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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Mil-Std-464C and Mil-Std-464D Electromagnetic Radiation Environment Evaluation

Many systems derive their electromagnetic radiation (EMR) environments from Mil-Std-464C or Mil-Std-464D, Electromagnetic Environmental Effects Requirements for Systems. This standard defines several EMR environments based on the type of system and expected application. Many nuclear weapon (NW) systems reference the ordnance environments as the starting point for their functional EMR requirements, since any item intended to go into Department of Defense (DOD) custody is expected to be certified hazards of electromagnetic radiation to ordnance (HERO) safe when exposed to the environments listed in Mil-Std-464 Table 9. This environment is defined as the envelope of all sources any system in DOD custody may ever encounter, however, and may include sources that are not relevant for a particular system. This document is intended to provide additional clarity on the Mil-Std-464C and Mil-Std-464D EMR environments, specifically the driving sources for the maximum ordnance levels. This supplementary information may be used to guide tailoring of relevant environments or application to different systems with the additional consideration of any shielding that may reduce the external environments defined in the military standard.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2016

2014 Runtime Systems Summit. Runtime Systems Report

This report summarizes runtime system challenges for exascale computing, that follow from the fundamental challenges for exascale systems that have been well studied in past reports, e.g., [6, 33, 34, 32, 24]. Some of the key exascale challenges that pertain to runtime systems include parallelism, energy efficiency, memory hierarchies, data movement, heterogeneous processors and memories, resilience, performance variability, dynamic resource allocation, performance portability, and interoperability with legacy code. In addition to summarizing these challenges, the report also outlines different approaches to addressing these significant challenges that have been pursued by research projects in the DOE-sponsored X-Stack and OS/R programs. Since there is often confusion as to what exactly the term “runtime system” refers to in the software stack, we include a section on taxonomy to clarify the terminology used by participants in these research projects. In addition, we include a section on deployment opportunities for vendors and government labs to build on the research results from these projects. Finally, this report is also intended to provide a framework for discussing future research and development investments for exascale runtime systems, and for clarifying the role of runtime systems in exascale software.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The greenhouse gas cost of agricultural intensification with groundwater irrigation in a Midwest U.S. row cropping system

Abstract Groundwater irrigation of cropland is expanding worldwide with poorly known implications for climate change. This study compares experimental measurements of the net global warming impact of a rainfed versus a groundwater‐irrigated corn (maize)–soybean–wheat, no‐till cropping system in the Midwest US, the region that produces the majority of U.S. corn and soybean. Irrigation significantly increased soil organic carbon (C) storage in the upper 25 cm, but not by enough to make up for the CO 2 ‐equivalent (CO 2 e) costs of fossil fuel power, soil emissions of nitrous oxide (N 2 O), and degassing of supersaturated CO 2 and N 2 O from the groundwater. A rainfed reference system had a net mitigating effect of −13.9 (±31) g CO 2 e m −2 year −1 , but with irrigation at an average rate for the region, the irrigated system contributed to global warming with net greenhouse gas (GHG) emissions of 27.1 (±32) g CO 2 e m −2 year −1 . Compared to the rainfed system, the irrigated system had 45% more GHG emissions and 7% more C sequestration. The irrigation‐associated increase in soil N 2 O and fossil fuel emissions contributed 18% and 9%, respectively, to the system's total emissions in an average irrigation year. Groundwater degassing of CO 2 and N 2 O are missing components of previous assessments of the GHG cost of groundwater irrigation; together they were 4% of the irrigated system's total emissions. The irrigated system's net impact normalized by crop yield (GHG intensity) was +0.04 (±0.006) kg CO 2 e kg −1 yield, close to that of the rainfed system, which was −0.03 (±0.002) kg CO 2 e kg −1 yield. Thus, the increased crop yield resulting from irrigation can ameliorate overall GHG emissions if intensification by irrigation prevents land conversion emissions elsewhere, although the expansion of irrigation risks depletion of local water resources.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Practical auxiliary basis implementation of Rung 3.5 functionals

