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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Real-Time, Simultaneous Soil Water Content and Meteorological Data Measurement to Support TRACER over Harris County, Texas (Field Campaign Report: Part I)

The main purpose of this project was to provide ground-truth and satellite-based soil water content data in the Houston, Texas, area to support the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s 2022 field campaign, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This involved installing four soil monitoring stations at different locations in the Houston area, two of which were part of the ARM facility and two were ancillary. The two stations associated directly with ARM were installed alongside other facilities managed and maintained by the TRACER research team during the intensive operational period (IOP), one located at the La Porte, Texas airport and the other near Guy, Texas. Data from these stations were assimilated with similar data collected by the Harris County Flood Control District (HCFCD) to improve the spatial coverage of the real-time monitoring network. The ground-truth data were compared to the satellite-based (National Aeronautics and Space Administration [NASA]’s Soil Moisture Active Passive [SMAP] mission) data in the TRACER area of interest, and analyzed further to nowcast gridded data over the Houston area. The nowcasted, gridded data product was made available to TRACER researchers for use in climate and land-atmosphere interaction modeling that can help understand formation and persistence of convective storms in dense urban areas, and predict possible environmental events such as floods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Real-Time, Simultaneous Soil Water Content and Meteorological Data Measurement to Support TRACER over Harris County, Texas Field Campaign Report: Part II

The main purpose of this project was to provide ground-truth and satellite-based soil water content data in the Houston, Texas, area to support the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s 2022 field campaign, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This involved installing four soil monitoring stations at different locations in the Houston area, two of which were part of the ARM facility and two were ancillary. The two stations associated directly with ARM were installed alongside other facilities managed and maintained by the TRACER research team during the intensive operational period (IOP), one located at the La Porte, Texas airport and the other located near Guy, Texas. Data from these stations were assimilated with similar data collected by the Harris County Flood Control District (HCFCD) to improve the spatial coverage of the real-time monitoring network. The ground-truth data were compared to the satellite-based (National Aeronautics and Space Administration [NASA]’s Soil Moisture Active Passive [SMAP] mission) data in the TRACER area of interest, and analyzed further to nowcast gridded data over the Houston area. The nowcasted, gridded data product was made available to TRACER researchers for use in climate and land-atmosphere interaction modeling that can help understand formation and persistence of convective storms in dense urban areas, and predict possible environmental events such as floods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

EPWgen (EPW generator) [SWR-26-017]

EPWgen fetches hourly station observations (NOAA/Meteostat), fills gaps with MERRA2 reanalysis, merges data, and writes EPW files with computed headers (HDD/CDD, ground temperatures). It also runs QC checks, supports CSV-driven batch and metered-variable exports, and provides a PyQt5 GUI with mapping and progress tracking for single/multi-year workflows.

Bianchi, Carlo [National Laboratory of the Rockies↗
DOE OSTI2023

Idaho National Laboratory’s FY 22 Greenhouse Gas Report

A greenhouse gas (GHG) inventory is a systematic approach to account for the production and release of certain gases generated by an institution from various emission sources. The gases of interest are those that climate science has identified as related to anthropogenic global climate change. This document presents an inventory of GHGs generated during fiscal year (FY) 2022 by Idaho National Laboratory (INL)—a Department of Energy (DOE) sponsored entity located in southeastern Idaho. In recent years, concern has grown about the environmental impact of GHGs. This, together with a desire to decrease harmful environmental impacts, would be enough to encourage the calculation of an inventory of the total GHGs generated at INL. Additionally, INL has a desire to see how its emissions compare with similar institutions, including other DOE national laboratories. Executive Order 14057 requires that federal agencies and institutions track and report GHG emissions where required. INL’s GHG inventory was calculated according to methodologies identified in federal GHG guidance documents using operational control boundaries. It measures emissions generated in three scopes: (1) INL emissions produced directly by stationary or mobile combustion and by fugitive emissions, (2) the share of emissions generated by entities from which INL purchased electrical power, and (3) indirect or shared emissions generated by outsourced activities that benefit INL (occurring outside INL’s organizational boundaries, but are a consequence of INL’s activities). This inventory found that INL generated 75,572.42 metric tons (MT) of CO2 equivalent (CO2e) emissions during FY 2022. The following conclusions were made from looking at the results of the individual contributors to INL’s FY 2022 GHG inventory: • Electricity (including the associated transmission and distribution losses) is the largest contributor to INL’s GHG inventory, with over 50% of the CO2e emissions. • Other sources with high emissions were mobile combustion (fleet fuels), employee commuting, stationary combustion (facility fuels), and waste disposal (fugitive emissions from the onsite landfill). • Sources with low emissions were waste disposal (contracted disposal), fugitive emissions from refrigerants, wastewater treatment (onsite and contracted), and business ground travel (in personal and rental vehicles). This report details the methods behind quantifying INL’s GHG inventory and discusses lessons learned on better practices by which information important to tracking GHGs can be tracked and recorded. It is important to note that because this report differentiates between those portions of INL that are managed and operated by Battelle Energy Alliance, LLC (BEA) and those managed by other contractors, it includes only INL’s activities overseen by BEA. It is assumed that other contractors will provide similar reporting for those activities they manage, where appropriate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Idaho National Laboratory’s FY 2021 Greenhouse Gas Report

