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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Critical role of structural order in bipolar redox-active molecules for organic redox flow batteries

Bipolar redox-active molecules (BRMs) have been suggested as a means to address crossover related issues in all-organic redox flow batteries (RFBs). In such species, electron donors (anolytes) and electron acceptors (catholytes) are linked by a chain, and the same chemical composition is used in both anode and cathode compartments to reduce chemical gradients and unbalanced ion transport. The resultant RFBs resemble the aqueous vanadium RFBs, but offer greater design flexibility and potentially more favorable electrochemical and physicochemical properties. Yet the complex trade-offs in these properties have been a complication. Here we developed a fundamental rubric to uncover the likely origins in the performance metrics of these BRMs that are salient for their use in RFBs. Methylene linked phenothiazine and phthalimide moieties were employed as model BRMs and variations in their properties and molecular conformations were evaluated by systematically varying the methylene linker. Our results revealed that even minimalistic changes in the linker length resulted in dramatic oscillations in the solubility and stability. Using crystallography, quantum chemistry, and molecular dynamics, we clarify that the seemingly fluctuating behavior is due to (1) the inter- and intra-molecular charge transfer between the donor and acceptor through bond or/and through space; (2) the formation of distinctive packing/clustering motifs. Both interactions are strongly dependent on the molecular conformation. As these structural factors modify the electronic structure of both electroactive functional groups and do not change monotonically, the structure–property response in BRMs is often complex. Finally, accordingly, these behaviors need to be taken into account in developing BRMs and knowledge of these structural factors will allow the more rational design of BRMs for grid-scale energy storage.

25 ENERGY STORAGE↗
DOE OSTI2022

Molecular interactions in diffusion-controlled aldol condensation with mesoporous silica nanoparticles

The aldol reaction of p-nitrobenzaldehyde in amino-catalyzed mesoporous silica nanoparticles (MSN) has revealed varying catalytic activity with the size of the pores of MSN. The pore size dependence related to the reactivity indicates that the diffusion process is important. A detailed molecular-level analysis for understanding diffusion requires assessment of the noncovalent interactions of the molecular species involved in the aldol reaction with each other, with the solvent, and with key functional groups on the pore surface. Such an analysis is presented here based upon the effective fragment potential (EFP). The EFP method can calculate the intermolecular interactions, decomposed into Coulomb, polarization, dispersion, exchange-repulsion, and charge-transfer interactions. In this study, the potential energy surfaces corresponding to each intermolecular interaction are analyzed for homo- and hetero-dimers with various configurations. The monomers that compose dimers are five molecules such as p-nitrobenzaldehyde, acetone, n-hexane, propylamine, and silanol. The results illustrate that the dispersion interaction is crucial in most dimers.

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

Roadmap on exsolution for energy applications

Over the last decade, exsolution has emerged as a powerful new method for decorating oxide supports with uniformly dispersed nanoparticles for energy and catalytic applications. Due to their exceptional anchorage, resilience to various degradation mechanisms, as well as numerous ways in which they can be produced, transformed and applied, exsolved nanoparticles have set new standards for nanoparticles in terms of activity, durability and functionality. In conjunction with multifunctional supports such as perovskite oxides, exsolution becomes a powerful platform for the design of advanced energy materials. In the following sections, we review the current status of the exsolution approach, seeking to facilitate transfer of ideas between different fields of application. We also explore future directions of research, particularly noting the multi-scale development required to take the concept forward, from fundamentals through operando studies to pilot scale demonstrations.

25 ENERGY STORAGE↗
DOE OSTI2026

Modulating Mid-Gap Electronic States Through Site-Selective Modification in B-Pbx/B'-CuyV2O5/CdS Heterostructures for Photocatalytic Hydrogen Evolution