Approximate exchange-correlation functionals for Kohn-Sham density functional theory often benefit from incorporating exact exchange. Exact exchange is constructed from the noninteracting reference system's nonlocal one-particle density matrix γ(r{sup -vector},r{sup -vector}′). Rung 3.5 functionals attempt to balance the strengths and limitations of exact exchange using a new ingredient, a projection of γ(r{sup -vector},r{sup -vector} ′) onto a semilocal model density matrix γ{sub SL}(ρ(r{sup -vector}),∇ρ(r{sup -vector}),r{sup -vector}−r{sup -vector} ′). γ{sub SL} depends on the electron density ρ(r{sup -vector}) at reference point r{sup -vector}, and is closely related to semilocal model exchange holes. We present a practical implementation of Rung 3.5 functionals, expanding the r{sup -vector}−r{sup -vector} ′ dependence of γ{sub SL} in an auxiliary basis set. Energies and energy derivatives are obtained from 3D numerical integration as in standard semilocal functionals. We also present numerical tests of a range of properties, including molecular thermochemistry and kinetics, geometries and vibrational frequencies, and bandgaps and excitation energies. Rung 3.5 functionals typically provide accuracy intermediate between semilocal and hybrid approximations. Nonlocal potential contributions from γ{sub SL} yield interesting successes and failures for band structures and excitation energies. The results enable and motivate continued exploration of Rung 3.5 functional forms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Optical eye tracking system for real-time noninvasive tumor localization in external beam radiotherapy

Purpose: External beam radiotherapy currently represents an important therapeutic strategy for the treatment of intraocular tumors. Accurate target localization and efficient compensation of involuntary eye movements are crucial to avoid deviations in dose distribution with respect to the treatment plan. This paper describes an eye tracking system (ETS) based on noninvasive infrared video imaging. The system was designed for capturing the tridimensional (3D) ocular motion and provides an on-line estimation of intraocular lesions position based on a priori knowledge coming from volumetric imaging. Methods: Eye tracking is performed by localizing cornea and pupil centers on stereo images captured by two calibrated video cameras, exploiting eye reflections produced by infrared illumination. Additionally, torsional eye movements are detected by template matching in the iris region of eye images. This information allows estimating the 3D position and orientation of the eye by means of an eye local reference system. By combining ETS measurements with volumetric imaging for treatment planning [computed tomography (CT) and magnetic resonance (MR)], one is able to map the position of the lesion to be treated in local eye coordinates, thus enabling real-time tumor referencing during treatment setup and irradiation. Experimental tests on an eye phantom and seven healthy subjects were performed to assess ETS tracking accuracy. Results: Measurements on phantom showed an overall median accuracy within 0.16 mm and 0.40° for translations and rotations, respectively. Torsional movements were affected by 0.28° median uncertainty. On healthy subjects, the gaze direction error ranged between 0.19° and 0.82° at a median working distance of 29 cm. The median processing time of the eye tracking algorithm was 18.60 ms, thus allowing eye monitoring up to 50 Hz. Conclusions: A noninvasive ETS prototype was designed to perform real-time target localization and eye movement monitoring during ocular radiotherapy treatments. The device aims at improving state-of-the-art invasive procedures based on surgical implantation of radiopaque clips and repeated acquisition of X-ray images, with expected positive effects on treatment quality and patient outcome.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Ensemble density functional theory method correctly describes bond dissociation, excited state electron transfer, and double excitations

State-averaged (SA) variants of the spin-restricted ensemble-referenced Kohn-Sham (REKS) method, SA-REKS and state-interaction (SI)-SA-REKS, implement ensemble density functional theory for variationally obtaining excitation energies of molecular systems. In this work, the currently existing version of the SA-REKS method, which included only one excited state into the ensemble averaging, is extended by adding more excited states to the averaged energy functional. A general strategy for extension of the REKS-type methods to larger ensembles of ground and excited states is outlined and implemented in extended versions of the SA-REKS and SI-SA-REKS methods. The newly developed methods are tested in the calculation of several excited states of ground-state multi-reference systems, such as dissociating hydrogen molecule, and excited states of donor–acceptor molecular systems. For hydrogen molecule, the new method correctly reproduces the distance dependence of the lowest excited state energies and describes an avoided crossing between the doubly excited and singly excited states. For bithiophene–perylenediimide stacked complex, the SI-SA-REKS method correctly describes crossing between the locally excited state and the charge transfer excited state and yields vertical excitation energies in good agreement with the ab initio wavefunction methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2026

