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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Unraveling the nature of sulfide ions in hydrometallurgical recycling of NCM622 cathode material

The use of lithium-ion batteries (LIBs) has increased dramatically since its initial inception in the late 20th century. Such a surge in the LIB market and industry has resulted in a huge demand for mineral resources. Besides, the large scale of production will lead to massive amounts of waste batteries in the end. As such, recycling is seen as an end-of-pipe process to resolve sustainability and environmental concerns. The hydrometallurgical recycling is considered to be the most prominent method to recover cathode materials from spent LIBs owing to its high leaching efficiency and low energy costs. A series of procedures including pretreatment of the spent LIBs, acid leaching of the black mass, chemical co-precipitation of the hydroxide precursor, and sintering of the cathode active material need to be operated precisely. In this aspect, the impurities introduced during the process could pose a serious threat to the reaction stability as well as recycling consistency. Here, the impact of sulfide ions on recovered LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NCM622) cathode material with the method of hydrometallurgy is first investigated in detail. This study shows that hydrometallurgical process is not obviously influenced by sulfide impurity. No signs of secondary phase or impurity inclusion are spotted in synthesized cathodes. Under 5 at % sulfide concentration conditions, the obtained NCM622 cathode exhibits a capacity of 159.4 mAh/g after 100 cycles at 1/3C, which is at the same level as virgin benchmark. The difference in rate performance between cathodes with and without additional sulfide is less than 2 % or even smaller. In short, the results indicate a neutral status of sulfide ions in hydrometallurgical recycling.

25 ENERGY STORAGE↗
DOE OSTI2022

Public Health Response and Medical Management of Internal Contamination in Past Radiological or Nuclear Incidents: A Review

Following a radiological or nuclear emergency, workers, responders and the public may be internally contaminated with radionuclides. Screening, monitoring and assessing any internal contamination and providing necessary medical treatment, especially when a large number of individuals are involved, is challenging. Experience gained and lessons learned from the management of previous incidents would help to identify gaps in knowledge and capabilities on preparedness for and response to radiation emergencies. In this paper, eight largescale and five workplace radiological and nuclear incidents are reviewed cross 14 technical areas, under the broader topics of emergency preparedness, emergency response and recovery processes. The review findings suggest that 1) new strategies, algorithms and technologies are explored for rapid screening of large populations; 2) exposure assessment and dose estimation in emergency response and dose reconstruction in recovery process are supported by complementary sources of information, including ‘citizen science’; 3) surge capacity for monitoring and dose assessment is coordinated through national and international laboratory networks; 4) evidence-based guidelines for medical management and follow-up of internal contamination are urgently needed; 5) mechanisms for international and regional access to medical countermeasures are investigated and implemented; 6) long-term health and medical follow up programs are designed and justified; and 7) capabilities and capacity developed for emergency response are sustained through adequate resource allocation, routine nonemergency use of technical skills in regular exercises, training, and continuous improvement.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Sustainable Li-ion anode material from Fe-catalyzed graphitization of paper waste

We report a novel method for the conversion of paper towel waste to biographite anode material is developed and optimized for use in Li-ion batteries. The surge in demand for Li-ion battery anode materials coupled with the unsustainable and inefficient methods of producing battery-grade graphite necessitate alternative carbon feedstocks and graphitization technologies. Paper waste (PW) is identified as a suitable carbon feedstock for iron-catalyzed graphitization due to its sustainability, low cost, low ash content, and ample supply for the intended end use. A Box Behnken experimental design for statistical optimization is pursued for untreated and pre-carbonized PW with factors of temperature (1100-1300 °C), hold time (1-5 h), and iron catalyst loading (0.5-1.5x fixed carbon content) with biographite crystal size as the primary response variable. Temperature and iron catalyst loading are found to be significant factors, whereas hold time is found to be insignificant. Reversible capacities of the biographite anodes are found to be 340-355 mAh g-1 with 99% capacity retention over 100 cycles, indicating good electrochemical performance relative to commercial graphite anodes. The initial Coulombic efficiency of untreated and pre-carbonized biographites, however, are 77% and 75%, respectively, suggesting parasitic reactions including electrolyte decomposition.