A greenhouse gas (GHG) inventory is a systematic approach to account for the production and release of certain gases generated by an institution from various emission sources. The gases of interest are those that climate science has identified as related to anthropogenic global climate change. This document presents an inventory of GHGs generated during Fiscal Year (FY) 2021 by Idaho National Laboratory (INL)—a Department of Energy (DOE) sponsored entity located in southeastern Idaho. In recent years, concern has grown about the environmental impact of GHGs. This, together with a desire to decrease harmful environmental impacts, would be enough to encourage the calculation of an inventory of the total GHGs generated at INL. Additionally, INL has a desire to see how its emissions compare with similar institutions, including other DOE national laboratories. Executive Order 13834 requires that federal agencies and institutions track and report GHG emissions where required. INL’s GHG inventory was calculated according to methodologies identified in federal GHG guidance documents using operational control boundaries. It measures emissions generated in three scopes: (1) INL emissions produced directly by stationary or mobile combustion and by fugitive emissions, (2) the share of emissions generated by entities from which INL purchased electrical power, and (3) indirect or shared emissions generated by outsourced activities that benefit INL (occurring outside INL’s organizational boundaries but are a consequence of INL’s activities). This inventory found that INL generated 81,185.05 metric tons (MT) of CO 2 equivalent (CO 2 e) emissions during FY 2021. The following conclusions were made from looking at the results of the individual contributors to INL’s FY 2021 GHG inventory: Electricity (including the associated transmission and distribution losses) is the largest contributor to INL’s GHG inventory, with over 50% of the CO 2 e emissions; Other sources with high emissions were mobile combustion (fleet fuels), employee commuting, stationary combustion (facility fuels), and waste disposal (fugitive emissions from the onsite landfill); Sources with low emissions were waste disposal (contracted disposal), fugitive emissions from refrigerants, wastewater treatment (onsite and contracted), and business ground travel (in personal and rental vehicles). This report details the methods behind quantifying INL’s GHG inventory and discusses lessons learned on better practices by which information important to tracking GHGs can be tracked and recorded. It is important to note that because this report differentiates between those portions of INL that are managed and operated by Battelle Energy Alliance, LLC (BEA) and those managed by other contractors, it includes only INL’s activities overseen by BEA. It is assumed that other contractors will provide similar reporting for those activities they manage, where appropriate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Idaho National Laboratory’s FY 2020 Greenhouse Gas Report