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Data items will occasionally be removed from OSM if they are misidentified, if they no longer exist, if they are duplicates of another item, or similar. For that reason, updated versions of this database may not contain all data center locations included in previous versions. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2022

Wind and Solar Hybrid Power Plants for Energy Resilience

Wind-solar-storage hybrid power plants represent a significant and growing share of new proposed projects in the United States (U.S.). Their uptake is supported by increasing renewable energy market share, technical abilities for dispatch and control, and decreasing wind, solar, and battery storage costs. Simultaneously, generation and storage resources are increasingly used in distributed power systems. While concerns around the reliability of the aging, transforming U.S. electric grid are growing, diversifying energy resources through hybridization or spatial distribution provides an opportunity to enhance power system resilience compared to single-source generation. Understanding where to build hybrids for resilience value, rather than bulk power supply, has not been fully explored in previous studies. Therefore, in this study, we complete a national complementarity analysis to identify areas in the U.S. that are particularly suited for wind-solar hybrid power plant development. We show the importance of seasonal and diurnal patterns in assessing complementarity, and identify that regions in the Great Plains, Midwest, and Southeast are particularly suited for hybrid power plants. We demonstrate the resilience value of hybridization for a reference system based near Memphis, Tennessee, and show optimal sizing of wind, solar, and storage assets given 1.0 and 0.9 critical load factors. Results indicate that pairing wind and solar assets better meet constant load demand and reduce storage requirements compared to solar alone. These results enable future work integrating complementarity metrics in resilience frameworks and indicate a need for more finer resolution of local resource, demand, and hazard data.

14 SOLAR ENERGY↗
DOE OSTI2014

CO2-Binding Organic Liquids Gas Capture with Polarity-Swing-Assisted Regeneration Full Technology Feasibility Study B1 - Solvent-based Systems

PNNL, Fluor Corporation and Queens University (Kingston, ON) successfully completed a three year comprehensive study of the CO2BOL water-lean solvent platform with Polarity Swing Assisted Regeneration (PSAR). This study encompassed solvent synthesis, characterization, environmental toxicology, physical, thermodynamic and kinetic property measurements, Aspen Plus™ modeling and bench-scale testing of a candidate CO2BOL solvent molecule. Key Program Findings The key program findings are summarized as follows: • PSAR favorably reduced stripper duties and reboiler temperatures with little/no impact to absorption column • >90% CO2 capture was achievable at reasonable liquid-gas ratios in the absorber • High rich solvent viscosities (up to 600 cP) were successfully demonstrated in the bench-scale system. However, the projected impacts of high viscosity to capital cost and operational limits compromised the other levelized cost of electricity benefits. • Low thermal conductivity of organics significantly increased the required cross exchanger surface area, and potentially other heat exchange surfaces. • CO2BOL had low evaporative losses during bench-scale testing • There was no evidence of foaming during bench scale testing • Current CO2BOL formulation costs project to be $35/kg • Ecotoxicity (Water Daphnia) was comparable between CO2BOL and MEA (169.47 versus 103.63 mg/L) • Full dehydration of the flue gas was determined to not be economically feasible. However, modest refrigeration (13 MW for the 550 MW reference system) was determined to be potentially economically feasible, and still produce a water-lean condition for the CO2BOLs (5 wt% steady-state water loading). • CO2BOLs testing with 5 wt% water loading did not compromise anhydrous performance behavior, and showed actual enhancement of CO2 capture performance. • Mass transfer of CO2BOLs was not greatly impeded by viscosity • Facile separation of antisolvent from lean CO2BOL was demonstrated on the bench cart • No measurable solvent degradation was observed over 4 months of testing – even with 5 wt% water present

