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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Nanoparticle-Induced Disorder at Complex Liquid–Liquid Interfaces: Effects of Curvature and Compositional Synergy on Functional Surfaces

The self-assembly of surfactant monolayers at interfaces plays a sweeping role in tasks ranging from household cleaning to the regulation of the respiratory system. The synergy between different nanoscale species at an interface can yield assemblies with exceptional properties, which enhance or modulate their function. However, understanding the mechanisms underlying coassembly, as well as the effects of intermolecular interactions at an interface, remains an emerging and challenging field of study. Herein, we study the interactions of gold nanoparticles striped with hydrophobic and hydrophilic ligands with phospholipids at a liquid–liquid interface and the resulting surface-bound complexes. We show that these nanoparticles, which are themselves minimally surface active, have a direct concentration-dependent effect on the rapid reduction of tension for assembling phospholipids at the interface, implying molecular coassembly. Through the use of sum frequency generation vibrational spectroscopy, we reveal that nanoparticles impart structural disorder to the lipid molecular layers, which is related to the increased volumes that amphiphiles can sample at the curved surface of a particle. The results strongly suggest that hydrophobic and electrostatic attractions imparted by nanoparticle functionalization drive lipid–nanoparticle complex assembly at the interface, which synergistically aids lipid adsorption even when lipids and nanoparticles approach the interface from opposite phases. The use of tensiometric and spectroscopic analyses reveals a physical picture of the system at the nanoscale, allowing for a quantitative analysis of the intermolecular behavior that can be extended to other systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Partitioning of Complex Fluids at Mineral Surfaces

This report summarizes the results obtained during the LDRD project entitled "Partitioning of Complex Fluids at Mineral Interfaces." This research addressed fundamental aspects of such interfaces, which are relevant to energy-water applications in the subsurface, including fossil energy extraction and carbon sequestration. This project directly addresses the problem of selectivity of complex fluid components at mineral-fluid interfaces, where complex fluids are defined as a mixture of hydrophobic and hydrophilic components: e.g., water, aqueous ions, polar/nonpolar organic compounds. Specifically, this project investigates how adsorption selectivity varies with surface properties and fluid composition. Both experimental and molecular modeling techniques were used to better understand trends in surface wettability on mineral surfaces. The experimental techniques spanned the macroscale (contact angle measurements) to the nanoscale (cryogenic electronic microscopy and vibrational spectroscopy). We focused on an anionic surfactant and a well-characterized mineral phase representative of clay phases present in oil- and gas-producing shale deposits. Collectively, the results consistently demonstrate that the presence of surfactant in the aqueous fluid significantly affects the mineral-fluid interfacial structure. Experimental and molecular modeling results reveal details of the surfactant structure at the interface, and how this structure varies with surfactant coverage and fluid composition.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2025

Roles of surface Mn(III) and MgOH + /CaOH + complexation in photochemically assisted Mn 2+ oxidation and Todorokite formation

Todorokite, a Mn oxide phase commonly found in seafloor Mn nodules, is one of the most abundant Mn oxides in nature and has wide applications in environmental engineering, including heavy metal remediation, contaminant adsorption for water purification, and catalysis for organic pollutant degradation. However, traditional abiotic formation of todorokite reported to date typically requires high temperature, pressure, and pH outside circumneutral conditions, or involves several days of phase transformations from precursor phases. In this study, we demonstrate rapid todorokite formation within 6 h via photochemically assisted oxidation of Mn 2+ (aq) in the presence of Mg 2+ or Ca 2+ , notably at ambient temperature and pressure. The concentrations of aqueous MgOH + and CaOH + , as well as the pH (initial 9 or 6), had significant collective influences on the crystalline phases of the formed Mn oxide solids. The proportions of the Mn oxidation states (IV, III, and II) and the extent of Mn(III) surface complexation with MgOH + or CaOH + controlled the crystalline phases (todorokite, feitknechtite, and birnessite) and the extent of cation incorporation into the resulting Mn oxide solids. Specifically, the oxidation state of Mn influenced the crystallization of different Mn oxide phases, and the formed Mn(III) complexed with MgOH + or CaOH + facilitated the formation of todorokite, along with cation incorporation. X-ray pair distribution function analysis revealed that incorporated Mg species were located at the inside corner sites of the 5 × 3 MnO 6 octahedral tunnel structure of todorokite, suggesting complexation between MgOH + and Mn(III) at the corners of the tunnel. Furthermore, this study provides novel insights into the elusive formation of todorokite and its potential for applications in advanced water treatment and environmental remediation.

