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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Characterization of Encapsulated Corrosion Inhibitors for Environmentally Friendly Smart Coatings

The NASA Kennedy Space Center's Corrosion Technology Lab at the Kennedy Space Center in Florida, U.S.A. has been developing multifunctional smart coatings based on the microencapsulation of environmentally friendly corrosion indicators, inhibitors and self-healing agents. This allows the incorporation of autonomous corrosion control functionalities, such as corrosion detection and inhibition as well as the self-healing of mechanical damage, into coatings. This paper presents technical details on the characterization of inhibitor-containing particles and their corrosion inhibitive effects using electrochemical and mass loss methods. Three organic environmentally friendly corrosion inhibitors were encapsulated in organic microparticles that are compatible with desired coatings. The release of the inhibitors from the microparticles in basic solution was studied. Fast release, for immediate corrosion protection, as well as long-term release for continued protection, was observed. The inhibition efficacy of the inhibitors, incorporated directly and in microparticles, on carbon steel was evaluated. Polarization curves and mass loss measurements showed that, in the case of 2MBT, its corrosion inhibition effectiveness was greater when it was delivered from microparticles.

Corrosion↗
NASA NTRS2015

Release Properties and Electrochemical Characterization of Encapsulated Corrosion Inhibitors for Environmentally Friendly Smart Coatings

The NASA Kennedy Space Center's Corrosion Technology Lab at the Kennedy Space Center in Florida, U.S.A. has been developing multifunctional smart coatings based on the microencapsulation of environmentally friendly corrosion indicators, inhibitors and self-healing agents. This allows for the incorporation of autonomous corrosion control functionalities, such as corrosion detection and inhibition as well as the self-healing of mechanical damage, into coatings. This paper presents technical details on the characterization of inhibitor-containing particles and their corrosion inhibitive effects using electrochemical and mass loss methods. Three organic environmentally friendly corrosion inhibitors were encapsulated in organic microparticles that are compatible with desired coatings. The total inhibitor content and the release of one of the inhibitors from the microparticles in basic solution was measured. Particles with inhibitor contents of up 60 wt% were synthesized. Fast release, for immediate corrosion protection, as well as long-term release for continued protection, was observed. The inhibition efficacy of the inhibitors, both as the pure materials and in microparticles, on carbon steel was evaluated. Polarization curves and mass loss measurements showed that, in the case of 2MBT, its corrosion inhibition effectiveness was greater when it was delivered from microparticles.

Coatings↗
NASA NTRS2006

The 'Biologically-Inspired Computing' Column

The field of Biology changed dramatically in 1953, with the determination by Francis Crick and James Dewey Watson of the double helix structure of DNA. This discovery changed Biology for ever, allowing the sequencing of the human genome, and the emergence of a "new Biology" focused on DNA, genes, proteins, data, and search. Computational Biology and Bioinformatics heavily rely on computing to facilitate research into life and development. Simultaneously, an understanding of the biology of living organisms indicates a parallel with computing systems: molecules in living cells interact, grow, and transform according to the "program" dictated by DNA. Moreover, paradigms of Computing are emerging based on modelling and developing computer-based systems exploiting ideas that are observed in nature. This includes building into computer systems self-management and self-governance mechanisms that are inspired by the human body's autonomic nervous system, modelling evolutionary systems analogous to colonies of ants or other insects, and developing highly-efficient and highly-complex distributed systems from large numbers of (often quite simple) largely homogeneous components to reflect the behaviour of flocks of birds, swarms of bees, herds of animals, or schools of fish. This new field of "Biologically-Inspired Computing", often known in other incarnations by other names, such as: Autonomic Computing, Pervasive Computing, Organic Computing, Biomimetics, and Artificial Life, amongst others, is poised at the intersection of Computer Science, Engineering, Mathematics, and the Life Sciences. Successes have been reported in the fields of drug discovery, data communications, computer animation, control and command, exploration systems for space, undersea, and harsh environments, to name but a few, and augur much promise for future progress.

