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

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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Microbial assimilation of lignin-derived aromatic compounds and conversion to value-added products

Lignin is an abundant and sustainable source of aromatic compounds that can be converted to value-added products. However, lignin is underutilized, since depolymerization produces a complex mixture of aromatic compounds that is difficult to convert to a single product. Microbial conversion of mixed aromatic substrates provides a potential solution to this conversion challenge. Recent advances have expanded the range of lignin-derived aromatic substrates that can be assimilated and demonstrated efficient conversion via central metabolism to new potential products. Here, the development of additional non-model microbial hosts and genetic tools for these hosts have accelerated engineering efforts. However, yields with real depolymerized lignin are still low, and additional work will be required to achieve viable conversion processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Modeling the Value Recovery of Rare Earth Permanent Magnets at End-of-Life

Permanent magnets containing rare earth elements (REEs) such as Dysprosium and Neodymium offer an advantage over non-REE containing magnets (e.g. ferrite or AlNiCo) in terms of power relative to size. However, REE availability has varied significantly in recent years leading to volatility in the cost of rare earth permanent magnets (REPMs). The supply of REEs can be increased by recycling consumer products and industrial machinery that contain REPMs at product end-of-life (EOL). This paper discusses the REE recovery process for EOL products. The optimal dismantling of products is examined with an emphasis placed on obtaining used REPMs. The challenge of collecting, managing, transporting, and processing used products is addressed through the development of a cost model for REPM recovery. This model is used to investigate several EOL strategies for recovering REPMs. Sensitivity analysis is conducted to identify the key factors that influence value recovery economics. A hard disk drive serves as a case study for model demonstration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Characterizing value-added pellets obtained from blends of miscanthus, corn stover, and switchgrass

The current pellet industry primarily relies on woody biomass. Inclusion of a diverse feedstock, such as herbaceous biomass, is necessary to meet the rising demand for pellets in heat and power generation, and for biofuel production. This study was motivated by the need to densify biomass, improving its naturally low energy density, to reach the required pellet standards for biofuel conversion. Here, we developed value-added miscanthus pellets blended with different ratios of corn stover and switchgrass and analyzed their chemical, physical, and mechanical properties. Pure miscanthus pellet durability index (PDI) was less than 85 %, well below the ISO 17225-6 standard for herbaceous pellets. While increasing switchgrass and corn stover ratios increases durability beyond 94 %, it also increases ash content from 1.6 % to 4.6 %, a quality unfavorable for biofuel conversion. The moisture content of the blended pellets varied from 7.12 % to 12.45 %, and positively correlated with the durability of the pellets. Pure miscanthus pellets had the highest bulk density, 633 kg/m 3 , while pellets containing 75 % miscanthus and 25 % corn stover had the lowest density, 564 kg/m 3 . The findings of this study also identified a decrease in the pellet bulk density with the increase in ash content and pellet diameter.

09 BIOMASS FUELS↗
DOE OSTI2019

Comparative life cycle analysis for value recovery of precious metals and rare earth elements from electronic waste

There is an ever-increasing concern regarding the electronic waste (e-waste), which is the fastest growing waste stream in the world. Incentivized by various legislations and the intrinsic value of critical metals inside, recycling of e-waste is becoming an attractive business opportunity that also benefits the environment. We report a novel electrochemical recovery (ER) process has been developed as a promising alternative to the existing pyrometallurgical and hydrometallurgical processes based technologies to recover base metals, precious metals, and rare earth elements (REEs) from e-waste. Experimental results indicate that the ER process has lower chemical consumption, enhanced control, and reduced energy demand compared to the pyrometallurgical and the hydrometallurgical processes. To quantify and compare the environmental performances of the three technologies, life cycle analysis has been conducted. Results show that the ER process outperforms the other two processes in almost all impact categories adopted in TRACI and ILCD while there is no clear winner between the hydrometallurgical and the pyrometallurgical processes. The highest impactful input for the ER method is hydrochloric acid, and for the pyrometallurgical method is copper scrap, while for the hydrometallurgical method, it is hydrogen peroxide, an oxidizer that accelerates base metal extraction process, that dominates the overall environmental footprint. The environmental viability of the ER process warrants the further development of ER process at industrial scale.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Technoeconomic Analysis of High-Value, Crystalline Silicon Photovoltaic Module Recycling Processes

