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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The PAU Survey: narrow-band photometric redshifts using Gaussian processes

Here, we study the performance of the hybrid template machine learning photometric redshift (photo- z ) algorithm delight , which uses Gaussian processes, on a subset of the early data release of the Physics of the Accelerating Universe Survey (PAUS). We calibrate the fluxes of the 40 PAUS narrow bands with six broad-band fluxes ( uBVriz ) in the Cosmic Evolution Survey (COSMOS) field using three different methods, including a new method that utilizes the correlation between the apparent size and overall flux of the galaxy. We use a rich set of empirically derived galaxy spectral templates as guides to train the Gaussian process, and we show that our results are competitive with other standard photometric redshift algorithms. delight achieves a photo- z 68th percentile error of σ 68 = 0.0081(1 + z ) without any quality cut for galaxies with i auto < 22.5 as compared to 0.0089(1 + z ) and 0.0202(1 + z ) for the bpz and annz 2 codes, respectively. delight is also shown to produce more accurate probability distribution functions for individual redshift estimates than bpz and annz 2. Common photo- z outliers of delight and bcnz 2 (previously applied to PAUS) are found to be primarily caused by outliers in the narrow-band fluxes, with a small number of cases potentially indicating spectroscopic redshift failures in the reference sample. In the process, we introduce performance metrics derived from the results of bcnz 2 and delight , allowing us to achieve a photo- z quality of σ 68 < 0.0035(1 + z ) at a magnitude of i auto < 22.5 while keeping 50 per cent objects of the galaxy sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

West Village Community: Quality Management Processes and Preliminary Heat Pump Water Heater Performance

West Village, a multiuse project underway at the University of California Davis, represents a groundbreaking sustainable community that incorporates energy efficiency measures and on-site renewable generation to achieve community-level goals of ultra high efficiency. The project, when complete, will provide housing for students, faculty, and staff, and maintain a vision to minimize the community’s environmental impact by reducing building energy use, providing on-site renewable energy generation, and encouraging alternative forms of transportation. The focus of this research concerns the 192 student apartments completed in 2011 under Phase I of the West Village multi-year project. The developer implemented numerous aggressive energy efficiency measures that are estimated to achieve 37% source energy savings over the Building America Benchmark. There are two primary objectives of this research. The first is to evaluate performance and efficiency of central heat pump water heaters for domestic water heating in ultra-efficient buildings. The second is to evaluate the effectiveness of quality assurance and quality control processes in ensuring proper system startup and operation and documenting compliance with efficiency programs. This research additionally recommends measures to promote successful implementation of quality processes in large-scale, high performance communities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Effects of Photonic Curing Processing Conditions on MAPbI 3 Film Properties and Solar Cell Performance

Thermal annealing is the most used postdeposition materials processing method in laboratory research, but due to its slow speed and high energy cost, it is not compatible with the upscaling and commercialization of perovskite solar cell (PSC) manufacturing. Here, we adapt photonic curing (PC), which uses millisecond light pulses to deliver energy to the sample, to replace thermal annealing for crystallization of methylammonium lead iodide (MAPbI 3 ) films and rapid fabrication of PSCs. We study how PC conditions affect the outcome of MAPbI 3 conversion from the precursor to the crystalline perovskite phase by evaluating the films’ optical, crystalline, and morphological properties, as well as PSC performance. The results are understood using simulated film temperature profiles. We show that MAPbI 3 is readily converted under a wide range of PC conditions. While previous reports all used short pulses (<3 ms), we find that longer pulses produce more dense films and higher-performing PSCs. We achieve a champion power conversion efficiency in a PC-processed MAPbI 3 PSC of 11.26% under forward scan and 10.34% under reverse scan, with the processing time for the MAPbI 3 layer reduced by 30,000-fold, from 10 min to 20 ms. Using a 6 in. lamp, spatial uniformity tests show a cross-web efficiency variation of 5%. Our results indicate that using longer pulse lengths, >10 ms, is the best PC strategy for perovskite conversion, and PC is a promising annealing method for large-area, high-throughput PSC manufacturing.

