimization via Unsupervised Probabilistic Learning On Manifolds

This report investigates the use of unsupervised probabilistic learning techniques for the analysis of hypersonic trajectories. The algorithm first extracts the intrinsic structure in the data via a diffusion map approach. Using the diffusion coordinates on the graph of training samples, the probabilistic framework augments the original data with samples that are statistically consistent with the original set. The augmented samples are then used to construct conditional statistics that are ultimately assembled in a path-planing algorithm. In this framework the controls are determined stage by stage during the flight to adapt to changing mission objectives in real-time. A 3DOF model was employed to generate optimal hypersonic trajectories that comprise the training datasets. The diffusion map algorithm identfied that data resides on manifolds of much lower dimensionality compared to the high-dimensional state space that describes each trajectory. In addition to the path-planing worflow we also propose an algorithm that utilizes the diffusion map coordinates along the manifold to label and possibly remove outlier samples from the training data. This algorithm can be used to both identify edge cases for further analysis as well as to remove them from the training set to create a more robust set of samples to be used for the path-planing process.

42 ENGINEERING↗

DOE OSTI2023

Field Validation of Cloud Properties Sensor (SAIL Field Campaign Report)

The purpose of the Field Validation of Cloud Properties Sensor – SAIL campaign was to deploy Aerodyne’s extended-wavelength TWST cloud optical properties sensor (TWST-CPS) in an operationally relevant environment with co-located, externally validated sensors. Colocation with The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s deployment of its second Mobile Facility (AMF2) on the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign at Crested Butte, Colorado was ideal because of the variety of operational sensors that can measure some of the same cloud properties using different modalities. While cloud property sensors have long existed, they tend to be costly to produce and maintain. Our sensor measures absolute spectral radiance over 440-1700 nm and retrieves cloud optical depth (COD), droplet effective radius (Reff), and thermodynamic phase (Phase). Our prototype is built predominantly from off-the-shelf components and uses uncooled spectrometers. A low-cost, easy-to-use sensor such as this could allow deployment at many more sites for greater spatial coverage. Instrument deployment to test robust operations and a new stray-light baffle design, and the continued development of analysis and retrieval algorithms using the data from this deployment, are central technical objectives of Aerodyne Research’s U.S. Department of Energy Small Business Innovative Research Phase 2 contract (DE-SC0020473, Low-cost shortwave spectroradiometer for retrieval of cloud properties).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Field Validation of Cloud Properties Sensor – SAIL Field Campaign Report

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

CARBON-TO-OXYGEN RATIOS IN M DWARFS AND SOLAR-TYPE STARS

It has been suggested that high C/O ratios (>0.8) in circumstellar disks lead to the formation of carbon-dominated planets. Based on the expectation that elemental abundances in the stellar photospheres give the initial abundances in the circumstellar disks, the frequency distributions of C/O ratios of solar-type stars have been obtained by several groups. The results of these investigations are mixed. Some find C/O > 0.8 in more than 20% of stars, and C/O > 1.0 in more than 6%. Others find C/O > 0.8 in none of the sample stars. These works on solar-type stars are all differential abundance analyses with respect to the Sun and depend on the adopted C/O ratio in the Sun. Recently, a method of molecular line spectroscopy of M dwarfs, in which carbon and oxygen abundances are derived respectively from CO and H{sub 2}O lines in the K band, has been developed. The resolution of the K- band spectrum is 20,000. Carbon and oxygen abundances of 46 M dwarfs have been obtained by this nondifferential abundance analysis. Carbon-to-oxygen ratios in M dwarfs derived by this method are more robust than those in solar-type stars derived from neutral carbon and oxygen lines in the visible spectra because of the difficulty in the treatment of oxygen lines. We have compared the frequency distribution of C/O distributions in M dwarfs with those of solar-type stars and have found that the low frequency of high-C/O ratios is preferred.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Crowded Field Galaxy Photometry: Precision Colors in the CLASH Clusters

