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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Screening and Discovery of Metal Compound Active Sites for Strong and Selective Adsorption of N 2 in Air

Photocatalytic nitrogen fixation has the potential to provide a greener route for producing nitrogen-based fertilizers under ambient conditions. Computational screening is a promising route to discover new materials for the nitrogen fixation process, but requires identifying “descriptors” that can be efficiently computed. In this work, we argue that selectivity toward the adsorption of molecular nitrogen and oxygen can act as a key descriptor. A catalyst that can selectively adsorb nitrogen and resist poisoning of oxygen and other molecules present in air has the potential to facilitate the nitrogen fixation process under ambient conditions. Here we provide a framework for active site screening based on multifidelity density functional theory (DFT) calculations for a range of metal oxides, oxyborides, and oxyphosphides. The screening methodology consists of initial low-fidelity fixed geometry calculations and a second screening in which more expensive geometry optimizations were performed. The approach identifies promising active sites on several TiO 2 polymorph surfaces and a VBO 4 surface, and the full nitrogen reduction pathway is studied with the BEEF-vdW and HSE06 functionals on two active sites. The findings suggest that metastable TiO 2 polymorphs may play a role in photocatalytic nitrogen fixation, and that VBO 4 may be an interesting material for further studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1977

X-ray sensitive oblique imaging device

Instrument employs light reflecting surface (evaporated aluminum coating or minor substrate) behind phosphor screen to improve effective quantum efficiency in dual process: fraction of incoming X-rays are converted to photoelectrons at photocathode; and X-rays that pass through photocathode and thin X-ray transparent membrane enter phosphor screen.

Hallam, K. L.↗
NASA NTRS2004

Variable Shadow Screens for Imaging Optical Devices

Variable shadow screens have been proposed for reducing the apparent brightnesses of very bright light sources relative to other sources within the fields of view of diverse imaging optical devices, including video and film cameras and optical devices for imaging directly into the human eye. In other words, variable shadow screens would increase the effective dynamic ranges of such devices. Traditionally, imaging sensors are protected against excessive brightness by use of dark filters and/or reduction of iris diameters. These traditional means do not increase dynamic range; they reduce the ability to view or image dimmer features of an image because they reduce the brightness of all parts of an image by the same factor. On the other hand, a variable shadow screen would darken only the excessively bright parts of an image. For example, dim objects in a field of view that included the setting Sun or bright headlights could be seen more readily in a picture taken through a variable shadow screen than in a picture of the same scene taken through a dark filter or a narrowed iris. The figure depicts one of many potential variations of the basic concept of the variable shadow screen. The shadow screen would be a normally transparent liquid-crystal matrix placed in front of a focal-plane array of photodetectors in a charge-coupled-device video camera. The shadow screen would be placed far enough from the focal plane so as not to disrupt the focal-plane image to an unacceptable degree, yet close enough so that the out-of-focus shadows cast by the screen would still be effective in darkening the brightest parts of the image. The image detected by the photodetector array itself would be used as feedback to drive the variable shadow screen: The video output of the camera would be processed by suitable analog and/or digital electronic circuitry to generate a negative partial version of the image to be impressed on the shadow screen. The parts of the shadow screen in front of those parts of the image with brightness below a specified threshold would be left transparent; the parts of the shadow screen in front of those parts of the image where the brightness exceeded the threshold would be darkened by an amount that would increase with the excess above the threshold.

Lu, Ed↗
DOE OSTI2022

200-IA-1 Operable Unit Human Health Risk and Kd Screen

The purpose of this environmental calculation file (ECF) is to provide the following: Document the data processing and data reduction steps taken to prepare the 200-IA-1 Operable Unit (OU) data set that will be used to calculate the sample-specific screening level human health risk evaluation; Document the data processing and data reduction steps taken to prepare the 200-IA-1 OU data set that will be used to identify analytes that could potentially impact groundwater in the future beneath the 200-IA-1 OU representative waste sites; Document the assumptions, equations, and methodologies used to calculate the screening levels for human health cancer risks and noncancer hazards for each representative waste site assigned to the 200-IA-1 OU. Individual measured soil concentrations from 0 to 4.6 m (15 ft) below ground surface (bgs) (shallow vadose zone) are used to calculate the total excess lifetime cancer risk (ELCR) and hazard index (HI) for the outdoor worker scenario to determine if there is a basis for remedial action. Individual measured soil concentrations from the ground surface to the groundwater table are used for the distribution coefficient (Kd) screen to identify analytes that could potentially impact groundwater in the future beneath the 200-IA-1 OU representative waste sites. This ECF supports DOE/RL-2020-51, 200-IA-1 OU Focused Feasibility Study, under the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA). A risk characterization based upon the evaluation of the health risk estimates developed in this ECF will be presented in the focused feasibility study report.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
NASA NTRS1979