Abiotic Mn2+ oxidation↗
NASA NTRS1976

A nonlinear finite-element analysis of wings in steady incompressible flows with wake roll-up

The problem of lifting surfaces and complex aircraft configurations in steady incompressible flow is considered. For lifting surfaces the problem is formulated in terms of an integral equation relating the potential discontinuity on wing and wake to the normal derivative of the potential on the lifting surface. For complex configurations the problem is formulated in terms of an integral equation relating the potential to its normal derivative on the surface of the aircraft. The integral equation is approximated by a system of linear algebraic equations obtained by dividing the surfaces into small quadrilateral elements and by assuming the potential (or the potential discontinuity) and its normal derivative to be constant within each element. The wake geometry is obtained by iteration by satisfying the condition that the velocity be tangent to the surface of the wake and that the potential discontinuity be constant along the streamlines.

Suciu, E. O.↗
NASA NTRS2017

Surface-Height Determination of Crevassed Glaciers-Mathematical Principles of an Autoadaptive Density-Dimension Algorithm and Validation Using ICESat-2 Simulator (SIMPL) Data

Glacial acceleration is a main source of uncertainty in sea-level-change assessment. Measurement of ice-surface heights with a spatial and temporal resolution that not only allows elevation-change calculation, but also captures ice-surface morphology and its changes is required to aid in investigations of the geophysical processes associated with glacial acceleration.The Advanced Topographic Laser Altimeter System aboard NASAs future ICESat-2 Mission (launch 2017) will implement multibeam micropulse photon-counting lidar altimetry aimed at measuring ice-surface heights at 0.7-m along-track spacing. The instrument is designed to resolve spatial and temporal variability of rapidly changing glaciers and ice sheets and the Arctic sea ice. The new technology requires the development of a new mathematical algorithm for the retrieval of height information.We introduce the density-dimension algorithm (DDA) that utilizes the radial basis function to calculate a weighted density as a form of data aggregation in the photon cloud and considers density an additional dimension as an aid in auto-adaptive threshold determination. The auto-adaptive capability of the algorithm is necessary to separate returns from noise and signal photons under changing environmental conditions. The algorithm is evaluated using data collected with an ICESat-2 simulator instrument, the Slope Imaging Multi-polarization Photon-counting Lidar, over the heavily crevassed Giesecke Braer in Northwestern Greenland in summer 2015. Results demonstrate that ICESat-2 may be expected to provide ice-surface height measurements over crevassed glaciers and other complex ice surfaces. The DDA is generally applicable for the analysis of airborne and spaceborne micropulse photon-counting lidar data over complex and simple surfaces.

Herzfeld, Ute C.↗
DOE OSTI2022

Dissociative electron attachment to 5-bromo-uracil: non-adiabatic dynamics on complex-valued potential energy surfaces

Electron induced dissociation reactions are relevant to many fields, ranging from prebiotic chemistry to cancer treatments. However, the simulation of dissociation electron attachment (DEA) dynamics is very challenging because the auto-ionization widths of the transient negative ions must be accounted for. We propose an adaptation of the ab initio multiple spawning (AIMS) method for complex-valued potential energy surfaces, along the lines of recent developments based on surface hopping dynamics. Our approach combines models for the energy dependence of the auto-ionization widths, obtained from scattering calculations, with survival probabilities computed for the trajectory basis functions employed in the AIMS dynamics. The method is applied to simulate the DEA dynamics of 5-bromouracil in full dimensionality, i.e., taking all the vibrational modes into consideration. The propagation starts on the $π_{2}^{*}$ resonance state and describes the formation of Br - anions mediated by non-adiabatic couplings. The potential energies, gradients and non-adiabatic couplings were computed with the fractional-occupancy molecular orbital complete-active-space configuration-interaction method, and the calculated DEA cross section are consistent with the observed DEA intensities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Theoretical investigation of surface chemical reactivity of compositionally disordered multi-metallic alloys

