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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Novel perspective on a conventional technique: Impact of ultra-low temperature on bacterial viability and protein extraction

Ultra-low temperature (ULT) storage of microbial biomass is routinely practiced in biological laboratories. However, there is very little insight regarding the effects of biomass storage at ULT and the structure of the cell envelope, on cell viability. Eventually, these aspects influence bacterial cell lysis which is one of the critical steps for biomolecular extraction, especially protein extraction. Therefore, we studied the effects of ULT-storage (-80°C) on three different bacterial platforms: Escherichia coli , Bacillus subtilis and the cyanobacterium Synechocystis sp. PCC 6803. By using a propidium iodide assay and a modified MTT assay we determined the impact of ULT storage on cellular viability. Subsequently, the protein extraction efficiency was determined by analyzing the amount of protein released following the storage. The results successfully established that longer the ULT-storage time lower is the cell viability and larger is the protein extraction efficiency. Interestingly, E . coli and B . subtilis exhibited significant reduction in cell viability over Synechocystis 6803. This indicates that the cell membrane structure and composition may play a major role on cell viability in ULT storage. Interestingly, E . coli exhibited concomitant increase in cell lysis efficiency resulting in a 4.5-fold increase (from 109 μg/ml of protein on day 0 to 464 μg/ml of protein on day 2) in the extracted protein titer following ULT storage. Furthermore, our investigations confirmed that the protein function, tested through the extraction of fluorescent proteins from cells stored at ULT, remained unaltered. These results established the plausibility of using ULT storage to improve protein extraction efficiency. Towards this, the impact of shorter ULT storage time was investigated to make the strategy more time efficient to be adopted into protocols. Interestingly, E . coli transformants expressing mCherry yielded 2.7-fold increase (93 μg/mL to 254 μg/mL) after 10 mins, while 4-fold increase (380 μg/mL) after 120 mins of ULT storage in the extracted soluble protein. We thereby substantiate that: (1) the storage time of bacterial cells in -80°C affect cell viability and can alter protein extraction efficiency; and (2) exercising a simple ULT-storage prior to bacterial cell lysis can improve the desired protein yield without impacting its function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Data and scripts associated with a manuscript investigating impacts of solid phase extraction on freshwater organic matter optical signatures and mass spectrometry pairing

This data package is associated with the publication “Investigating the impacts of solid phase extraction on dissolved organic matter optical signatures and the pairing with high-resolution mass spectrometry data in a freshwater system” submitted to “Limnology and Oceanography: Methods.” This data is an extension of the River Corridor and Watershed Biogeochemistry SFA’s Spatial Study 2021 (https://doi.org/10.15485/1898914). Other associated data and field metadata can be found at the link provided. The goal of this manuscript is to assess the impact of solid phase extraction (SPE) on the ability to pair ultra-high resolution mass spectrometry data collected from SPE extracts with optical properties collected on ambient stream samples. Forty-seven samples collected from within the Yakima River Basin, Washington were analyzed dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), absorbance, and fluorescence. Samples were subsequently concentrated with SPE and reanalyzed for each measurement. The extraction efficiency for the DOC and common optical indices were calculated. In addition, SPE samples were subject to ultra-high resolution mass spectrometry and compared with the ambient and SPE generated optical data. Finally, in addition to this cross-platform inter-comparison, we further performed and intra-comparison among the high-resolution mass spectrometry data to determine the impact of sample preparation on the interpretability of results. Here, the SPE samples were prepared at 40 milligrams per liter (mg/L) based on the known DOC extraction efficiency of the samples (ranging from ~30 to ~75%) compared to the common practice of assuming the DOC extraction efficiency of freshwater samples at 60%. This data package folder consists of one main data folder with one subfolder (Data_Input). The main data folder contains (1) readme; (2) data dictionary (dd); (3) file-level metadata (flmd); (4) final data summary output from processing script; and (5) the processing script. The R-markdown processing script (SPE_Manuscript_Rmarkdown_Data_Package.rmd) contains all code needed to reproduce manuscript statistics and figures (with the exception of that stated below). The Data_Input folder has two subfolders: (1) FTICR and (2) Optics. Additionally, the Data_Input folder contains dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data (SPS_NPOC_Summary.csv) and relevant supporting Solid Phase Extraction Volume information (SPS_SPE_Volumes.csv). Methods information for the optical and FTICR data is embedded in the header rows of SPS_EEMs_Methods.csv and SPS_FTICR_Methods.csv, respectively. In addition, the data dictionary (SPS_SPE_dd.csv), file level metadata (SPS_SPE_flmd.csv), and methods codes (SPS_SPE_Methods_codes.csv) are provided. The FTICR subfolder contains all raw FTICR data as well as instructions for processing. In addition, post processed FTICR molecular information (Processed_FTICRMS_Mol.csv) and sample data (Processed_FTICRMS_Data.csv) is provided that can be directly read into R with the associated R-markdown file. The Optics subfolder contains all Absorbance and Fluorescence Spectra. Fluorescence spectra have been blank corrected, inner filter corrected, and undergone scatter removal. In addition, this folder contains Matlab code used to make a portion of Figure 1 within the manuscript, derive various spectral parameters used within the manuscript, and used for parallel factor analysis (PARAFAC) modeling. Spectral indices (SPS_SpectralIndices.csv) and PARAFAC outputs (SPS_PARAFAC_Model_Loadings.csv and SPS_PARAFAC_Sample_Scores.csv) are directly read into the associated R-markdown file. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Data for Zheng et al. (2025), "AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry"