A greenhouse gas (GHG) inventory is a systematic approach to account for the production and release of certain gases generated by an institution from various emission sources. The gases of interest are those that climate science has identified as related to anthropogenic global climate change. This document presents an inventory of GHGs generated during fiscal year (FY) 2020 by Idaho National Laboratory (INL)—a Department of Energy (DOE) sponsored entity located in southeastern Idaho. In recent years, concern has grown about the environmental impact of GHGs. This, together with a desire to decrease harmful environmental impacts, would be enough to encourage the calculation of an inventory of the total GHGs generated at INL. Additionally, INL has a desire to see how its emissions compare with similar institutions, including other DOE national laboratories. Executive Order 13834 requires that federal agencies and institutions track and report GHG emissions where required. INL’s GHG inventory was calculated according to methodologies identified in federal GHG Guidance documents using operational control boundaries. It measures emissions generated in three scopes: (1) INL emissions produced directly by stationary or mobile combustion and by fugitive emissions, (2) the share of emissions generated by entities from which INL purchased electrical power, and (3) indirect or shared emissions generated by outsourced activities that benefit INL (occurring outside INL’s organizational boundaries, but are a consequence of INL’s activities). This inventory found that INL generated 76,494.12 metric tons (MT) of CO2 equivalent (CO 2 e) emissions during FY 2020. The following conclusions were made from looking at the results of the individual contributors to INL’s FY 2020 GHG inventory: (1) Electricity (including the associated transmission and distribution losses) is the largest contributor to INL’s GHG inventory, with over 50% of the CO 2 e emissions; (2) Other sources with high emissions were employee commuting, mobile combustion (fleet fuels), stationary combustion (facility fuels), and waste disposal (fugitive emissions from the onsite landfill); and (3) Sources with low emissions were waste disposal (contracted disposal), fugitive emissions from refrigerants, wastewater treatment (onsite and contracted), and business ground travel (in personal and rental vehicles). This report details the methods behind quantifying INL’s GHG inventory and discusses lessons learned on better practices by which information important to tracking GHGs can be tracked and recorded. It is important to note that because this report differentiates between those portions of INL that are managed and operated by Battelle Energy Alliance, LLC (BEA) and those managed by other contractors, it includes only INL’s activities overseen by BEA. It is assumed that other contractors will provide similar reporting for those activities they manage, where appropriate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Spectroscopic quadrupole moments in 124 $\mathrm{Xe}$

The Xe isotopic chain with four valence protons above the Z=50 shell closure is an ideal laboratory for the study of the evolution of nuclear deformation. At the N=82 shell closure, 136 Xe presents all characteristics of a doubly closed shell nucleus with a spherical shape. In the very neutron-deficient isotopes close to N=50, the α-decay chain of Xe was investigated to probe the radioactive decay properties near the drip-line and the magicity of 100 Sn. Additionally, the Xe isotopes present higher order symmetries in the nuclear deformation such as the octupole degree of freedom near N=60 and N=90 or O(6) symmetry in stable isotopes. The relevance of the O(6) symmetry has been investigated by measuring the spectroscopic quadrupole moment of the first excited states in 124 Xe. In the O(6) symmetry limit, the spectroscopic quadrupole moment of collective states is expected to be null. A stable 124 Xe beam with energies of 4.03A MeV and 4.11 A MeV was used to bombard a nat W target at the GANIL facility. Excited states were populated via the safe Coulomb excitation reaction. The collision of the heavy ions with a large Z at low energy make this reaction sensitive to the diagonal E2 matrix element of the excited states. The recoils were detected in the VAMOS++ magnetic spectrometer and the γ rays in the AGATA tracking array. The least squares fitting code gosia was used for the analysis to extract both E2 and M1 transitional and E2 diagonal matrix elements. The rotational ground state band was populated up to the 8$^{+}_{1}$ state as well as the 2$^{+}_{2}$ and 4$^{+}_{2}$ states. Using high precision spectroscopic data to constrain the gosia fit, the spectroscopic quadrupole moments of the 2$^{+}_{1}$, 4$^{+}_{1}$, and 6$^{+}_{1}$ states were determined for the first time. The spectroscopic quadrupole moments were found to be negative, large, and constant in the ground state band underlining the prolate axially deformed ground state band of 124 Xe. Here, the present experimental data confirm that the O(6) symmetry is substantially broken in 124 Xe .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

SPRUCE Ground Observations of Phenology in Experimental Plots, 2019

This data set consists of phenological transition dates, as derived from direct observations of vegetative and reproductive phenology recorded by a human observer, from the SPRUCE experiment during 2019, the third full year of whole-ecosystem warming (Hanson et al. 2017). Both spring and autumn phenological events are included. Since April 2016, human observers have been directly tracking the phenology of both woody and herbaceous species on a weekly schedule within the SPRUCE experimental chambers. The observed date report here is the first survey date on which an event/phenophase was definitively observed. The SPRUCE experiment is located within the S1 peat bog at the Marcell Experimental Forest, approximately 40 km north of Grand Rapids in north-central Minnesota, USA. User note: Ground observations of phenology from 2016-2021 are available. See SPRUCE Ground Observations of Phenology in Experimental Plots, 2021 https://doi.org/10.25581/spruce.094/1874936 for the most recent data as well as links to all other ground phenology datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Reconciliation of asynchronous satellite-based $\mathrm{NO_2}$ and $\mathrm{XCO_2}$ enhancements with mesoscale modeling over two urban landscapes

