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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Calcium-Facilitated Aggregation and Precipitation of the Uranyl Peroxide Nanocluster U 60 in the Presence of Na-Montmorillonite

The unique and diverse features of uranyl peroxide nanoclusters may contribute to the enhanced mobility of uranium in the environment. This study examines the sorption of the uranyl peroxide nanocluster [UO 2 (O 2 )(OH)] 60 60- (U 60 ) to Na-montmorillonite (SWy-2), plagioclase (anorthite), and quartz (SiO 2 ) as a function of time, U 60 concentration, and mineral concentration. SWy-2 was studied in both its untreated form as well as after two different pretreatments, denoted as partially treated SWy-2 and fully treated SWy-2. U 60 was removed (~99%) from solution in the presence of untreated and partially treated SWy-2. However, U 60 was not removed from suspensions containing anorthite, quartz, or fully treated SWy-2, even after several months. The removal of U 60 from suspensions containing untreated SWy-2 is promoted in part by the exchange of Li + counter-ions, normally weakly associated with U 60 in solution, for Ca 2+ ions naturally present in the clay. In solution, Ca 2+ ions induce the aggregation of nanoclusters, which precipitate on the surface of SWy-2. Ca-rich U 60 aggregates associated with SWy-2 were identified and characterized by scanning electron microscopy with energy dispersive spectroscopy, Raman spectroscopy, and X-ray photoelectron spectroscopy. This research enhances our understanding of the molecular-scale processes controlling U 60 behavior at the mineral–water interface.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2019

Trace Element Mass Flow Rates from U.S. Coal Fired Power Plants

Trace elements (TEs) exit coal-fired power plants (CFPPs) via solid, liquid, and gaseous waste streams. Estimating the TE concentrations of these waste streams is essential to selecting pollution controls and estimating emission reduction benefits. Our report presents a generalizable mass balance model for estimating TE mass flow rates in CFPP waste streams and evaluates model accuracy for the U.S. coal fleet given current data constraints. We stochastically estimate, using a bootstrapping approach, the 2015 plant-level mass flow rates of Hg, Se, As, and Cl to solid, liquid, and gas phase waste streams by combining publicly available data for combusted coal TE concentrations with estimates of TE partitioning within installed air pollution control processes. When compared with measured and reported data on TE mass flow rates, this model generally overestimates masses by 30–50%, with larger errors for Hg. The partitioning estimates are consistent for Se, As, and Cl removal from flue gas, but tend to underestimate Hg removal. While our model is suitable for first-order estimates of TE mass flows, future work to enhance model performance should focus on collecting and using new data on TE concentrations in the coal blend, where data quality is the weakest.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

Development and Validation of a Dynamic Response Model for a Cold Flow Circulating Fluidized Bed

A dynamic response model has been created of the Cold Flow Circulating Fluidized Bed at NETL in Morgantown, WV. The model is considered dynamic, as opposed to steady state, because it is used to predict the transient responses of gas and solids flows throughout the unit as process conditions vary. The model was built in ProTrax with Advanced Continuous Simulation Language (ACSL) custom code. Dynamic experiments, varying both gas and solids flows, in the CFB unit have been used to validate the accuracy of the model. The advantage of this model is its utility in predicting gas hold up and solids flow throughout the unit during transitions of process conditions. Accurate predictions of these phenomena are important in process control and optimization. The dynamic experiments used in validating the model include modulations of the system pressure, move air (solids flow), and riser gas velocity with step and sinusoidal changes.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2019

Molecular Dynamics Simulations of the Adsorption of Phthalate Esters on Smectite Clay Surfaces