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystems and soil function. Salinity affects soil carbon cycling by directly impacting microbial activity and indirectly altering soil physicochemical properties, but current models inadequately represent these complexities. This dataset contains the observational and modeling data from Zheng et al. (2025), which described a process-based modeling framework that couples soil solution chemistry with microbial carbon cycling reactions to study the impacts of soil salinization. This conceptual model is implemented numerically into the open-source geochemical program PHREEQC 3.0 (Parkhurst and Appelo, 2013). This dataset consists of: - Figure2_AquaMEND_salinity_buffer: Contains model simulation outputs to assess the impact of three different cation exchange and surface complexation processes on salinity buffering (Fig. 2 from Zheng et al. 2025). - Figure3_Salinity_function: Contains salinity function fitting for literature data (Fig. 3 from Zheng et al. 2025). - Figure4_AquaMEND_microbial_mechanisms: Contains model simulation outputs for testing various microbial process-based hypotheses related to soil salinization, including microbial mortality, carbon use efficiency (CUE), extracellular enzyme activity, and other microbial mechanisms (Fig. 4 from Zheng et al. 2025). - Figure5_AquaMEND_Redox: Contains on model simulation outputs to evaluate shifts among key redox processes, such as aerobic respiration, sulfate reduction, and methanogenesis (Fig.5 from Zheng et al. 2025). - Figure6_AquaMEND_sorption: Contains on model simulation outputs for investigating the effects of salinity on dissolved organic matter (DOM) sorption and desorption processes (Fig. 6 from Zheng et al. 2025). - Figure7_AquaMEND_process_couple: Contains on model simulation outputs for exploring coupled biotic-abiotic processes and their interactions (Fig. 7 from Zheng et al. 2025). - data: Includes datasets used to develop salinity response functions and evaluate salinity buffering capacity. Datasets for MEND model calibration. - database: Contains the `.dat` file required by PHREEQC for model execution. - README.md: A Markdown plain text file describing the computational tools and directories. Files are a mixture of plain text CSV (comma-separated value) and plain text *.dat files written by the model; no special software is required to read them.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL SALINIT↗
DOE OSTI2023

Computational Analysis of the Impact of Boundary Conditions on a Particle-Laden Flow: A Case Study in a Pressurized Oxy-Coal Combustor

Designing an effective burner is vital for the development of coal combustion technologies. Because of high pressure, the volumetric fraction of the coal particles in the injected fuel in a pressurized oxy-combustion (POC) burner approaches or even exceeds the limitations allowed by the commercial computational fluid dynamics codes (e.g., Ansys Fluent). Consequently, for such high particle volumetric fractions, the interplay between the particles, the fluid flow, and the burner wall needs to be re-evaluated. The present computational work is a first step in a systematic analysis of the roles of various characteristics involved in the POC process, such as the method of particle release, its location, and the particle size. Specifically, pulverized coal is burned under an elevated pressure of 15 bar in an O 2 /CO 2 environment. A 100 kW, a POC combustor, is modeled with Ansys Fluent using the Reynolds-averaged Navier−Stokes approach. It is revealed that for this pilot-scale, pressurized burner, the gas phase flow velocity in the near-wall region exhibits anomalies. With the major focus on POC, this work aims to eliminate/reduce the impact of high particle loading on the gas-phase flow. To scrutinize the role of particle loading in the near-wall region and eliminate the impact of this velocity on POC downstream, the particle−gas interplay in the boundary layer is investigated by means of the computational simulations incorporating the coupling between the turbulent flow and the particles. It is found that the tuning of the particle release location makes the gas-phase flow velocity in the presence of particles consistent with the pure gas flow velocity profile. The particles size is also found to have a significant impact on the particle trajectory.