14 SOLAR ENERGY↗
DOE OSTI2013

Defect Engineering, Cell Processing, and Modeling for High-Performance, Low-Cost Crystalline Silicon Photovoltaics

The objective of this project is to close the efficiency gap between industrial multicrystalline silicon (mc-Si) and monocrystalline silicon solar cells, while preserving the economic advantage of low-cost, high-volume substrates inherent to mc-Si. Over the course of this project, we made significant progress toward this goal, as evidenced by the evolution in solar-cell efficiencies. While most of the benefits of university projects are diffuse in nature, several unique contributions can be traced to this project, including the development of novel characterization methods, defect-simulation tools, and novel solar-cell processing approaches mitigate the effects of iron impurities ("Impurities to Efficiency" simulator) and dislocations. In collaboration with our industrial partners, this project contributed to the development of cell processing recipes, specialty materials, and equipment that increased cell efficiencies overall (not just multicrystalline silicon). Additionally, several students and postdocs who were either partially or fully engaged in this project (as evidenced by the publication record) are currently in the PV industry, with others to follow.

14 SOLAR ENERGY↗
DOE OSTI2019

Integrated Hydrogen Sensor and Separator for Parabolic Trough Expansion Tanks

The National Renewable Energy Laboratory (NREL) and Acciona Energy USA Global are developing and implementing a process that addresses the issue of hydrogen buildup in parabolic trough power plants. Our method selectively removes hydrogen from the expansion tanks of the power plant to control hydrogen levels in the circulating heat-transfer fluid (HTF). As part of this effort, we developed a sensor that measures hydrogen partial pressure in the expansion-tank headspace gas. During previous work, we demonstrated that our sensor measures hydrogen levels over a wide range of partial pressure from 1.33 mbar down to 0.003 mbar. In this paper, we report our most recent work, in which we conceived and developed an integrated process module that performs both hydrogen sensing and separating functions. The sensor/separator measures hydrogen partial pressure in the headspace gas in the same way as our original sensor design. Additionally, the integrated module separates hydrogen from the headspace gas to reduce hydrogen to the level needed to maintain the performance of receivers in the collector field. Sensor data from the integrated module also provide an estimate of the rate at which hydrogen is being extracted from the headspace gas. We designed and fabricated a laboratory-scale integrated module and determined its performance in our laboratory at NREL. Testing showed that the module performed as expected in both sensing and separating modes. The accuracy of the sensing function was +/-10%. The hydrogen extraction rate for the separating mode was consistent with our modeling predictions. The primary benefit of this module is its simple design, both in terms of function and incorporation into the HTF subsystem of the power plant. The integrated module can be installed close to the HTF expansion tanks, where it draws headspace gas from the tanks, removes hydrogen, and returns the treated gas back to the tanks. We are currently installing a test-scale process at the Nevada Solar One (NSO) power plant to demonstrate this process and determine its operational performance. Results from the test-scale process will be used to specify and design the full-scale process that will be installed at NSO.

14 SOLAR ENERGY↗
DOE OSTI2025

Assessing the coating implications of slurry formulations in NCMA and LFMP blend cathodes for lithium-ion batteries

This paper investigates the implications of slurry formulations and electrode processing on the performance of lithium-ion battery (LIB) cathodes, focusing on Nickel Cobalt Manganese Aluminum (NCMA) and Lithium Ferro Manganese Phosphate (LFMP) blends. Through a comprehensive examination of electrode processing steps, from material selection to coating application, we elucidate the critical role of processing parameters in shaping electrode morphology and electrochemical behavior. Rheological studies reveal the influence of slurry composition on viscosity and flow behavior, highlighting the importance of achieving optimal rheological properties for uniform coating deposition. Electrochemical characterization, including cyclic voltammetry and rate capability tests, unveils the electrochemical behavior of NCMA, LFMP, and their blend, showcasing the synergistic effects of material blending on battery performance. In conclusion, our findings underscore the intricate relationship between slurry formulation, electrode processing, and LIB performance, offering valuable insights for the design and optimization of high-performance electrode materials for next-generation batteries.