The partitioning of organic contaminants between water and solid surfaces is a key process controlling their fate and transport in natural environments. A novel methodology was developed to predict the adsorption of organic contaminants by smectite clay minerals (high specific surface area adsorbents abundant in natural soils) using molecular dynamics (MD) simulations. The methodology models a stack of flexible Ca- montmorillonite lamellae in direct contact with a bulk aqueous reservoir and uses the metadynamics technique to facilitate the exploration of the free energy landscape. The methodology was tested and validated in the case of six phthalate esters, widely used chemical plasticizers with endocrine disrupting properties. Simulation predictions reveal strong phthalate adsorption, especially for the larger and more hydrophobic phthalates. Predicted partition coefficients (K d values) are consistent with collected batch experimental data. Adsorption was observed on both the exterior basal surfaces and within the interlayer nanopore, with phthalate molecules predominately adopting a flat orientation on the clay surface. Intercalation was also detected in complementary X-ray diffraction (XRD) experiments. A strong inverse relationship between extent of adsorption and clay surface charge density was observed, as phthalate molecules preferentially occupied the more hydrophobic uncharged patches on each surface. Detailed analysis of the free energy of adsorption revealed that phthalate affinity for the clay surface results from a small favorable van der Waals contribution and a large favorable entropic contribution. Overall, this research demonstrates the substantial affinity of smectite clays for phthalate esters and establishes a computational methodology capable of predicting the water-clay partition coefficients of organic contaminants, a key parameter in environmental fate and transport models.

36 MATERIALS SCIENCE↗
DOE OSTI2019

P-Mart: Interactive Analysis of Ion Abundance Global Proteomics Data

The use of mass-spectrometry-based techniques for global protein profiling of biomedical or environmental experiments has become a major focus in research centered on biomarker discovery; however, one of the most important issues recently highlighted in the new era of omics data generation is the ability to perform analyses in a robust and reproducible manner. This has been hypothesized to be one of the issues hindering the ability of clinical proteomics to successfully identify clinical diagnostic and prognostic biomarkers of disease. P-Mart (https://pmart.labworks.org) is an interactive web-based software environment that enables domain scientists to perform quality-control processing, statistics, and exploration of large-complex proteomics data sets without requiring statistical programming. P-Mart is developed in a manner that allows researchers to perform analyses via a series of modules, explore the results using interactive visualization, and finalize the analyses with a collection of output files documenting all stages of the analysis and a report to allow reproduction of the analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Retaining large and adjustable elastic strains of kilogram-scale Nb nanowires [Better Superconductor by Elastic Strain Engineering: Kilogram-scale Free-Standing Niobium Metal Composite with Large Retained Elastic Strains]

Crystals held at ultrahigh elastic strains and stresses may exhibit exceptional physical and chemical properties. Individual metallic nanowires can sustain ultra-large elastic strains of 4-7%. However, retaining elastic strains of such magnitude in kilogram-scale nanowires is challenging. Here, we find that under active load, ~5.6% elastic strain can be achieved in Nb nanowires in a composite material. Moreover, large tensile (2.8%) and compressive (-2.4%) elastic strains can be retained in kilogram-scale Nb nanowires when the composite is unloaded to a free-standing condition. It is then demonstrated that the retained tensile elastic strains of Nb nanowires significantly increase their superconducting transition temperature and critical magnetic fields, corroborating ab initio calculations based on BCS theory. This free-standing nanocomposite design paradigm opens new avenues for retaining ultra-large elastic strains in great quantities of nanowires and elastic-strain-engineering at industrial scale.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Designing MOFs-Derived FeS 2 @Carbon Composites for High-Rate Sodium Ion Storage with Capacitive Contributions

We present that sodium-ion batteries suffer the disadvantages of poor rate performance and cycling stability due to its sluggish sodiation kinetics. A rational design strategy for both materials compositions and structures has been proposed to meet these challenges. Herein, a triple-component composite derived from metal organic frameworks, comprising FeS 2 , nitrogen sulfur co-doped porous carbon, and reduced graphene oxide (FeS 2 @NSC/G), has been successfully synthesized. With the capacities contributions from different sodium storage routes (diffusion-controlled processes and surface capacitive processes) at varies rate conditions, it is aiming to make full use of each component in the electrode composite and their unique porous structures. Expected electrode properties have been achieved and related electrochemical could behaviors have also been investigated. Finally, the strategy would present a promising thought for composites design, which enhance high-rate electrochemical energy storage performances.