Automated Array Assembly, Phase 2

The large scale production of silicon solar cell array panels is discussed. The cost and performance of three manufacturing sequences designed to convert silicon sheet and wafers into solar panels is analyzed. The production of ion implanted and furnace annealed solar cells made using solar grade n- and p-type wafers is examined. The performance of production size lots is examined with regard to the relationship between the ion implant and furnace anneal parameters and the ability to form consistently good thick film screen printed contacts. The spray on antireflection coating process is evaluated. The performance of several lots of cells before and after coating is measured. The structure and refractive index of the RCA I (TiO2) coating is compared with commercial solutions. Sensitivity of coated, screen printed cells to the post heat treatment required to cure the films is assessed.

Daiello, R. V.↗
DOE OSTI2022

Automatic Waveform Quality Control for Surface Waves Using Machine Learning

Surface-wave seismograms are widely used by researchers to study Earth’s interior and earthquakes. To extract information reliably and robustly from a suite of surface waveforms, the signals require quality control screening to reduce artifacts from signal complexity and noise. This process has usually been completed by human experts labeling each waveform visually, which is time consuming and tedious for large data sets. We explore automated approaches to improve the efficiency of waveform quality control processing by investigating logistic regression, support vector machines, K-nearest neighbors, random forests (RF), and artificial neural networks (ANN) algorithms. To speed up signal quality assessment, we trained these five machine learning (ML) methods using nearly 400,000 human-labeled waveforms. The ANN and RF models outperformed other algorithms and achieved a test accuracy of 92%. We evaluated these two best-performing models using seismic events from geographic regions not used for training. The results show that the two trained models agree with labels from human analysts but required only 0.4% of the time. Although the original (human) quality assignments assessed general waveform signal-to-noise, the ANN or RF labels can help facilitate detailed waveform analysis. Our investigations demonstrate the capability of the automated processing using these two ML models to reduce outliers in surface-wave-related measurements without human quality control screening.

58 GEOSCIENCES↗
DOE OSTI2025

Process-Microstructure-Property Relationships in Low Heat Input Wire-Arc Additive Manufacturing (WAAM) of Ni-Based Superalloy Haynes 282

Conference presentation on WAAM process optimization on Ni-based superalloy Haynes® 282®. This alloy is targeted for advanced power generation systems for its superior high temperature mechanical properties. Wire-arc additive manufacturing (WAAM) offers attractive cost and materials savings with high deposition rates. Based on initial build process optimization, WAAM blocks were made, and screened for defects using high-throughput CT scanning. The microstructural evolution in arc energy range of 250-700 J/mm was characterized in the as-built and aged conditions, using electron microscopy. Results showed self-consistent microstructure across conditions, with grain size dependence on arc energy, MC and M6C carbides in as-built, and blocky grain boundary M23C6 in as-heat-treated condition. Further reductions in as-built porosity were explored through 20+ combinations of H2 and CO2 additions to shielding gas. Initial results show improved wetting behavior, and bead overlap with up to 1% H2 and up to 0.25% CO2. Combination of experimentally determined datasets provided comprehensive understanding of process-structure-property relationships in WAAM Haynes 282.

Haynes 282↗
DOE OSTI2020

Novel structured Sm 0.5 Sr 0.5 CoO 3-δ cathode for intermediate and low temperature solid oxide fuel cells