Hinchey, Mike↗
DOE OSTI2026

Structure of Complex Liquid–Liquid Extraction Organic Phases for Rare Earth Separations

Complex, multicomponent liquids with hierarchical structure and phase transitions are encountered in many natural and industrial processes, including in chemical separations. One notable example is aggregation and organic phase splitting in liquid–liquid extraction (LLE) of metal ions. While these two phenomena that have long been closely associated, a mechanistic link between mesoscale structure and the capacity-limiting organic phase splitting remains elusive due to complexity of these systems. Here, in this study, we combine small-angle X-ray scattering (SAXS), X-ray photon correlation spectroscopy (XPCS), and molecular dynamics simulation to reveal a comprehensive picture of structure at the nano- and mesoscale in these complex solutions. For the representative case of rare earth extraction from an acidic aqueous phase by a malonamide extractant in dodecane, we investigate a wide range of process-relevant extractant and acid concentrations to provide a complete picture of how aggregation depends on composition. We decompose organic phase structure from SAXS into two contributions, which together can capture the scattering at all compositions: composition fluctuations described by the Ornstein–Zernike equation at low wavenumber Q, and nanostructure modeled by a “pre-peak” at intermediate Q. The former contains information about the thermodynamics of demixing, while the latter reflects nanoscopic self-assembly of the extractant and extracted solutes. While fluctuations have typically not been considered in the literature, we find they in fact dominate the total structure for nearly all practical conditions. As only the fluctuations have a strong temperature response, we confirm this attribution with temperature-dependent SAXS measurements, including for extracted europium nitrate complexes. SAXS and XPCS measurements near the critical point find static and dynamic scaling consistent with theory. Overall, this new paradigm for understanding LLE organic phases connects composition, nanoscale, and mesoscale structuring to phase behavior, providing both a comprehensive picture of solution structure and a quantitative link between aggregation and third phase formation.

Peroutka, Allison A. [Argonne National Laboratory ↗
DOE OSTI2020

Colloidal Synthesis Path to 2D Crystalline Quantum Dot Superlattices

By combining colloidal nanocrystal synthesis, self-assembly, and solution phase epitaxial growth techniques, we developed a general method for preparing single dot thick atomically attached quantum dot (QD) superlattices with high-quality translational and crystallographic orientational order along with state-of-the-art uniformity in the attachment thickness. The procedure begins with colloidal synthesis of hexagonal prism shaped core/shell QDs (e.g., CdSe/CdS), followed by liquid subphase self-assembly and immobilization of superlattices on a substrate. Solution phase epitaxial growth of additional semiconductor material fills in the voids between the particles, resulting in a QD-in-matrix structure. The photoluminescence emission spectra of the QD-in-matrix structure retains characteristic 0D electronic confinement. Importantly, annealing of the resulting structures removes inhomogeneities in the QD–QD inorganic bridges, which our atomistic electronic structure calculations demonstrate would otherwise lead to Anderson-type localization. The piecewise nature of this procedure allows one to independently tune the size and material of the QD core, shell, QD–QD distance, and the matrix material. These four choices can be tuned to control many properties (degree of quantum confinement, quantum coupling, band alignments, etc.) depending on the specific applications. Lastly, cation exchange reactions can be performed on the final QD-in-matrix, as demonstrated herein with a CdSe/CdS to HgSe/HgS conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Comparative Density Functional Theory Study of Magnetic Exchange Couplings in Dinuclear Transition-Metal Complexes