25 ENERGY STORAGE↗
DOE OSTI2026

Biopolymer-Templated Titania Film Formation for Nanostructured Coatings Revealed by Machine Learning-Supported Time-Resolved Analysis

This study presents a machine learning approach to derive the film formation of biopolymer-templated titania nanostructures during spray deposition, in combination with in situ grazing-incidence small-angle X-ray scattering (GISAXS). A neural network trained on synthetic GISAXS data directly predicts domain-size distributions from experimental two-dimensional scattering patterns, capturing the full kinetics of nanostructure evolution with high temporal resolution. The predictions reveal hierarchical size distributions and periodic growth features, consistent with layer-by-layer spray deposition and validated by complementary scanning electron microscopy (SEM) imaging. Quantitative comparison with conventional parametric GISAXS fits shows good qualitative agreement, with systematic differences explained by domain-shape assumptions and resolved by applying a geometric scaling factor. Simulated SEM-like surfaces derived from neural network outputs reproduce the porous, foam-like nanoscale morphology observed experimentally, reinforcing the method’s credibility. This integrated approach enables real-time, nondestructive, statistically averaged monitoring of bulk nanostructure development in functional coatings, offering a scalable methodology to accelerate the characterization and process control of sustainably manufactured nanostructured titania films for energy-related applications such as photocatalysis and photovoltaics.

Heger, JulianEliah↗
DOE OSTI2026

Self-Assembly Driven Microlithography via Near-Infrared Light Activation

Current vat photopolymerization (VP) relies on UV or visible light to start the rapid crosslinking of liquid photocurable resins into 3D-printed structures. Here, we develop a self-assembly-driven photopatterning approach to photothermally generate polymeric solids by combining thermoplasmonic nanoparticles and thermoresponsive polymers, in which near-infrared (NIR) light activates thermoplasmonic heating of nanoparticles, triggering the irreversible self-assembly of thermoresponsive polymers into insoluble mesoglobules. A small amount of thermal initiator and crosslinker leads to irreversible self-assembly of polymer nanocomposites. NIR light offers deeper penetration and reduced scattering compared to UV, enabling more uniform curing of thicker or filled materials and expanded process control for composites or opaque systems. Thermoplasmonic heat generation is achieved using surface-modified gold nanorods (AuNRs) with a longitudinal localized surface plasmon resonance peak in the NIR region. Key variables such as polymer composition, molecular weight, physical interactions at the nanoparticle–polymer interface, which can be tuned by surface functionalization, AuNR concentration, and pH can be used to tailor the assembly behavior of these systems, including photothermal effect, flocculation, and cloud point temperature, and the mechanical properties of the final structures. Collectively, these results highlight a platform for photothermally-driven microlithography of polymer solids with diverse, tunable macroscopic properties, enabled by low-energy NIR light-activated self-assembly.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Electrochemical Nutrient Recovery for the Food–Energy–Water Nexus at Municipal Wastewater Facilities: Multivariate Analyses of Seasonal Sampling and Reactor Performance

Digester-equipped municipal wastewater facilities generate recycle streams with high nutrient loads that increase energy consumption and can cause environmental pollution. The reduction of these loads through electrochemical nutrient recovery (ENR) could enhance the food–energy–water nexus by producing fertilizer (struvite). This study investigated the recovery process through a 1 year sampling of recycle streams and the implementation of nutrient recovery. Time series analyses showed that P (as orthophosphate) concentration was time-variant in digester effluent streams, while N (as ammonia) concentration was time-variant in only the aerobic system. Furthermore, these two nutrient concentrations did not correlate in any of the recycle streams. Subsequent multivariate screening analyses identified anode type, NH 4 + concentration, cathodic potential, P concentration, and temperature as most significant for ENR. Finally, the optimum conditions of cathodic potential, anode area-to-volume ratio, and temperature applied to a real recycle stream resulted in 95% P recovery with 0.03 kWh/kg P. This energy consumption is significantly lower than process energy for conventional P fertilizers (1.1 kWh/kg P) and chemical recovery processes at scale (1.7–12.9 kWh/kg P). Overall, this study recommended specific process controls for nutrient recovery, expanded the variables evaluated for ENR, and demonstrated the ability to significantly impact energy demand associated with P-based fertilizers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Real-Time KMC Simulation of Vacancy-Mediated Intermixing in Au@Ag Octahedral Core–Cubic Shell Nanocrystals with Ab Initio-Guided Kinetics