25 ENERGY STORAGE↗
DOE OSTI2015

Impact of individual nuclear masses on r -process abundances

We have performed for the first time a comprehensive study of the sensitivity of r-process nucleosynthesis to individual nuclear masses across the chart of nuclides. Using the latest version (2012) of the Finite-Range Droplet Model, we consider mass variations of ±0.5 MeV and propagate each mass change to all affected quantities, including Q values, reaction rates, and branching ratios. We find such mass variations can result in up to an order of magnitude local change in the final abundance pattern produced in an r-process simulation. As a result, we identify key nuclei whose masses have a substantial impact on abundance predictions for hot, cold, and neutron star merger r-process scenarios and could be measured at future radioactive beam facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Ancilla-assisted process tomography of a deployed fiber link

We perform ancilla-assisted process tomography over a deployed 1.6 km fiber-optic link using Bayesian inference, confirming a stable, high-fidelity polarization channel. Overall, our approach should offer value for in situ analyses of entanglement networks.

Rahman, Arefur [Arizona State University]↗
DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗
DOE OSTI2020

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N: One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an ''intelligent'' mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗
DOE OSTI2017

Final Scientific/Technical Report: Low Cost, Structurally Advanced Novel Electrode and Cell Manufacturing

This document is the final technical report from 24M Technologies on the project titled: Low Cost, Structurally Advanced Novel Electrode and Cell Manufacturing. All of the program milestones and deliverables were completed during the performance of the award. Specific accomplishments are 1) 24M demonstrated the processability and electrochemical performance of semi-solid electrodes with active volume contents increased by 10% relative to the program baseline; 2) electrode-level metrics, quality, and yield were demonstrated at an 80 cm 2 electrode footprint; 3) these electrodes were integrated into cells with consistent capacities and impedances, including cells delivered to Argonne National Laboratory for independent testing; 4) those processes were scaled to a large-format (> 260 cm 2 ) electrode footprint and quality and yield were demonstrated; 5) a high-volume manufacturing approach for large-format electrode fabrication was demonstrated; and 6) large-format cells (> 100 Ah capacity) were prototyped with consistent capacity and impedance, including cells which were delivered to Argonne National Laboratory for independent testing.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2013

AutoDrug: fully automated macromolecular crystallography workflows for fragment-based drug discovery

New software has been developed for automating the experimental and data-processing stages of fragment-based drug discovery at a macromolecular crystallography beamline. A new workflow-automation framework orchestrates beamline-control and data-analysis software while organizing results from multiple samples. AutoDrug is software based upon the scientific workflow paradigm that integrates the Stanford Synchrotron Radiation Lightsource macromolecular crystallography beamlines and third-party processing software to automate the crystallography steps of the fragment-based drug-discovery process. AutoDrug screens a cassette of fragment-soaked crystals, selects crystals for data collection based on screening results and user-specified criteria and determines optimal data-collection strategies. It then collects and processes diffraction data, performs molecular replacement using provided models and detects electron density that is likely to arise from bound fragments. All processes are fully automated, i.e. are performed without user interaction or supervision. Samples can be screened in groups corresponding to particular proteins, crystal forms and/or soaking conditions. A single AutoDrug run is only limited by the capacity of the sample-storage dewar at the beamline: currently 288 samples. AutoDrug was developed in conjunction with RestFlow, a new scientific workflow-automation framework. RestFlow simplifies the design of AutoDrug by managing the flow of data and the organization of results and by orchestrating the execution of computational pipeline steps. It also simplifies the execution and interaction of third-party programs and the beamline-control system. Modeling AutoDrug as a scientific workflow enables multiple variants that meet the requirements of different user groups to be developed and supported. A workflow tailored to mimic the crystallography stages comprising the drug-discovery pipeline of CoCrystal Discovery Inc. has been deployed and successfully demonstrated. This workflow was run once on the same 96 samples that the group had examined manually and the workflow cycled successfully through all of the samples, collected data from the same samples that were selected manually and located the same peaks of unmodeled density in the resulting difference Fourier maps.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Biodegradation Behaviour of Thermoplastic Starch: The Roles of Carboxylic Acids on Cassava Starch

