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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Role of Surface Hydroxyls and Lattice Oxygen in Governing Selectivity and Restructuring During Acetic Acid Conversion on Fe 3 O 4 (001)

Understanding the reactivity of carboxylic acids on metal oxide surfaces is critical for elucidating ketonization mechanisms relevant to biomass upgrading. Here, we investigate the adsorption and thermal decomposition of acetic acid (CH 3 COOH) on Fe 3 O 4 (001) using scanning tunneling microscopy (STM), temperature-programmed reaction spectroscopy (TPRS), and X-ray photoelectron spectroscopy (XPS). At room temperature, acetic acid adsorbs dissociatively to form ordered bidentate acetate (CH 3 COO) overlayer that lifts the (√2 × √2)R 45° surface reconstruction. TPRS reveals ketene (CH 2 CO) as the dominant product, along with CO, CO 2 , and H 2 O, the latter evolving via a Mars–van Krevelen (MvK) mechanism. Isotopic labeling shows preferential CO 2 formation from the carboxyl carbon and a more balanced CO/CO 2 ratio from the methyl carbon, suggesting distinct oxidation pathways. STM imaging reveals embedded acetate intermediates filling surface oxygen vacancies created in MvK steps. Upon product formation completion (~700 K), extensive surface etching is observed, with pits elongated along the octahedral Fe rows. Approximately 20% of the surface oxygen is removed, consistent with vacancy formation stoichiometry inferred from product distributions. These findings demonstrate that carboxylate-induced restructuring of Fe 3 O 4 (001) involves both surface healing and reduction processes, offering mechanistic insights relevant to ketonization and broader carboxylic acid chemistry on metal oxides.

acetic acid↗
DOE OSTI2025

Advanced All-Fluorinated Electrolytes for Extended Cycle Life and Stability of Li||SPAN Batteries

Achieving long-term stability and consistent capacity in lithium (Li) metal batteries with sulfurized polyacrylonitrile (SPAN) cathodes requires precisely engineered electrolytes to optimize interphase formation and redox reversibility. Here, this study presents 1,1-difluoro-2-(2-methoxyethoxy)ethane (DFE)-based localized high-concentration electrolytes (LHCEs), incorporating fluorinated components such as salt, solvating solvent, and diluent for improved electrode stability. Molecular dynamics simulations and surface analyses reveal that the DFE-LHCE with 1,2-bis(1,1,2,2-tetrafluoroethoxy)ethane (BTFEE) diluent produces uniform and robust interphase layers on both cathode and anode, enriched with inorganic species like LiF and Li 2 O. These properties lead to prolonged redox reversibility of the SPAN cathode, suppressed side reactions, and extended cycle life for Li||SPAN cells. Remarkably, DFE-BTFEE-LHCE enables Li||SPAN coin cells with an areal capacity of ∼7 mAh cm -2 for SPAN to retain 81.3% capacity after 200 cycles and pouch cells of 0.12 Ah with 8 mAh cm -2 of SPAN and lean electrolyte to maintain 96.4% capacity over 80 cycles. These findings pave the way for advancing Li||SPAN battery technologies.

25 ENERGY STORAGE↗
DOE OSTI2024

Water, Solute, and Ion Transport in De Novo-Designed Membrane Protein Channels

Biological organisms engineer peptide sequences to fold into membrane pore proteins capable of performing a wide variety of transport functions. Synthetic de novo-designed membrane pores can mimic this approach to achieve a potentially even larger set of functions. Here, in this work, we explore water, solute, and ion transport in three de novo designed β-barrel membrane channels in the 5–10 Å pore size range. We show that these proteins form passive membrane pores with high water transport efficiencies and size rejection characteristics consistent with the pore size encoded in the protein structure. Ion conductance and ion selectivity measurements also show trends consistent with the pore size, with the two larger pores showing weak cation selectivity. MD simulations of water and ion transport and solute size exclusion are consistent with the experimental trends and provide further insights into structure–function correlations in these membrane pores.