Fossil fuel carbon dioxide (CO 2ff ), the main driver of global warming and climate change, is often co-emitted with nitrogen oxides (NO x ) and precursors to ground-level ozone from anthropogenic sources like power plants or vehicles. In urban and suburban areas, satellite-based NO 2 can be used as a proxy to track the emissions of CO 2ff . Because of NO 2 ’s shorter lifetime, urban NO 2 plumes are more distinguishable from backgrounds and more sensitive to variations in emissions. However, the combination of these two gases is limited by the asynchrony among NO 2 and CO 2 monitoring satellites. We used CO 2ff simulated by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) model to reconcile the tropospheric NO 2 vertical column density (VCD) from the Tropospheric Monitoring Instrument (TROPOMI) and column-averaged dry-air mole fractions of carbon dioxide enhancements (ΔXCO 2 ) from Orbiting Carbon Observatory 3 (OCO-3) Snapshot Area Maps (SAMs) over a multicity area, Washington D.C.-Baltimore (DC-Balt), and a basin city, Mexico City. NO 2 /CO 2ff ratios over DC-Balt are smaller than Mexico City, indicative of stricter emission restrictions, a more combustion-efficient vehicle fleet, and higher combustion efficiency due to lower altitude in DC-Balt. For single-track cases, the spatial correlations between NO 2 and ΔXCO 2 over Mexico City are stronger than DC-Balt because the NO 2 and CO 2 are mostly trapped in the valley of Mexico City, while DC-Balt is severely affected by distant sources (i.e., US East Coast cities). Using multi-track averaging, spatial correlation coefficients increase with the number of days used for averaging. The correlations reached a maximum when averaging >12 continuous images for DC-Balt and > 10 continuous images for Mexico City. This finding indicates that multi-track averaging using modeled CO 2ff as a proxy is helpful to filter the noise in single-track images, to cancel the interference from distant sources, and to magnify correlations between NO 2 and CO 2ff . Mexico City showed stronger spatial correlations but weaker temporal correlations than DC-Balt due to biomass burning hot spots and large transport errors caused by the trapping effects of the surrounding mountains. Tracking the 20-day moving average of CO 2ff emissions using TROPOMI NO 2 seems technically feasible, considering the relationship between correlation coefficients and the number of available satellite images.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Accelerator and Beam Physics of the Muon g-2 Experiment at Fermilab

The physics case of the Muon g-2 Experiment at Fermilab is outstanding and has recently attracted significant attention from its first official results. Although its measurements involve high energy physics methods, such as counting positron production rates with the use of calorimeters and beam diagnostics with tracking detectors, this experiment is strongly bound to accelerator and beam physics. This paper reviews the principles of the experiment and the details necessary to provide a solid ground for the beam-dynamics uncertainties and the corrections of the systematic effects influencing the output of the experiment: a single numerical value, which may unveil new physics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Utility-Scale Solar Data Update (2020 Edition) [Slides]

Berkeley Lab’s 2020 update of utility-scale solar data and trends provides an overview of key trends in the U.S. market, with a focus on 2019. Highlights of this year’s update include: More than 4.5 GWAC of utility-scale solar (i.e., ground-mounted solar projects larger than 5 MWAC) achieved commercial operations in 2019, bringing cumulative capacity to 29 GWAC. Projects are spread across all 10 regions that we track, though more heavily concentrated in the sunniest regions. The median installed cost of projects that came online in 2019 fell to $\$$1.4/WAC ($\$$1.2/WDC), down 20% from 2018 and down by more than 70% from 2010. 77% of projects and 88% of capacity added in 2019 used single-axis tracking. Average capacity factors range from 17% in the least-sunny regions to 30% where it is sunniest. Single-axis tracking adds roughly five percentage points to capacity factor in the regions with the strongest solar resource. Nationwide average levelized power purchase agreement (PPA) prices fell to $\$$24/MWh in 2019, down 17% from 2018 and more than 80% since 2010. Thirty-nine projects (totaling 4.2 GWAC) in our PPA price sample include battery storage (totaling 2.3 GWAC and 9.5 GWh). In the “lower 48” states, a number of these recent PV+battery PPAs have been inked in the mid-$\$$20/MWh range (levelized in 2019 dollars).Not including the 30% investment tax credit (ITC), the median levelized cost of energy (LCOE) from utility-scale PV has declined by 85% since 2010, to $\$$40/MWh in 2019. When the 30% ITC is included within the LCOE calculation, the median LCOE closely tracks the median PPA price over time. In higher-penetration markets like CAISO, the value of solar has been declining, but falling PPA prices have largely kept pace, preserving solar's net value. At the end of 2019, there were nearly 370 GW of solar in interconnection queues from all 7 ISOs and 30 additional utilities across the country. Nearly a third of this proposed solar capacity is paired with battery storage.