25 ENERGY STORAGE↗
DOE OSTI2023

Salinity exposure affects lower-canopy specific leaf area of upland trees in a coastal deciduous forest

Sea level rise and increasing storm surges are likely to affect the canopy physiology, ecology, and structure of coastal forests, even well in advance of tree mortality. Laboratory and greenhouse studies have documented that saltwater exposure can trigger changes in leaf-level physiology and morphology, but few in situ studies have examined how tree-specific leaf area (SLA), the ratio of leaf area to mass and a crucial trait and model parameter, is affected by saline soils. We conducted an observational study of SLA in a mid-Atlantic (USA) coastal deciduous forest, taking advantage of a natural gradient in salinity along a tidal creek. Measured SLA of the 239 trees and seven species sampled ranged from Carya glabra (N = 6 trees, mean SLA = 277.9±36.3cm 2 /g) to Fagus grandifolia (N=60, 321.9±62.9cm 2 g); as expected, trees species and canopy position (sun versus shade) significantly affected SLA. For trees (N=100) directly exposed to the tidal creek, salinity was highly significant after accounting for species (P<0.001), with trees in the lower reaches of the creek having lower SLA. Leaf area index (LAI), computed from SLA and litter traps, ranged from 4.8 to 15.8 and was inversely related to salinity exposure; the spatial variability in leaf litter production contributed much more to LAI uncertainty than did SLA variability. These in situ results are correlative but consistent with the hypothesis, based on previous greenhouse studies, that the stress of chronic salinity exposure changes species’ leaf morphology. Our findings are useful for understanding the growing effects of saltwater intrusion into upland forests, as well as parameterizing and testing ecosystem-scale models simulating forest stressors and disturbances at the terrestrial-aquatic interface.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Sustainable valorization of waste tires: Selective hydrotreating for renewable p-cymene production

The escalating global concern over waste tire management driven by the surge in automobiles necessitates sustainable and innovative solutions. Here, this study posits a novel approach by introducing a selective catalytic hydrogenation and dehydrogenation process using a tandem two-stage pressurized fixed-bed reactor, aiming to convert waste tires into valuable sulfur-free p-cymene. The experimental results indicate that among the studied catalysts including Pt/C, Pd/C, Ru/C, and Ni/Al 2 O 3 -SiO 2 , the Pd/C exhibits concomitant hydrogenation and dehydrogenation functionalities, achieving full conversion and displaying 100 % selectivity towards p-cymene from limonene model compound. Furthermore, the Pd/C catalyst demonstrates remarkable efficiency in converting real-world waste tires into p-cymene, yielding up to 134.8 mg/g at optimal conditions. Importantly, this catalyst also facilitates complete hydrodesulfurization activity, addressing environmental concerns by producing sulfur-free liquid products. This innovative method not only optimizes p-cymene synthesis from waste tires but also contributes to environmental sustainability, showcasing both economic and ecological viability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Enabling machine learning-ready HPC ensembles with Merlin

With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensemble data. With complexities such as multi-component workflows, heterogeneous machine architectures, parallel file systems, and batch scheduling, care must be taken to facilitate this analysis in a high performance computing (HPC) environment. Here, we present Merlin, a workflow framework to enable large ML-friendly ensembles of scientific HPC simulations. By augmenting traditional HPC with distributed compute technologies, Merlin aims to lower the barrier for scientific subject matter experts to incorporate ML into their analysis. As a producer–consumer workflow model, Merlin enables multi-machine, cross-batch job, dynamically allocated yet persistent workflows capable of utilizing surge-compute resources. Key features of Merlin are a flexible HPC-centric interface, low per-task overhead, multi-tiered fault recovery, and a hierarchical sampling algorithm that allows for $\mathscr{O}$(N) task execution and $\mathscr{O}$(N ln N) task queuing to ensembles of millions of tasks. In addition to Merlin’s design, we test the algorithm’s performance in an HPC center and demonstrate the ability to enqueue 40 million simulations in 100 s, with a 30 millisecond per-task overhead that is independent of ensemble size. Finally, we describe some example applications that Merlin has enabled on leadership-class HPC resources, such as the ML-augmented optimization of nuclear fusion experiments and the calibration of infectious disease models to study the progression of and possible mitigation strategies for COVID-19.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Improved multiline HVDC circuit breakers with asymmetric conducting branches

