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

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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Preliminary Observations on the Hydrogen Redistribution Feedback in YH-Moderated Monolithic Microreactors.

Nuclear microreactors promise to open new markets for nuclear industry. This is due to their potential competitive cost in non-traditional market segments, e.g., mines, forward military basis, extraterrestrial surfaces and remote areas, and inherently safe characteristics that make them deployable where other power sources are not available or difficult to exploit. Transition metal dihydrides have been considered among the most promising candidates for moderating nuclear microreactors. In particular, yttrium hydride (YH\textsubscript{x}) has been selected for high temperature applications due to its high thermal stability and relatively high hydrogen retention at temperatures exceeding $870^\circ C$. One of the main issues associated with the use of hydrides is that, when exposed to temperature, stress, or concentration gradients, the hydrogen contained in the metallic matrix tends to redistribute and leak from the moderating elements, potentially leading to reactivity losses and power swings. The purpose of this paper is to gain a better physical understanding of the neutronic feedback associated with the hydrogen redistribution in YH\textsubscript{x}, by using Griffin and Bison. This feedback is inherently multiphysics, since the hydrogen distribution is strongly dependent on the moderator temperature spatial distribution. In particular, we want to understand the sign (+/-) of the neutronic feedback, its order of magnitude, and its underlying physical causes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Uncovering grain and subgrain microstructure at the scale of additive manufacturing melt tracks with a scalable cellular automaton solidification model

Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. Here, the highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-Nickel Cathodes with Mechanical and Interfacial Robustness via Tailored Concentration Gradients for Stable Li-Ion Batteries

Here, we have developed a versatile mathematical framework integrated with an automated reactor system to design and reify highly customizable full concentration gradient (FCG) in high-nickel cathodes for advanced Li-ion batteries. This method provides precise and independent control of the average composition, slope, and curvature of FCGs, enabling the optimization of structural and mechanical properties of the cathode materials. We have showcased this method with Ni 0.8 Co 0.1 Mn 0.1 (OH) 2 precursors of controlled FCGs, which unlocked an optimized cathode with excellent cycling stability without crack formation after repeated cycles. This work opens up new possibilities for the design and manufacturing of advanced cathode materials, enabling safer, high-performance batteries.

25 ENERGY STORAGE↗
DOE OSTI2026

Manipulation of the orbital angular momentum of soft X-ray beams by consecutive diffractive optics

Production and manipulation of orbital angular momentum (OAM) of coherent soft X-ray beams is demonstrated utilizing consecutive diffractive optics. OAM addition is observed upon passing the beam through consecutive fork gratings. Here, the OAM of the beam was found to be decoupled from its spin angular momentum (SAM). Practical implementation of angular momentum control by consecutive devices in the X-ray regime opens new experimental opportunities, such as direct measurement of the beam’s OAM without resorting to phase-sensitive techniques, including holography. OAM analyzers utilizing fork gratings can be used to characterize the beams produced by synchrotron and free electron lasers sources; they can also be used in scattering experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins

