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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Functionalized porous organic polymers as uranium nano-traps for efficient uranium extraction

Compositions are provided for efficient uranium extraction, for example from wastewater, seawater, or other water sources. The compositions can include a functionalized porous organic polymer functionalized with one or more uranium binding moieties, e.g. having a plurality of amidoxime or amidrazone groups covalently attached thereto. The compositions can include covalent organic frameworks, porous aromatic frameworks, and various porous organic polymers, especially those having a hierarchical pore size distribution over a range of pore sizes. The compositions can have functional groups such as amidoxime or an amidrazone covalently attached thereto. The hierarchical pore size distribution can be determined based upon at least 60% of the pore sizes in the range of pore sizes having a pore volume of at least 0.01 cm 3 g −1 in the pore size distribution at 77 K. Methods of making the compositions and methods of using the compositions are also provided.

Ma, Shengqian↗
DOE OSTI2019

Development of a Data-Derived Sooting Index Including Oxygen-Containing Fuel Components

Particulate matter (PM) emissions from spark-ignited engines, particularly those with direct injection, now exceed those of light-duty diesel engines equipped with diesel particle filters. Fuel chemistry is one of several interacting factors that determine the amount of PM produced during combustion. Understanding the relationship between fuel chemistry and PM emissions is therefore essential in identifying fuels with a lower tendency to form soot. However, existing predictive models have been shown to perform poorly when fuel blends include a large proportion of oxygenated molecules. In this study, we report a new analysis of the data from the EPAct V2 data set with the objective of developing an emission index that adequately handles the effects of oxygenate blending on vehicle and engine emissions. Our approach uses regularized linear regression to select the most important parameters in predicting normalized vehicle emissions as a function of fuel composition and bulk fuel properties. Interestingly, our data-derived metric reproduces a similar functional form to the particulate matter index equation, including a chemical tendency to form soot as well as the vapor pressure. The resulting metric better predicts PM formation in the EPAct V2 data set as a function of fuel properties and composition than existing models.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2014

Vertical distribution of structural components in corn stover

In the United States, corn ( Zea mays L.) stover has been targeted for second generation fuel production and other bio-products. Our objective was to characterize sugar and structural composition as a function of vertical distribution of corn stover (leaves and stalk) that was sampled at physiological maturity and about three weeks later from multiple USA locations. A small subset of samples was assessed for thermochemical composition. Concentrations of lignin, glucan, and xylan were about 10% greater at grain harvest than at physiological maturity, but harvestable biomass was about 25% less due to stalk breakage. Gross heating density above the ear averaged 16.3 ± 0.40 MJ kg⁻¹, but with an alkalinity measure of 0.83 g MJ⁻¹, slagging is likely to occur during gasification. Assuming a stover harvest height of 10 cm, the estimated ethanol yield would be >2500 L ha⁻¹, but it would be only 1000 L ha⁻¹ if stover harvest was restricted to the material from above the primary ear. Vertical composition of corn stover is relatively uniform; thus, decision on cutting height may be driven by agronomic, economic and environmental considerations.

09 BIOMASS FUELS↗
DOE OSTI2022

Z-Contrast Enhancement in Au–Pt Nanocatalysts by Correlative X-ray Absorption Spectroscopy and Electron Microscopy: Implications for Composition Determination

The properties of bimetallic nanoparticles (BNPs) vary widely as a function of their composition and size distributions. X-ray absorption fine structure analysis is commonly used to characterize their structure, but its application to elements that are close to each other in the periodic table is hampered by poor Z-contrast. For this study, we trained an artificial neural network to recognize the partial coordination numbers in AuPt NPs synthesized via peptide templating using their X-ray absorption near-edge structure spectra. This approach, combined with scanning transmission electron microscopy analysis, revealed unique details of this prototype catalytic system that has different forms of heterogeneities at both the intra- and inter-particle levels. Our method based on the enhancement of Z-contrast of metal species will have implications for compositional studies of BNPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

An integrated insight into the response of sedimentary microbial communities to heavy metal contamination

Response of biological communities to environmental stresses is a critical issue in ecology, but how microbial communities shift across heavy metal gradients remain unclear. To explore the microbial response to heavy metal contamination (e.g., Cr, Mn, Zn), the composition, structure and functional potential of sedimentary microbial community were investigated by sequencing of 16S rRNA gene amplicons and a functional gene microarray. Analysis of 16S rRNA sequences revealed that the composition and structure of sedimentary microbial communities changed significantly across a gradient of heavy metal contamination and the relative abundances were higher for Firmicutes, Chloroflexi and Crenarchaeota, but lower for Proteobacteria and Actinobacteria in highly contaminated samples. Also, molecular ecological network analysis of sequencing data indicated that their possible interactions might be enhanced in highly contaminated communities. Correspondently, key functional genes involved in metal homeostasis (e.g., chrR, metC, merB), carbon metabolism and organic remediation showed a higher abundance in highly contaminated samples, indicating that bacterial communities in contaminated areas may modulate their energy consumption and organic remediation ability. This study indicated that the sedimentary indigenous microbial community may shift the composition and structure as well as function priority and interaction network to increase their adaptability and/or resistance to environmental contamination.