Alloys are widely used in both academic and industrial research as heterogeneous catalysts for accelerating technologically important reactions ranging from hydrocarbon reforming, selective hydrogenation, to electrochemical reactions involving hydrogen and oxygen that are fundamental and indispensable to a sustainable future energy infrastructure. Most basic catalysis research has been limited to combinations of two elements that are usually ordered in some manner at the nanoscale because doing so allows observable results to be easily rationalized. It however leaves a huge material space consisting of multi metallic, compositionally disordered alloys unexplored. This research demonstrates a viable theoretical approach combining different types of first principles calculations (including Green’s function-based Korringa–Kohn–Rostoker coherent potential approximation (KKR–CPA) and planewave-based density functional theory) to enable the surface chemical reactivity of compositionally complex alloy surfaces to be investigated. We demonstrate the approach by investigating hydrogen adsorption and evolution on two types of compositionally disordered alloys: a quaternary CoCrFeNi high-entropy alloy, and binary Pt-3d base metal alloys.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1986

Surface energy fluxes in complex terrain

The emphasis of the 1985 NASA project activity was on field measurements of wind data and heat balance data. Initiatives included a 19 station mountaintop monitoring program, testing and refining the surface flux monitoring systems and packing and shipping equipment to the People's Republic of China in preparation for the 1986 Tibet Experiment. Other work included more extensive analyses of the 1984 Gobi Desert and Rocky Mountain observations plus some preliminary analyses of the 1985 mountaintop network data. Details of our field efforts are summarized and results of our data analyses are presented.

Reiter, E. R.↗
NASA NTRS1986

Application of the TranAir full-potential code to complete configurations

The TranAir computer code solves the full-potential equation for transonic flow by combining a rectangular box of flow-field grid points with networks of surface panels. Complex geometry is easily represented since surface conforming flow-field grids are not used. Application of TranAir to the F-16A is presented for free-stream Mach numbers of 0.6 and 0.90, at an angle of attack of four degrees.

Erickson, L. L.↗
DOE OSTI2021

Perspectives on Machine Learning-assisted Plasma Medicine: Towards Automated Plasma Treatment

Cold atmospheric plasmas (CAPs) have shown great promise for medical applications through their synergistic chemical, electrical, and thermal effects, which can induce therapeutic outcomes. However, safe and reproducible plasma treatment of complex biological surfaces poses a major hurdle to the widespread adoption of CAPs for medical applications. Predictive modeling of the mutual interactions between the plasma and biological surfaces and, thus, systematic approaches to quantify and predict plasma treatment outcomes remain largely elusive due to the lack of mechanistic understanding of plasma-surface interactions that can span across vastly different length-and time-scales. In addition, real-time sensing capabilities in biomedical CAP devices are often limited, which can be detrimental to plasma treatment due to the intrinsic plasma and surface variability during the treatment, as well as sensitivity to external perturbations. All of these challenges can make reproducible and effective plasma treatment of biological surfaces difficult to realize, which is further compounded by errors due to human operation of hand-held CAP devices. Machine learning and data-driven approaches can be particularly useful in addressing these challenges in three major ways: (i) data-driven modeling of hard-to-model plasma-surface interactions and plasma treatment outcomes; (ii) learning data analytics for plasma and surface diagnostics in real-time; and (iii) developing predictive controllers that enable reliable and effective CAP treatments. Furthermore, this paper discusses the promise of machine learning to accelerate plasma medicine research in these areas, toward machine learning-assisted and automated CAP treatment of complex biological surfaces.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Catalytic resonance theory: Circumfluence of programmable catalytic loops