Here, this paper proposes two improved multiline HVDC circuit breakers (DCBs) for HVDC grid applications, including type-1 improved multiline DCB and type-2 improved multiline DCB. The two improved DCBs draw on the core idea of extended H-bridge. m adjacent DC transmission lines share a single main breaker (MB) and surge arrester. Due to the extended H-bridge design, bidirectional current flow can be achieved by a unidirectional MB. An upper conducting branch and a lower conducting branch are connected to a DC line. The upper and lower conducting branches in the two improved multiline DCBs are asymmetric. The upper conducting branch of both two improved DCBs is formed by a load commutation switch (LCS) and an ultra-fast disconnector (UFD). The lower conducting branch of the type-1 improved scheme is composed of a diode and a UFD; and of the type-2 improved scheme is made up of diode stack. Compared with other DCBs, the proposed type-1 DCB and type-2 DCB are more cost effective. Among the five DCBs, the type-2 improved scheme requires the least number of individual switching actions. The effectiveness and feasibility of the proposed schemes are verified through simulation of a bipolar three-terminal HVDC grid in PSCAD/EMTDC.

42 ENGINEERING↗
DOE OSTI2023

Balancing molecular level influences of intermolecular frustrated Lewis pairs (FLP) for successful design of FLP catalysts for hydrogen storage applications

The rise in energy demands and the deleterious environmental issues related to fossil fuels has led to a surge of interest in hydrogen as a "green" alternative. Hydrogen's extraordinary energy density makes it a potential energy and economic "power"-house. Significant research has been dedicated to materials-based hydrogen storage. One area, liquid organic hydrogen carriers (LOHC) is of substantial interest for the reversible transportation of hydrogen from production to end-use facilities. There are challenges associated with this technology including the dependency on precious metal-based catalysts. Recent work in frustrated Lewis pair (FLP) catalysis demonstrates promise for addressing these challenges. Here this review is focused on assessing recent literature on the utilization of intermolecular FLP main group catalysts for improved hydrogenation/dehydrogenation of various substrates including potential LOHC complexes. This review will present an overview of FLPs, highlight potential hydrogen storage applications, and propose areas where knowledge gaps exist that require further investigations.

08 HYDROGEN↗
DOE OSTI2021

Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer

Natural language processing (NLP), which aims to convert human language into expressions that can be analyzed by computers, is one of the most rapidly developing and widely used technologies in the field of artificial intelligence. Natural language processing algorithms convert unstructured free text data into structured data that can be extracted and analyzed at scale. In medicine, this unlocking of the rich, expressive data within clinical free text in electronic medical records will help untap the full potential of big data for research and clinical purposes. Recent major NLP algorithmic advances have significantly improved the performance of these algorithms, leading to a surge in academic and industry interest in developing tools to automate information extraction and phenotyping from clinical texts. Thus, these technologies are poised to transform medical research and alter clinical practices in the future. Radiation oncology stands to benefit from NLP algorithms if they are appropriately developed and deployed, as they may enable advances such as automated inclusion of radiation therapy details into cancer registries, discovery of novel insights about cancer care, and improved patient data curation and presentation at the point of care. However, challenges remain before the full value of NLP is realized, such as the plethora of jargon specific to radiation oncology, nonstandard nomenclature, a lack of publicly available labeled data for model development, and interoperability limitations between radiation oncology data silos. Successful development and implementation of high quality and high value NLP models for radiation oncology will require close collaboration between computer scientists and the radiation oncology community. Here, we present a primer on artificial intelligence algorithms in general and NLP algorithms in particular; provide guidance on how to assess the performance of such algorithms; review prior research on NLP algorithms for oncology; and describe future avenues for NLP in radiation oncology research and clinics.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Modeling atmospheric data and identifying dynamics Temporal data-driven modeling of air pollutants