We interfaced ..beta..-Pbx/..beta..'-CuyV2O5 compounds, with varying stoichiometries of precisely positioned Pb-ions (x) and Cu-ions (y) in interstitial sites along a tunnel-structured ?-V2O5 framework, with cysteine-capped CdS (cysCdS) quantum dots (QDs) to yield heterostructured photocatalysts. ..beta..-Pbx/..beta..'-CuyV2O5 compounds exhibit midgap electronic states with orbital contributions from both Cu 3d and stereochemically active Pb 6s states that show distinctive light-initiated reactivity with photoexcited QDs. ..beta..-Pbx/..beta..'-CuyV2O5/CdS heterostructures were prepared by linker-assisted assembly (LAA). Scanning and transmission electron microscopy, energy-dispersive X-ray spectroscopy, and Raman spectroscopy revealed that cysCdS QDs were deposited onto surfaces of ..beta..-Pbx/..beta..'-CuyV2O5 via LAA. HAXPES revealed that the site-selective positioning of Pb-ions and Cu-ions promoted close energetic alignment of the midgap states of ..beta..-Pbx/..beta..'-CuyV2O5 compounds with the valence-band maximum of cysCdS QDs. Transient absorption spectroscopy revealed that photogenerated holes were transferred from CdS QDs to midgap states of ..beta..-Pbx/..beta..'-CuyV2O5 compounds on time scales <50 ps. Finally, photoelectrochemical and photochemical experiments revealed that ..beta..-Pbx/..beta..'-CuyV2O5/CdS heterostructures promoted the photocatalytic reduction of H+ to H2. In photoelectrochemical experiments, under oxidative conditions, for all ..beta..-Pbx/..beta..'-CuyV2O5/CdS heterostructures, H2 was evolved at a Pt counter electrode while a sacrificial donor was oxidized at the heterostructure-functionalized working electrode. In contrast, under reductive conditions, for ..beta..-Pb0.152V2O5/CdS and ..beta..-Pbx/..beta..'-CuyV2O5/CdS heterostructures, H2 was evolved at the working electrode. In photochemical experiments, dispersed ..beta..-Pbx/..beta..'-CuyV2O5/CdS heterostructures promoted the reduction of H+ to H2 under white-light illumination; ..beta..'-Cu0.55V2O5/CdS and ..beta..-Pbx/..beta..'-CuyV2O5/CdS heterostructures, for which midgap states have Cu 3d orbital character, generated 2-fold more H2 than ..beta..-Pb0.152V2O5/CdS heterostructures. Cu-ion insertion thus appends additional acceptor surface states that improve ligand-mediated hole transfer from photoexcited QDs, but such states are intrinsically limited in mediating hole transport to the substrate as a result of the low mobility of holes in narrow Cu 3d-states. Our results reveal that the density and orbital character of midgap states of ..beta..-Pbx/..beta..'-CuyV2O5 compounds, tunable through recently developed site-selective ion insertion strategies, determine efficiencies of charge-transfer and charge-transport mechanisms that underpin photocatalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Kinetic simulation of a 50 mTorr capacitively coupled argon discharge over a range of frequencies and comparison to experiments

The effect of driving frequency in the range of 13.56–73 MHz on electron energy distribution and electron heating modes in a 50 mTorr capacitively coupled argon plasma discharge is studied using 1D-3V particle-in-cell simulations. Calculated electron energy probability functions exhibit three distinct “temperatures” for low-, mid-, and high-energy electrons at all the studied driving frequencies. When compared to published experimental data, the calculated probability functions show a reasonable agreement for the energy range resolved in the measurements (about 2–10 eV). Discrepancies due to limitations in experimental energy resolution outside this range lead to differences between computational and experimental values of the electron number density determined from the distribution functions, and the predicted effective electron temperature is within 25% of experimental values. The impedance of the discharge is interpreted in terms of a homogeneous equivalent circuit model, and the driving frequency dependence of the inferred combined sheath thickness is found to obey a known, theoretically derived, power law. The average power transferred from the field to the electrons (electron heating) is computed, and a region of negative heating near the sheath edge, particularly at higher driving frequencies, is identified. Analysis of the electron momentum equation shows that electron inertia, which on temporal averaging would be zero in a linear regime, is responsible for negative values of power deposition near the sheath edge at high driving frequencies due to the highly nonlinear behavior of the discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