14 SOLAR ENERGY↗
DOE OSTI2023

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded-aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consist of 80- channel detector plane histograms that accumulate photon counts over periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey data set between 14 and 195 keV. Survey data comprise >90% of all BAT data by volume and allow for the tracking of long-term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey data set has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis Python package, a wrapper for HEASoftpy, which provides a modern, opensource pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources, including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the Python code and exemplify its usefulness and accuracy by analyzing survey data of the Crab Nebula, NGC 2992, and a previously uncataloged MAXI transient. The BatAnalysis package allows for ~18 yr of BAT survey data to be used in a systematic way to study a large variety of astrophysical sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded-aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consist of 80-channel detector plane histograms that accumulate photon counts over periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey data set between 14 and 195 keV. Survey data comprise >90% of all BAT data by volume and allow for the tracking of long-term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey data set has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis Python package, a wrapper for HEASoftpy, which provides a modern, open-source pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources, including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the Python code and exemplify its usefulness and accuracy by analyzing survey data of the Crab Nebula, NGC 2992, and a previously uncataloged MAXI transient. The BatAnalysis package allows for ~18 yr of BAT survey data to be used in a systematic way to study a large variety of astrophysical sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Townsend's Ground Squirrel Conservation on the Hanford Site for Calendar Year 2025

The U.S. Department of Energy (DOE), Hanford Field Office (HFO) conducts ecological monitoring on the DOE-managed portion of Hanford Site (hereby referred to as Central Hanford) to collect and track data needed to ensure compliance with an array of environmental laws, regulations, and policies governing HFO activities. Ecological monitoring data provides baseline information about the plants, animals, and habitat under HFO stewardship on the Hanford Site, which is required for accurate ecological impact assessment decision making under the National Environmental Policy Act and the Comprehensive Environmental Response, Compensation, and Liability Act. In addition, ecological monitoring helps ensure that HFO, its contractors, and other entities conducting activities on the Hanford Site are in compliance with DOE/EIS-0222-F, Final Hanford Comprehensive Land Use Plan Environmental Impact Statement. HFO places priority on monitoring plant and animal species or habitats that have specific regulatory protections or requirements; that are rare and/or declining (federal or state listed endangered, threatened, or sensitive species); or are of significant interest to federal, state, or tribal governments or to the public.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Global High‐Resolution Mesoscale Convective System Database Using Satellite‐Derived Cloud Tops, Surface Precipitation, and Tracking

Abstract A new methodology is developed to construct a global (60°S–60°N) long‐term (2000–2019) high‐resolution (∼10‐km h) mesoscale convective system (MCS) database by tracking MCS jointly using geostationary satellite infrared brightness temperature ( T b ) and precipitation feature (PF) characteristics from the Integrated Multi‐satellitE Retrievals for GPM precipitation data sets. Independent validation shows that the satellite‐based MCS data set is able to reproduce important MCS statistics derived from ground‐based radar network observations in the United States and China. We show that by carefully considering key PF characteristics in addition to T b signatures, the new method significantly improves upon previous T b ‐only methods in detecting MCSs in the midlatitudes for all seasons. Results show that MCSs account for over 50% of annual total rainfall across most of the tropical belt and in selected regions of the midlatitudes, with a strong seasonality over many regions of the globe. The tracking database allows Lagrangian aspects such as MCS lifetime and translational speed and direction to be analyzed. The longest‐lived MCSs preferentially occur over the subtropical oceans. The land MCSs have higher cloud‐tops associated with more intense convection, and oceanic MCSs have much higher rainfall production. While MCSs are observed in many regions of the globe, there are fundamental differences in their dynamic and thermodynamic structures that warrant a better understanding of processes that control their evolution. This global database provides significant opportunities for observational and modeling studies of MCSs, their characteristics, and roles in regional and global water and energy cycles, as well as their hydrologic and other impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High speed vibration compensation using magnetic fiducials via NIMBLE

