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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Conversion of Waste PET Plastic to Aramid Fiber

A three-step synthesis was used to convert waste polyethylene terephthalate (PET) into the high value polymer, poly-para-phenylene terephthalamide (PPTA), used in the production of high strength aramid fiber, such as Kevlar. Improvements to the polymerization reaction by addition of calcium chloride to the solvent, N-methyl-2-pyrrolidone (NMP), and rigorous anhydrous conditions enabled the production of a PET-derived PPTA with a 4.15 dL/g inherent viscosity in sulfuric acid that is amenable to fiber spinning. PPTA fibers were spun using a wet spinning apparatus under varied process parameters to assess their impact on fiber surface morphology, diameter, and the mechanical properties of the fibers. Select fibers were subjected to a post-spinning heat treatment at 150 °C , which improved the tensile strength and modulus by 100% and 30%, respectively, relative to the as-spun fibers. Techno-economic and life cycle analyses were conducted to evaluate the economic feasibility and the life-cycle greenhouse gases (GHG) emissions of the approach. In conclusion, the results suggest the potential for up to a 30% cost reduction, and comparable GHG emissions against conventional petroleum-based processes.

Lifecycle Analysis↗
DOE OSTI2025

Glass-Bonded Monazite Waste Forms for Lanthanide and Actinide Immobilization: From Theoretical Design to Scale-Up Production and Characterization

The development of nuclear waste forms for both existing and future nuclear wastes is critical to ensuring global environmental safety. This study focuses on waste management from molten salt reactors, where fuel exists in a salt form and could be processed in real time for the removal of neutron poisons such as xenon isotopes (e.g., 135 Xe) and rare earth elements (REEs, e.g., 149 Sm). To ensure safe, stable, and long-term disposal in geological repositories, REEs must be incorporated into a durable waste form. Iron-phosphate glasses are a promising candidate due to their low melting points, high chemical durability, and their ability to incorporate high concentrations of REEs. In this study, we successfully prepared iron-phosphate glass waste forms with high Nd loadings (up to 37 mass %) in batch sizes ranging from small (23 g) to large (1600 g). The resulting materials contained up to 75 mass % NdPO 4 , contributing to their mechanical resilience and exceptional chemical durability. These findings highlight the potential of iron-phosphate glasses as high-efficiency, chemically durable waste forms and demonstrate the successful transition from theoretical design to scaled-up production.

amorphous materials↗
DOE OSTI2026

Delamination of Multilayer Plastic Films to Recover Polyethylene with Favorable Mechanical Properties

Multilayer plastic films play a critical role in packaging, with each polymer layer contributing specific properties to the multilayer film. Multilayer plastic films are not currently recyclable due to the bound polymers. With multilayer film production of about 20 million metric tons in 2024 and rising, endof- life treatment becomes pressing. This work presents a scalable solvent-based delamination recycling process that is applied to commercial postindustrial multimaterial films to unbind the materials within a multilayer film by dissolving only the adhesive layer and recover polyethylene (PE) as an intact solid film. Solventbased delamination is a simple process that allows the complete recovery of materials and solvents used in the process. The delaminating solvent, 88% formic acid in water, induces delamination of PE/PEI/PET and PE/PU/PET films at 70 °C in under an hour. Recovered PE has no contamination detected by Fourier transform infrared spectroscopy and mechanical properties on par with those of virgin resin. The recovery of high-quality solid PE film fit for reprocessing, at low operating temperatures and with closed-loop solvent reuse, promotes delamination as a low energy consumption and environmentally friendly recycling process. PE recovered from delamination can be reused in equivalent products, promoting circularity of multimaterial films.

chemical recycling↗
DOE OSTI2025

Interactions of Polar and Nonpolar Groups of Alcohols in Zeolite Pores

Understanding the quantitative interactions among zeolite pore walls, Bro̷nsted acid sites, and molecules with both polar and nonpolar regions is essential for scoping out the potential of zeolites as sorbents and catalysts. Purely siliceous zeolites (MFI and Beta in the present study) are hydrophobic, whereas those containing aluminum are considered hydrophilic, preferentially adsorbing organic molecules even in aqueous environments. To characterize these interactions, we use primary alcohols of increasing molecular weight, quantifying their specific interactions in the confined pore space of the alkyl (CH x ) and OH groups. Three types of interactions were identified: (i) alkyl CH x groups interacting with the zeolite pore walls (approximately 10 kJ mol −1 per carbon), (ii) alcohol OH groups interacting with the pore walls (30−35 kJ mol −1 ), and (iii) alcohol OH groups interacting with Bro̷nsted acid sites (37 kJ mol −1 ). All three interactions were well mirrored by computational simulations. The contribution of the alkyl CH x groups was inferred from the incremental increase in sorption enthalpy with increasing molecular weight; the interaction strength of the OH groups was determined by extrapolating the global adsorption enthalpy of the alcohols to a hypothetical OH group without an alkyl group. This value was identical to the adsorption enthalpy of water. The experiments demonstrated that only water has an adsorption enthalpy on zeolite pore walls lower than its condensation enthalpy (30−35 kJ mol −1 vs 45 kJ mol −1 ), limiting the concentration of water that can be adsorbed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Unravelling the Stability Stressors of Atomically Dispersed Fe–N–C Oxygen Reduction Catalysts