Chemical reactions on heterogeneous catalyst surfaces exhibit complex networks of elementary reactions with multiple pathways to fluid phase products, sometimes leading to surface reaction loops consisting of a closed cycle reaction pathway. While conventional catalysts at steady state exhibit zero net flux in either direction around a catalytic loop, the loop turnover frequency of three-species surface loops was evaluated in this work via microkinetic modeling to assess the reaction loop behavior resulting from a catalytic surface oscillating between two or more surface energy states. For dynamic heterogeneous catalysts undergoing applied oscillations of surface energy (i.e., programs), surface reaction loops of three species were shown to exhibit non-zero net flow of molecules around the loop, with the extent of loop turnover frequency varying with the applied frequency and amplitude of a sinusoidal or square wave oscillation. Alternatively, some dynamic surface reactions exhibited oscillations only between two surface species or resulted in surfaces covered by a single species at all times. Here, more complex behavior was observed for dynamic surface programs of three distinct electronic states, with the temporal order of applied states controlling the direction of flow of molecules within a three-molecule surface loop. Catalytic loops have the potential to limit overall catalytic reaction rates and use energy in programmable catalysts, while some applications could purposely impose non-zero loop turnover frequency for improved surface reaction control.

Catalysis↗
DOE OSTI2024

Heterogeneous Organochromium Catalysts for Stereoselective Isoprene Polymerization

In this study, heterogeneous organochromium catalysts have been developed via surface lithiation of traditional surface organometallic complexes to mediate stereoselective isoprene polymerization. Chemisorption of the molecular complex Cr(CH 2 SiMe 3 ) 4 on high surface area anatase titania nanoparticles as well as on a silica support led to the bipodal complexes Cr/TiO 2 and Cr/SiO 2 , respectively. Subsequent reductive lithium intercalation with n-butyllithium led to the formation of lower valent Cr 2+ species Cr/LTO and Cr/Li/SiO 2 . Alternatively, Cr(CH 2 SiMe 3 ) 4 was allowed to react with nBuLi-reduced anatase titania (LTO) to provide Cr/LTO Inv . Cr/LTO and Cr/Li/SiO 2 both polymerize isoprene with very high activities (154 and 174 kg molCr –1 h –1 , respectively) to provide polyisoprene with cis-1,4 selectivity up to 82% in toluene at 50 °C. On the other hand, Cr/SiO 2 provides polyisoprene with excellent trans-1,4 selectivity up to 98% (16 kg molCr –1 h –1 ), and Cr/TiO 2 was catalytically inactive. Cr/LTO Inv is less active and selective, and X-ray absorption spectroscopy (XAS) measurements of the precatalyst revealed the presence of a mixture of metallic Cr 0 , Cr 4+ , and only minor Cr 2+ species. Thus, surface lithiation can promote the formation of lower valent metal centers which enable stereocontrol in isoprene polymerizations and may be extended as a general protocol to other catalytic systems.

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

Machine learning potential assisted exploration of complex defect potential energy surfaces

Abstract Atomic-scale defects generated in materials under both equilibrium and irradiation conditions can significantly impact their physical and mechanical properties. Unraveling the energetically most favorable ground-state configurations of these defects is an important step towards the fundamental understanding of their influence on the performance of materials ranging from photovoltaics to advanced nuclear fuels. Here, using fluorite-structured thorium dioxide (ThO 2 ) as an exemplar, we demonstrate how density functional theory and machine learning interatomic potential can be synergistically combined into a powerful tool that enables exhaustive exploration of the large configuration spaces of small point defect clusters. Our study leads to several unexpected discoveries, including defect polymorphism and ground-state structures that defy our physical intuitions. Possible physical origins of these unexpected findings are elucidated using a local cluster expansion model developed in this work.

36 MATERIALS SCIENCE↗