This repository of global hydrogeologic datasets contains aquifer properties on 0.5° scale, including depth to groundwater (Fan et al., 2013), aquifer thickness (de Graaf et al., 2015), WHYMap aquifer classes (Richts et al., 2011), recharge (Döll and Fiedler, 2008; Gleeson et al., 2016), lakes (Messager et al., 2016), porosity and permeability (Gleeson et al., 2014), digitized and geo-processed from their respective sources. Globally gridded aquifer properties could be used independently to estimate global groundwater availability or used as critical inputs to the superwell model to simulate groundwater extraction and provide estimates of pumped volumes and unit costs under user-specific scenarios. Key resources related to this data are: Niazi, H., Ferencz, S. B., Graham, N. T., Yoon, J., Wild, T. B., Hejazi, M., Watson, D. J., & Vernon, C. R. (2025). Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1. Geoscientific Model Development, 18(5), 1737-1767. https://doi.org/10.5194/gmd-18-1737-2025 superwell model repository which uses this data to simulate groundwater extraction and provides estimates of the global extractable volumes and unit-costs ($/km3) of accessible groundwater production under user-specified extraction scenarios. Repository Overview Main output: aquifer_properties_rec.csv contains all processed outputs, including aquifer properties like porosity, permeability, recharge, lake areas, aquifer thickness, and depth to groundwater. shapefiles.zip: contains all digitized GIS databases and shapefile for all aquifer properties prep_inputs.R and prep_inputs_recharge_lakes.R: R scripts that process the shapefiles to produce the aquifer_properties_rec.csv file plot_inputs.R: R script for plotting the maps and conducting preliminary analysis on the available groundwater volume basin_to_country_mapping.csv, basin_country_region_mapping.csv and continent_county_mapping.csv provide the mapping between continents, 32 energy-economic macro regions, countries, and water basins for post-processing aquifer_properties_rec.csv Maps: Each map visualizes the spatial distribution of one of the aquifer properties across the globe map_in_Porosity.png map_in_Permeability.png map_in_Aquifer_thickness.png map_in_Depth_to_water.png map_in_Recharge.png map_in_Grid_area_km.png map_in_Lake_area_km.png map_in_WHYClass.png Sample inputs sample_inputs.py: this script samples inputs from the aquifer_properties_rec dataset, ensuring the sampled and original inputs maintain the same distributions sampled_data_100.csv contains 100 sampled data points and sampled_data_100.png compares their distributions Dataset Overview The main outputs are consolidated in a comprehensive aquifer_properties_rec.csv file and include the following fields: GridCellID: Unique identifier for each (roughly 0.5°) grid cell Continent: Continent name Country: Country name GCAM_basin_ID: Identifier for GCAM hydrologic basin Basin_long_name: Full name of the basin WHYClass: Hydrogeologic classification based on WHYMap aquifer classes (Richts et al., 2011) Porosity: Soil porosity (%) (Gleeson et al., 2014) Permeability: Soil permeability (in square meters; Gleeson et al., 2014) Aquifer_thickness: Thickness of the aquifer (in meters; de Graaf et al., 2015) Depth_to_water: Depth to groundwater (in meters; Fan et al., 2013) Recharge: long-term annual averaged recharge rates (in m/yr; Döll and Fiedler, 2008; Gleeson et al., 2016) Grid_area: Area of the grid cell (in square meters) Lakes_area: Area of inland lakes (in square meters; Messager et al., 2016) Key References The datasets are digitized versions of global hydrogeologic properties from the following key literature sources: Depth to Groundwater: Fan, Y., Li, H., & Miguez-Macho, G. (2013). Global Patterns of Groundwater Table Depth. Science, 339(6122), 940-943. https://doi.org/10.1126/science.1229881 Aquifer Thickness: de Graaf, I. E. M., Sutanudjaja, E. H., van Beek, L. P. H., & Bierkens, M. F. P. (2015). A high-resolution global-scale groundwater model. Hydrol. Earth Syst. Sci., 19(2), 823-837. https://doi.org/10.5194/hess-19-823-2015 Porosity and Permeability: Gleeson, T., Moosdorf, N., Hartmann, J., & van Beek, L. P. H. (2014). A glimpse beneath earth's surface: GLobal HYdrogeology MaPS (GLHYMPS) of permeability and porosity. Geophysical Research Letters, 41(11), 3891-3898. https://doi.org/10.1002/2014GL059856 Aquifer classes: Richts, A., Struckmeier, W. F., & Zaepke, M. (2011). WHYMAP and the Groundwater Resources Map of the World 1:25,000,000. In J. A. A. Jones (Ed.), Sustaining Groundwater Resources: A Critical Element in the Global Water Crisis (pp. 159-173). Springer Netherlands. https://doi.org/10.1007/978-90-481-3426-7_10 Recharge: Döll, P., & Fiedler, K. (2008). Global-scale modeling of groundwater recharge. Hydrol. Earth Syst. Sci., 12(3), 863-885. https://doi.org/10.5194/hess-12-863-2008; Gleeson, T., Befus, K. M., Jasechko, S., Luijendijk, E., & Cardenas, M. B. (2016). The global volume and distribution of modern groundwater. Nature Geoscience, 9(2), 161-167. https://doi.org/10.1038/ngeo2590 Inland Lakes: Messager, M. L., Lehner, B., Grill, G., Nedeva, I., & Schmitt, O. (2016). Estimating the volume and age of water stored in global lakes using a geo-statistical approach. Nature Communications, 7(1), 13603. https://doi.org/10.1038/ncomms13603 Cite as Niazi, H., Watson, D., Hejazi, M., Yonkofski, C., Ferencz, S., Vernon, C., Graham, N., Wild, T., & Yoon, J. (2024). Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins. MultiSector Dynamics-Living, Intuitive, Value-adding, Environment. https://doi.org/10.57931/2484226 Contact Reach out to Hassan Niazi or open an issue in the superwell repository for questions or suggestions.