Enhancing the catalytic stability of Fe–N–C catalysts for cathodic oxygen reduction in proton-exchange membrane fuel cells (PEMFCs) necessitates an in-depth understanding of their degradation mechanisms. Here, this study identifies key stressors affecting the stability of Fe–N–C catalysts, specifically acidic environment, oxygen (O 2 ), and reactive oxygen species (ROS). Through ex situ/operando experiments, we show that the oxidation of local carbon by acidic environment + O 2 + ROS, along with the demetalation of catalytic FeN x C y sites by O 2 or O 2 + ROS, is the primary factor responsible for the initial fast degradation of Fe–N–C catalysts. The demetalation of FeN x C y sites, influenced by O 2 , in particular by O 2 + ROS, leads to the subsequent gradual degradation of Fe–N–C. Notably, FeN 4 C 12 -type active sites are more susceptible to demetalation than FeN 4 C 10 -type sites in O 2 or O 2 + ROS. Our findings indicate that, besides constructing more stable FeN x C y sites, preventing local carbon oxidation and scavenging of ROS are all critical for maintaining the stability of Fe–N–C catalysts.

Xie, Xiaohong [Pacific Northwest National Laborato↗
DOE OSTI2025

Assessment of Extinction‐, Satellite‐, and Model‐Based Vertical Cloud Condensation Nuclei (CCN) Retrieval Methods Using Airborne CCN Measurements Over the Southern Great Plains

Abstract Accurate estimates of the vertical profile of cloud condensation nuclei (CCN) concentration are crucial to better quantify aerosol‐cloud interactions. We assessed the correlation between the vertical CCN concentrations obtained from extinction‐, satellite‐, and model‐based retrieval methods and airborne CCN concentrations collected at 0.24% supersaturation within the 3, 9, 27, and 81 km regions centered over the U.S. Department of Energy's Atmospheric Radiation Measurement User Facility Southern Great Plains (SGP) site during the spring and summer of 2016. The extinction profiles at a wavelength 355 nm were provided by the ground‐based Raman lidar. Our analysis showed moderate correlation between dry‐corrected extinction and airborne CCN data. We found the retrieved number concentration of CCN (RNCCN) method showed regression best‐fit slopes close to unity and consistent prediction errors for the majority of the data. The Lenhardt et al. (2023, https://doi.org/10.5194/amt‐16‐2037‐2023 ) method showed similar conclusions but only during spring, whereas the Mamouri and Ansmann (2016, https://doi.org/10.5194/acp‐16‐5905‐2016 ) method showed poor correlation. The Shinozuka et al. (2015, https://doi.org/10.5194/acp‐15‐7585‐2015 ) satellite‐based method exhibited reasonable agreement during summer but poor correlation during periods where both high (∼1,400 #/cm 3 ) and low (∼50 #/cm 3 ) airborne CCN concentrations were observed. The Copernicus Atmosphere Monitoring Service reanalysis modeled 3‐D CCN data set showed a moderate to weak positive correlation but performed poorly at high airborne CCN concentrations. Our analysis suggests the extinction‐based RNCCN method performed better than other methods across most observation periods under the diverse meteorological conditions observed at the SGP site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

E3SM‐Arctic: Regionally Refined Coupled Model for Advanced Understanding of Arctic Systems Interactions

Earth system models are essential tools for climate projections, but coarse resolutions limit regional accuracy, especially in the Arctic. Regionally refined meshes (RRMs) enhance resolution in key areas while maintaining computational efficiency. This paper provides an overview of the United States (U.S.) Department of Energy's (DOE's) Energy Exascale Earth System Model version 2.1 with an Arctic RRM, hereafter referred to as E3SMv2.1-Arctic, for the atmosphere (25 km), land (25 km), and ocean/ice (10 km) components. We evaluate the atmospheric component and its interactions with land, ocean, and cryosphere by comparing the RRM (E3SM2.1-Arctic) historical simulations (1950–2014) with the uniform low-resolution (LR) counterpart, reanalysis products, and observational data sets. The RRM generally reduces biases in the LR model, improving simulations of Arctic large-scale mean fields, such as precipitation, atmospheric circulation, clouds, atmospheric river frequency, and sea ice thickness. However, it introduces a seasonally dependent surface air temperature bias, reducing the LR cold bias in summer but enhancing the LR warm bias in winter, which contributes to the underestimated winter sea ice area and volume. Radiative feedback analysis shows similar climate feedback strengths in both model configurations, with the RRM exhibiting a more positive surface albedo feedback and contributing to a stronger surface warming than LR. These findings underscore the importance of high-resolution modeling for advancing our understanding of Arctic climate changes and their broader global impacts, although some persistent biases appear to be independent of model resolution at 10–100 km scales.