Recycling is an important circular economy strategy, and for photovoltaics (PV), the one that has received the greatest research attention. Recycling of PV modules is required in Europe; everywhere else it competes in the market of end-of-life options, where cost is a primary decision factor. The vast majority of PV modules sold globally are crystalline-silicon (c-Si); most of the rest of the market are cadmium telluride thin film modules whose primary manufacturer runs its own commercial-scale recycling program. While many different c-Si recycling approaches and technologies have been proposed, they generally lack accompanying cost estimates or enough process information to model costs. Herein we develop detailed estimates of seven categories of capital and operating costs along with estimates of revenue from recovered materials for each step in two proposed recycling processes for c-Si PV modules. Using these results, we develop a hypothetical third recycling process merging process steps from the original two, estimate surcharges required to achieve minimum sustainable prices for each recycling process, as well as consider how economies of scale could reduce costs. Increasing the purity of and identifying higher-value markets for recovered materials are approaches to reducing costs and increasing recycling rates in voluntary markets.

crystalline silicon↗
DOE OSTI2017

The value of demand response in Florida

Many electrical loads may be operated flexibly to provide grid services, including peaking capacity, reserves, and load shifting. The authors model 14 demand end uses in Florida and analyze their operational impacts and overall value for a wide range of solar penetrations and grid flexibility options. They find demand response is able to reduce production costs, reduce the number of low-load hours for traditional generators, reduce starting of gas generators, and reduce curtailment.

14 SOLAR ENERGY↗
DOE OSTI2020

Denoising atomic resolution 4D scanning transmission electron microscopy data with tensor singular value decomposition

Tensor singular value decomposition (SVD) is a method to find a low-dimensional representation of data with meaningful structure in three or more dimensions. Here, tensor SVD has been applied to denoise atomic-resolution 4D scanning transmission electron microscopy (4D STEM) data. On data simulated from a SrTiO 3 [100] perfect crystal and a Si [110] edge dislocation, tensor SVD achieved an average peak signal-to-noise ratio (PSNR) of ~40 dB, which matches or exceeds the performance of other denoising methods, with processing times at least 100 times shorter. On experimental data from SrTiO 3 [100] and LiZnSb [11 2 ¯ 0]/GaSb [110] samples, tensor SVD denoises multiple GB 4D STEM data sets in ten minutes on a typical personal computer. Denoising with tensor SVD improves both convergent beam electron diffraction patterns and virtual-aperture annular dark field images.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Hidden values in bauxite residue (red mud): Recovery of metals

Highlights: • Current iron recovery techniques using red mud are depicted. • Advantages and disadvantages exist in different recovering processes. • Economic and environmental friendly integrated usage of red mud is promising. - Abstract: Bauxite residue (red mud) is a hazardous waste generated from alumina refining industries. Unless managed properly, red mud poses significant risks to the local environment due to its extreme alkalinity and its potential impacts on surface and ground water quality. The ever-increasing generation of red mud poses significant challenges to the aluminium industries from management perspectives given the low proportion that are currently being utilized beneficially. Red mud, in most cases, contains elevated concentrations of iron in addition to aluminium, titanium, sodium and valuable rare earth elements. Given the scarcity of iron supply globally, the iron content of red mud has attracted increasing research interest. This paper presents a critical overview of the current techniques employed for iron recovery from red mud. Information on the recovery of other valuable metals is also reviewed to provide an insight into the full potential usage of red mud as an economic resource rather than a waste. Traditional hydrometallurgy and pyrometallurgy are being investigated continuously. However, in this review several new techniques are introduced that consider the process of iron recovery from red mud. An integrated process which can achieve multiple additional values from red mud is much preferred over the single process methods. The information provided here should help to improve the future management and utilization of red mud.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Value-creating upcycling of retired electric vehicle battery cathodes