CFD↗
DOE OSTI2023

Solar Farm Development Impacts on Eastern Box Turtle ( Terrapene carolina ) Home Ranges

Eastern Box Turtle (Terrapene carolina) populations have declined drastically since 1970 because of continued destruction and fragmentation of their habitat. Although they are known to shift their home ranges because of environmental degradation, it is unknown how solar arrays impact Eastern Box Turtles. From 2011–2018, we collected data on Eastern Box Turtle movement and occupancy in a 79-ha solar farm. The solar farm is divided into six fenced areas, each containing wildlife openings for movement of terrestrial fauna every 23 m around the fenced solar arrays. For this work, we hypothesized that the solar arrays changed the home range sizes of turtles that interacted with the field. We fitted 41 Eastern Box Turtles with radio transmitters and tracked their locations twice per week in June–August from 2011–2018. Seventeen turtles had home ranges that overlapped with the solar arrays whereas 24 turtles had home ranges that never interacted with the solar arrays. We calculated home range sizes and tested for differences between overlapping and nonoverlapping groups. We further considered if the number of observations within the solar farm impacted home range size and displacement. We found that Eastern Box Turtles that used the solar farm exhibited 55–83% larger home ranges on average than turtles in natural habitats, but there was no significant association of home range size with the amount of time observed within the solar farm. Finally, we discuss strategies to mitigate negative impacts of solar farm development on turtles.

Radio telemetry↗
DOE OSTI2020

Impacts of climate and biophysical variability on global agriculture markets

Agricultural production is highly sensitive to changes in climate and weather patterns. The focus of the great majority of studies assessing climate impacts on agriculture has been on mean changes in agricultural responses. However, the manner in which global agricultural markets respond to the interannual variability of the climate and biophysical shocks is poorly understood. Here we show a strong transmission of interannual variations in climate-induced biophysical yield shocks to agriculture markets, which is magnified further by endogenous market fluctuations. We demonstrate the importance of imperfect versus perfect expectations of market and weather in generating the market fluctuations that play a key role in transferring the interannual variations to markets. We find that the volatility of market prices and consumption could be potentially reduced on average by 55% and 41%, respectively, with improved expectations, where agricultural producers make better decisions to adapt to climate and biophysical variability. We also find much heterogeneity in interannual variability across crops and regions, which is considerably mediated by trade as part of the economic response. Our study provides new insights on climate impacts on agricultural market variability and lays a foundation for further investigating the full range of climate impacts on biophysical and human systems.

Zhao, Xin↗
DOE OSTI2020

Fluorine Limits and Impacts in High-Level Waste Glass Compositions

The impact of elevated fluorine (F) content on Hanford high-level waste (HLW) glasses has not previously been studied in detail. This effort represents the first systematic study to determine what F concentration limits should be used for the design of alkali-borosilicate-based Hanford Waste Treatment and Immobilization Plant (WTP) HLW glasses, and to document the technical basis for that limit. If alkali borosilicate glass made from Hanford HLW can accommodate a large amount of F, the large capital costs for complex sludge washing facilities may be avoided, as would much of the operational costs and negative schedule impacts associated with handling the large volumes of water required to dissolve these salts. In order to determine a limit for F in likely HLW glass compositions, an evaluation was conducted on glasses with F ≤ 0.90 mass% from previous nuclear waste glass studies. The collected dataset contains 239 glasses (232 HLW glasses and 7 LAW glasses) including 109 glasses with 0.9 ≤ F mass% ≤ 2.5, 116 with 2.5 < F mass% ≤ 8.0, and 14 with F mass% ≥ 8 (max. F mass% = 17.42). The collected composition and property data were analyzed to determine the basis for the F tolerance, i.e. the maximum F concentration that can be processed without potential issues. Fluorine volatility, product consistency test (PCT) response, liquidus temperature (T L ), glass melt viscosity, and crystallinity have been investigated. No limits for F concentration can be made based on F volatility, T L , or glass melt viscosity, because the data show that high F in glasses do not indicate, with high probability, being restricted by those property constrains. However, crystallinity and PCT response were used to estimate the F tolerance. The results show that glasses with high F (≥ 0.90 mass%) are more likely to form large fractions of F-containing crystal phases which may increase PCT responses, i.e. decrease the glass durability. Based on the results of crystallinity and PCT data, the F tolerance of 4.5 mass% is estimated. There is no evidence of other glass components, such as calcium oxides and alkali metal oxides have combined impacts with F on the glass properties. Overall, the available high-F glass data is limited, especially in the designed HLW glass composition regions. Future work on formulation and testing of HLW glasses with F ≥ 0.9 mass% will close the data gaps and expand operational flexibility with respect to the fluoride tolerances. Volatility of F from melters and corrosion of materials in contact with glass melts are important for processing of high-F wastes; yet no test data are currently available. It is recommended tests be conducted to address these two potential issues.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Sensor Impacts Evaluation and Verification: Expert Interview Responses