Science & Technology - Other Topics↗
DOE OSTI2025

Conductive Liquid Metal Vitrimer Composites for Reconfigurable and Recyclable Flexible Electronics

Liquid metal (LM) elastomer composites exhibit excellent functionality for stretchable electronics and wearables, but limited recycling and reuse pathways constrain their sustainable use. Here, to address these challenges amid growing concerns over electronic waste, a conductive LM–vitrimer composite is presented that enables recyclable and reconfigurable electronics. This soft and stretchable composite features uniformly distributed LM inclusions that enhance thermal conductivity by 6.53× and enable the formation of conductive traces with electrical self-healing, while the vitrimer provides structural restoration. The dynamic covalent bonds of the vitrimer matrix are leveraged for both reprocessing the composite and chemically recovering 94% of the LM. This liquid-state filler slightly reduces the vitrimer's stiffness to 2.63 MPa (≈20% lower), while maintaining its high stretchability (>135% strain) and thermal stability. It is further examined how ultrasonicated LM inclusions interact with the vitrimer matrix and demonstrate the composite's self-healing and recyclability through two distinct approaches: 1) thermomechanical reprocessing, which restores fragmented composites under heat and compression for circuit reconfiguration; and 2) chemical recycling, which recovers the embedded LM for reuse in fabricating new composites and redesigned circuitry. With the integration of recyclability and diverse functional capabilities, LM–vitrimer composites emerge as a promising material platform for sustainable, flexible electronics.

Han, Youngshang [Univ. of Washington, Seattle, WA ↗
DOE OSTI2018

A Thermodynamic Model to Estimate the Formation of Complex Nitrides of Al{sub x}Mg{sub (1–x)}N in Silicon Steel

A complex nitride of Al{sub x}Mg{sub (1−x)}N was observed in silicon steels. A thermodynamic model was developed to predict the ferrite/nitride equilibrium in the Fe-Al-Mg-N alloy system, using published binary solubility products for stoichiometric phases. The model was used to estimate the solubility product of nitride compound, equilibrium ferrite, and nitride compositions, and the amounts of each phase, as a function of steel composition and temperature. In the current model, the molar ratio Al/(Al + Mg) in the complex nitride was great due to the low dissolved magnesium in steel. For a steel containing 0.52 wt pct Al{sub s}, 10 ppm T.Mg., and 20 ppm T.N. at 1100 K (827 °C), the complex nitride was expressed by Al{sub 0.99496}Mg{sub 0.00504}N and the solubility product of this complex nitride was 2.95 × 10{sup −7}. In addition, the solution temperature of the complex nitride increased with increasing the nitrogen and aluminum in steel. The good agreement between the prediction and the detected precipitate compositions validated the current model.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Quantified uncertainty in thermodynamic modeling for materials design

Phase fractions, compositions and energies of the stable phases as a function of macroscopic composition, temperature, and pressure (X-T-P) are the principle correlations needed for the design of new materials and improvement of existing materials. They are the outcomes of thermodynamic modeling based on the CALculation of PHAse Diagrams (CALPHAD) approach. Here, the accuracy of CALPHAD predictions vary widely in X-T-P space due to experimental error, model inadequacy and unequal data coverage. In response, researchers have developed frameworks to quantify the uncertainty of thermodynamic property model parameters and propagate it to phase diagram predictions. In most previous studies, uncertainty was represented as intervals on phase boundaries (with respect to composition or temperature) and was unable to represent the uncertainty in invariant reactions or in the stability of phase regions. In this work, we propose a suite of tools that leverages samples from the multivariate model parameter distribution to represent uncertainty in forms that surpass previous limitations and are well suited to materials design. These representations include the distribution of phase diagrams and their features, as well as the dependence of phase stability and the distributions of phase fraction, composition, activity and Gibbs energy on X-T-P location - irrespective of the total number of components. Most critically, the new methodology allows the material designer to interrogate a certain composition and temperature domain and get in return the probability of different phases to be stable, which can positively impact materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Natural organic matter composition and nanomaterial surface coating determine the nature of platinum nanomaterial-natural organic matter corona