The electrification revolution in the automobile and other industries demands annual production capacity of batteries of at least 10 2 GWh, which presents a twofold challenge: supply of key materials such as cobalt and nickel and recycling when batteries are retired from use. Pyrometallurgical and hydrometallurgical recycling are currently used in industry but suffer from complexity, high costs, and secondary pollution. Here we report a molten-salt-based method for direct recycling (MSDR) that is environmentally benign and creates value on the basis of a techno-economic analysis using real-world data and price information. We also experimentally demonstrate the feasibility of MSDR by upcycling a low-nickel polycrystalline LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC) cathode material into Ni-rich (Ni > 65%) single-crystal NMCs with increased energy density (>10% increase) and outstanding electrochemical performance (>94% capacity retention after 500 cycles). This work may open opportunities for closed-loop recycling of electric vehicle batteries and manufacturing of next-generation NMC cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2019

The conservation value of forest fragments in the increasingly agrarian landscape of Sumatra

Throughout the world, tropical rainforests are being destroyed at an alarming rate, reducing many unprotected habitats to small fragments of remnant forests within the cleared landscape. Understanding the best way to provide wildlife habitat amid changing landscapes is essential for land use planning, especially in biodiversity hotspots like Indonesia. However, little is known about the conservation significance and mammalian use of forest fragments in Sumatra. In this study, camera trap surveys were conducted within Bukit Barisan Selatan National Park and five surrounding forest fragments, and species composition metrics were used to compare their use. Twenty-eight species of mammals were found in the forest and 21 in the surrounding fragments. The fragments harbored a subset of the species found within the primary forest, as well as several species not observed in the forest. Critically endangered species such as Sunda pangolin (Manis javanica) and Sumatran tiger (Panthera tigris sumatrae) were found in the fragments, along with species of conservation concern such as marbled cat (Pardofelis marmorata) and Asiatic golden cat (Pardofelis temminickii). The biodiversity found within the fragments suggests that these small patches of remnant forest may be of conservation value to certain mammal species and may facilitate connectivity across the landscape.

biodiversity, tropical forests, mammals↗
DOE OSTI2023

Comparative Techno-economic Analysis and Life Cycle Assessment of Producing High-Value Chemicals and Fuels from Waste Plastic via Conventional Pyrolysis and Thermal Oxo-degradation

The rapid rise in global plastic production in recent decades has resulted in the massive generation of plastic waste. Over 75% of the plastic waste generated in the United States was sent to landfills, with a meager 8.7% recycled. Plastics are valuable feedstocks for platform chemicals and fuels. Chemical upcycling of waste high-density polyethylene (HDPE) is gaining more attention as a potentially feasible and environmentally friendly plastic waste management technology. Conventional pyrolysis (CPY) and thermal oxo-degradation (TOD) are two chemical upcycling technologies actively researched for decomposing waste HDPE into valuable chemicals and fuels. However, there are few studies on the techno-economic analysis (TEA) and life cycle assessment (LCA) of these technologies for converting waste HDPE to valuable products. This study conducts a comparative TEA and LCA study of the thermochemical decomposition of waste HDPE to produce gaseous (ethylene and propylene) and liquid (naphtha, diesel, and wax) products by CPY and TOD. The study elucidates and compares the impact of hydrocracking longer chain hydrocarbons to produce more valuable products on the TEA and LCA. The TEA showed that the fixed capital investment could range from $\$32.5$ million for TOD without hydrocracking to $\$244$ million for CPY with hydrocracking scenarios. Annual revenues range from $\$28.1$ million to $\$71.5$ million in favor of scenarios with hydrocracking. However, the net present value ranges from $\$1.4$ million to $\$265.8$ million in favor of scenarios without hydrocracking. Sensitivity analysis showed that fixed capital cost, facility capacity, and product prices have the biggest impact on the process economics of the facilities, while utilities and waste transportation to refineries have the biggest impact on environmental impacts. Here, the LCA showed that primary products from scenarios without hydrocracking can be more environmentally friendly than virgin products from petroleum processes. However, TOD and CPY with hydrocracking primary products have more emissions than those of virgin products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

How Accurate Is Density Functional Theory at Predicting Dipole Moments? An Assessment Using a New Database of 200 Benchmark Values