aquifer thickness↗
DOE OSTI2019

COMBLE Ice Nucleating Particle Measurements

These data list ice nucleating particle (INP) number concentrations active in the immersion freezing mode per large volumes of air collected using filters, sampled atop the AOS trailer, part of AMF1, sited at Nordmela Harbor, Andøya Island, Norway, from 01 December 2019 to 26 May 2020, as part of the Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE). Collections were made over periods of 6 to 74 hours (average 34 h and 42 m3 filtered), with periods tailored to integrate cold-air outbreaks or flanking periods of non-cold-air outbreak air. We used open-faced polycarbonate filters that were sampled at a height of 4 m AGL on the AOS trailer (6 m below its inlet), 6-8 m ASL and 30 m inland from the harbor wall, and near the other AMF measurements. Filters were stored and returned frozen to Colorado State University (CSU), where immersion freezing measurements over a range from 0 to typically -28°C were made using the CSU Ice Spectrometer (IS). This first entailed the removal of particles (agitation of filter in 0.1 µm filtered ultrapure water) from filters to create aliquot suspensions that were subdivided (and frozen) for subsequent analyses. One portion was used to obtain a basic temperature spectrum of INP number concentrations on the basis of the freezing of an array of smaller liquid aliquots during cooling, and relation of the frozen fraction to the total air volume sampled. A subset of other portions of the original suspension aliquots were heat treated (95°C for 20 min) to denature biological INPs (a reduction in concentrations reveals the proportion of all INPs that were likely of biological origin, such as microbial or proteinaceous) and digested in 10% H2O2 at 95°C under UV-B illumination to remove all organic carbon INPs; the residual is presumed to be inorganic (likely mineral) INPs. Other samples have been archived frozen for future potential testing of INP source compositions and aerosol chemical and biological source attribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Synthesis of 2D layered transition metal (Ni, Co) hydroxides via edge-on condensation

Abstract Layered transition metal hydroxides (LTMHs) with transition metal centers sandwiched between layers of coordinating hydroxide anions have attracted considerable interest for their potential in developing clean energy sources and storage technologies. However, two-dimensional (2D) LTMHs remain largely understudied in terms of physical properties and applications in electronic devices. Here, for the first time we report > 20 μm α-Ni(OH) 2 2D crystals, synthesized from hydrothermal reaction. And an edge-on condensation mechanism assisted with the crystal field geometry is proposed to understand the 2D intra-planar growth of the crystals, which is also testified through series of systematic comparative studies. We also report the successful synthesis of 2D Co(OH) 2 crystals (> 40 μm) with more irregular shape due to the slightly distorted octahedral geometry of the crystal field. Moreover, the detailed structural characterization of synthesized α-Ni(OH) 2 are performed. The optical band gap energy is extrapolated as 2.54 eV from optical absorption measurements and the electronic bandgap is measured as 2.52 eV from reflected electrons energy loss spectroscopy (REELS). We further demonstrate its potential as a wide bandgap (WBG) semiconductor for high voltage operation in 2D electronics with a high breakdown strength, 4.77 MV/cm with 4.9 nm thickness. The successful realization of the 2D LTMHs opens the door for future exploration of more fundamental physical properties and device applications.