High-Accuracy Semiempirical Quantum Models Based on a Minimal Training Set

A great need exists for computationally efficient quantum simulation approaches that can achieve an accuracy similar to high-level theories at a fraction of the computational cost. In this regard, we have leveraged a machine-learned interaction potential based on Chebyshev polynomials to improve density functional tight binding (DFTB) models for organic materials. The benefit of our approach is two-fold: (1) many-body interactions can be corrected for in a systematic and rapidly tunable process, and (2) high-level quantum accuracy for a broad range of compounds can be achieved with ~0.3% of data required for one advanced deep learning potential. Our model exhibits both transferability and extensibility through comparison to quantum chemical results for organic clusters, solid carbon phases, and molecular crystal phase stability rankings. Overall, our efforts thus allow for high-throughput physical and chemical predictions with up to coupled-cluster accuracy for systems that are computationally intractable with standard approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Active Learning A Neural Network Model For Gold Clusters & Bulk From Sparse First Principles Training Data

Small metal clusters are of fundamental scientific interest and of tremendous significance in catalysis. These nanoscale clusters display diverse geometries and structural motifs depending on the cluster size; a knowledge of this size-dependent structural motifs and their dynamical evolution has been of longstanding interest. Given the high computational cost of first-principles calculations, molecular modeling and atomistic simulations such as molecular dynamics (MD) has proven to be an important complementary tool to aid this understanding. Classical MD typically employ predefined functional forms which limits their ability to capture such complex size-dependent structural and dynamical transformation. Neural Network (NN) based potentials represent flexible alternatives and in principle, well-trained NN potentials can provide high level of flexibility, transferability and accuracy on-par with the reference model used for training. A major challenge, however, is that NN models are interpolative and requires large quantities (similar to 10 4 or greater) of training data to ensure that the model adequately samples the energy landscape both near and far-from-equilibrium. A highly desirable goal is minimize the number of training data, especially if the underlying reference model is first-principles based and hence expensive. In this work, we introduce an active learning (AL) scheme that trains a NN model on-the-fly with minimal amount of first-principles based training data. Our AL workflow is initiated with a sparse training dataset (similar to 1 to 5 data points) and is updated on-the-fly via a Nested Ensemble Monte Carlo scheme that iteratively queries the energy landscape in regions of failure and updates the training pool to improve the network performance. Using a representative system of gold clusters, we demonstrate that our AL workflow can train a NN with similar to 500 total reference calculations. Using an extensive DFT test set of similar to 1100 configurations, we show that our AL-NN is able to accurately predict both the DFT energies and the forces for clusters of a myriad of different sizes. Our NN predictions are within 30 meV/atom and 40 meV/angstrom of the reference DFT calculations. Moreover, our AL-NN model also adequately captures the various size-dependent structural and dynamical properties of gold clusters in excellent agreement with DFT calculations and available experiments. We finally show that our AL-NN model also captures bulk properties reasonably well, even though they were not included in the training data.

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

Crystallographic orientation-dependent strain hardening in a precipitation-strengthened Al-Cu alloy

While the strengthening of Al-Cu alloys due to precipitation has been extensively studied, the effect of crystallographic orientation of the matrix and precipitates, as well as precipitate morphology, on the strain hardening behavior is not well understood. In this paper, we investigate this effect with in situ neutron diffraction during deformation of an Al-Cu alloy (206) after multiple aging treatments. Precipitate-dislocation interactions were found to change from precipitate shearing for microstructures predominantly containing GPI and θ" precipitates to Orowan looping for microstructures with primarily θ' and θ precipitates. Notably, significant anisotropy in strain hardening behavior was observed when θ' precipitates were present, which was attributed to crystallographic orientation dependent load transfer from the Al matrix to the θ' precipitates. The anisotropic load transfer is hypothesized to be caused by the extent of rotation of high aspect-ratio θ' precipitates, owing to dislocations looping around them during plastic deformation of the matrix. Predictions from an analytical model describing the anisotropic magnitude of load transfer from precipitate rotation agree well with experimental results, successfully validating the precipitate rotation hypothesis and explaining the anisotropic strain hardening behavior. This model allows for the prediction of stresses separately in the precipitate and matrix phases as a function of crystallographic orientation, only given the bulk mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Small molecule crystals with 1D water wires modulate electronic properties of surface water networks