Natural organic matter corona (NOM corona) is an interfacial area between nanomaterials (NMs) and the sur- rounding environment, which gives rise to NMs' unique surface identity. While the importance of the formation of natural organic matter (NOM) corona on engineered nanomaterials (NMs) to NM behavior, fate, and toxicity has been well-established, the understanding of how NOM molecular properties affect NOM corona composition remains elusive due to the complexity and heterogeneity of NOM. This is further complicated by the variation of NOMs from different origins. Here we use eight NOM isolates of different molecular composition and ultrahigh resolution Fourier-transform ion cyclotron resonance-mass spectrometry (ESI-FT-ICR-MS) to determine the mol- ecular composition of platinum NM-NOM corona as a function of NOM composition and NM surface coating. We observed that the composition of PtNM-NOM corona varied with the composition of the original NOM. The per- centage of NOM formulas that formed PVP-PtNM-NOM corona was higher than those formed citrate-PtNM-NOM corona, due to increased sorption of NOM formulas, in particular condensed hydrocarbons, to the PVP coating. The relative abundance of heteroatom formulas (CHON, CHOS, and CHOP) was higher in the PVP-PtNM-NOM corona than in citrate-PtNM-corona which was in turn higher than those in the original NOM isolate, indicating preferential partitioning of heteroatom-rich molecules to NM surfaces. The relative abundance of CHO, CHON, CHOS, CHOP and condensed hydrocarbons in PtNM-NOM corona increased with their increase in NOM isolates. Furthermore, PtNM-NOM corona is rich with compounds with high molecular weight. This study demonstrates that the composition and properties of PtNM-NOM corona depend on NOM molecular properties and PtNM sur- face coating. The results here provide evidence of molecular interactions between NOM and NMs, which are crit- ical to understanding NM colloidal properties (e.g., surface charge and stability), interaction forces (e.g., van der Waals and hydrphobic), environmental behaviors (e.g., aggregation, disso.

Baalousha, Mohammed↗
DOE OSTI2022

Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping

Application of artificial intelligence (AI), and more specifically machine learning, to the physical sciences has expanded significantly over the past decades. In particular, science-informed AI, also known as scientific AI or inductive bias AI, has grown from a focus on data analysis to now controlling experiment design, simulation, execution and analysis in closed-loop autonomous systems. The CAMEO (closed-loop autonomous materials exploration and optimization) algorithm employs scientific AI to address two tasks: learning a material system’s composition-structure relationship and identifying materials compositions with optimal functional properties. By integrating these, accelerated materials screening across compositional phase diagrams was demonstrated, resulting in the discovery of a best-in-class phase change memory material. Key to this success is the ability to guide subsequent measurements to maximize knowledge of the composition-structure relationship, or phase map. In this work we investigate the benefits of incorporating varying levels of prior physical knowledge into CAMEO’s autonomous phase-mapping. This includes the use of ab-initio phase boundary data from the AFLOW repositories, which has been shown to optimize CAMEO’s search when used as a prior.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

A large scale system approach for stability analysis of multi-unit SMR plants - 248

In this paper we present a framework based on large scale system theory for analyzing the stability of coupled advanced high temperature molten salt small modular reactors. It has been suggested that small modular reactors be coupled through a common molten salt energy repository, called a salt vault. Using vector Lyapunov functions the connective stability of multiple reactors coupled through a salt vault can be guaranteed. In this theory, scalar Lyapunov functions are assigned to portions of the composite system state space. Functions are constructed for each small modular reactor (SMR), each Brayton cycle, and the salt vault. These functions are then aggregated, becoming components of a vector Lyapunov function. If this vector function possesses special properties, the composite system is stable. Bounds on the connective stability of a multi-reactor plant can be found in terms of a free parameter, in this case the mass of molten salt in the salt vault. Examining bounds on the connective stability allows one to use control theory as a tool for making performance and economic design decisions related to the size of the salt vault. This technique can produce a constraint that is used in a design optimization problem for finding the smallest-possible salt vault that ensures stability. It can also be used as an indicator of interconnection and its effect on system behavior. This, in turn, could be used to guide multi-unit control system design to ensure that highly coupled systems behave favorably. The theory for multi-unit control and operation is discussed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Density Functional Theory Investigation of the NiO@Graphene Composite as a Urea Oxidation Catalyst in the Alkaline Electrolyte