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

PySAGES: flexible, advanced sampling methods accelerated with GPUs

Abstract Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of the relevant underlying free energy landscapes. In this sense, software that can be seamlessly adapted to a broad range of complex systems is essential. Building on past efforts to provide open-source community-supported software for advanced sampling, we introduce PySAGES, a Python implementation of the Software Suite for Advanced General Ensemble Simulations (SSAGES) that provides full GPU support for massively parallel applications of enhanced sampling methods such as adaptive biasing forces, harmonic bias, or forward flux sampling in the context of molecular dynamics simulations. By providing an intuitive interface that facilitates the management of a system’s configuration, the inclusion of new collective variables, and the implementation of sophisticated free energy-based sampling methods, the PySAGES library serves as a general platform for the development and implementation of emerging simulation techniques. The capabilities, core features, and computational performance of this tool are demonstrated with clear and concise examples pertaining to different classes of molecular systems. We anticipate that PySAGES will provide the scientific community with a robust and easily accessible platform to accelerate simulations, improve sampling, and enable facile estimation of free energies for a wide range of materials and processes.

Chemistry↗
DOE OSTI2019

Climate-driven oscillation of phosphorus and iron limitation in the North Pacific Subtropical Gyre

The supply of nutrients is a fundamental regulator of ocean productivity and carbon sequestration. Nutrient sources, sinks, residence times, and elemental ratios vary over broad scales, including those resulting from climate-driven changes in upper water column stratification, advection, and the deposition of atmospheric dust. These changes can alter the proximate elemental control of ecosystem productivity with cascading ecological effects and impacts on carbon sequestration. Here, we report multidecadal observations revealing that the ecosystem in the eastern region of the North Pacific Subtropical Gyre (NPSG) oscillates on subdecadal scales between inorganic phosphorus (P i ) sufficiency and limitation, when P i concentration in surface waters decreases below 50–60 nmol⋅kg −1 . In situ observations and model simulations suggest that sea-level pressure changes over the northwest Pacific may induce basin-scale variations in the atmospheric transport and deposition of Asian dust-associated iron (Fe), causing the eastern portion of the NPSG ecosystem to shift between states of Fe and P i limitation. Our results highlight the critical need to include both atmospheric and ocean circulation variability when modeling the response of open ocean pelagic ecosystems under future climate change scenarios.

Pacific Decadal Oscillation↗
DOE OSTI2024

Mitigating Scattering in a Quantum System Using Only an Integrating Sphere

Strong quantum correlated sources are essential but delicate resources for quantum information science and engineering protocols. Decoherence and loss are the two main disruptive processes that lead to the loss of nonclassical behavior in quantum correlations. In quantum systems, scattering can contribute to both decoherence and loss. In this work, we present an experimental scheme capable of significantly mitigating the adverse impact of scattering in quantum systems. Our quantum system is composed of a two-mode squeezed light generated with the four-wave-mixing process in hot rubidium vapor and a scatterer is introduced to one of the two modes. An integrating sphere is then placed after the scatterer to recollect the scattered photons. We use mutual information between the two modes as the measure of quantum correlations and demonstrate a 47.5% mutual information recovery from scattering, despite an enormous photon loss of greater than 85%. Our scheme is the very first step toward recovering quantum correlations from disruptive random processes and thus has the potential to bridge the gap between proof-of-principle demonstrations and practical real-world implementations of quantum protocols. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