Additive manufacturing (AM) technology, specifically 3D printing, holds great promise for in-orbit manufacturing. In-space printing can significantly reduce the mass, cost, and risk of long-term space exploration by enabling replacement parts to be made as needed and reducing dependence on Earth. However, printing in a zero-gravity environment poses challenges due to the absence of a rigid ground for the print platform, which can result in vibrational and rotational forces that may impact printing integrity. Here, to address this issue, this paper proposes a novel linear magnetic position tracking algorithm, named Navigation Integrating Magnets By Linear Estimation (NIMBLE), for dynamic vibration compensation during 3D printing of truss structures in space. Compared to the most commonly used nonlinear optimization method, the NIMBLE algorithm is more than two orders of magnitude faster. With only a single 3-axis magnet sensor and a small NdFeB magnet, the NIMBLE algorithm provides a simple and easily implemented tracking solution for in-orbit 3D printing.

3D printing in space↗
DOE OSTI2026

Complex and Unusual Excited-State Relaxation Dynamics of 9,9′-Bifluorenylidene Revealed by Comprehensive Time-Resolved Spectroscopy and MRSF-TDDFT Calculations

Design of novel photochemical molecular motors often requires molecular building blocks that exhibit rather unusual photoactivity, for which conventional analyses of spectroscopic data can lead to conflicting interpretations. We here systematically investigated the excited-state relaxation dynamics of one such molecule, 9,9′-bifluorenylidene (BF), through comprehensive and complementary integration of ultrafast transient absorption (TA) and femtosecond stimulated Raman (FSRS) spectroscopies and first-principles mixed-reference spin-flip time-dependent density functional theory (MRSF-TDDFT). TA and FSRS identified two sequentially formed transients following photoexcitation. The decay kinetics of the two intermediates differ in response to excitation wavelengths and the viscosity/polarity of solvents. MRSF-TDDFT calculations reveal a direct, barrierless internal-conversion pathway from the bright Franck−Condon state to a dark S1 minimum, where the excited-state population is transiently trapped, accounting for the first transient species observed in spectroscopic experiments. Further tracking down along the PES with MRSF-TDDFT mapped out two nonradiative relaxation pathways via conical intersections that connect the dark S 1 state to three configurations in the ground-state manifolds, within which a ring structure with a C8−C8′ bond and the vibrationally excited ground-state BF were identified from spectroscopic and kinetic data. The complexity of relaxation kinetics was attributed to the flexible torsional and twisting motions about the C9−C9′ bridge bond enabled by the diradical character of the S 1 state. These findings clarify unusual photoactive relaxation dynamics stemming from a novel correlation between structural flexibility and shifting electronic characteristics, and they demonstrate the importance of integrating spectroscopic and advanced electronic structure calculation studies for judicious clarification of complex, competing relaxation pathways of excited states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Intense windstorms in the northeastern United States

Abstract. Windstorms are a major natural hazard in many countries. The objective of this study is to identify and characterize intense windstorms during the last 4 decades in the US Northeast and determine both the sources of cyclones responsible for these events and the manner in which those cyclones differ from the cyclone climatology. The windstorm detection is based on the spatial extent of locally extreme wind speeds at 100 m height from the ERA5 reanalysis database. During the top 10 windstorms, wind speeds exceed their local 99.9th percentile over at least one-third of land-based ERA5 grid cells in this high-population-density region of the USA. Maximum sustained wind speeds at 100 m during these windstorms range from 26 to over 43 ms−1, with wind speed return periods exceeding 6.5 to 106 years (considering the top 5 % of grid cells during each storm). Property damage associated with these storms, with inflation adjusted to January 2020, ranges from USD 24 million to over USD 29 billion. Two of these windstorms are linked to decaying tropical cyclones, three are Alberta clippers, and the remaining storms are Colorado lows. Two of the 10 re-intensified off the east coast, leading to development of nor'easters. These windstorms followed frequently observed cyclone tracks but exhibit maximum intensities as measured using 700 hPa relative vorticity and mean sea level pressure that is 5–10 times the mean values for cyclones that followed similar tracks over this 40-year period. The time evolution of wind speeds and concurrent precipitation for those windstorms that occurred after the year 2000 exhibit good agreement with in situ ground-based and remote sensing observations, plus storm damage reports, indicating that the ERA5 reanalysis data have a high degree of fidelity for large, damaging windstorms such as these. A larger pool of the top 50 largest windstorms exhibit evidence of only weak serial clustering, which is in contrast to the relatively strong serial clustering of windstorms in Europe.

58 GEOSCIENCES↗