Developing efficient and low-cost urea oxidation reaction (UOR) catalysts is a promising but still challenging task for environment and energy conversion technologies such as wastewater remediation and urea electrolysis. In this work, NiO nanoparticles that incorporated graphene as the NiO@Graphene composite were constructed to study the UOR process in terms of density functional theory. The single-atom model, which differed from the previous heterojunction model, was employed for the adsorption/desorption of urea and CO 2 in the alkaline media. As demonstrated from the calculated results, NiO@Graphene prefers to adsorb the hydroxyl group than urea in the initial stage due to the stronger adsorption energy of the hydroxyl group. After NiOOH@Graphene was formed in the alkaline electrolyte, it presents excellent desorption energy of CO 2 in the rate-determining step. Electronic density difference and the d band center diagram further confirmed that the Ni(III) species is the most favorable site for urea oxidation while facilitating charge transfer between urea and NiO@Graphene. Moreover, graphene provides a large surface for the incorporation of NiO nanoparticles, enhancing the electron transfer between NiOOH and graphene and promoting the mass transport in the alkaline electrolyte. Notably, this work provides theoretical guidance for the electrochemical urea oxidation work.

25 ENERGY STORAGE↗
DOE OSTI2020

Chemical short-range order in derivative Cr–Ta–Ti–V–W high entropy alloys from the first-principles thermodynamic study

The development of high-entropy alloys (HEAs) focuses on exploring compositional regions in multi-component systems with all alloy elements in equal or near-equal atomic concentrations. Initially it was based on the main idea that high mixing configurational entropy contributions to the alloy free energy could promote the formation of a single solid solution phase. By using the ab-initio based Cluster Expansion (CE) Hamiltonian model constructed for the quinary bcc Cr–Ta–Ti–V–W system in combination with Monte Carlo (MC) simulations, we show that the phase stability and chemical short-range order (SRO) of the equiatomic quinary and five sub-quaternary systems, as well as their derivative alloys, can dramatically change the order–disorder transition temperatures (ODTT) as a function of alloy compositions. In particular, it has been found, that the equiatomic quaternary Ta–Ti–V–W and Cr–Ta–Ti–W alloys had the lowest order–disorder transition temperature (500 K) among all the analysed equiatomic compositions. In all investigated alloy systems, the strongest chemical ordering has been observed between Cr and V, which led to the conclusion that decreasing the concentration of either Cr or V might be beneficial in terms of decreasing the ODTT. It also predicts that increasing concentration of Ti significantly decreases the ODTT. Our analysis of chemical SRO as a function of alloy composition allows to understand the microstructure evolution of HEAs as a function of temperature in excellent agreement with available experimental observations. Importantly, our free energy of mixing and SRO calculations predict that the origin of precipitates formed by Cr- and V-rich in the sub-quaternary Cr–Ta–V–W system is driven by the thermodynamics. The modelling results are in an excellent agreement with experimental observation of Cr and V segregation in the W 0.38 Ta 0.36 Cr 0.15 V 0.11 alloy which in turns shows an exceptional radiation resistance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Amorphous transparent conducting oxides in context: Work function survey, trends, and facile modification

The work functions of various amorphous and crystalline transparent conducting oxides (TCO5) were measured using Kelvin probe. The films, made by pulsed laser deposition, exhibited varying work functions dependent on the composition and deposition parameters. Tin oxide showed the largest work functions of the oxides measured, while zinc oxide showed the lowest. Binary and ternary combinations of the basis TCOs showed intermediate work functions dependent on the endpoint components. Amorphous TCO5, important in OPV and other technological applications, exhibited similar work functions to their crystalline counterparts. UV/ozone treatment of TCOs temporarily increased the work function, consistent with proposed defect mechanisms associated with near-surface changes in carrier content and Fermi level. Finally, a method for facile adjustment of the work function of commercial TCOs by atomic layer deposition (ALD) capping layers was presented, illustrated by the growth of zinc oxide layers on commercial crystalline ITO films.