This work evaluates the effect of water vapor pressure on the surface conductivity of a hydrated small molecule crystal under dry and wet conditions. The crystal contains a discrete metal complex with waters of hydration in structural positions and in 1D water wires. Under dry conditions, the surface of the hydrated crystal behaves as a near ideal capacitor. Under wet conditions, the waters of hydration serve as a template to assemble surface water networks by organization of water from the environment. The surface water provides pathways for charge transfer attributed to proton mobility that increases conductivity by > 3 orders in magnitude. Modulation between wet and dry conditions tunes the conductivity of the crystal surface via a two-step process, which has been evaluated kinetically as a function of the water vapor pressure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Respiratory Vinyl Chloride Reductive Dechlorination to Ethene in TceA-Expressing Dehalococcoides mccartyi

Bioremediation of chlorinated ethenes in anoxic aquifers hinges on organohalide-respiring Dehalococcoidia expressing vinyl chloride (VC) reductive dehalogenase (RDase). The tceA gene encoding the trichloroethene-dechlorinating RDase TceA is frequently detected in contaminated groundwater but not recognized as a biomarker for VC detoxification. We demonstrate that tceA-carrying Dehalococcoides mccartyi (Dhc) strains FL2 and 195 grow with VC as an electron acceptor when sufficient vitamin B 12 (B 12 ) is provided. Strain FL2 cultures that received 50 μg L –1 B 12 completely dechlorinated VC to ethene at rates of 14.80 ± 1.30 μM day –1 and attained 1.64 ± 0.11 × 10 8 cells per μmol of VC consumed. Strain 195 attained similar growth yields of 1.80 ± 1.00 × 10 8 cells per μmol of VC consumed, and both strains could be consecutively transferred with VC as the electron acceptor. Proteomic analysis demonstrated TceA expression in VC-grown strain FL2 cultures. Resequencing of the strain FL2 and strain 195 tceA genes identified non-synonymous substitutions, although their consequences for TceA function are currently unknown. The finding that Dhc strains expressing TceA respire VC can explain ethene formation at chlorinated solvent sites, where quantitative polymerase chain reaction analysis indicates that tceA dominates the RDase gene pool.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Structures and Free Energies of Cerium Ions in Acidic Electrolytes

The Ce 3+ /Ce 4+ redox potential changes with the electrolyte, which could be due to unequal anion complexation free energies between Ce 3+ and Ce 4+ or a change in the solvent electrostatic screening. Ce complexation with anions and solvent screening also affect the solubility of Ce and charge transfer kinetics for electrochemical reactions involving waste remediation and energy storage. Here, we report the structures and free energies of cerium complexes n seven acidic electrolytes based on Extended X-ray Absorption Fine Structure, LTV vis, and Density Functional Theory calculations. Ce 3+ coordinates with nine water molecules as [Ce(H 2 O) 9 ] 3+ in all studied electrolytes. However, Ce 4+ complexes with anions in all electrolytes except HClO 4 . Thus, our results suggest that Ce 4+ anion complexation leads to the large shifts in standard redox potential. Long range screening effects are smaller than the anion complexation energies but could be responsible for changes in the Ce solubility with acid.

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

Aqueous-soluble bipyridine cobalt($\tiny{II}$/$\tiny{III}$) complexes act as direct redox mediators in photosystem I-based biophotovoltaic devices

Sustainable energy production is critical for meeting growing worldwide energy demands. Due to its stability and reduction potential, photosystem I (PSI) is attractive as the photosensitizer in biophotovoltaic devices. Herein, we characterize aqueous and organic solvent soluble synthetic bipyridine-based cobalt complexes as redox mediators for PSI-based biophotovoltaics applications. Cobalt-based complexes are not destructive to protein and have appropriate midpoint potentials for electron donation to PSI. We report on PSI stability in organic solvents commonly used in biophotovoltaics. We also show the effects of a mixed organic solvent phase on PSI reduction kinetics, slowing reduction rates approximately 8–38 fold as compared to fully aqueous systems, with implications for dye regeneration rates in PSI-based biophotovoltaics. Further, we show evidence of direct electron transfer from cobalt complexes to PSI. Finally, we report on photocurrent generation from Co mediator-PSI biophotovoltaic devices. Taken together, we discuss the development of novel Co complexes and our ability to fine-tune their characteristics via functional groups and counteranion choice to drive interaction with a biological electron acceptor on multiple levels from redox midpoints, spectral overlap, and solvent requirements, among others. This work suggests that fine-tuning of redox active species for interaction with a biological partner is possible for the creation and improvement of low cost, carbon-neutral energy production in the future.