We present that dipole moments are a simple, global measure of the accuracy of the electron density of a polar molecule. Dipole moments also affect the interactions of a molecule with other molecules as well as electric fields. To directly assess the accuracy of modern density functionals for calculating dipole moments, we have developed a database of 200 benchmark dipole moments, using coupled cluster theory through triple excitations, extrapolated to the complete basis set limit. This new database is used to assess the performance of 88 popular or recently developed density functionals. The results suggest that double hybrid functionals perform the best, yielding dipole moments within about 3.6-4.5% regularized RMS error versus the reference values - which is not very different from the 4% regularized RMS error produced by coupled cluster singles and doubles. Many hybrid functionals also perform quite well, generating regularized RMS errors in the 5-6% range. Lastly, some functionals, however, exhibit large outliers, and local functionals in general perform less well than hybrids or double hybrids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

What Levels of Coupled Cluster Theory Are Appropriate for Transition Metal Systems? A Study Using Near-Exact Quantum Chemical Values for 3d Transition Metal Binary Compounds

Transition metal compounds are traditionally considered to be challenging for standard quantum chemistry approximations like coupled cluster (CC) theory, which are usually employed to validate lower level methods like density functional theory (DFT). To explore this issue, we present a database of bond dissociation energies (BDEs) for 74 spin states of 69 diatomic species containing a 3d transition metal atom and a main group element, in the moderately sized def2-SVP basis. The presented BDEs appear to have an (estimated) 3σ error less than 1 kJ/mol relative to the exact solutions to the nonrelativistic Born-Oppenheimer Hamiltonian. These benchmark values were used to assess the performance of a wide range of standard single reference CC models, as the results should be beneficial for understanding the limitations of these models for transition metal systems. We find that interactions between metals and monovalent ligands like hydride and fluoride are well described by CCSDT. Similarly, CCSDTQ appears to be adequate for bonds between metals and nominally divalent ligands like oxide and sulfide. However, interactions with polyvalent ligands like nitride and carbide are more challenging, with even CCSDTQ(P)Λ yielding errors on the scale of a few kJ/mol. We also find that many perturbative and iterative approximations to higher order terms either yield disappointing results or actually worsen the performance relative to the baseline low level CC method, indicating that complexity does not always guarantee accuracy.

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

Emergence of a Low-Energy Peak in the Smoothed Absolute Value Circular Dichroism Spectra of Small Helical Gold Nanorods

We calculate, using time-dependent density functional theory, absorption and circular dichroism (CD) spectra for a series of small helical gold nanorod structures with a width of 0.6 nm and length increasing from 0.7 nm for Au 24 to 1.9 nm for Au 56 . For a low-energy window, ranging from 1.7 to 4.1 eV, broadening the lines in the absorption spectra results in a low energy peak which previous studies have identified as the (localized) plasmon resonance. As expected, the absorption peak position of the plasmon resonance systematically redshifts as the length of the nanorod increases. However, trends in the CD and straightforwardly broadened CD spectra are more difficult to discern. We introduce the idea of an absolute value CD spectrum and show that broadening the lines results in a low energy peak that has not previously been reported. The peak position systematically redshifts as the length of the nanorod increases but over a significantly smaller range than that for the absorption spectrum.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Quantifying the Value of Technology and Policy Innovation in Water Resource Portfolios

Abstract Recent water infrastructure planning models demonstrate that explicitly accounting for hydrological changes in long‐term water planning reduces costs and increases system robustness. However, current models do not consider the effects of other changes occurring in the system over long time horizons, namely technology and policy innovation. By leveraging state‐of‐the‐art dynamic control techniques, we propose a suite of tools that explicitly relate hydrologic change, technology innovation, and policy interventions to system‐level water costs. We design robust and cost‐optimal strategies for water supply expansion under hydrological variability and hundreds of plausible innovation states, for example, treatment cost and diversification improvements, deployment times, and demand reduction campaigns. Our approach circumvents the need to pre‐assign probabilities to innovation scenarios and, instead, directly calculates the effects of technology, policy, and hydrology variations on system cost and planning strategies to identify avenues of impactful innovation. These tools can support technology development hubs, urban, state, and federal water planners in anticipating cost implications of technology and policy innovation at the local level, and prioritizing high‐impact innovation goals based on quantitative targets. Results for the case study of Santa Barbara, California identify high‐value innovation attributes for the city as well as combinations of innovation attributes across technologies and policies, and quantify their potential utility cost reductions.