Yeh, T. C.↗
DOE OSTI2024

Aluminum/SmCo 5 composites for structural and magnetic applications

Metal-bonded magnetic composites (MBMCs) present a promising alternative to dense sintered magnets, particularly for intricate components. Compared to polymer-based bonded magnets, MBMCs have wider applicability in harsh environments. In this paper, we demonstrate a solid-state shear-based manufacturing technique to introduce localized magnetization into a paramagnetic aluminum matrix by embedding SmCo5 permanent magnet particles. Our magnetic composites display hard magnetic behavior with a coercivity of 13 kOe and a remanent magnetization of 4.32 emu/g. In addition to magnetization, we also report a 9% improvement in Young’s modulus. Despite the local temperature rise during processing, the magnetic phases didn’t decompose into unwanted phases, preserving the composite's hard magnetic properties. Creation of an interfacial metallurgical bond with the matrix ensured the suitability of the composites for structural applications. Our study investigates the mechanical, and functional properties of composites, paving the way for lightweight structural magnetic composites with a transformative potential in the aerospace, nuclear, and automotive applications. This work underscores the potential for further optimization and development to drive innovations in magnet and equipment design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

J-PLUS: Spectral evolution of white dwarfs by PDF analysis

We estimated the spectral evolution of white dwarfs with effective temperature using the Javalambre Photometric Local Universe Survey (J-PLUS) second data release (DR2), which provides 12 photometric optical passbands over 2176 deg 2 . We analyzed 5926 white dwarfs with r ≤ 19.5 mag in common between a white dwarf catalog defined from Gaia EDR3 and J-PLUS DR2. We performed a Bayesian analysis by comparing the observed J-PLUS photometry with theoretical models of hydrogen- and helium-dominated atmospheres. We estimated the probability distribution functions for effective temperature (T eff ), surface gravity, parallax, and composition; and the probability of having a H-dominated atmosphere (p H ) for each source. We applied a prior in parallax, using Gaia EDR3 measurements as a reference, and derived a self-consistent prior for the atmospheric composition as a function of T eff . We described the fraction of white dwarfs with a He-dominated atmosphere (f He ) with a linear function of the effective temperature at 5000 < T eff < 30 000 K. We find f He = 0.24 ± 0.01 at T eff = 10 000 K, a change rate along the cooling sequence of 0.14 ± 0.02 per 10 kK, and a minimum He-dominated fraction of 0.08 ± 0.02 at the high-temperature end. We tested the obtained p H by comparison with spectroscopic classifications, finding that it is reliable. We estimated the mass distribution for the 351 sources with distance d < 100 pc, mass M > 0.45 M ⊙ , and T eff > 6000 K. The result for H-dominated white dwarfs agrees with previous studies, with a dominant M = 0.59 M ⊙ peak and the presence of an excess at M ~ 0.8 M ⊙ . This high-mass excess is absent in the He-dominated distribution, which presents a single peak. The J-PLUS optical data provide a reliable statistical classification of white dwarfs into H- and He-dominated atmospheres. We find a 21 ± 3% increase in the fraction of He-dominated white dwarfs from T eff = 20 000 K to T eff = 5000 K.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Compositional dependence of Young's moduli for amorphous FeCo-SiO{sub 2} thin films

Systematic force-deflection measurements with microcantilevers and a combinatorial-deposition method have been used to investigate the Young's moduli of amorphous composite FeCo-SiO{sub 2} thin films as a function of film composition, with high compositional resolution. It is found that the modulus decreases monotonically with increasing FeCo content. Such a trend can be explained in terms of the metalloid atoms having a significant effect on the Young's moduli of metal-metalloid composites, which is associated with the strong chemical interaction between the metalloid and themetallic atoms rather than that between the metallic components themselves. This work provides an efficient and effective method to study the moduli of magnetic thin films over a largecomposition coverage, and to compare the relative magnitudes of moduli for differentcompositions at high compositional resolution.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Soot and Spectral Radiation Modeling for a High-Pressure Turbulent Spray Flame

Simulations are performed of a transient high-pressure turbulent n-dodecane spray flame under engine-relevant conditions. An unsteady RANS formulation is used, with detailed chemistry, a semi-empirical two-equation soot model, and a particle-based transported composition probability density function (PDF) method to account for unresolved turbulent fluctuations in composition and temperature. Results from the PDF model are compared with those from a locally well-stirred reactor (WSR) model to quantify the effects of turbulence-chemistry-soot interactions. Computed liquid and vapor penetration versus time, ignition delay, and flame lift-off height are in good agreement with experiment, and relatively small differences are seen between the WSR and PDF models for these global quantities. Computed soot levels and spatial soot distributions from the WSR and PDF models show large differences, with PDF results being in better agreement with experimental measurements. An uncoupled photon Monte Carlo method with line-by-line spectral resolution is used to compute the spectral intensity distribution of the radiation leaving the flame. This provides new insight into the relative importance of molecular gas radiation versus soot radiation, and the importance of turbulent fluctuations on radiative heat transfer.

33 ADVANCED PROPULSION SYSTEMS↗