WBS 4.1.2.31 Bioproduct Transition System Dynamics

Bioproducts are chemicals derived from a biomass feedstock; they can be produced on their own or as co-products of a biorefinery that also produces biofuels. Bioproducts have historically been difficult to scale up and bring to market, despite a broad understanding developed within BETO of the various conversion processes that can be used to produce bioproducts. Expanding the bioproducts industry by bringing more bioproducts to market would have a variety of positive impacts. Growth in the bioproducts industry would support the biofuels industry by enabling biorefinery co-products that yield additional revenue streams, allowing biofuel selling prices to be reduced and expanding the biofuels market. A larger bioproducts industry also has the potential to reduce carbon and other emissions associated with the U.S. chemical sector and contribute to increased price stability in some areas of the chemical market by shifting portions of the chemical sector away from reliance on fossil feedstocks. The key barrier to realizing these positive impacts is a lack of knowledge around the factors that prevent or enable bioproducts to reach the commercial market. To date, there has been essentially no research done on how successful bioproducts (commercially produced bioproducts that have captured market share) become successful, why failed bioproducts fail, and what the similarities and differences are between successful and failed bioproducts. The current project addresses this knowledge gap with a decision support tool that can be used by investors, technology developers and government agencies to bring more bioproducts to market, thereby simultaneously growing the bioproducts and biofuels industries. Development of the decision support tool was based on research on the technology development process and success rates in analogous industries, data gathered during previous BETO-funded projects, and a series of interviews with subject-matter experts within BETO, the bioproducts industry, and the investment community. This information formed a knowledge base around how bioproducts are developed from applied research to commercial scale was assembled, which was used to build the Bioproduct Transition Dynamics (BTD) model, a system dynamics (SD) model that tracks bioproduct development projects from applied research through the 'valley of death' of piloting and demoing to commercial scale production. The end-of-project goal is to release the BTD, along with supporting documentation, as a transparent open-source model that will inform decisions around bioproduct development and investments and enable more bioproducts to reach the market. The BTD takes as inputs techno-economic data on specific bioproducts, behavioral parameters for developers and investors, expectations around government support, and exogenous market factors. Model outputs include bioproduct technological progress over time, a cash flow statement for the development project, and market share estimates. Following initial model development, a sensitivity analysis was performed on a subset of model inputs to determine, first, if the BTD could be used to answer analysis questions of interest to BETO, and second, which of the inputs considered were most influential on bioproduct success. Results indicate that the BTD can be used to identify scenarios that enable bioproduct development, and that 'soft' or semi-quantitative factors play a large role in determining if a bioproduct will reach the market. A workshop was also held for subject-matter experts and prospective BTD users in July 2018. The workshop covered BTD model logic, input data and assumptions as well as the sensitivity analysis results and a discussion of potential use cases. Workshop feedback was used to identify additional model development tasks and was incorporated into a draft technical report completed in September 2018. BTD model development, validation and application will continue through 2019.

09 BIOMASS FUELS↗
DOE OSTI2024

Reducing Pb and Cl Mobility in Waste-to-Energy Fly Ashes via Chlorellestadite Formation

Sustainably sourced development minerals are vital to meeting the demand for low-carbon construction materials. A potential waste material that can be a low-carbon construction material for cementitious systems is waste-to-energy fly ash (WTE ash), a by-product of waste incineration. WTE ash contains chloride-bearing species and heavy metals, which can promote steel reinforcement corrosion and present long-term leaching risks. Here, we present a new multi-step ash treatment protocol involving dissolution and heating to transform the non-readily removable chlorides in WTE ash to Chlorellestadite (Ca 10 (SiO 4 ) 3 (SO 4 ) 3 Cl 2 ). Our results suggest that this transformation significantly reduces chloride release from WTE ash in an alkaline cement-like environment by over two orders of magnitude, from 1500 mg/l to less than 10 mg/l. This transformation also significantly reduces Pb mobility after treatment (from > 5 mg/l to < 0.5 mg/l), likely caused by the crystallo-chemical incorporation of Pb in Chlorellestadite. In contrast to the existing ash treatment methods, the proposed ash treatment protocol minimizes heavy metals volatilization while simultaneously reducing Pb mobility and chloride release through Chlorellestadite formation. Furthermore, these findings overcome limitations preventing the commercial use of WTE ash and thus opening up pathways towards a circular economy.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Role of phosphate source in improving the proton conductivity of tin pyrophosphate and its composite electrolytes