The performance of solid oxide fuel cell (SOFC) can be significantly enhanced using nanostructured cathode obtained by infiltration/impregnation method. However, this method has been limited due to multi-step preparation process and instability of the obtained nanoscale catalyst under long-term operation. We report here a simple, cost-effective and reproducible approach to fabricate nanostructured Sm 0.5 Sr 0.5 CoO 3-δ (SSC) cathode with enhanced performance and stability. The SSC powders were prepared by a freeze-drying method through a combustion route using Pluronic F-127 as the template. The SSC freeze-drying powders have unique morphology and a significant phase change at 750 °C. The oxygen non-stoichiometry (δ) of the SSC powders is 0.18 at room temperature, while the δ values are 0.66, 0.75 and 0.90 at 600 °C, 700 °C and 800 °C, respectively. The novel structured SSC cathode was prepared by screen-printing and one-step sintering process using the freeze-drying SSC powders. Maximum cell power densities of 0.83 and 1.13 W cm -2 are achieved at 550 °C and 600 °C, respectively for single cells with the novel structured SSC cathode. Moreover, single cells show excellent stability at 600 °C under a current density of 600 mA cm -2 over 250 h. This work expands opportunities to exploit nanotechnology in a wide range of intermediate and low temperature energy conversion devices.

25 ENERGY STORAGE↗
DOE OSTI2023

Techno-Economic Case Study: Low-Temperature Conversion Performance Based on Isolated Anatomical Fractions of Corn Stover

This report summarizes analysis conducted to support a case study under the Feedstock Conversion Interface Consortium (FCIC) focused on techno-economic analysis (TEA) modeling to quantify the process yield and resulting process cost impacts for processing isolated anatomical fractions of corn stover through a low-temperature conversion (biochemical) pathway. It is hypothesized that different individual anatomical fractions of corn stover vary in both composition and recalcitrance, giving biorefineries options in whether and how to deal with fractionated or whole biomass feedstock. By quantifying the techno-economic impacts of this variability, we provide actionable information for end users to understand tradeoffs in conversion system yields and economics in considering feedstock processing decisions at the biorefinery gate. For this study, we worked with FCIC researchers to obtain data on the compositional analysis and conversion performance of whole corn stover alongside three individual anatomical fractions (cobs, husks, and stalks) across key steps of the biorefinery conversion process within FCIC’s research scope—pretreatment and enzymatic hydrolysis. This TEA screening assessment highlighted biorefinery economic trade-offs observed through this approach. Namely, relative to processing whole stover biomass, two of the three anatomical fractions for which composition/conversion data were available (cobs and husks) demonstrated the ability to achieve higher fuel yields and lower minimum fuel selling prices (MFSPs), while the third fraction (stalks) led to the opposite result, as a composite reflection of compositional differences and process convertibility.

cost impacts↗
NASA NTRS1981

Molybdenum-tin as a solar cell metallization system

The operations of solar cell manufacture are briefly examined. The formation of reliable, ohmic, low-loss, and low-cost metal contacts on solar cells is a critical process step in cell manufacturing. In a commonly used process, low-cost metallization is achieved by screen printing a metal powder-glass frit ink on the surface of the Si surface and the conductive metal powder. A technique utilizing a molybdenum-tin alloy for the metal contacts appears to lower the cost of materials and to reduce process complexity. The ink used in this system is formulated from MoO3 with Sn powder and a trace amount of titanium resonate. Resistive losses of the resulting contacts are low because the ink contains no frit. The MoO3 is finally melted and reduced in forming gas (N2+H2) to Mo metal. The resulting Mo is highly reactive which facilitates the Mo-Si bonding.

Boyd, D. W.↗
DOE OSTI2024

Demystifying In Situ Pyrolysis Chemistry for High-Performance Polyanionic Cathodes in Sodium-Ion Batteries

In this article, the carbon coating strategy has emerged as an indispensable approach to improve the conductivity of polyanionic cathodes. However, owing to the complex reaction process between precursors of carbon and cathode, establishing a unified screening principle for carbonaceous precursors remains a technical challenge. Herein, we reveal that carbonaceous precursor pyrolysis chemistry undeniably influences the formation process and performance of Na 3 V 2 (PO 4 ) 3 (NVP) cathodes from in situ insights. By investigating three types of carbonaceous precursors, it is found that O/H-containing functional groups can provide more bonding sites for cathode precursors and generate a reducing atmosphere by pyrolysis, which is beneficial to the formation of polyanionic materials and a uniform carbon coating layer. Conversely, excessive pyrolysis of functional groups leads to a significant amount of gas, which is detrimental to the compactness of the carbon layer. Furthermore, the substantial presence of residual heteroatoms diminishes graphitization. In this case, it is demonstrated that carbon dots (CDs) precursors with suitable functional groups can comprehensively enhance the Na+ migration rate, reversibility, and interface stability of the cathode material. As a result, the NVP/CDs cathode displays outstanding capacity retention, maintaining 92% after 10,000 cycles at a high rate of 50 C. Altogether, these findings provide a valuable benchmark for carbon source selection for polyanionic cathodes.