The process of biodegradation upon modified thermoplastic starch with various types of carboxylic acids was performed via soil burial testing. As such, modification of thermoplastic starch via esterification with citric acid and ascorbic acid was made varied within the range of 1–4 by weight percentage (% w/w). As a result, after citric acid modification and ascorbic acid modification displayed higher moisture resistivity (15.04 and 20.46%) compared to thermoplastic starch, which resulted in 43.79% respectively. In addition, environmental degradation was determined by performing a biodegradation process by using compost soil. Besides, Fourier transform infrared spectroscopy and high performance liquid chromatography tests were carried out to assess the biodegradability attribute of the starch film. The findings showed that the both citric acid and ascorbic acid modifications exhibited lower rates of weight loss, consequently due to the action demonstrated by of carboxylic acids that inhibited the invasion of microbial after exposure to environmental degradation. Furthermore, the optical analysis revealed that both citric acid and ascorbic acid possessed capability to retard the invasion of microbial upon modifications observed from its rather limited formation of microbial colonies. Nevertheless, the carbonyl index portrayed lower growth rate for citric acid and ascorbic acid, in comparison to unmodified thermoplastic starch. Hence, the study concludes that the addition of carboxylic acid had reduced the rate of degradation for the thermoplastic starch, besides improving moisture resistivity.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Influence of Single-Point Incremental Force Process Parameters on Forming Characteristics and Microstructure Evolution of AA-6061 Alloy Sheet

Single-point incremental forming (SPIF) process comprises a set of process variables, such as forming tool diameter, vertical pitch, spindle rotation speed, and tool velocity, which may affect the forming behavior of the sheet to be deformed. The objective of this work is to study the effect of SPIF process parameters on forming characteristics and microstructure development for the AA-6061 (T6) aluminum alloy sheet. The SPIF experiments and finite element (FE) simulations were performed at different process parameters to achieve conical shapes from the AA-6061 blanks. The effect of process parameters on forming forces, thickness uniformity in wall region of the cone and surface roughness of the blank was analyzed. A detailed microstructure study was performed to analyze the effect of process variables on microstructure and texture evolution during the SPIF process. This study reveals that the process parameters are likely to influence the texture development especially at high tool diameter and vertical pitch values. Therefore, suitability and consequences of using different combinations of tool diameter and vertical pitch values are discussed for AA-6061 alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Data processing pipeline for Tianlai experiment

The Tianlai project is a 21cm intensity mapping experiment for detecting dark energy by measuring the baryon acoustic oscillation (BAO) features in the large scale structure power spectrum. This experiment provides an opportunity to test the data processing methods for cosmological 21cm signal extraction, which is still a great challenge in current radio astronomy research. The 21cm signal is much weaker than the foregrounds and easily aected by the imperfections in the instrumental responses. Furthermore, processing the large volumes of interferometer data poses a practical challenge. We have developed a data processing pipeline called tlpipe to process the drift scan survey data from the Tianlai experiment. It performs oine data processing tasks such as radio frequency interference (RFI) agging, array calibration, binning, and map-making, etc. It also includes utility functions needed for the data analysis, such as data selection, transformation, visualization and others. A number of new algorithms are implemented, for example the eigenvector decomposition method for array calibration and the Tikhnov regularization for m-mode analysis. In this paper we describe the design and implementation of the pipeline and illustrate its functions with some analysis of real data. Finally, we outline directions for future development of this publicly code.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Improved Glow Discharge Polymer Removal from Beryllium Capsules Using Ozone