13 HYDRO ENERGY↗
DOE OSTI2025

AI Improves the Accuracy, Reliability, and Economic Value of Continental‐Scale Flood Predictions

Accurate flood early warnings are critical to minimize damage and loss of life. Current large‐scale operational forecasting systems, however, have limited accuracy, description of uncertainty, and computational efficiency. While Artificial intelligence (AI) can address these limitations in principle, the accuracy and reliability of AI forecasts have thus far proven insufficient. Here we present a novel hybrid framework that integrates AI‐based machinery termed Errorcastnet (ECN) with the National Water Model (NWM) to showcase the potential of ensemble AI flood forecasts over the contiguous U.S. ECN boosts prediction accuracy four‐ to six‐fold across lead times of 1–10 days, while providing uncertainty quantification. It also outperforms Google's state‐of‐the‐art global AI model. ECN‐based forecasts offer superior economic value (up to four‐fold) for decision‐making as compared to those from NWM alone. ECN performs well in varied ecoregions, physiography, and land management conditions. The framework is computationally efficient, enabling national‐scale ensemble forecasts in minutes.

artificial intelligence↗
DOE OSTI2026

The Value of Forecasters‐in‐the‐Loop in Real‐Time Flood Forecasting in the Age of Machine Learning

Machine learning (ML) applications in hydrological forecasting are increasingly prevalent and show great potential. However, many previous studies have only evaluated performance through reanalysis or retrospective simulations compared to simplified baselines. This study provides the first assessment of ML performance against actual operational forecasting systems operated by the California Nevada River Forecast Center (CNRFC), which combines the Community Hydrologic Prediction System (CHPS) with forecasters-in-the-loop. Results demonstrate that forecasters-in-the-loop systems consistently outperform ML models in both general forecasts and flood alerting across lead times up to 96 hr, even when ML models use observed forcings, while CNRFC operational process relies on biased weather forecasts. Our analysis reveals that forecaster expertise maintains forecast reliability despite inaccurate precipitation inputs, with human-guided systems showing superior performance degradation characteristics at extended lead times. These findings highlight the irreplaceable value of human expertise in operational forecasting and caution against overstating current ML capabilities in real-world applications.

Tran, Vinh Ngoc [Univ. of Michigan, Ann Arbor, MI ↗
DOE OSTI2026

Quasi‐Steady State Supersaturation: Do High Values Derived From ESCAPE Represent Real High Supersaturations and the Potential for Condensational Invigoration?

Deep convective clouds were intensively sampled during the Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE) with coordinated flights of the NRC Convair-580 and SPEC Learjet. A total of 219 updraft core segments were sampled over coastal Texas and Louisiana under diverse meteorological conditions. Median updraft properties included widths of ∼1 km, velocities of 4.8 m s −1 , droplet number concentrations of ∼400 cm −3 , and liquid water contents of 0.9 g m −3 . The limitations of using the quasi-steady state approximation to derive supersaturations were explored. Supersaturation (S QSS ) estimated from in situ observations under a quasi-steady state assumption averaged 0.4% but occasionally exceeded 2%, with values >1% (high supersaturations) identified as statistical outliers. Two case studies illustrated the conditions linked to high supersaturations. In a storm over the Gulf, median core S QSS reached 2.46% in the developing stage compared to 2.17% in the mature stage under similar thermodynamic conditions. In a storm over coastal Louisiana, S QSS peaked near 11% within a 13.7-m s −1 updraft, accompanied by predominantly supercooled liquid droplets at −13°C and exceptionally low diameter concentrations of 0.29 mm cm −3 . Bootstrap analysis of all sampled cores showed that high supersaturations are most probable in cold and mixed-phase regimes with moderate to strong updrafts and are strongly influenced by vertical velocity and droplet number concentrations. In conclusion, while extreme supersaturations (∼10%) were rare, their occurrence underscores the need for targeted multiplatform observations to resolve their spatiotemporal variability and assess their potential role in deep convective invigoration.

54 ENVIRONMENTAL SCIENCES↗