The sensor configuration/deployment method has critical impacts on energy efficient building control and thermal comfort. However, traditional sensor techniques for building operation and fault detection and diagnostics (FDD) are not necessarily optimal in terms of energy efficiency and thermal comfort, and their global effects are not thoroughly investigated. In an effort to address and overcome this limitation, a multilaboratory and multiyear project, “Sensor Impact Evaluation and Verification,” was proposed. Its purpose is to develop a framework to investigate the impacts of sensor deployment and configuration on building energy optimization, FDD, occupant thermal comfort, and potentially grid efficiency. The first project task was a literature review to establish a solid knowledge of and a background related to sensor technologies and placement. To accomplish this task, an extensive review of previous research literature was performed. A series of expert interviews were conducted to augment the findings of the literature review. This report summarizes the interview design and interview results and findings. The interview was designed and performed to (1) investigate the current status and limitations of sensor configuration, (2) identify the research gaps and expectations for potential improvements in sensor configuration and deployment, and (3) integrate expert (e.g., researcher, building operation practitioner) knowledge and experience to develop use-case scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Electrification Futures Study: Methodological Approaches for Assessing Long-Term Power System Impacts of End-Use Electrification

By its nature, electrification enhances the coupling between the electric sector and end-use sectors. Assessing the impacts of electrification requires both an examination of the complex interactions between sectors and a broader assessment of multiple parts of the energy system. The Electrification Futures Study (EFS) uses several complementary modeling and analysis tools to analyze the impacts of electrification on the U.S. energy system. In particular, the EFS relies on an overarching scenario analysis approach, but through the use of separate modeling approaches designed to assess various electricity demand- and supply-side futures. The primary model employed to generate the supply-side scenarios is the Regional Energy Deployment System (ReEDS) model, which is a capacity expansion model for the U.S. electricity system through 2050. Traditionally, the model has been primarily exercised in scenario analysis that implicitly assumed limited electrification. Because of this assumption, resulting future load profiles are approximated by historical ones, load growth is driven primarily by population and economic growth only, and changes in direct end-use natural gas consumption do not effect natural gas costs for electricity generation. In this report, we (1) reflect the potential for resource sharing between regions given these changes in demand, (2) represent how changes in natural gas consumption in end-use sectors could impact the economics of natural gas-fired generation, and (3) document a new model representation of demand-side flexibility used for the EFS. These improvements to ReEDS are employed for the EFS supply-wide analysis, which is summarized in a companion EFS report titled Electrification Futures Study: Scenarios of Power System Evolution and Infrastructure Development for the United States (Murphy et al. 2019). The data and methods documented in this report could also be adapted for other models with similar scope and limitations as ReEDS, and these data and methods could be used to assess future electric system scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Impact of undoped substrates on high performance silicon solar cells