Utilization of core–shell rather than monometallic nanocrystals (NCs) facilitates fine-tuning of NC properties for applications. However, compositional evolution via intermixing can degrade these properties prompting recent experimental studies. We develop an atomistic-level stochastic model for vacancy-mediated intermixing exploiting a formalism which allows incorporation at an ab initio density functional theory level of not just the thermodynamics of vacancy formation, but also relevant diffusion barriers for a vast number of possible local environments (in the core and in the shell, at the interface, and in the intermixed phase). This facilitates a predictive treatment and comprehensive understanding of intermixing on the relevant time scale (e.g., 10 1 –10 3 s). In contrast, previous modeling at the atomistic level utilized only unrealistic generic prescriptions of barriers or employed simplified continuum treatments. For Au@Ag octahedral core–cubic shell NCs, our modeling not only captures the experimentally observed rate or time scale for intermixing of ~100 s at 450 °C for 60 nm NCs, but also elucidates the underlying rate controlling processes and the effective intermixing barrier.

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

Development of a UiO-Type Thin Film Electrocatalysis Platform with Redox-Active Linkers

Metal-organic frameworks (MOFs) as electro- catalysis scaffolds are appealing due to the large concentration of catalytic units that can be assembled in three dimensions. To harness the full potential of these materials, charge transport to the redox catalysts within the MOF has to be ensured. Here in this paper, we report the first electroactive MOF with the UiO/PIZOF topology (Zr(dcphOH-NDI)), i.e., one of the most widely used MOFs for catalyst incorporation, by using redox-active naphthalene diimide-based linkers (dcphOH-NDI). Hydroxyl groups were included on the dcphOH-NDI linker to facilitate proton transport through the material. Potentiometric titrations of Zr(dcphOH-NDI) show the proton-responsive behavior via the -OH groups on the linkers and the bridging Zr-μ 3 -OH of the secondary building units with pK a values of 6.10 and 3.45, respectively. When grown directly onto transparent conductive fluorine-doped tin oxide (FTO), 1 μm thin films of Zr(dcphOH-NDI)@FTO could be achieved. Zr(dcphOH-NDI)@FTO displays reversible electrochromic behavior as a result of the sequential one-electron reductions of the redox-active NDI linkers. Importantly, 97% of the NDI sites are electrochemically active at applied potentials. Charge propagation through the thin film proceeds through a linker-to-linker hopping mechanism that is charge-balanced by electrolyte transport, giving rise to cyclic voltammograms of the thin films that show characteristics of a diffusion-controlled process. The equivalent diffusion coefficient, D e , that contains contributions from both phenomena was measured directly by UV/vis spectroelectrochemistry. Using KPF 6 as electrolyte, De was determined to be D e (KPF 6 ) = (5.4 ± 1.1) × 10 -11 cm 2 s -1 , while an increase in countercation size to n-Bu 4 N + led to a significant decrease of D e by about 1 order of magnitude (D e (n-Bu 4 NPF 6 ) = (4.0 ± 2.5) × 10 -12 cm 2 s -1 ).