Energy Exascale Earth System Model (E3SM)↗
DOE OSTI2026

Hierarchical Testing of a Hybrid Machine Learning‐Physics Global Atmosphere Model

Machine learning (ML)-based models have demonstrated high skill and computational efficiency, often outperforming conventional physics-based models in weather and subseasonal predictions. While prior studies have assessed their fidelity in capturing synoptic-scale atmospheric dynamics, their performance across timescales and under out-of-distribution forcing, such as +3K or +4K uniform-warming forcings, and the sources of biases remain elusive, to establish the model's reliability for Earth science. Here, we design three sets of experiments targeting synoptic-scale phenomena, interannual variability, and out-of-distribution uniform-warming forcings. We evaluate the Neural General Circulation Model (NeuralGCM), a hybrid model integrating a dynamical core with ML-based component, against observations and physics-based Earth system models (ESMs). At the synoptic scale, NeuralGCM captures the evolution and propagation of extratropical cyclones with performance comparable to ESMs. At the interannual scale, when forced by El Niño-Southern Oscillation sea surface temperature (SST) anomalies, NeuralGCM successfully reproduces associated teleconnection patterns but exhibits deficiencies in capturing nonlinear response. Under out-of-distribution uniform-warming forcings, NeuralGCM simulates similar responses in global-average temperature and precipitation and reproduces large-scale tropospheric circulation features similar to those in ESMs. Notable weaknesses include overestimating the tracks and spatial extent of extratropical cyclones, biases in the teleconnected wave train triggered by tropical SST anomalies, and differences in upper-level warming and stratospheric circulation responses to SST warming compared to physics-based ESMs. The causes of these weaknesses were explored. Despite the noted weaknesses, NeuralGCM reproduces responses across experiments reasonably and performs comparably to ESMs. By integrating a dynamical core with ML, NeuralGCM shows potential for developing ML-based ESMs.

global warming↗
DOE OSTI2025

Elevated Forest Canopy Loss After Wildfires in Moist and Cool Forests in the Pacific Northwest

Wildfire frequency, intensity, and rate of spread are increasing across the Western U.S, resulting in more severe ecosystem impacts. Significant tree mortality can occur years after fire events, but this has received little attention compared to the immediate tree loss during a fire. We overlapped forest cover loss data with burn severity maps in the U.S. Pacific Northwest and quantified the total and delayed forest canopy loss after fires. We found that wildfires resulted in total canopy loss fraction (CLF) of 84%, 53%, and 22% within 3 years in areas burned at high, moderate, and low severity, respectively. The delayed canopy loss accounted for approximately 1/3, 1/2, and 2/3 of the total canopy loss for high, moderate, and low severity burns. Delayed canopy loss was greater in moist and cool areas than in dry and warm areas, likely because tree species in wetter environments were less adapted to survive when fires did occur. Across all forests, delayed CLF doubled as temperature increased from the climatological mean to a hot anomaly and tripled as vapor pressure deficit increased from a wet anomaly to a dry anomaly. Fire impacts on forest ecosystems are likely to intensify under future climate scenarios as wildfires expand into areas that historically experienced infrequent fires. The impacts can also be exacerbated by more frequent compound extreme events, such as droughts, heatwaves, and fires. These findings highlight the urgent need for targeted forest management strategies, particularly in mesic forests, to mitigate future fire impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Upcycled high-strength aluminum alloys from scrap through solid-phase alloying

Although recycling secondary aluminum can lead to energy consumption reduction compared to primary aluminum manufacturing, products produced by traditional melt-based recycling processes are inherently limited in terms of alloy composition and microstructure, and thus final properties. To overcome the constraints associated with melting, we have developed a solid-phase recycling and simultaneous alloying method. This innovative process enables the alloying of 6063 aluminum scrap with copper, zinc, and magnesium to form a nanocluster-strengthened high-performance aluminum alloy with a composition and properties akin to 7075 aluminum alloy. The unique nanostructure with a high density of Guinier-Preston zones and uniformly precipitated nanoscale η‘/Mg(CuZn) 2 strengthening phases enhances both yield and ultimate tensile strength by >200%. By delivering high-performance products from scrap that are not just recycled but upcycled , this scalable manufacturing approach provides a model for metal reuse, with the option for on-demand upcycling of a variety of metallic materials from scrap sources.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Long-read RNA sequencing atlas of human microglia isoforms elucidates disease-associated genetic regulation of splicing