Today's highest-efficiency silicon solar cells typically operate near the threshold between low-level and high-level injection. It is not well understood if pushing further into a regime in which the cell operating point is solidly in high-level injection at all times of the day has further benefits for the solar cell performance. From a reliability perspective, cells fabricated on lower doped silicon have a larger breakdown voltage. This advantage can affect the design of modules allowing higher voltages and a relaxation of the number of bypass diodes needed. In this project, we present a comprehensive assessment, both experimental and using simulation, of how bulk resistivity, light intensity, and operation temperature impact the performance of the silicon solar cell. This work incorporates a comprehensive device physics analysis assisted by numerical simulation. The source code is now available under General Public License (GPL3), and to further leverage the findings of this project and outreach people outside of the scientific community, we are working with www.pveducation.org (which receives >1 million visitors a year) to create interactive content using our simulation results. The simulation results indicate that high bulk resistivity wafers (>>10 Ωcm) require bulk Shockley-Read-Hall (SRH) lifetimes in the millisecond range to outperform wafers with standard bulk resistivities (<10 Ωcm). Additionally, above bulk resistivities of 10 Ωcm (the exact value depends on the bulk characteristics of the wafer), the cell efficiency is weakly dependent on the bulk resistivity. As a result, ingot manufactures may have an opportunity to further reduce wafer cost by growing higher resistivity ingots that are more tolerant to resistivity variations. This project is particularly relevant today, as solar cell architectures with improved surface passivation and milliseconds lifetimes wafers are commercially available, leveraging potential benefits of using higher bulk resistivities. Outside of interdigitated back contact (IBC) cell, reported studies on high resistivity silicon (>100 Ωcm) are very limited. To the best of our knowledge, this project provides for the first-time experimental insight on solar cells fabricated on wafers with bulk resistivities up to several thousand Ωcm, delivering a comprehensive vision of their performance under real-world temperature and light intensity operation conditions. We manufactured and characterized solar cells with bulk resistivities in the range of 1 Ωcm to >15k Ωcm. Under standard testing conditions (STC), we measured solar cells efficiencies over 20% over the entire range of bulk resistivities, using our baseline cell processing. To evaluate the cell performance in real-world operation conditions, the solar cells were measured at different temperatures (25-80°C) and at different light intensities (0.1-1 suns). The measurements show that the bulk resistivity does not impact the solar cell response to temperature and light intensity. Similar thermal coefficients (TC) were measured for standard and high bulk resistivities, and they are comparable with the TC values reported in the literature for standard bulk resistivities <10 Ωcm. After light soaking, the solar cell didn’t show signs of light-induced degradation (LID). This result was expected since n-type float zone (FZ) wafers were used in this work, i.e. low traces of boron and low concentration of oxygen (oxygen is typically found in the seed end of Czochralski (CZ) ingots). We measured for high bulk resistivities (>10 Ωcm) extremely high breakdown voltages (>1000V). In conclusion, the insight provided by this project can positively impact the levelized cost of energy (LCOE) of the photovoltaic systems through its effect on cell and ingot manufacturing yield, silicon cell power output, and module reliability.

14 SOLAR ENERGY↗
DOE OSTI2020

Oak Ridge Response to Versatile Test Reactor Environmental Impact Statement Data Request

The Versatile Test Reactor (VTR) is a fast-spectrum test reactor being developed in the United States under the direction of the US Department of Energy Office of Nuclear Energy (DOE-NE). The VTR mission is to enable accelerated testing of advanced reactor fuels and materials required for advanced reactor technologies. The conceptual design of the 300 MWth sodium-cooled metallic-fueled pool-type fast reactor has been led by the US National Laboratories in collaboration with General Electric–Hitachi and Bechtel National, Inc. In support of the VTR project, DOE issued a Notice of Intent (NOI) in the Federal Register on August 5, 2019, announcing the intent to prepare an Environmental Impact Statement (EIS) in accordance with the National Environmental Policy Act (NEPA) and its implementing regulations. The EIS will evaluate alternatives for a versatile reactor–based fast-neutron source facility and associated facilities for the preparation, irradiation, and post-irradiation examination (PIE) of test/experimental fuels and materials. Specifically, the NOI identified two siting alternatives for the VTR reactor facility: Idaho National Laboratory (INL) or Oak Ridge National Laboratory (ORNL). In addition, the NOI also specified two siting alternatives for VTR fuel fabrication: INL and the Savannah River Site (SRS). This report provides information in response to data requests made to ORNL to fill in site-specific knowledge gaps to develop a high-quality EIS. The responses provided are not required to provide full details in every aspect; instead, they adequately bound possible environmental impacts or provide sufficient information to adequately assess likely environmental impacts. This work is being performed under a subcontract from INL to ORNL using DOE-NE funds and is directed by DOE-NE and DOE-ID. Leidos has been contracted by DOE-NE to write the VTR EIS, so most data requests have come from Leidos but were often routed through INL or DOE-ID. DOE-ID is overseeing the NEPA and EIS processes for the VTR project. Leidos will use the information provided in this report to inform the VTR EIS and will also cite this document to establish a clear, publicly available source of the information. Section 2 of this report briefly describes the proposed ORNL VTR Alternative and illustrates the location of the proposed site for the ORNL VTR Alternative. Sections 3 through 7 provide direct responses to data requests received by ORNL. These sections use a tabular format in which data requests are divided into separate items to be addressed; the items are numbered, the data requests are restated with more topical information included, and then the responses are provided. Initial data requests and follow-on requests for additional information (RAIs) are combined under the original data request fields. Finally, Section 8 presents summarized conclusions and describes future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Agricultural Impacts on Nitrogen Cycling: Climate and Air Pollution (Final Technical Report)