25 ENERGY STORAGE↗
DOE OSTI2025

Molecular property prediction for very large databases with natural language processing: a case study in ionic liquid design

The prospect of using artificial intelligence (AI) to accurately screen very large databases of compounds for multiple properties has yet to be realized. Here, we explore this possibility using ionic liquids (ILs) which offer unique physicochemical properties and excellent tunability, making them highly versatile solvents for various research applications. Screening millions of potential ILs for the best perfomance for use in specific tasks with experimental methods alone however, is impractical. Further, traditional’ physics-based computational chemistry is hindered by high computational cost. To address this challenge, we leverage a natural language processing (NLP)-based molecular embedding technique with advanced machine learning (ML) models to predict seven key IL properties: viscosity, density, ionic conductivity, surface tension, melting temperature, toxicity, and water solubility. Comprehensive datasets for these properties are obtained, then NLP featurization with Mol2vec is compared with other featurization techniques such as 2D Morgan fingerprints, and 3D quantum chemistry-derived sigma profiles. NLP-based featurization exhibited the best predictive performance, achieving the highest R 2 and lowest RMSE values for all the studied IL properties. Further, we present case studies of how ILs might be screened using combined property criteria for practical cases – lignocellulosic biomass processing, CO 2 capture, and optimal electrolytes for batteries – screening a novel database of ∼10.6 million generated feasible ILs. The results introduce NLP as a powerful tool for engineering many designer solvents with desirable properties for task specific applications.

Mohan, Mood [Oak Ridge National Laboratory (ORNL),↗
NASA NTRSDate not supplied

Predicting Char Yield of High-Temperature Resins

A simulation protocol is developed to predict the char yield of organic resins during high-temperature processing. Simulation protocol in silico methods can help screen promising new formulations for advanced materials, but previously no chemistry-sensitive technique existed to predict the important experimental value of char yield. The method utilizes a reactive force field (ReaxFF) to model the chemical transformation of precursor monomers into carbonized structures during three processing stages: ramp-up to processing temperatures (~3000 K), pyrolysis, and quenching. Achieving good agreement with experimental char yields requires continuous removal of small byproduct molecules to mimic outgassing, and the application of high pressure to eliminate porosity and encourage graphitization. More than ten different resin chemistries are investigated, including arylacetylenes, cyanate esters, phthalonitriles, and polyimides, representing a diverse group of precursors with respect to initial cyclic content, heteroatoms and reactive groups. The protocol correctly predicts the relative char yield between the investigated chemistries and provides quantitative agreement with experimental values, especially for high char yield resins. The properties of the resins during processing are compared, including outgassing products, morphology of the final chemical configurations, cyclic content and mechanical properties.

polymer simulations, molecular dynamics↗
NASA NTRS2001

Automated Fiber Placement of PEEK/IM7 Composites with Film Interleaf Layers

The incorporation of thin discrete layers of resin between plies (interleafing) has been shown to improve fatigue and impact properties of structural composite materials. Furthermore, interleafing could be used to increase the barrier properties of composites used as structural materials for cryogenic propellant storage. In this work, robotic heated-head tape placement of PEEK/IM7 composites containing a PEEK polymer film interleaf was investigated. These experiments were carried out at the NASA Langley Research Center automated fiber placement facility. Using the robotic equipment, an optimal fabrication process was developed for the composite without the interleaf. Preliminary interleaf processing trials indicated that a two-stage process was necessary; the film had to be tacked to the partially-placed laminate then fully melted in a separate operation. Screening experiments determined the relative influence of the various robotic process variables on the peel strength of the film-composite interface. Optimization studies were performed in which peel specimens were fabricated at various compaction loads and roller temperatures at each of three film melt processing rates. The resulting data were fitted with quadratic response surfaces. Additional specimens were fabricated at placement parameters predicted by the response surface models to yield high peel strength in an attempt to gage the accuracy of the predicted response and assess the repeatability of the process. The overall results indicate that quality PEEK/lM7 laminates having film interleaves can be successfully and repeatability fabricated by heated head automated fiber placement.