Atmospheric modelling has recently experienced a surge with the advent of deep learning. Most of these models, however, predict concentrations of pollutants following a data-driven approach in which the physical laws that govern their behaviors and relationships remain hidden. Furthermore, with the aid of real-world air quality data collected hourly in different stations throughout Madrid, we present a case study using a series of data-driven techniques with the following goals: (1) Find systems of ordinary differential equations that model the concentration of pollutants and their changes over time; (2) assess the performance and limitations of our model using stability analysis; (3) reconstruct the time series of chemical pollutants not measured in certain stations using delay coordinate embedding results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Sustainable recovery of Rare Earth Elements (REEs) from coal and coal ash through urban mining: A Nature Based Solution (NBS) for circular economy

The demand for rare earth elements (REEs) has surged in recent years, driven by their crucial role in various industrial applications and their uneven geological distribution. As a result, urban mining from secondary resources, particularly coal and coal ash, has gained traction as a sustainable solution within a circular economy framework. This study highlights the significant presence of REEs in coal and coal ash, revealing that certain samples contain REE concentrations that rival traditional ores. Notably, coal ash has the potential to yield approximately 312,000 tons of REEs annually, far exceeding global demand. The research delves into advanced techniques for analyzing REEs, including elemental, isotopic, and mineralogical studies. Additionally, it explores innovative extraction methods such as the use of green solvents, nature-based solutions, and bioleaching and biosorption. By leveraging coal and its byproducts as secondary resources, this study underscores the opportunity to reduce dependence on conventional mining, enhancing the sustainability of REE recovery. Here, a comprehensive literature review was conducted to highlight technological advancements and emerging opportunities that can address current challenges in this field.

Circular economy↗
DOE OSTI2022

Impacts of climate change on future hurricane induced rainfall and flooding in a coastal watershed: A case study on Hurricane Harvey

The warming climate is likely to increase hurricane-associated extreme rainfall and lead to sea-level rise (SLR). Thus, how the floods induced by intense hurricanes respond to these potential changes is of great concern. This study investigates the future warmer climate impacts on hurricane-induced extreme rainfall, and—more importantly—the subsequent compound flooding at the watershed scale (from an event-based analysis perspective). To this goal, a modeling framework is designed based on the Distributed Hydrology Soil Vegetation Model (DHSVM), the Two-Dimensional fvand the Regional Community Earth System Model (R-CESM). The framework was applied to Hurricane Harvey (2017) at the Clear Creek watershed (a coastal watershed in the southern Houston) as a case study. The results show that the projected maximum rainfall totals over the watershed would be exacerbated by 17.7 % and 49.7 % in the 2050s and 2090s (respectively) under Representative Concentration Pathway 8.5 (RCP 8.5). This means a 16.1 % increase in Harvey rainfall over the watershed per degree Celsius increase in Mean Surface Temperature over the Gulf of Mexico region (18°~31° N, 77°~98° W). Meanwhile, the increases in maximum inundation extent would be 11.0 % (2050s) and 19.5 % (2090s). Furthermore, considerable increases in maximum inundation depth and duration in regions along the middle and downstream of Clear Creek (and also those around Clear Lake) are expected. The projected SLR will have little effect on the maximum inundation depth and extent if storm surge changes are not taken into account; meanwhile, it will influence the inundation duration at downstream locations. In conclusion, this modeling framework can be also applied at other coastal watersheds to evaluate the projected climate change impacts on the compound flooding induced by extreme climate events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Unlocking the value of recycling scrap from Li-ion battery manufacturing: Challenges and outlook

The growing global trend toward mobile electrification is primarily driven by the rising popularity of electric vehicles, leading to an unprecedented surge in demand for lithium-ion batteries. As a result, the importance of battery recycling has become increasingly apparent. Battery recycling aims to recover valuable materials from both spent batteries and battery manufacturing scraps. By recycling these resources, the reliance on raw material extraction is reduced, which benefits resource conservation and minimizes the need for new mining operations. While significant attention has been given to the recycling of spent batteries, less emphasis has been placed on the recycling and recovery of battery scraps. However, it is important to recognize that many gigafactories are still taking steps to improve their manufacturing processes, and end-of-life batteries take approximately 10 years to become suitable for recycling, the manufacturing scraps will serve as the primary sources for recycling in this decade. This review delves into the progress in recycling technologies associated with battery manufacturing scraps, shedding light on the challenges, opportunities, and evolving perspectives surrounding battery manufacturing scrap recycling. In conclusion, we aim to contribute to the knowledge base of battery manufacturing scrap recycling and promote a more comprehensive understanding of the subject.

