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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Environmentally improved CdTe photovoltaic recycling through novel technologies and facility location strategies

Abstract Photovoltaic waste is projected to reach up to 78 million tons across globally dispersed locations through 2050. Current recycling infrastructure is inadequate to process these waste volumes responsibly. This necessitates commercializing novel, environmentally advantageous photovoltaic recycling technologies that improve upon incumbent industrial operations. CdTe photovoltaic recycling is a promising candidate for improvements as 25,000 tons of spent modules are recycled worldwide annually. This paper evaluates the operational performance and compares six novel technologies, the incumbent technology used in industry and one technology which extends the incumbent process across ten environmental impact categories. The tradeoff between incurring a transportation burden (ship or road) to recycle in a large‐scale centralized facility with a higher operational efficiency and avoiding transportation by recycling in a small‐scale decentralized facility with a lower operational efficiency is evaluated. Thermal delamination to eliminate the ethylene vinyl acetate and separate the photovoltaic glass panels is preferable to the incumbent mechanical process across nine environmental impact categories and decreases the climate‐change impact of CdTe photovoltaic recycling by 23%. Bath and probe sonication are ineffective for delamination, and the use of organic solvents is more environmentally burdensome than the incumbent mechanical process. Centralized recycling with shipping is environmentally preferable than with road‐based transportation. For every 100‐km increase in road transportation from the decentralized to the centralized facility, the inventory requirement in the centralized facility should be 6% lower than the decentralized facility for centralized recycling to have a lower climate‐change impact than decentralized recycling. The corresponding value for shipping is 0.4%.

Ravikumar, Dwarakanath↗
DOE OSTI2026

Fluorescence Signatures of Rare Earth Metals during Precipitation in Various Conditions

Fluorescence spectroscopy is a widely used sensor methodology that analyzes light emitted from a compound or element as it decays from an excited state. This technique is very sensitive and selective, which is ideal to characterize analytes at lower limits of detection. Key example targets of significant industry and research interest include rare earth elements (REEs) such as dysprosium (Dy) and europium (Eu). These are widely used in advanced technologies including semiconductors, electric vehicle motors, lasers, and permanent magnets. Identifying new sources and responsible reutilization of REEs is essential, and new approaches to extract and recycle REEs could be notably enhanced through the integration of on-line sensors. The sensors can support faster process design, informed scale-up, and cost-effective deployment. This study covers the initial exploration of applying fluorescence-based on-line monitoring to REEs within a precipitation process. This study demonstrates the successful scale-up of a fluorescence -based sensing approach, from stationary cuvettes and small-volume microfluidic devices to continuous flow systems operating at the bench scale (10-25mL). This work also provides initial insight into the challenges of signal’s effects and utility within a turbid environment. Using a modular design for monitoring flowing solutions in a flow tube, fluorescence can be characterized for a variety of analytical targets. In this study, detection performance parameters between the cuvette and flow tube system were compared. Additionally, the response of Dy during precipitation by sodium bicarbonate in the two measurement designs was explored. This letter represents a starting point to bridge the gap between traditional fluorescence sensor measurements in a cuvette to future developments that explore the ability to integrate fluorescence sensors into extraction and separation processes at industrially relevant scales.

fluorescence↗
DOE OSTI2026

Corrections to official ENDF/B Evaluation Releases for SCALE Nuclear Data

The official ENDF/B nuclear data evaluation releases in the past two decades have incrementally incorporated more detailed information, new nuclide evaluations, and very often have improved the accuracy of radiation transport codes when modeling shielding, fission reactors, criticality benchmarks, and fusion systems. However, like any large collaborative data compilation, these releases have all included small errors. This report documents the small corrections to ENDF/B releases ENDF/B-VII.1, ENDF/B-VIII.0, and ENDF/B-VIII.1 that have been applied during nuclear data processing to produce data libraries for the SCALE code system.