Metal pyrophosphates (MPPs) in general, and tin pyrophosphate (TPP) in particular, have received significant interest in the last decade due to their potential as proton conductors for electrolyte application in intermediate temperature (IT)-fuel cells. However, for MPP based electrolytes, despite high reported proton conductivities, achieving good fuel cell performance and high open circuit voltage (OCV) remains a challenge with synthesis methods playing a crucial role in determining the final proton conductivity. Here we report the role of phosphate precursor in determining the TPP proton conductivity by examining five different precursors: (1) phosphoric acid (TPP-PA), (2) ammonium hydroxide + phosphoric acid (TPP-NH 4 OH), (3) diammonium phosphate (TPP-DAP), (4) tetramethylammonium sulphate + phosphoric acid (TPP-TMAP), and (5) tetrabutylammonium phosphate (TPP-TBAP), where a maximum conductivity of 88 mS cm -1 at 200 °C was obtained for TPP prepared from the TBAP precursor. TPP prepared from all of the different precursors formed the crystalline cubic Pa-3 with combining macron] phase after sintering at 650 °C for 2.5 hours. Furthermore, TPP-TBAP/Nafion® composite membranes prepared with a 90 : 10 ratio exhibited an OCV of 0.98 V and produced a maximum peak power density (PPD) of 630 mW cm -2 at an operating temperature of 220 °C. Our results demonstrate the significant impact of the TPP precursor on proton conductivity and fuel cell performance.

36 MATERIALS SCIENCE↗
NASA NTRS2011

Lunabotics Mining Competition: Inspiration Through Accomplishment

NASA's Lunabotics Mining Competition is designed to promote the development of interest in space activities and STEM (Science, Technology, Engineering, and Mathematics) fields. The competition uses excavation, a necessary first step towards extracting resources from the regolith and building bases on the moon. The unique physical properties of lunar regolith and the reduced 1/6th gravity, vacuum environment make excavation a difficult technical challenge. Advances in lunar regolith mining have the potential to significantly contribute to our nation's space vision and NASA space exploration operations. The competition is conducted annually by NASA at the Kennedy Space Center Visitor Complex. The teams that can use telerobotic or autonomous operation to excavate a lunar regolith geotechnical simulant, herein after referred to as Black Point-1 (or BP-1) and score the most points (calculated as an average of two separate 10-minute timed competition attempts) will eam points towards the Joe Kosmo Award for Excellence and the scores will reflect ranking in the on-site mining category of the competition. The minimum excavation requirement is 10.0 kg during each competition attempt and the robotic excavator, referred to as the "Lunabot", must meet all specifications. This paper will review the achievements of the Lunabotics Mining Competition in 2010 and 2011, and present the new rules for 2012. By providing a framework for robotic design and fabrication, which culminates in a live competition event, university students have been able to produce sophisticated lunabots which are tele-operated. Multi-disciplinary teams are encouraged and the extreme sense of accomplishment provides a unique source of inspiration to the participating students, which has been shown to translate into increased interest in STEM careers. Our industrial sponsors (Caterpillar, Newmont Mining, Harris, Honeybee Robotics) have all stated that there is a strong need for skills in the workforce related to robotics and automated machines. In 2010, 22 United States (US) universities competed, and in May 2011 the competition was opened to international participation, with 46 Universities attending. There were 12 international teams and 34 US teams. This combined total directly inspired an estimated 544 university students. More students and the public were engaged via internet broadcasting and social networking media. This is expected to be of value for actual future space missions, as knowledge is gained from testing many innovative prototypes in simulated lunar regolith. More information is available at www.nasa.gov/lunabotics/.