25 ENERGY STORAGE↗
DOE OSTI2022

Inactivation of multiple human pathogens by Fathhome's dry sanitizer device: Rapid and eco-friendly ozone-based disinfection

SARS-CoV-2 spread rapidly, causing millions of deaths across the globe. As a result, demand for medical supplies and personal protective equipment (PPE) surged and supplies dwindled. Separate entirely, hospital-acquired infections have become commonplace and challenging to treat. To explore the potential of novel sterilization techniques, this study evaluated the disinfection efficacy of Fathhome's ozone-based, dry-sanitizing device by dose and time response. Inactivation of human pathogens was tested on non-porous (plastic) surfaces. 95.42-100% inactivation was observed across all types of vegetative microorganisms and 27.36% inactivation of bacterial endospores tested, with no residual ozone detectable after completion. These results strongly support the hypothesis that Fathhome's commercial implementation of gas-based disinfection is suitable for rapid decontamination of a wide variety of pathogens on PPE and other industrially relevant materials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

New frontiers in atom probe tomography: a review of research enabled by cryo and/or vacuum transfer systems

There has been a recent surge in the use of cryo and/or vacuum specimen preparation and transfer systems that are broadening the scope of research enabled by the microscopy technique of atom probe tomography. This is driven by the fact that, like for many microscopes, the application of atom probe to air and temperature sensitive materials or wet biological specimens has previously been limited by through-air-transfer and through-vacuum-transfer at room temperature. Here we provide an overview of the critical areas of research that require these new transfer and analysis protocols, as well as a review of current advances in transfer devices, environmental cells and glove boxes for controlled sample manipulation. This includes the study of catalysis and corrosion, the application of atom probe to biological samples, the study of liquid-solid interfaces, natural ageing investigations and the analysis of hydrogen in metals.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Generalist multimodal AI: A review of architectures, challenges and opportunities

Multimodal models are expected to be a critical component to future advances in artificial intelligence. Here, this field is starting to grow rapidly with a surge of new design elements motivated by the success of foundation models in natural language processing (NLP) and vision. It is widely hoped that further extending the foundation models to multiple modalities (e.g., text, image, video, sensor, time series, graph, etc.) will ultimately lead to generalist multimodal models, i.e. one model across different data modalities and tasks. However, there is little research that systematically analyzes recent multimodal models (particularly the ones that work beyond text and vision) with respect to the underling architecture proposed. Therefore, this work provides a fresh perspective on generalist multimodal models (GMMs) via a novel architecture and training configuration specific taxonomy. This includes factors such as Unifiability, Modularity, and Adaptability that are pertinent and essential to the wide adoption and application of GMMs. The review further highlights key challenges and prospects for the field and guide the researchers into the new advancements.

Artificial intelligence (AI)↗
DOE OSTI2021

OC6 Phase Ib: Validation of the CFD predictions of difference-frequency wave excitation on a FOWT semisubmersible

During the previous OC5 11 project, state-of-the-art mid-fidelity engineering tools for floating wind systems were found to consistently underpredict the nonlinear, low-frequency responses of semisubmersible offshore wind platforms, leading to substantial errors in the structural loads because of low-frequency surge and pitch resonance. To examine this underprediction, a coordinated investigation with computational fluid dynamics (CFD) simulations and model-basin experiments was carried out. Both investigations involved a fixed and simplified OC5-DeepCwind semisubmersible in bichromatic waves. The wave excitations - especially the nonlinear, difference-frequency excitation - on the structure from the CFD simulations were compared to the experimental measurements for validation, with uncertainty analyses for both the experimental and the CFD results. Furthermore, the wave excitations on each column of the semisubmersible were measured separately in the experiment, allowing the validation of the CFD results to be done on a per-column basis. Overall, the CFD predictions of the difference-frequency excitations agree with the experimental measurements, suggesting the CFD solutions can be used as a reference for tuning and improving the engineering-level tools and can provide a means to better understand the underprediction at low frequencies.

16 TIDAL AND WAVE POWER↗