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

A Small Temperate Lake in the 21st Century: Dynamics of Water Temperature, Ice Phenology, Dissolved Oxygen, and Chlorophyll a

It is unclear how small temperate lakes will evolve physically and biologically in the whole water column under future climate because previous modeling studies usually focused on only one or two physical or biological state variables in the surface waters. To fill this gap, we used a well-validated lake biogeochemistry model driven with different climate scenarios to predict the dynamics of ice phenology, water temperature, dissolved oxygen (DO) and chlorophyll in a small Canadian temperate lake during the 21st century, considering the influence of catchment hydrology. We find that the ice season and ice thickness of the lake would shrink substantially, resulting in a positive energy feedback between climate and the lake. Due to the reduced heat diffusion and water mixing, the dynamics of water temperature in surface waters and deep waters are considerably different, with surface waters warmed dramatically but deep waters muted to warming. The lake DO concentrations would be depleted by warming in the whole column but the controlling processes are depth dependent. The chlorophyll concentration in the lake is inertia to climate change, mainly due to the mismatch of the timings of peak solar radiation and thermal and nutrient optima. Our analysis indicates that the influence of catchment hydrology is large on the dynamics of DO, but not on other state variables we have examined. Finally, this study suggests that small temperate lakes could be sensitive to climate change but their physical and biological responses could be diverse.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Soil Organic Matter Temperature Sensitivity Cannot be Directly Inferred From Spatial Gradients

Developing and testing decadal-scale predictions of soil response to climate change is difficult because there are few long-term warming experiments or other direct observations of temperature response. As a result, spatial variation in temperature is often used to characterize the influence of temperature on soil organic carbon (SOC) stocks under current and warmer temperatures. This approach assumes that the decadal-scale response of SOC to warming is similar to the relationship between temperature and SOC stocks across sites that are at quasi steady state; however, this assumption is poorly tested. We developed four variants of a Reaction-network-based model of soil organic matter and microbes using measured SOC stocks from a 4,000-km latitudinal transect. Each variant reflects different assumptions about the temperature sensitivities of microbial activity and mineral sorption. All four model variants predicted the same response of SOC to temperature at steady state, but different projections of transient warming responses. The relative importance of Q max , mean annual temperature, and net primary production, assessed using a machine-learning algorithm, changed depending on warming duration. When mineral sorption was temperature sensitive, the predicted average change in SOC after 100 years of 5 °C warming was –18% if warming decreased sorption or +9% if warming increased sorption. When microbial activity was temperature sensitive but mineral sorption was not, average site-level SOC loss was 5%. Here, we conclude that spatial climate gradients of SOC stocks are insufficient to constrain the transient response; measurements that distinguish process controls and/or observations from long-term warming experiments, especially mineral fractions, are needed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Achievements and Prospects of Global Broadband Seismographic Networks After 30 Years of Continuous Geophysical Observations

Global seismographic networks (GSNs) emerged during the late nineteenth and early twentieth centuries, facilitated by seminal international developments in theory, technology, instrumentation, and data exchange. The mid- to late-twentieth century saw the creation of the World-Wide Standardized Seismographic Network (1961) and International Deployment of Accelerometers (1976), which advanced global geographic coverage as seismometer bandwidth increased greatly allowing for the recording of the Earth's principal seismic spectrum. The modern era of global observations and rapid data access began during the 1980s, and notably included the inception of the GEOSCOPE initiative (1982) and GSN (1988). Through continual improvements, GEOSCOPE and the GSN have realized near-real time recording of ground motion with state-of-art data quality, dynamic range, and timing precision to encompass 180 seismic stations, many in very remote locations. Data from GSNs are increasingly integrated with other geophysical data (e.g., space geodesy, infrasound and Interferometric Synthetic Aperture Radar). Globally distributed seismic data are critical to resolving crust, mantle, and core structure; illuminating features of the plate tectonic and mantle convection system; rapid characterization of earthquakes; identification of potential tsunamis; global nuclear test verification; and provide sensitive proxies for environmental changes. As the global geosciences community continues to advance our understanding of Earth structure and processes controlling elastic wave propagation, GSN infrastructure offers a springboard to realize increasingly multi-instrument geophysical observatories. Here, we review the historical, scientific, and monitoring heritage of GSNs, summarize key discoveries, and discuss future associated opportunities for Earth Science.