59 BASIC BIOLOGICAL SCIENCES↗
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 OSTI2025

Developing Fluorescence-Based Sensors to Support Rare Earth Element Separation

Rare earth elements (REEs) are essential to most renewable energy technologies. Unfortunately, as we transition to sustainable energy production, the demand for REEs is rapidly growing well beyond current rates of production. As a result, novel means of efficient, scalable, and easily adaptable methods for processing primary and recycle feedstocks are needed. Development and integration of sensors for highly selective in-line monitoring can support more efficient design and testing of such novel separation processes, as well as more cost-effective deployment of those separation flowsheets. Work here will explore the application of fluorescence spectroscopy, a highly sensitive and selective technique, to quantify multiple lanthanides in complex mixtures including known interferents or quenching agents. Results include identification of the optimal excitation wavelength and the limit of detection of various rare earth elements as well as the performance of data-science-based quantification approaches in streams where “unknowns” are present. Overall, the data science tools in conjunction with optical sensor data were able to quantify analytes in the presence of other lanthanides which can be anticipated in the actual industrial stream. Here we include characterization of lanthanides in a microfluidic device similar to those used in new process development. This study demonstrates the capability of utilizing fluorescence spectroscopy to quantify analytes in a complicated solution matrix, suggesting this is a successful approach for in-line monitoring to optimize the separation efficiency in an industrial stream.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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

Synergy in Materials: Leveraging Phosphosilicate Waste Forms for Electrochemical Salt Waste

Here, waste forms containing glassy and crystalline phosphate and silicate phases were produced to immobilize salt waste simulants from pyroprocessing and characterized by using Raman spectroscopy, Mössbauer spectroscopy, X-ray diffraction, scanning electron microscopy, heat capacity, and chemical durability measurements. In this work, a phosphosilicate waste form is presented to leverage the benefits of both borosilicate glasses and iron phosphate glasses. To improve waste loading, prior to immobilization, salt simulants were successfully dechlorinated using ammonium dihydrogen phosphate, mixed with a borosilicate frit (5–30 wt %) and Fe 2 O 3 , and vitrified. Additions of 2.5–15 wt % borosilicate glass (NBS3) improved normalized release rates for Cs relative to iron-phosphates without NBS3, resulting in chemical durabilities similar to high-level waste borosilicate glass reference materials. The release rates of the alkalis (i.e., Li, Na, K, Cs) were the lowest with the addition of 5 wt % NBS3. Although Sr was not specifically targeted in this study, evidence exists that it preferentially partitioned with Si to form an amorphous droplet phase within the iron phosphate glass matrix.

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

Systematic Mapping of Bacterial CRISPRa Systems for Synergistic Gene Activation Reveals Antagonistic Effects

CRISPR gene activation (CRISPRa) tools have shown great promise for bacterial strain engineering but often require customization for each intended application. Our goal is to create generalizable CRISPRa tools that can overcome previous limitations of gene activation in bacteria. In eukaryotic cells, multiple activators can be combined for synergistic gene activation. To identify potential effectors for synergistic activation in bacteria, we systematically characterized bacterial activator proteins with a set of engineered synthetic promoters. We found that optimal target sites for different activators could vary by up to 200 bases in the region upstream of the transcription start site (TSS). These optimal target sites qualitatively matched previous reports for each activator, but the precise targeting rules varied between different promoters. By characterizing targeting rules in the same promoter context, we were able to test activator combinations with each effector positioned at its optimal target site. We did not find any activator combinations that produced synergistic activation, and we found that many combinations were antagonistic. Furthermore, this systematic investigation highlights fundamental mechanistic differences between bacterial and eukaryotic transcriptional activation systems and suggests that alternative strategies will be necessary for strong bacterial gene activation at arbitrary endogenous targets.