Heldebrant, David J↗
DOE OSTI2025

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗
DOE OSTI2026

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗
DOE OSTI2016

Influence of Anion Delocalization on Electron Transfer in a Covalent Porphyrin Donor–Perylenediimide Dimer Acceptor System

Photodriven electron transfer from a donor excited state to an assembly of electronically coupled acceptors has been proposed to enhance charge transfer efficiency in functional organic electronic materials. However, the circumstances under which this may occur are difficult to investigate in a controlled manner in disordered donor–acceptor materials. Here we investigate the effects of anion delocalization on electron transfer using zinc meso-tetraphenylporphyrin (ZnTPP) as a donor and a perylene-3,4:9,10-bis(dicarboximide) dimer as the acceptor (PDI 2 ). The PDI units of the dimer are positioned in a cofacial orientation relative to one another by attachment of the imide group of each PDI to the 4- and 5-positions of a xanthene spacer. Furthermore, the distal imide group of one PDI is linked to the para-position of one ZnTPP phenyl group to yield ZnTPP-PDI 2 . The data for the dimer are compared to two different ZnTPP-PDI monomer reference systems designed to probe electron transfer to each of the individual PDI molecules comprising PDI 2 . The electron transfer rate from the ZnTPP lowest excited singlet state to PDI 2 is increased by 50% relative to that in ZnTPP-PDI, when the data are corrected for the statistics of having two electron acceptors. Femtosecond transient IR absorption spectroscopy provides evidence that the observed enhancement in charge separation results from electron transfer producing a delocalized PDI 2 anion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Solvation Phenomena in Dilute Solutions: Formal, Experimental Evidence, and Modeling Implications

We review the fundamentals underlying a general molecular-based formalism for the microscopic interpretation of the solvation phenomena involving sparingly soluble solutes in compressible media, an approach that hinges around the unambiguous splitting of the species correlation function integrals into short-(finite) and long-ranged (diverging) contributions at infinite dilution, where this condition is taken as the reference system for the derivation of composition expansions. Then, we invoke the formalism (a) to illustrate the well-behaved nature of the solvation contributions to the mechanical partial molecular properties of solutes at infinite dilution, (b) to guide the development of, and provide molecular-based support to, the macroscopic modeling of high-temperature dilute aqueous-electrolyte solutions, (c) to study solvation effects on the kinetic rate constants of reactions in near-critical solvents in an attempt to understand from a microscopic perspective the macroscopic evidence regarding the thermodynamic pressure effects, and (d) to interpret the microscopic mechanism behind synergistic solvation effects involving either co-solutes or co-solvents, and provide a molecular argument on the unsuitability of the van der Waals one-fluid (vdW-1f) mixing rules for the 2 description of weakly attractive solutes in compressible solvents. Finally, we develop thermodynamically consistent perturbation expansions, around the infinite dilution reference, for the species residual properties in binary and ternary mixtures, and discuss the theoretical and modeling implications behind ad hoc first-order truncated expansions.

Chialvo, Ariel A↗
DOE OSTI2019

A complete quasiclassical map for the dynamics of interacting fermions

We present a strategy for mapping the dynamics of a fermionic quantum system to a set of classical dynamical variables. The approach is based on imposing the correspondence relation between the commutator and the Poisson bracket, preserving Heisenberg's equation of motion for one-body operators. In order to accommodate the effect of two-body terms, we further impose quantization on the spin-dependent occupation numbers in the classical equations of motion, with a parameter that is determined self-consistently. Expectation values for observables are taken with respect to an initial quasiclassical distribution that respects the original quantization of the occupation numbers. The proposed classical map becomes complete under the evolution of quadratic Hamiltonians and is extended for all even order observables. We show that the map provides an accurate description of the dynamics for an interacting quantum impurity model in the coulomb blockade regime, at both low and high temperatures. In conclusion, the numerical results are aided by a novel importance sampling scheme that employs a reference system to reduce significantly the sampling effort required to converge the classical calculations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Micro- and nanostructured electro-active polymer actuators as smart muscles for incontinence treatment