Brown, Jesse M. [Oak Ridge National Laboratory (OR↗
DOE OSTI2024

Automated Inspection of Criticality Control Overpacks for Surplus Plutonium Disposition: Qualification Update – 25313

In an effort to reduce the amount of nuclear waste in South Carolina, the Department of Energy (DOE) tasked the Savannah River Site (SRS) with diluting and disposing of the amount of plutonium in the state. This process involves the movement and shipment of over 100,000 criticality control overpacks (CCOs) throughout the project lifespan, lending itself to the use of automation to reduce worker radiation exposure and more efficiently utilize human capital. Due to the large scope, this overarching process was broken down into several different “automation projects” to be developed. The first opportunity pursued was the receipt and inspection of empty CCO drums coming into SRS, identified as Automation Project 1 (AP1), and is the focus of this paper. AP1 was developed to unpack incoming CCOs and inspect them for unwanted foreign objects and any damage to the drum or its contents. This process is accomplished by the combination of an automated guided vehicle (AGV) that delivers CCOs to a robotic arm which uses a suite of custom tools to disassemble a CCO, inspect the inside and outside of the CCO and its inner criticality control container (CCC), reassemble the CCC and CCO, and apply a tamper indicating device (TID) to the inspected drum. In past years, the robotic work cell had been developed in a small-scale testing facility for proof-of-concept. This year, major improvements were made to the robotic work cell to perform the process, including integration into the final facility where CCOs will be inspected. Other technical improvements include the implementation of sensor feedback and safety relays into the control system to allow the state of the work cell to be better tracked, and additional development of the TID application process to complete the robotic inspection. Further enhancements were made to the robotic vision processes and robot pathing, as well as development on a computer vision inspection process to detect inspection criteria anomalies in CCOs. In addition to developmental improvements, the work cell underwent a six-month testing period to ensure the project requirements were met. Results of this testing period demonstrate the work cell’s capability to meet project throughput goals at an acceptable level, successfully document the status of each CCO inspected, and reduce the toll on technical operations’ human power by two thirds. At the time of this paper, the work cell is capable of autonomously handling up to eight CCOs with an AGV, delivering CCOs to and from the robot work cell, and having a robotic arm perform a full receipt and inspection procedure on each CCO. Moving forward, repeatability will be improved so that these CCOs can be run back-to-back seamlessly, as well as improving the system to handle more significant edge cases and failure modes.

Spivey, Nicholas↗
DOE OSTI2022

A universal co-solvent dilution strategy enables facile and cost-effective fabrication of perovskite photovoltaics

Cost management and toxic waste generation are two key issues that must be addressed before the commercialization of perovskite optoelectronic devices. We report a groundbreaking strategy for eco-friendly and cost-effective fabrication of highly efficient perovskite solar cells. This strategy involves the usage of a high volatility co-solvent, which dilutes perovskite precursors to a lower concentration (<0.5 M) while retaining similar film quality and device performance as a high concentration (>1.4 M) solution. More than 70% of toxic waste and material cost can be reduced. Mechanistic insights reveal ultra-rapid evaporation of the co-solvent together with beneficial alteration of the precursor colloidal chemistry upon dilution with co-solvent, which in-situ studies and theoretical simulations confirm. The co-solvent tuned precursor colloidal properties also contribute to the enhancement of the stability of precursor solution, which extends its processing window thus minimizing the waste. This strategy is universally successful across different perovskite compositions, and scales from small devices to large-scale modules using industrial spin-coating, potentially easing the lab-to-fab translation of perovskite technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Encapsulation Residual Stress and Ferrite Loss in Inductive Coil Assemblies

As inductive wireless charging reaches higher power levels, thermal management and mechanical durability become more critical. To address these concerns, past works have demonstrated the benefit of encapsulating coil assemblies in thermally conductive materials. However, due to the sensitivity of the MnZn ferrites commonly used in coil assemblies to mechanical stress, care must be taken to avoid creating large stresses in the ferrite that cause higher hysteresis loss. The stress formation in the encapsulant curing process is overviewed and modeled and an experiment is performed to demonstrate the effect in a small-scale coil assembly. Finally, the effect is shown in the reduced coil-coil efficiency of a first generation high power inductive power transfer prototype using a stiff epoxy compared to better performance in a second prototype using a softer thermally-conductive silicone encapsulant.

Foote, Andrew↗
DOE OSTI2020

Three-dimensional super line-localization in low signal-to-noise microscope images via prior-apprised unsupervised learning (PAUL)