Hulcher, A. Bruce↗
NASA NTRSDate not supplied

Predicting Char Yield of High-Temperature Resins

A simulation technique has been developed for predicting the char yield of organic resins during high-temperature processing. In silico methods can aid in the screening of new advanced materials for a number of important properties, but no chemistry-sensitive protocol currently exists for predicting the important experimental value of char yield. The proposed method utilizes a reactive force field (ReaxFF) to model the chemical transformation of precursor monomers into carbonized structures during three processing stages: ramp-up to pyrolysis temperatures (~3000 K), pyrolysis, and quenching. Achieving good agreement with experimental char yields requires continuous removal of small by-product molecules to mimic outgassing, and the application of high pressure to encourage the formation of a dense, glassy network. Six different resin chemistries were investigated: an ethynyl, a phenylethynyl, a cyanate ester, a phthalonitrile, acrylonitrile, and adamantane. These candidates represent a diverse group of precursors with respect to initial cyclic content, presence of heteroatoms, and types of reactive groups. The protocol developed accurately predicts the relative char yield between the investigated chemistries and provides quantitative agreement with experimental values, especially for high char yield resins. Several simulated properties of the carbonized structures are compared with experimental results, including outgassing products, morphology of the final chemical configurations, cyclic content, and mechanical properties.

polymer simulations, molecular dynamics↗
DOE OSTI2023

Investigation of the Effect of Chrome and Nickel Concentrations During Two-Piston Splat Quenching of Austenitic Stainless Steels

For solidification rates at or near equilibrium solidification conditions the effects of chrome (Cr) and nickel (Ni) on stainless steel solidification modes and microstructures are well detailed. However, fusion-based additive manufacturing (FBAM) processes that rely on faster, more rapid solidification rates call for a more in-depth understanding of the effects of rapid solidification on the solidification behavior and how these change with variations in alloy composition. Eleven custom stainless steel (SS) alloys with unique compositions based on 316L were made using targeted alloying element additions to generate feedstock with Cr/Ni eq ratios ranging from 0.9 to 2.1. Two-piston splat quenching (SQ) was used to produce rapid solidification conditions similar to those achieved in powder bed fusion processes in a fraction of the time and cost of traditional methods. Employing heat transfer simulations, SEM, TEM, and STEM characterization techniques, the SQ process was found to consistently produce solidification rates estimated to be between ~ 0.4 and 1.6 m/s. Five unique solidification microstructures were identified within the rapidly solidified SQ samples (primary austenite, massively transformed ferrite to austenite, primary austenite and massively transformed ferrite to austenite, primary ferrite, and primary ferrite and massively transformed ferrite to austenite). Both the primary ferrite solidification mode and primary ferrite phase were found to form at lower Cr/Ni eq values than previously predicted. SQ samples with compositions that were within the compositional specifications for 316L SS, an alloy which is commonly used in FBAM processes, demonstrated a wider range of potential solidification modes and microstructures that could form at rapid solidification rates than expected. Finally, by using SQ as a means to simulate rapid solidification conditions similar to those observed in FBAM processes, potential new alloy compositions can be screened faster and more cost effectively than purchasing and running test batches of the metallic powder.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Physics-coupled data-driven design of high-temperature alloys

We present a materials design loop, which streamlines physics-coupled machine learning (ML) surrogate models to discover new alloy chemistries with improved properties. The efficacy is demonstrated by discovering a high-temperature alumina-forming austenitic (AFA) stainless steel with enhanced creep, followed by experimental validation. The ML models have been trained using a well-curated, highly consistent experimental dataset augmented with synthetic microstructural features from a computational thermodynamic approach. We have populated a large number of hypothetical AFA alloys to explore the high-dimensional composition space and have predicted their creep properties by providing the same synthetic input features obtained from the trained ML models. Uncertainties from the ML training were taken as thresholds for truncating predicted results to identify alloys with improved or deteriorated creep. Individual elemental compositions have been determined via probability density distribution analysis from the group of alloys at the top and bottom of the predicted creep values for further virtual and experimental validations. In conclusion, we anticipate that this workflow can be applied to screen desired conditions, such as chemistry and processing parameters, in high-dimensional space through physics-guided data analytics.

Alloy design↗