Copper-doped beryllium spheres are an attractive ablator for inertial confinement fusion experiments. Beryllium spheres are made by sputtering beryllium onto spherical plastic mandrels which must then be removed through a hole that is laser drilled through the shell wall. The currently used mandrel material is glow discharge polymer. This material cannot be removed by solvent and must be “burned” out. The burnout process was originally performed by etching with dry air at 425°C, but this process can substantially roughen the inner surface, which can seed instabilities and increase mix during implosion experiments. In this paper, we explore the use of pure oxygen and ozone to reduce process temperature and improve inner and outer surface quality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Low Regeneration Temperature Sorbents for Direct Air Capture of CO 2

Susteon Inc., in partnership with University of Wyoming and SoCalGas, successfully met all major technical objectives to (1) scale up the ionic liquid catalyst for amine-based sorbents for improved desorption and absorption kinetics, (2) evaluate the catalyzed amine-based sorbents for direct CO 2 capture process to determine CO 2 adsorption and desorption rates and energy requirements, and (3) based on the experimental results, develop a conceptual process design to perform a preliminary economic assessment to evaluate the potential for DAC process cost reduction using the catalyzed sorbents. Amine doped solid sorbents are effective for DAC applications and can be regenerated by heat or by a combination of heat, steam, and vacuum. The best sorbent composition identified was polyethyleneimine (PEI) on fumed silica with 200 ppm ionic liquid catalyst. This sorbent formulation was shown to have a CO 2 breakthrough capacity twice that of the non-catalyzed sorbent, in laboratory tests with air at 75% relative humidity (RH). The CO 2 adsorption rate was also 40% higher than that of the non-catalyzed sorbent. This type of sorbents has the attributes required for lowering the overall cost of DAC with high CO 2 capacity and high rate of adsorption. The combination of an industrially utilized amine-based sorbent with a highly active catalyst to form a new class of materials for DAC provides a technically viable pathway for reducing the cost of DAC to <$100/tonne of CO 2 . Laboratory measurements show that the silica/PEI (polyethyleneimine) sorbents with 100 ppm of ionic liquid catalyst have almost 100% higher CO 2 cyclic capacity and 40% higher adsorption rate. Generally, CO 2 desorption occurred at higher temperatures with a rate of desorption 10 times faster than adsorption (which occurred at ambient conditions). Therefore, adsorption rate is a much more important factor in the cost of DAC because it is directly linked to the CAPEX of the total system and the cycle time (i.e., sorbent productivity in ton/day of CO 2 captured per unit volume of the air contactor). An initial process design, coupled with techno-economic analysis, based on optimal experimental results and preliminary resulting from structured sorbent testing, showed a path to lower the DAC cost from the current cost of over $200/tonne CO 2 to less than $100/tonne with a scale-up, mature state of the technology, with projected material and process improvements. These results demonstrate the effectiveness of the catalyst in silica/PEI sorbents in enhancing sorbents’ CO 2 working capacity, in (a) increasing the rate of adsorption and desorption, and (b) in lowering the CAPEX and OPEX of the DAC system employing the ionic liquid catalyzed sorbents.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Implementing the LSST Software Stack for DESGW processing and the Integration of Convolutional Neural Networks into the DESGW Pipeline

The Dark Energy Survey Gravitational Wave (DESGW) group strives to understand thelargescale structure of the universe and galaxies by looking for electromagnetic signatures intelescope images following gravitational wave detections. The DESGW group uses a processing pipeline to perform difference imaging to look for potential candidates. In order to perform these searches more effectively, we first explored using an alternative processing pipeline, the LSST Software Stack to analyze the telescope images. Because the LSST software stack is currently transitioning between its generation 2 and generation 3 system, we decided that while the software will be usable in the future once generation 3 is complete, at the moment its incompleteness makes it impractical to use. We then decided to work on improving the current pipeline by developing a module that integrates a Convolutional Neural Network (CNN) to test difference imaging products for bad subtractions due to misalignment.

Navarro, Alexander↗