We have successfully added a parameterization of ammonia emissions from synthetic fertilizer and manure from agriculture to Earth System Models. We have evaluated how emissions change in the future and the processes driving these changes. We have examined the impact of agricultural ammonia emissions on present-day air quality and have evaluated the impact of resolving the emissions with high temporal resolution. We have also examined the impact of how Earth System Models treat the cycling of emissions in soils. Our code, the Flows of Agricultural Nitrogen – version 2 – model (FANv2) has been run in both the CLM framework and the ELM framework. To my knowledge the code has not yet been fully implemented into ELM. Volatilization of ammonia (NH3) from fertilizers and livestock wastes forms a significant pathway of nitrogen losses in agricultural ecosystems and constitutes the largest source of atmospheric emissions of NH3. We have provided a major update to the process model FAN (Flow of Agricultural Nitrogen), which evaluates NH3 emissions interactively within an Earth system model; in this work, the Community Earth System Model (CESM) is used. The updated version (FANv2) includes a more detailed treatment of both physical and agricultural processes, which allows the model to differentiate between the volatilization losses from animal housings, manure storage, grazed pastures, and the application of manure and different types of mineral fertilizers. The modeled ammonia emissions are first evaluated at a local scale against experimental data for various types of fertilizers and manure, and they are subsequently run globally to evaluate NH3 emissions for 2010–2015 based on gridded datasets of fertilizer use and livestock populations. Comparison of regional emissions shows that FANv2 agrees with previous inventories for North America and Europe and is within the range of previous inventories for China. However, due to higher NH3 emissions in Africa, India, and Latin America, the global emissions simulated by FANv2(48 Tg N) are 30 %–40 % higher than in the existing inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Enhancing Resilience of Urban Systems Against Climate-Induced Floods Using Advanced Data-Driven and Computing Techniques: A Driver-Pressure-State-Impact-Response (DPSIR) Framework

Focal Area: This white paper proposes advanced data-driven and computing techniques to improve the predictability of extreme climate events (precipitation) and focuses on comprehending their impact dynamics to enhance resilience of urban systems. Science Challenge: In urban systems, climate change has presented significant challenges related to accurate spatiotemporal prediction of extreme climate events (heavy precipitation) and their impacts, i.e. flooding. The occurrence of extreme climate events and their compounding repercussions on the built environment make urban systems increasingly more vulnerable. The interactions between extreme climate events, urban systems, and the corresponding impacts are irregular, non-linear, and dynamic, making it difficult to standardize resilience. As it stands, the management of complex urban systems is affected by uncertainties related to the nature of short- and long-term consequences caused by extreme events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Proceedings from the State of the Science and Technology for Minimizing Impacts to Bats from Wind Energy

The U.S. Department of Energy Wind Energy Technologies Office (DOE WETO), and the National Renewable Energy Laboratory convened a workshop entitled the State of the Science and Technology for Minimizing Impacts to Bats from Wind Energy on 13–14 November 2019. The objectives of the workshop were to (1) Identify the current impact minimization measures that are, or can be, used to reduce bat fatalities at wind energy facilities, (2) Assess the current effectiveness of those minimization measures, (3) Identify and assess the research and development (R&D) opportunities needed to optimize and improve the effectiveness of current minimization and deterrent technologies and inform the development of future solutions; and (4) Identify potential emerging or novel methods for informing impact minimization measures at or around wind energy facilities. Specifically, the workshop focused on deterrent and curtailment strategies. For deterrents, the discussion centered on the existing technology (i.e., ultrasonic deterrents, dim-UV light, and texture coating), integration with wind turbines (either retrofitting or out of the box installation), effectiveness, validation studies, and cost (e.g., technology, installation, validation, and maintenance). For curtailment, the conversation was divided into blanket curtailment (i.e., based on time and wind speed) and smart curtailment (i.e., blanket curtailment plus additional variables such as temperature or bat activity). The workshop included plenary presentations, panels, and breakout sessions to share data and stakeholder perspectives, and engage participants. Although there are several priority topics related to bat and wind energy, this workshop focused the discussion on the current technologies and strategies that are, or can be, used to reduce bat fatalities at wind energy facilities, status of research and development (R&D) of minimization measures, opportunities to optimize costs and improve effectiveness, and potential emerging or novel approaches to explore. This workshop took a holistic approach and discussed all aspects associated with advancing deterrent technologies and curtailment strategies, including the technological, biological, economic, and regulatory barriers faced by the wind energy and wildlife community.