Multicenter transition-metal complexes (MCTMs) with magnetically interacting ions have been proposed as components for information-processing devices and storage units. For any practical application of MCTMs as magnetic units, it is crucial to characterize their magnetic behavior, and in particular, the isotropic magnetic exchange coupling, J, between its magnetic centers. Due to the large size of typical MCTMs, density functional theory is the only practical electronic structure method for evaluating the J coupling. Here, we assess the accuracy of different density functional approximations for predicting the magnetic couplings of eight dinuclear transition-metal complexes, including five dimanganese, two dicopper, and one divanadium with known reliable experimental J couplings spanning from ferromagnetic to strong antiferromagnetic. The density functionals considered include global hybrid functionals which mix semilocal density functional approximations and exact exchange with a fixed admixing parameter, six local hybrid functionals where the admixing parameters are extended to be spatially dependent, the SCAN and r 2 SCAN meta-generalized gradient approximations (GGAs), and two widely used GGAs. We found that global hybrids tested in this work have a tendency to over-correct the error in magnetic coupling parameters from the Perdew–Burke–Ernzerhof (PBE) GGA as seen for manganese complexes. The performance of local hybrid density functionals shows no improvement in terms of bias and is scattered without a clear trend, suggesting that more efforts are needed for the extension from global to local hybrid density functionals for this particular property. The SCAN and r 2 SCAN meta-GGAs are found to perform as well as benchmark global hybrids on most tested complexes. We further analyze the charge density redistribution of meta-GGAs as well as global and local hybrid density functionals with respect to that of PBE, in connection to the self-interaction error or delocalization error.

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

Self-regenerative noble metal catalysts supported on high-entropy oxides

Discovery of anti-sintering noble metal catalysts is challenging, as supported noble metal species tend to aggregate at high temperatures, leading to severely deteriorated catalytic performances. Here we show that 1 wt% of noble metal species including Au, Pd and Ru can be incorporated into high-entropy oxides (HEOs) through entropy stabilization at 900 °C in air. A reversible temperature-dependent dissolution–exsolution process is observed for Au-HEO. Further correlation with distinct CO oxidation capabilities demonstrates the potential to utilize the entropy effect to access self-regenerative catalysts for catalytic reactions.

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

Deep learning for characterizing the self-assembly of three-dimensional colloidal systems

Creating a systematic framework to characterize the structural states of colloidal self-assembly systems is crucial for unraveling the fundamental understanding of these systems’ stochastic and non-linear behavior. The most accurate characterization methods create high-dimensional neighborhood graphs that may not provide useful information about structures unless these are well-defined reference crystalline structures. Dimensionality reduction methods are thus required to translate the neighborhood graphs into a low-dimensional space that can be easily interpreted and used to characterize non-reference structures. We investigate a framework for colloidal system state characterization that employs deep learning methods to reduce the dimensionality of neighborhood graphs. The framework next uses agglomerative hierarchical clustering techniques to partition the low-dimensional space and assign physically meaningful classifications to the resulting partitions. In this work, we first demonstrate the proposed colloidal self-assembly state characterization framework on a three-dimensional in silico system of 500 multi-flavored colloids that self-assemble under isothermal conditions. We next investigate the generalizability of the characterization framework by applying the framework to several independent self-assembly trajectories, including a three-dimensional in silico system of 2052 colloidal particles that undergo evaporation-induced self-assembly.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Variational design principles for nonequilibrium colloidal assembly

Using large deviation theory and principles of stochastic optimal control, we show that rare molecular dynamics trajectories conditioned on assembling a specific target structure encode a set of interactions and external forces that lead to enhanced stability of that structure. Such a relationship can be formulated into a variational principle, for which we have developed an associated optimization algorithm and have used it to determine optimal forces for targeted self-assembly within nonequilibrium steady-states. We illustrate this perspective on inverse design in a model of colloidal cluster assembly within linear shear flow. We find that colloidal clusters can be assembled with high yield using specific short-range interactions of tunable complexity. Shear decreases the yields of rigid clusters, while small values of shear increase the yields of nonrigid clusters. The enhancement or suppression of the yield due to shear is rationalized with a generalized linear response theory. Furthermore, by studying 21 unique clusters made of six, seven, or eight particles, we uncover basic design principles for targeted assembly out of equilibrium.