CRISPR activation↗
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

How Flood Hazards in a Warming Climate Could Be Amplified by Changes in Spatiotemporal Patterns and Mechanisms of Water Available for Runoff

Prior research on climate change impacts on flooding has primarily focused on changes in extreme rainfall magnitudes, often neglecting snow processes and spatiotemporal storm patterns, such as hyetograph shapes and areal reduction factors (ARFs). This study examines projected changes in extreme water available for runoff (W) events in two snow-dominated basins in the western United States: the Yakima River Basin (YRB) in Washington State and the Walker River Basin (WRB) spanning the California-Nevada border. We analyze changes in W magnitudes, mechanisms, hyetograph shapes, and ARFs, and study their compounded impacts on flood hazard. Our findings suggest increased extreme W magnitudes across a large portion of the basins, with steeper or flatter hyetographs, and higher ARF values under the future climate. These changes are driven by a shift from seasonal snowmelt to more rain-on-snow events at higher elevations and by increased rainfall at lower elevations. We then use a single event-based rainfall-runoff model to estimate flood hazard changes based on extreme W magnitudes, hyetograph shapes, ARFs, and their compounded impacts. Our analysis reveals that focusing solely on the magnitude of changes in extreme W can significantly underestimate future flood hazards and uncertainties. Ignoring future changes in spatiotemporal patterns can underestimate future flood hazards by 63% and underestimate the uncertainty in future flood events by 18% in the WRB. These results underscore the necessity of incorporating spatiotemporal dynamics into future flood hazard assessments to provide a more accurate evaluation of potential impacts.

54 ENVIRONMENTAL SCIENCES↗
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 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

Decomposing a Compound Flood Event in an Urban Pacific Northwest Estuary: Primary Drivers and Projections for the Future

The Duwamish River Estuary (DRE) of Washington is prone to compound flooding during atmospheric river (AR) events. The processes contributing to such flooding (coastal and fluvial) have remained opaque to municipalities that are increasingly impacted. Here, we conduct a suite of coupled atmosphere-hydrology-ocean model simulations with varying forcing combinations (tide, surge, and/or river discharge) to identify the primary drivers of compound flooding during a recent AR event. We also test year 2,100 climate forcing to project how flooding and drivers may change in the future for the same event. We identify a clear distinction between dynamics in the downstream, engineered portion of the DRE compared to the upstream, “natural” river. Downstream, tides dominate water levels but contributions from storm surge and nonlinear tide-surge interaction elevate tide-only high waters from no flooding to major flooding. Upstream, total water levels during the event are ∼6 cm higher than downstream due to an increasing influence of river discharge over surge and tides. Notably, nonlinear surge-river and tide-river interactions act to reduce upstream water levels up to 50% compared to estimates which linearly sum tides, surge, and river, likely reducing flood vulnerability. Under two future climate scenarios: one with only sea level rise (SLR) and another with SLR plus atmospheric warming, we find little change in mechanism contributions to water levels. Expanded flooding in both cases is largely due to SLR, as a ∼50% increase to river discharge under the warming scenario has no impact downstream and marginally increases (∼3 cm) water level upstream.

atmospheric river↗
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 OSTI2024

Topological flat bands in a family of multilayer graphene moiré lattices

Moiré materials host a wealth of intertwined correlated and topological states of matter, all arising from flat electronic bands with nontrivial quantum geometry. A prominent example is the family of alternating-twist magic-angle graphene stacks, which exhibit symmetry-broken states at rational fillings of the moiré band and superconductivity close to half filling. Here, we introduce a second family of twisted graphene multilayers made up of twisted sheets of M- and N-layer Bernal-stacked graphene flakes. Calculations indicate that applying an electric displacement field isolates a flat and topological moiré conduction band that is primarily localized to a single graphene sheet below the moiré interface. Phenomenologically, the result is a striking similarity in the hierarchies of symmetry-broken phases across this family of twisted graphene multilayers. Our results show that this family of structures offers promising new opportunities for the discovery of exotic new correlated and topological phenomena, enabled by using the layer number to fine tune the flat moiré band and its screening environment.

Electronic properties and materials↗
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↗