Mueller, Robert P.↗
DOE OSTI2025

Intercomparison of Three Continuous Monitoring Systems on Operating Oil and Gas Sites

We compare continuous monitoring systems (CMS) from three different vendors on six operating oil and gas sites in the Appalachian Basin using several months of data. We highlight similarities and differences between the three CMS solutions when deployed in the field and compare their output to concurrent top-down aerial measurements and to site-level bottom-up inventories. Furthermore, we compare vendor-provided emission rate estimates to estimates from an open-source quantification algorithm applied to the raw CMS concentration data. This experimental setup allows us to separate the effect of the sensor platform (i.e., sensor type and arrangement) from the quantification algorithm. We find that 1) localization and quantification estimates rarely agree between the three CMS solutions on short time scales (i.e., 30 min), but temporally aggregated emission rate distributions are similar between solutions, 2) differences in emission rate distributions are generally driven by the quantification algorithm, rather than the sensor platform, 3) agreement between CMS and aerial rate estimates varies by CMS solution but is close to parity when CMS estimates are averaged across solutions, and 4) similar sites with similar bottom-up inventories do not necessarily have similar emission characteristics. These results have important implications for developing measurement-informed inventories and for incorporating CMS-inferred emission characteristics into emission mitigation efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Retrofitting Holcim Ste. Genevieve Cement Plant with CO2 Capture Plant Using Air Liquide Cryocap™ FG Technology