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

Toward autonomous design and synthesis of novel inorganic materials

Autonomous experimentation driven by artificial intelligence (AI) provides an exciting opportunity to revolutionize inorganic materials discovery and development. Herein, we review recent progress in the design of self-driving laboratories, including robotics to automate materials synthesis and characterization, in conjunction with AI to interpret experimental outcomes and propose new experimental procedures. We focus on efforts to automate inorganic synthesis through solution-based routes, solid-state reactions, and thin film deposition. In each case, connections are made to relevant work in organic chemistry, where automation is more common. Characterization techniques are primarily discussed in the context of phase identification, as this task is critical to understand what products have formed during synthesis. The application of deep learning to analyze multivariate characterization data and perform phase identification is examined. To achieve “closed-loop” materials synthesis and design, we further provide a detailed overview of optimization algorithms that use active learning to rationally guide experimental iterations. Lastly, we highlight several key opportunities and challenges for the future development of self-driving inorganic materials synthesis platforms.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fully variational incremental CASSCF

We report the complete-active-space self-consistent field (CASSCF) method is a canonical electronic structure theory that holds a central place in conceptualizing and practicing first principles simulations. For application to realistic molecules, however, the CASSCF must be approximated to circumvent its exponentially scaling computational costs. Applying the many-body expansion - also known as the method of increments - to CASSCF (iCASSCF) has been shown to produce a polynomially scaling method that retains much of the accuracy of the parent theory and is capable of treating full valence active spaces. Due to an approximation made in the orbital gradient, the orbital parameters of the original iCASSCF formulation could not be variationally optimized, which limited the accuracy of its nuclear gradient. Herein, a variational iCASSCF is introduced and implemented, where all parameters are fully optimized during energy minimization. This method is able to recover electronic correlations from the full valence space in large systems, produce accurate gradients, and optimize stable geometries as well as transition states. Demonstrations on challenging test cases, such as the oxoMn(salen)Cl complex with 84 electrons in 84 orbitals and the automerization of cyclobutadiene, show that the fully variational iCASSCF is a powerful tool for describing challenging molecular chemistries.

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

Precise Control of Noncovalent Interactions in Semiconducting Polymers for High-Performance Organic Field-Effect Transistors

Performed through side-chain engineering or by incorporating intramolecular locking units, the directionality and dynamic nature of noncovalent interactions are particularly attractive for the design of novel semiconducting materials in a wide variety of applications. This work investigates the nature and position of hydrogen bonding (intra- versus intermolecular), with the objective of developing a rational approach to the design of new semiconducting materials with improved properties in the solid state. To control the polymer chains’ self-assembly, a π-conjugated polymer incorporating a moiety capable of generating intramolecular hydrogen bonding is evaluated against a polymer that allows for intermolecular hydrogen bonding. Characterization through various techniques, optical spectroscopies, grazing incidence wide-angle x-ray scattering, and solution small-angle neutron scattering showed that intramolecular hydrogen bonds resulted in materials with improved crystallinity and higher effective conjugation in the solid state. Additionally, the effect of the noncovalent interaction configuration on the optoelectronic properties was analyzed in organic field-effect transistor fabrication. Devices prepared from the materials with intramolecular hydrogen bonds showed significantly higher performance, with three orders of magnitude higher charge mobility than their counterparts fabricated from polymers with intermolecular hydrogen bonds. These results confirm the importance of chemical design on polymer structures and offer a novel route for the design of high-efficiency semiconducting polymers for next-generation electronics.