Treatments of severe incontinence are currently based on purely mechanical systems that generally result in revision after three to five years. Our goal is to develop a prototype acting in a natural-analogue manner as artificial muscle, which is based on electro-active polymers. Dielectric actuators have outstanding performances including millisecond response times, mechanical strains of more than 10 % and power to mass densities similar to natural muscles. They basically consist of polymer films sandwiched between two compliant electrodes. The incompressible but elastic polymer film transduces the electrical energy into mechanical work according to the Maxwell pressure. Available polymer films are micrometers thick and voltages as large as kV are necessary to obtain 10 % strain. For medical implants, polymer films should be nanometer thin to realize actuation below 48 V. The metallic electrodes have to be stretchable to follow the strain of 10 % and remain conductive. Recent results on the stress/strain behavior of anisotropic EAP-cantilevers have shown dependencies on metal electrode preparation. We have investigated tunable anisotropic micro- and nanostructures for metallic electrodes. They show a preferred actuation direction with improved stress-strain behavior. The bending of the cantilever has been characterized by the laser beam deflection method. The impact of the electrode on the effective Young's Modulus is measured using an Ultra Nanoindentation Tester with an integrated reference system for soft polymer surfaces. Once ten thousand layers of nanometer-thin EAP actuators are available, devices beyond the envisioned application will flood the market.

36 MATERIALS SCIENCE↗
DOE OSTI2015

SU-E-T-516: Investigation of a Novel Radiochromic Radiation Reporting System Utilizing the Reduction of Ferric Ion

Purpose To introduce and characterize a new “reverse-Fricke” radiation reporting system utilizing the reduction of ferric ions (Fe{sup 3+}) to ferrous ions (Fe{sup 2+}). Methods Two formulations of the radiochromic reporting system, referred to as A and B, were prepared for investigation. Formulation-A consisted of 14 mM 1,10-phenanthroline, 42 mM ethanol, and 57 mM ammonium ferric oxalate in water. Formulation-B consisted of 27 mM 1,10-phenanthroline, 42 mM ethanol, and 28 mM ammonium ferric oxalate in water. Solutions were prepared immediately prior to irradiation with a Cobalt-60 unit with radiation doses of 0, 1, 5, 10, 15, 20, and 25 Gy. The change in optical density over the visible range of 450–650 nm was measured using a spectrophotometer immediately after irradiation. The effective atomic numbers of the formulations were calculated using Mayneord’s formula. Results Ionizing radiation energy absorbed in the solutions causes the reduction of ferric ions (Fe{sup 3+}) into ferrous ions (Fe{sup 2+}), which then forms a 1:3 red colored complex with 1,10-phenanthroline ([(C{sub 1} {sub 2}H{sub 8}N{sup 2}){sub 3}Fe]{sup 2+}) that can be measured spectrophotometrically. The absorbance spectra of the resulting complex displayed a peak maximum at 512 nm with a greater change in absorbance for Formulation-B after receiving comparable radiation doses. The change in absorbance relative to dose exhibited a linear response up to 25 Gy for both Formulation-A (R{sup 2} = 0.98) and Formulation-B (R{sup 2} = 0.97). The novel formulations were also nearly water equivalent (Zeff = 7.42) with effective atomic numbers of 7.65 and 7.52 and mass densities within 0.2% of water. Conclusion Both formulations displayed visible Fe{sup 2+} complex formation with 1,10-phenanthroline after irradiation using a Cobalt-60 source. The higher sensitivity measured for Formulation-B is attributed to the increase in 1,10-phenanthroline concentration and the increase in the 1,10-phenanthroline to ammonium ferric oxalate ratio. Further investigation of this radiation reporting system in a 3D matrix material is encouraged. NSF GRFP Grant Award #LH-102SPS.

60 APPLIED LIFE SCIENCES↗