Microglia, the innate immune cells of the central nervous system, have been genetically implicated in multiple neurodegenerative diseases. Mapping the genetics of gene expression in human microglia has identified several loci associated with disease-associated genetic variants in microglia-specific regulatory elements. However, identifying genetic effects on splicing is challenging because of the use of short sequencing reads. Here, we present the isoform-centric microglia genomic atlas (isoMiGA), which leverages long-read RNA sequencing to identify 35,879 novel microglia isoforms. We show that these isoforms are involved in stimulation response and brain region specificity. We then quantified the expression of both known and novel isoforms in a multi-ancestry meta-analysis of 555 human microglia short-read RNA sequencing samples from 391 donors, and found associations with genetic risk loci in Alzheimer’s and Parkinson’s disease. We nominate several loci that may act through complex changes in isoform and splice-site usage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Organic molecules are deterministically assembled in variably inundated river sediments, but drivers remain unclear

Dissolved organic matter (DOM) is central to ecosystem function. A fundamental challenge is understanding the processes leading to variation in the chemistry of organic molecules that comprise DOM. Here we study these processes in variably inundated riverbed sediments, as an understudied, yet ubiquitous component of rivers. Using null-model approaches adopted from community ecology, we found that within-site variation in environmental conditions caused non-random (i.e., deterministic) shifts in DOM chemistry. Deterministic shifts were observed across diverse biomes, though the strength of determinism varied substantially. We found that the strength of determinism decreased with increasing sediment moisture, but in the form of a constraint space. Many systems fell below the upper constraint boundary, however. We propose a conceptual model based on our results and other publications in which DOM assemblages are hypothesized to be increasingly deterministic across the continuum from the river water column to saturated sediment pore spaces to unsaturated and dry soils/sediments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Eastward-shifting boreal summer intraseasonal oscillation amplifies North America heatwave and wildfire risks in warming climate

Boreal summer intraseasonal oscillation (BSISO) is a key component of tropical climate variability, characterized by eastward and northeastward propagation of organized convection across the Indo-Pacific region. BSISO influences weather and climate extremes through atmospheric teleconnections, but its future changes and related extremes remain unclear. Here, based on Coupled Model Intercomparison Project Phase 6, we find that under a high-emission scenario, BSISO convection will shift eastward by ~3° (~300 km) in 2065–2099, driven by moisture profile changes associated with sea surface temperature warming over central-to-eastern Pacific. This eastward-shifted BSISO convection, along with a northward expansion of the westerly jet, strengthens the BSISO teleconnections that extend into broader areas of North America. These changes will increase the BSISO-related heatwave risks by 23% and wildfire risks by 3.5 times over northern North America compared to present-day conditions. The findings underscore the amplification of BSISO’s influence on extreme risks of extreme weather, emphasizing the need for improved adaptation and mitigation strategies for future climates.

BSISO teleconnection↗
DOE OSTI2024

Adding labile carbon to peatland soils triggers deep carbon breakdown

Peatlands store vast amounts of carbon, with deep peat carbon remaining stable due to limited thermodynamic energy and transport. However, climate change-induced increases in labile carbon inputs could destabilize these stores. Here, we combined DNA stable isotope probing with stable isotope-assisted metabolomics employing a multi-platform approach to investigate microbial dynamics driving deep peat carbon degradation upon labile carbon (e.g., glucose) amendment. Our findings highlight the vulnerability of deep peat carbon, as glucose addition triggers the breakdown of older organic matter. By uniquely integrating these techniques, we identified active glucose metabolizers to specific microbial populations and mapped carbon flow through microbial networks, elucidating their role in priming recalcitrant carbon mineralization. This multi-omics approach offers crucial insights into how changing resources reshape the peatland microbiome, enhancing our understanding of deep carbon processing, and refining model parameterization to predict microbial responses and carbon cycle feedbacks under global change pressures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

More land is needed for solar and wind infrastructure under a high renewables scenario in the Western US by 2050

Expanding United States electricity infrastructure to meet growing demand could require extensive power plant development footprints and land use conversion, depending on the mix of generation types chosen. Understanding where future power plant sitings are likely to take place and identifying potential conflicts and land-use tradeoffs will be key to identifying feasible and affordable investments and evaluating regional planning coordination needs. Here we use an integrated modeling framework that combines capacity expansion planning, hourly grid operations, and geospatial techno-economic analysis to develop projections (2025-2050) of power plant sitings in the Western United States (US) at a 1 km 2 resolution for a business-as-usual scenario and a high renewables penetration scenario. We find that 30% more land will be needed in the high renewables scenario as compared to business-as-usual, and that 75% of that development is projected to be located within 10 km of natural areas.

Mongird, Kendall [Pacific Northwest National Labor↗