Biological processes such as processive enzyme turnover and intracellular cargo tracking involve the dynamic motion of a small "article" along a curvilinear biopolymer track. To understand these processes that occur across multiple length and time scales, one must acquire both the trajectory of the particle and the position of the track along which it moves, possibly by combining high-resolution single-particle tracking with conventional microscopy. Yet, usually there is a significant resolution mismatch between these modalities: while the tracked particle is localized with a precision of 10 nm, the image of the surroundings is limited by optical difraction, with 200 nm lateral and 500 nm axial resolutions. Compared to the particle's trajectory, the surrounding curvilinear structure appears as a blurred and noisy image. This disparity in the spatial resolutions of the particle trajectory and the surrounding curvilinear structure image makes data reconstruction, as well as interpretation, particularly challenging. Analysis is further complicated when the curvilinear structures are oriented arbitrarily in 3D space. Here, we present a prior-apprised unsupervised learning (PAUL) approach to extract information from 3D images where the underlying features resemble a curved line such as a filament or microtubule. This three-stage framework starts with a Hessian-based feature enhancement, which is followed by feature registration, where local line segments are detected on repetitively sampled subimage tiles. In the final stage, statistical learning, segments are clustered based on their geometric relationships. Principal curves are then approximated from each segment group via statistical tools including principal component analysis, bootstrap and kernel transformation. This procedure is characterized on simulated images, where sub-voxel medium deviations from true curves have been achieved. The 3D PAUL approach has also been implemented for successful line localization in experimental 3D images of gold nanowires obtained using a multifocal microscope. Lastly, this work not only bridges the resolution gap between two microscopy modalities, but also allows us to conduct 3D super line-localization imaging experiments, without using super-resolution techniques.

42 ENGINEERING↗
NASA NTRS1994

Theory review: Line-driven instability and other causes of structure and variability in hot-star winds

The winds of the hot, luminous, OB stars are driven by the line-scattering of the star's continuum radiation flux. Several kinds of observational evidence indicate that such winds are highly structured and variable. This paper will review possible theoretical causes of such wind structure. For relatively small-scale, stochastic variability, I review the role of the strong intrinsic instability of the line-driving process itself. for larger scale structure, I describe recent efforts to examine how disturbances from the underlying, rotating star can be translated outward into propagating features in the wind.

Owocki, Stanley P.↗
NASA NTRS2014

Increased Tensile Strength of Carbon Nanotube Yarns and Sheets through Chemical Modification and Electron Beam Irradiation

The inherent strength of individual carbon nanotubes offers considerable opportunity for the development of advanced, lightweight composite structures. Recent work in the fabrication and application of carbon nanotube (CNT) forms such as yarns and sheets has addressed early nanocomposite limitations with respect to nanotube dispersion and loading; and has pushed the technology toward structural composite applications. However, the high tensile strength of an individual CNT has not directly translated to macro-scale CNT forms where bulk material strength is limited by inter-tube electrostatic attraction and slippage. The focus of this work was to assess post processing of CNT sheet and yarn to improve the macro-scale strength of these material forms. Both small molecule functionalization and e-beam irradiation was evaluated as a means to enhance tensile strength and Youngs modulus of the bulk CNT material. Mechanical testing results revealed a tensile strength increase in CNT sheets by 57 when functionalized, while an additional 48 increase in tensile strength was observed when functionalized sheets were irradiated; compared to unfunctionalized sheets. Similarly, small molecule functionalization increased yarn tensile strength up to 25, whereas irradiation of the functionalized yarns pushed the tensile strength to 88 beyond that of the baseline yarn.

composites↗
DOE OSTI2020

An open source analysis framework for large-scale building energy modeling

Full integration of building energy modelling into the design and retrofit process has long been a goal of building scientists and practitioners. However, significant barriers still exist. Among them are the lack of available: (1) configurable technology stacks for performing both small- and large-scale analyses, (2) different classes of algorithms compatible with common design workflows, and (3) analysis tools for effectively visualizing large-scale simulation results. This article discusses the OpenStudio® Analysis Framework: a scalable analysis framework for building energy modelling that was developed to overcome the three barriers listed above. The framework is open-source and scalable to facilitate wider adoption and has a clearly defined application programming interface upon which other applications can be built. It runs on high-performance computing systems, within cloud infrastructure, and on laptops, and uses a common workflow to enable different classes of algorithms. Lessons learned from previous development efforts are also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2018