We present a new method for photometering objects in galaxy clusters. We introduce a mode-filtering technique for removing spatially variable backgrounds, improving both detection and photometric accuracy (roughly halving the scatter in the red sequence compared to previous catalogs of the same clusters). This method is based on robustly determining the distribution of background pixel values and should provide comparable improvement in photometric analysis of any crowded fields. We produce new multiwavelength catalogs for the 25 CLASH cluster fields in all 16 bandpasses from the UV through the near-IR, as well as rest-frame magnitudes. A comparison with spectroscopic values from the literature finds a ∼30% decrease in the redshift deviation from previously released CLASH photometry. This improvement in redshift precision, in combination with a detection scheme designed to maximize purity, yields a substantial upgrade in cluster member identification over the previous CLASH galaxy catalog. We construct luminosity functions for each cluster, reliably reaching depths of at least 4.5 mag below M* in every case, and deeper still in several clusters. We measure M* , α, and their redshift evolution, assuming the cluster populations are coeval, and find little to no evolution of α,−0.9≲〈α〉≲−0.8, and M* values consistent with passive evolution. We present a catalog of galaxy photometry, photometric and spectroscopic redshifts, and rest-frame photometry for the full fields of view of all 25 CLASH clusters. Not only will our new photometric catalogs enable new studies of the properties of CLASH clusters, but mode-filtering techniques, such as those presented here, should greatly enhance the data quality of future photometric surveys of crowded fields.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Leveraging machine learning to enhance aerosol classification using Single-Particle Mass Spectrometry

Advancing automated classification of atmospheric aerosols from Single-Particle Mass Spectrometry (SPMS) data remains challenging due to overlapping ion signatures, compositional diversity, and limited labeled data. This study evaluates supervised and semi-supervised learning frameworks to enhance aerosol identification by jointly leveraging labeled and unlabeled spectra. Four models were compared: a supervised Support Vector Machine (SVM), a self-training SVM, a stacked autoencoder classifier, and a stacked autoencoder trained using a temporal-ensembling Mean Teacher approach. All models achieved high and stable accuracies (90.0 %–91.1 %), surpassing previous results on the same dataset (87 %) and matching the performance of state-of-the-art deep learning methods. Despite small global metric differences (≤ 1 %), semi-supervised variants yielded up to 5 %–10 % improvements for compositionally rare particle types – such as soot (0.77 % of spectra, F1-score: 0.93–0.97) and hazelnut pollen (0.98 % of spectra, F1-score: 0.97–1.00) – equating to roughly ∼ 187 additional correctly classified spectra. These gains are scientifically significant, as such rare particles exert disproportionate influence on radiative absorption and ice nucleation processes; their improved detection reduces modeled uncertainties in aerosol absorption optical depth and mixed-phase cloud ice nucleation rates. The models' residual misclassifications (≈ 9 %) largely arise from true spectral overlap among chemically adjacent species (e.g., Na- vs. K-feldspar, coated vs. uncoated feldspars), reflecting physical compositional continuity rather than algorithmic error. Collectively, these findings demonstrate that leveraging unlabeled data to learn robust spectral representations and refine classification enhances both fidelity and interpretability, bridging data-driven analysis with aerosol–climate process understanding.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1987

Periodic extinction of families and genera

Eight major episodes of biological extinction of marine families over the past 250 million years stand significantly above local background (P less than 0.05). These events are more pronounced when analyzed at the level of genus, and generic data exhibit additional apparent extinction events in the Aptian (Cretaceous) and Pliocene (Tertiary) Stages. Time-series analysis of these records strongly suggests a 26-million-year periodicity. This conclusion is robust even when adjusted for simultaneous testing of many trial periods. When the time series is limited to the four best-dated events (Cenomanian, Maestrichtian, upper Eocene, and middle Miocene), the hypothesis of randomness is also rejected for the 26-million-year period (P less than 0.0002).

Raup, David M.↗