The global cement manufacturing industry is a major contributor to carbon dioxide emissions. The International Energy Agency's "Net Zero Emissions by 2050 Scenario" identifies CCS as a major strategy for meeting that goal. This project is among the first attempts to transfer capture technology developed at coal-fired power plants to the cement industry. The main objective of the project is to execute and complete a front-end engineering and design (FEED) studies for commercial-scale, carbon capture projects that separates 95% of the total CO2 emissions at the Holcim (US) Ste. Genevieve cement manufacturing facility using Air Liquide’s Pressure Swing Adsorption system (PSA) assisted Cryocap™ technology. The Holcim Ste. Genevieve cement plant in Missouri, US, boasts one of the largest single cement production lines in the world, with a capacity of approximately 12,000 t/day. The plant currently uses traditional fuels, namely coal and petcoke. The captured CO2 will be pipeline and geological storage grade. The industrial host site emits approximately 3.0 million tonne CO2/yr. Air Liquide’s Cryocap™ technology has been developed over the last 18+ years for CO2 capture applications. It has been shown to be applicable to a variety of industrial applications (e.g., steel, cement, SMR, Fluidized Catalytic Crackers (FCCs)). Cryocap™ FG consists of a Pressure Swing Adsorption (PSA) unit coupled with a Cryogenic System. The PSA pre-concentrates the CO2 from the flue gas, while the cryogenic unit enables the CO2 purity to be increased to the desired level. The project team is led by the Prairie Research Institute at the University of Illinois at Urbana-Champaign. The tasks include: complete FEED study for retrofitting the industrial facility with a carbon capture system to support developing a detailed cost estimate; business case analysis outlining the anticipated revenue and credits if projects was built and operated; technoeconomic analysis (TEA) outlining how capture system achieves DOE capture goals; and life cycle (LCA) analysis demonstrating zero net carbon emissions. The FEED study was successfully completed. This includes completing the process basis of design; preliminary engineering; outside battery limits (OSBL) detailed engineering including a Zero Liquid Discharge (ZLD) wastewater treatment system; inside battery limits (ISBL) detailed engineering [1]. An overall project capital cost estimate within a -20%/+30% accuracy was developed. The major contributors to the Total Plant Cost (TPC), by system, are the costs associated with the Outside Battery Limit (OSBL) section of the plant which includes a new river water intake structure and a Zero Liquid Discharge (ZLD) system. By cost category, the major contributors to the TPC are equipment and subcontractor costs, followed closely by engineering, construction management, home office and contractor fees. The TEA has been created to reflect the findings of the project. It analyzes the economic performance of the Cryocap™ technology by reviewing the estimated capital costs, operating cost, and revenue. The Cost of Capture (COC) associated with the Cryocap™ technology for 95% CO2 capture, when considering NETL 2018 economic assumptions (42/58 debt/equity ratio, 5.15% interest on debt and 1.42% return on equity in real dollars) and 2022 economic assumptions (42/58 debt/equity ratio, 8.82% interest on debt and 4.90% return on equity in real dollars) was found to be much lower than that for the DOE-NETL’s base-line cases. The highest contributors to the COC are annualized capital expenditures (CAPEX) and electricity consumption which can be offset by using lower cost renewable sources. The LCA was conducted using OpenLCA which is an open-source software that is recommended by NETL. The database utilized for this study was a modified version of TRACI 2.1 (developed by the US. Environmental Protection Agency’s National Risk Management Research Laboratory and modified by NETL). The Cryocap™ FG technology does not consume fuels in significant quantities and does not utilize specialized chemical solvents subject to decomposition, such as those utilized in amine-based carbon capture systems. The Cryocap™ FG technology mainly utilizes electricity as its energy input; hence, its calculated emissions are mainly associated with the generation of electricity offsite and are dependent on the energy matrix of the grid at the time of project implementation. The water consumption impact of the Cryocap™ FG is mostly for makeup of the water lost by evaporation in the cooling tower; however, the carbon capture plant will be equipped with a ZLD system to avoid effluent streams and minimize water consumption. The successful construction and operation of this plant based on this study results will provide a means to demonstrate an economically attractive and transformational capture technology that can be used to retrofit existing plants and be deployed at new plants.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Atmospheric correction of airborne hyperspectral imaging spectroscopy (AHIS) to obtain high-quality surface reflectance is the prerequisite for remote sensing applications. Over the last decades, different atmospheric correction methods have been developed based on radiative transfer models (RTMs), however, the relative performances of different algorithms are unclear. Automated operational atmospheric correction methods to process large-volume AHIS data in a high-accurate and high-throughput manner are still lacking. Therefore, this study proposed an operational atmospheric correction pipeline for deriving surface reflectance from AHIS data. To ensure the accuracy and efficiency of the pipeline, we focused on three specific aspects: (1) selecting a suitable RTM for the development of atmospheric lookup tables (LUTs) by comparing the commercial MODerate resolution atmospheric TRANsmission (MODTRAN) and open-sourced Library for Radiative TRANsfer (LibRadTRAN) models, where the widely-used software, Atmospheric/Topographic Correction for Airborne Imagery (ATCOR), was used as benchmarks; (2) identifying key atmospheric correction parameters and determining suitable sources for parameter retrievals including AHIS, Moderate Resolution Imaging Spectroradiometer (MODIS), and AErosol RObotic NETwork (AERONET); and (3) testing the performance of using machine learning emulators to speed up the RTM-based atmospheric correction. Results indicate that (1) atmospheric correction based on MODTRAN LUTs can produce surface reflectance accurately with mean absolute errors < 0.05 and cosine similarities > 0.98 compared to field measurements, which is comparable to the software ATCOR and slightly outperforms the LibRadTRAN LUTs; (2) sobol global sensitivity analysis demonstrates that in the atmospheric correction, visibility and water vapor are two key parameters that can be accurately derived from AHIS in contrast to MODIS or AERONET data; and (3) Random Forest emulators can produce accurate estimations of surface reflectance with mean absolute errors < 0.03 and cosine similarities > 0.98 for higher processing efficiency and determine a suitable set of wavelengths for retrieving atmospheric visibility and water vapor. In conclusion, the proposed atmospheric correction pipeline also improved the four-stream radiative transfer theory for airborne applications by considering adjacent effects from airborne surrounding pixels and can also be applied for atmospheric correction of hyperspectral data from spaceborne missions.

47 OTHER INSTRUMENTATION↗