58 GEOSCIENCES↗
DOE OSTI2022

Formation Process of Particles and Cloud Condensation Nuclei Over the Amazon Rainforest: The Role of Local and Remote New-Particle Formation

Understanding the formation processes of particles and cloud condensation nuclei (CCN) in pristine environments is a major challenge in accurately assessing anthropogenic radiative forcing. Here, using a state-of-the-art model that systematically simulates the chemical processes controlling new-particle formation (NPF) and multi-scale chemical transport, we find that NPF contributes ~90% of the particle number and ~80% of the CCN at 0.5% supersaturation (CCN0.5%) in the pristine Amazon boundary layer during the wet season. The corresponding contributions are only ~30% and ~20% during the dry season because of prevalent biomass burning. In both seasons, about half of the NPF-induced particles and ~85% of the NPF-induced CCN0.5% in the boundary layer originate from the long-range transport of new particles formed hundreds to thousands of kilometers away. Moreover, about 50–65% of the NPF-induced particles and 35–50% of the NPF induced CCN0.5% originate from the downward transport of new particles formed in the free troposphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Impact of Inherited Morphology on Sandbar Migration During Mild Wave Seasons

Sandbars are ubiquitous morphologic features found in the nearshore environment throughout the world, yet predictive capabilities of their evolution remain limited. In order to provide new insights on the relevant processes controlling sandbar morphodynamics, this study uses a 41-year record of 637 monthly cross-shore profiles from Duck, North Carolina, USA, to derive complex empirical orthogonal functions representative of the two dominant modes of sandbar migrations: offshore and onshore propagation. Interference of these two modes produces commonly observed sandbar states. While mild wave energies are traditionally assumed to drive onshore sandbar migration, the offshore mode is repeatedly seen to dominate sandbar migration in mild wave seasons following anomalously high late-winter wave energy and when the inherited morphology is composed of a single bar or terrace, as opposed to a more common two-bar state. A data-derived conceptual model is presented synthesizing the effect of antecedent morphology and wave climate chronology on interannual trends in net offshore sandbar migration.

58 GEOSCIENCES↗
DOE OSTI2023

The Role of In-Cloud Wet Removal in Simulating Aerosol Vertical Profiles and Cloud Radiative Forcing

Among the physical processes controlling aerosol vertical profiles, in-cloud wet removal is of utmost importance while its representation in global climate models (GCMs) is crude. In this study, we implement into the Community Atmosphere Model version 6 (CAM6) a physically based aerosol wet removal parameterization scheme that explicitly treats aerosol activation, removal and resuspension. Evaluation against in-situ observations shows that the default scheme substantially overestimates the upper tropospheric black carbon (BC) and sea salt mass. Our physically based scheme reduces BC and sea salt mass by a factor of 10 and 1,000, respectively, in better agreement with observations. Also, the new scheme slightly increases number of aerosol particles between 12 nm and 4.8 μm in diameter, thereby mitigating the aerosol number underestimation in the default scheme. Our new scheme reduces the overestimation of coarse-mode aerosol (0.5–4.8 μm) number. Overall, the aerosol property changes (mass decrease and number increase) reduce the cloud condensation nuclei (CCN) concentration at low supersaturation (i.e., 0.02% and 0.1%), and increase CCN at high supersaturations (i.e., 0.5% and 1%). Consequently, the global annual mean cloud liquid water path increases by 1.89 g m -2 and the ice water path increases by 0.51 g m -2 . The global annual mean shortwave, longwave, and net cloud radiative forcing change by -1.06, 0.57, and -0.48 W m -2 , respectively. Further improvement is needed to reflect the real physics that the removal efficiencies for aerosol mass and number are disproportionate and to advect cloud-borne (activated) aerosols for a complete aerosol lifecycle.

54 ENVIRONMENTAL SCIENCES↗