13 HYDRO ENERGY↗
DOE OSTI2020

Impact of K-Optimization on Trap Concentration in (Ag,Cu)(In,Ga)Se 2 Solar Cells

Recent progress has been made in improving efficiency in Cu(In,Ga)Se 2 (CIGS) absorbers with steady increases in peak efficiency. One way this has been achieved is by adding Ag to CIGS (ACIGS) to achieve higher V OC . However, these efficiencies are still well below the Shockley-Queisser efficiency limit, and traps acting as recombination centers and compensating centers are one thing limiting the solar efficiency. Past research in CIGS has shown that alkali treatment can improve the efficiency and metastability problems in CIGS, but less is understood about the role of alkali treatments in ACIGS. Here, we investigate the impact of potassium in ACIGS through its impact on trap incorporation and minority carrier lifetime. The samples in this study were grown in a roll-to-roll coater with Mo, ACIGS, CdS, and ZnO structure. Both cells were grown identically except the second (K-optimized) cell was grown with increased K-doping of the Mo contact and was more Cu-poor near the surface to optimize the K profile. This resulted in an efficiency increase from 16.8% to 18.7% for the K-optimized cell, which was mostly due to a 65 mV V OC increase. The doping profile showed a 2X increase in acceptor concentration of the K-optimized cell (2.5×10 15 cm -3 ) which suggests that the K was better incorporated into the ACIGS after these optimizations. To characterize the traps in these cells, deep level transient and optical spectroscopy were used. The DLOS measurements showed an EV+0.98 eV trap whose concentration was reduced 10X in the K-optimized cell (4×10 14 cm -3 ). This is consistent with previous results from the alkali treatment in CIGS, which also showed a decrease in near-conduction band trap concentration [1], but the reduction was larger than previous studies possibly indicating the combination of K and Cu-poor surface may both have aided in reducing the EV+0.98 eV trap concentration. The other primary trap is the mid-gap trap (EV+0.58 eV), which was quantified using DLTS. Its concentration decreased from 9×10 13 cm -3 to 4×10 13 cm -3 in the K-optimized sample, which is a 2X reduction. Previous studies have shown this trap is likely an efficient recombination center [2], which makes sense because it is near mid-gap. This trap has also been associated with V OC instability and reduction, so reducing this trap concentration is essential to achieve high V OC and cell efficiency. To help confirm this association, time-resolved photoluminescence measurements have shown in this sample set and a previous study that the minority carrier lifetime (19 ns baseline to 56 ns K-optimized) and this EV+0.56 eV trap concentration are inversely proportional, which would be expected for a recombination-limited carrier lifetime. The K optimization of ACIGS results in significantly improved cell efficiency and reduced trap concentrations that correlate with the improved material and electrical properties. We will report on this and the impact of the K optimization on the cell metastability.

14 SOLAR ENERGY↗
DOE OSTI2021

Assessing Cognitive Impacts of Errors from Machine Learning and Deep Learning Models: Final Report

Due to their recent increases in performance, machine learning and deep learning models are being increasingly adopted across many domains for visual processing tasks. One such domain is international nuclear safeguards, which seeks to verify the peaceful use of commercial nuclear energy across the globe. Despite recent impressive performance results from machine learning and deep learning algorithms, there is always at least some small level of error. Given the significant consequences of international nuclear safeguards conclusions, we sought to characterize how incorrect responses from a machine or deep learning-assisted visual search task would cognitively impact users. We found that not only do some types of model errors have larger negative impacts on human performance than other errors, the scale of those impacts change depending on the accuracy of the model with which they are presented and they persist in scenarios of evenly distributed errors and single-error presentations. Further, we found that experiments conducted using a common visual search dataset from the psychology community has similar implications to a safeguards- relevant dataset of images containing hyperboloid cooling towers when the cooling tower images are presented to expert participants. While novice performance was considerably different (and worse) on the cooling tower task, we saw increased novice reliance on the most challenging cooling tower images compared to experts. These findings are relevant not just to the cognitive science community, but also for developers of machine and deep learning that will be implemented in multiple domains. For safeguards, this research provides key insights into how machine and deep learning projects should be implemented considering their special requirements that information not be missed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