Hi-C2.1 Observations of Solar Jetlets at Edges of Network Lanes

We present high resolution (0.2”) high cadence (5s) extreme ultraviolet (EUV) observations of small-­scale jetlet-­like features and spicule-­like features observed with NASA’s High-­resolution Coronal Imager2.1 (Hi-C) during its 5‐min observing span. We investigate the magnetic setting of 4 on-disk jetlets and 2 on-­disk spicules by using high resolution 172A images from Hi-­‐C and EUV images from Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly (AIA) and line-­of-­sight magnetograms from SDO/Helioseismic and Magnetic Imager (HMI). The jetlets and spicules are at edges of magnetic network lanes. From magnetograms co-­aligned with the Hi-­C and AIA images, we find that the jetlets stem from sites of likely flux cancelation between merging majority-polarity and weaker minority-­polarity flux, but in contrast to larger jetlets observed by IRIS some do not show obvious enhanced brightenings at their base. Based on the similarity of these observations of approx. 4 obvious Hi-­C small jetlets with our previous observations of 10 IRIS larger jetlets and approx. 30 coronal jets in quiet regions and coronal holes, we infer that flux cancelation is probably the essential process in the buildup and triggering of jetlets. Our observations suggest that network jetlet eruptions, large and small, are small-scale analogs of both larger-­scale coronal jet eruptions and the still-­larger-­scale eruptions that makemajor CMEs. For simplicitywe will use termjetlets for jetlet-­like features and spicules for spicule-­like features.

Panesar, Navdeep K.↗
DOE OSTI2026

A fast and robust computational modeling approach for density and shape predictions in powder metallurgy hot isostatic pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that produces near-net-shape parts with high material utilization and uniform microstructures. PM-HIP is frequently used for producing small-scale parts with complicated geometries and is potentially economical for producing large-scale parts. However, excessive post-HIP shape distortions can reduce its effectiveness and economic advantage, especially for larger parts. A PM-HIP computational model can predict and help mitigate these distortions. However, due to complex deformation mechanisms and thermo-mechanical coupling present in PM-HIP processes, these non-linear computational models sometimes become numerically unstable. The numerical instabilities in these models can lead to very slow convergence or no convergence at all, which often translates to slow and unreliable models. These limitations are more pronounced in large models with complicated geometries. Hence, in this work, an alternative modeling approach is presented that improves numerical stability and computational performance. The presented approach achieves these improvements through approximating the fully coupled thermo-mechanical PM-HIP model as a decoupled model and adding inertial damping to the model’s mechanical part. In conclusion, a comparison with the fully coupled model indicated a slight dip in prediction accuracy (<5% error) but significant improvements in numerical stability (>20 times larger time step size) and computational performance (5-10 times speed-up with less computational resource usage) when using the presented approach.

Hot isostatic pressing↗
NASA NTRS1993

Impact damage in filament wound composite bottles

Increasingly, composite materials are being used in advanced structural applications because of the significant weight savings they offer when compared to more traditional engineering materials. The higher cost of composites must be offset by the increased performance that results from reduced structural weight if these new materials are to be used effectively. At present, there is considerable interest in fabricating solid rocket motor cases out of composite materials, and capitalizing on the reduced structural weight to increase rocket performance. However, one of the difficulties that arises when composite materials are used is that composites can develop significant amounts of internal damage during low velocity impacts. Such low velocity impacts may be encountered in routine handling of a structural component like a rocket motor case. The ability to assess the reduction in structural integrity of composite motor cases that experience accidental impacts is essential if composite rocket motor cases are to be certified for manned flight. While experimental studies of the post-impact performance of filament wound composite motor cases haven been proven performed (2,3), scaling impact data from small specimens to full scale structures has proven difficult. If such a scaling methodology is to be achieved, an increased understanding of the damage processes which influence residual strength is required. The study described herein was part of an ongoing investigation of damage development and reduction of tensile strength in filament wound composites subjected to low velocity impacts. The present study, which focused on documenting the damage that develops in filament wound composites as a result of such impacts, included two distinct tasks. The first task was to experimentally assess impact damage in small, filament wound pressure bottles using x-ray radiography. The second task was to study the feasibility of using digital image processing techniques to assist in determining the 3-D distribution of damage from stereo x-ray pairs.

Highsmith, Alton L.↗
DOE OSTI2020

Stable Methane Isotopologues From Northern Lakes Suggest That Ebullition Is Dominated by Sub‐Lake Scale Processes