36 MATERIALS SCIENCE↗
NASA NTRS1986

Clay energetics in chemical evolution

Clays have been implicated in the origin of terrestrial life since the 1950's. Originally they were considered agents which aid in selecting, concentrating and promoting oligomerization of the organic monomeric substituents of cellular life forms. However, more recently, it has been suggested that minerals, with particular emphasis on clays, may have played a yet more fundamental role. It has been suggested that clays are prototypic life forms in themselves and that they served as a template which directed the self-assembly of cellular life. If the clay-life theory is to have other than conceptual credibility, clays must be shown by experiment to execute the operations of cellular life, not only individually, but also in a sufficiently concerted manner as to produce some semblance of the functional attributes of living cells. Current studies are focussed on the ability of clays to absorb, store and transfer energy under plausible prebiotic conditions and to use this energy to drive chemistry of prebiotic relevance. Conclusions of the work are applicable to the role of clays either as substrates for organic chemistry, or in fueling their own life-mimetic processes.

Coyne, L. M.↗
DOE OSTI2021

Heavily Tungsten–Doped Sodium Thioantimonate Solid–State Electrolytes with Exceptionally Low Activation Energy for Ionic Diffusion

A strategy for modifying the structure of solid-state electrolytes (SSEs) to reduce the cation diffusion activation energy is presented. Two heavily W-doped sodium thioantimonate SSEs, Na 2.895 W 0.3 Sb 0.7 S 4 and Na 2.7 W 0.3 Sb 0.7 S 4 are designed, both exhibiting exceptionally low activation energy and enhanced room temperature (RT) ionic conductivity; 0.09 eV, 24.2 mS/cm and 0.12 eV, 14.5 mS/cm. At –15 °C the Na 2.895 W 0.3 Sb 0.7 S 4 displays a total ionic conductivity of 5.5 mS/cm. Here, the 30 % W content goes far beyond the 10–12 % reported in the prior studies, and results in novel pseudo-cubic or orthorhombic structures. Calculations reveal that these properties result from a combination of multiple diffusion mechanisms, including vacancy defects, strongly correlated modes and excessive Na-ions. An all-solid-state battery (ASSB) using Na 2.895 W 0.3 Sb 0.7 S 4 as the primary SSE and a sodium sulfide (Na 2 S) cathode achieves a reversible capacity of 400 mAh g –1 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Genetic Fusion of Thermoresponsive Polypeptides with UCST–type Behavior Mediates 1D Assembly of Coiled–Coil Bundlemers

Thermoresponsive resilin-like polypeptides (RLPs) of various lengths were genetically fused to two different computationally designed coiled coil-forming peptides with distinct thermal stability, to develop new strategies to assemble coiled coil peptides via temperature-triggered phase separation of the RLP units. Furthermore, their successful production in bacterial expression hosts was verified via gel electrophoresis, mass spectrometry, and amino acid analysis. Circular dichroism (CD) spectroscopy, ultraviolet-visible (UV/Vis) turbidimetry, and dynamic light scattering (DLS) measurements confirmed the stability of the coiled coils and showed that the thermosensitive phase behavior of the RLPs was preserved in the genetically fused hybrid polypeptides. Cryogenic-transmission electron microscopy and coarse-grained modeling revealed that functionalizing the coiled coils with thermoresponsive RLPs leads to their thermally triggered noncovalent assembly into nanofibrillar assemblies.

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

Energy catalysis needs ligands with high oxidative stability

Replacing fossil fuel-based energy by renewable sources is a transition that society needs to make to meet future energy demand and simultaneously address climate change. Coupling renewable energy sources with electrochemical catalysis provides a promising path to carbon-neutral fuels and chemicals when the necessary reducing equivalents and protons are harvested from water. Developing highly active, stable, and inexpensive electrocatalysts for the oxygen evolution reaction (OER) is accordingly a centerpiece of a renewable energy portfolio. Whereas viable OER catalysts are heterogeneous in nature, owing to their oxidative stability, the realization of stable molecular OER catalysts greatly expands the horizon of energy science with the ability to tune OER energetics and mechanisms with fidelity. In this perspective, current challenges in the field of molecular OER catalysis are addressed with promising lines of research that are directed to designing ligands that can withstand the harsh oxidizing environment of OER.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