LightMAT - Continuous fiber malleable thermoset composites with sub-1-minute dwell times; validation of impact performance and evaluation of the efficacy of the compression forming process (CRADA 409 Final Report)

In spite of carbon fiber composite materials’ significant impact on light-weighting, performance, and efficiency in the aerospace industry, adoption of these materials has been slow in high-volume industries such as automotive. Two major barriers to adoption are cost and cycle-time. Current approaches to thermoset composite part production are dependent on in-mold curing of thermosets which are not optimal for high volume, high throughput production due to limitations and inefficiencies associated with the in-mold cure itself. In addition, ancillary activities, such as transport and storage of shelf-life-limited uncured, or B-staged prepreg materials typically necessitate refrigerated transport and storage which significantly impacts the economic and energy costs associated with manufacturing. Furthermore, limited out-life means that trimmings cannot typically be used as they partially cure during initial production leading to high scrap rates (+20% is common). Finally, the need to cure in-mold drives cycle times to multiple minutes in the best cases, and 10’s of minutes to hours in most cases. Mallinda is developing polyimine malleable thermoset prepreg composite materials which have excellent mechanical properties (100 GPa tensile modulus, 2 GPA tensile strength, 2.4% elongation at break) and high operating temperatures (Tg>200°C). At scale, polyimine resins are commensurate in price with commodity epoxy resins. What distinguishes malleable thermoset prepreg from traditional thermoset prepreg materials, is that they are fully cured during Mallinda’s roll-to-roll production of prepreg laminate. This results in 5 key value-differentiating benefits. First, it simplifies manufacturing logistics by enabling ambient transportation and storage, and by significantly extending out-life and shelf-life almost indefinitely. Second, elimination of autoclave curing reduces the economic and energy costs to the customer. Third, scrap rates can be reduced as malleable thermoset prepreg materials are directly reusable. Fourth, the manufacturing consolidation step can be roughly 10x faster than traditional thermosets, because the resin is already cured. Parts can be made via compression forming by the application of heat and pressure to quickly vitrify and consolidate a multilayer part – easily leading to sub 3-minute cycle times (at lab scale we have demonstrated a 20 second dwell time, with room for further optimization). Finally, the closed-loop cradle-to-cradle solution-based recyclability of malleable thermoset composites can also contribute significantly to the future of sustainable lightweight materials. The focus of this project was the development, optimization and validation of malleable thermoset composite materials which exhibit manufacturing cycle times of 3-minute or less, high speed impact performance on par with incumbent technologies, and defect-free consolidation of 3 dimensional parts. Government funding is required on this project because Mallinda is a start-up company whose focus is the development and scale-up of the described technology for introduction to the transportation segment. Unlike incumbent industry players, Mallinda is bringing a completely new and highly relevant malleable thermoset technology to bear on the problem of high throughput composites. As a small business, Mallinda relies on a combination of government R&D funding and private capital to perform development work.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Impacts of Increasing Electrification on State Fleet Operations and Charging Demand

State fleets represent an enticing opportunity to explore the near-term feasibility of fleet electrification. In many instances, state fleet operations encompass a wide geographic area with fleet locations for many vehicles. Serving these wide areas will require a significant amount of energy and, in the case of electric vehicles (EVs), a significant level of charging power. The peak demand as a result of this charging demand is of interest for fleets, with impacts on both utility bills and installation costs ranking among some of the greatest concerns. The combination of a wide operational area and multiple fleet locations positions state fleets as ideal candidates to understand the impacts of vehicle charging on fleet operations. As the availability of electric drivetrains expands beyond light-duty sedans, fleets need to understand when it will be appropriate operationally and financially to start adding electric drivetrains to their fleets. Throughout this process, it will also be important to understand the charging implications of fleet electrification and the resulting impacts to facility electrical systems. To better understand these considerations, NREL contracted Sawatch Labs to analyze the role that increasing state fleet electrification may have on the charging demand at fleet parking facilities.

33 ADVANCED PROPULSION SYSTEMS↗