Abstract Stable isotopes have emerged as popular study targets when investigating emission of methane (CH 4 ) from lakes. Yet little is known on how isotopic patterns conform to variations in emission magnitudes—a highly relevant question. Here, we present a large multiyear data set on stable isotopes of CH 4 ebullition (bubbling) from three small adjacent subarctic lakes. The δ 13 C‐CH 4 and δD‐CH 4 range from −78.4‰ to −53.1‰ and from −369.8‰ to −218.8‰, respectively, and vary greatly among the lakes. The signatures suggest dominant hydrogenotrophic methanogenesis, particularly in the deep zones, but there are also signals of seemingly acetoclastic production in some high fluxing shallow areas, possibly fueled by in situ vegetation, but in‐sediment anaerobic CH 4 oxidation cannot be ruled out as an alternative cause. The observed patterns, however, are not consistent across the lakes. Neither do they correspond to the spatiotemporal variations in the measured bubble CH 4 fluxes. Patterns of acetoclastic and hydrogenotrophic production plus oxidation demonstrate that gains and losses of sediment CH 4 are dominated by sub‐lake scale processes. The δD‐CH 4 in the bubbles was significantly different depending on measurement month, likely due to evaporation effects. On a larger scale, our isotopic data, combined with those from other lakes, show a significant difference in bubble δD‐CH 4 between postglacial and thermokarst lakes, an important result for emission inventories. Although this characteristic theoretically assists in source partitioning studies, most hypothetical future shifts in δD‐CH 4 due to high‐latitude lake area or production pathway are too small to lead to atmospheric changes detectable with current technology.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Polar stratospheric cloud processed air and potential vorticity in the Northern Hemisphere lower stratosphere at mid-latitudes during winter

The present study compares small-scale (less than 100 km) features in ER-2 measurements of ClO, O3, H2O, N2O, and NO(y) outside the lower stratospheric Arctic vortex of 1988-1989 with features on potential vorticity maps from ECMWF. The potential vorticity maps are obtained from T106 analyses and forecasts. Some of the plots were truncated to lower resolution (T63 or T42) which smooths out the finer-scale structure. Comparison of these lower resolution plots shows how much detail is lost by excessive smoothing. It is also evident that the forecast plots lose fine-scale structure due to dissipation in the model resulting mainly from horizontal diffusion. It is concluded that blobs of air on the maps at latitudes between the vortex edge and 25 deg N having potential vorticities characteristic of the vortex did indeed originate from the vortex, but that the real atmosphere is more sharply differentiated than the meteorological analyses, implying that the potential vorticity maps underestimate the amount of peeled-off material.

Tuck, A. F.↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Innovative Polyhydroxyalkanoates (PHA) Production with Microbial Electrochemical Technology (MET)

The project “Innovative Polyhydroxyalkanoates (PHA) Production with Microbial Electrochemical Technology (MET)” addressed food waste disposal challenges by successfully converting food waste to bioplastics (known as PHAs). The novel process created by our team of researchers from universities, national labs, and industry substantially enhanced overall carbon conversion efficiency of food waste processing (> 50%), while reducing disposal costs (> 25%). The project showed economic viability potential at community scale through pilot-scale demonstration at a relevant scale (50 L reactor volume) with more than 100 hours of PHA production using realistic conditions. The project goal was to valorize food waste by shunting traditional anaerobic digestion processing and creating a value-added PHA processing route that improves the economics and sustainability of local, community-scale, wet organic waste treatment. First, the food waste undergoes microbial-based, dark fermentation to break down the food to small carbon chains known as volatile fatty acids (VFAs). Instead of microorganisms converting the VFAs into methane using normal anaerobic digestion processing, our innovative process inhibits methane production. This preserves the produced VFAs for extraction and use by a novel Haloferax mediterranei (HM) archaea, which effectively converts the VFAs to bioplastics. The project added microbial electrochemical cells (MEC) to the dark fermentation process to enhance the VFAs produced and optimize the type of bioplastics formed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Topology, landscapes, and biomolecular energy transport

While ubiquitous, energy redistribution remains a poorly understood facet of the nonequilibrium thermodynamics of biomolecules. At the molecular level, finite-size effects, pronounced nonlinearities, and ballistic processes produce behavior that diverges from the macroscale. Here, we show that transient thermal transport reflects macromolecular energy landscape architecture through the topological characteristics of molecular contacts and the nonlinear processes that mediate dynamics. While the former determines transport pathways via pairwise interactions, the latter reflects frustration within the landscape for local conformational rearrangements. Unlike transport through small-molecule systems, such as alkanes, nonlinearity dominates over coherent processes at even quite short time- and length-scales. Our exhaustive all-atom simulations and novel local-in-time and space analysis, applicable to both theory and experiment, permit dissection of energy migration in biomolecules. The approach demonstrates that vibrational energy transport can probe otherwise inaccessible aspects of macromolecular dynamics and interactions that underly biological function.

59 BASIC BIOLOGICAL SCIENCES↗