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

A substituent-dependent deep-blue pyrene-based chemosensor for trace nitroaniline sensing

Nitroaniline (NA) is a kind of high toxicity and pathogenic amine derivative, and the trace monitoring of nitroaniline has become an urgent problem in terms of both the environment and security. Herein, two K-region multiple substituted pyrene-based luminogens with reasonable photoluminescence efficiency and blue emission (408–430 nm) have been synthesized and characterized. Their photophysical properties were carefully investigated in solution and in the solid state by experimental and density functional theory (DFT) methods. It is worth mentioning that both of these π-electron rich and extended π-conjugated materials were used for the detection of electron deficient nitroaromatics (NACs) based on a photo-induced electron transfer (PET) mechanism, and a sensitive response towards NA, especially for p-NA with a limit of detection (LOD) as low as 8.58 × 10 -9 M, was observed, with a fluorescence quenching efficiency up to 99.5%. In conclusion, these research results provided a low-cost and simple strategy for trace nitroaniline sensing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effect of hollow fiber membrane packing on the performance of modules formed with fiber tows

Membrane processes are the preferred option for many gas separations. Hollow fiber membranes are commonly used in these processes. Commercial hollow fiber membrane modules are often fabricated from small groups of fibers (i.e., a tow) that are arranged into a larger cylindrical bundle. The existence of fiber tows can lead to packing non-uniformity. This nonuniformity can result in nonideal fluid distribution in the shell and be detrimental to module performance. In this work, full three-dimensional models of flow and mass transfer within fiber bundles formed from tows have been developed. These models account for the detailed fiber arrangement within modules and are solved to evaluate module separation performance in terms of stage cut and required membrane area as a function product gas purity for carbon capture applications. Results are presented illustrating the effects of varying fiber packing arrangements within a tow and varying tow packing arrangements. Further, the results suggest smaller tows are preferred over larger tows, at fixed overall fiber packing and lower intra- and inter-tow packings are preferred. To reduce the computational cost of simulating large fiber bundles, the use of an equivalent planar bundle is proposed (EPB). A simple procedure for determining the geometry of the EPB is described and validated through comparisons of calculated performance metrics with results obtained from full three-dimensional simulations.

42 ENGINEERING↗
DOE OSTI2022

Alpert multi-wavelets for functional inverse problems: direct optimization and deep learning

Computational engineering models often contain unknown entities (e.g. parameters, initial and boundary conditions) that require estimation from other measured observable data. Estimating such unknown entities is challenging when they involve spatio-temporal fields because such functional variables often require an infinite-dimensional representation. Here, we address this problem by transforming an unknown functional field using Alpert wavelet bases and truncating the resulting spectrum. Hence the problem reduces to the estimation of few coefficients that can be performed using common optimization methods. We apply this method on a one-dimensional heat transfer problem where we estimate the heat source field varying in both time and space. The observable data is comprised of temperature measured at several thermocouples in the domain. This latter is composed of either copper or stainless steel. The optimization using our method based on wavelets is able to estimate the heat source with an error between 5% and 7%. We analyze the effect of the domain material and number of thermocouples as well as the sensitivity to the initial guess of the heat source. Finally, we estimate the unknown heat source using a different approach based on deep learning techniques where we consider the input and output of a multi-layer perceptron in wavelet form. We find that this deep learning approach is more accurate than the optimization approach with errors below 4%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Anisotropic hybridization in CeRhSn

The optical conductivity σ⁡(ω, T) of CeRhSn was studied by broadband infrared spectroscopy. Temperature-dependent spectral weight transfer occurs over high energy (0.8 eV) and temperature (~500 K) scales, classifying CeRhSn as a mixed-valent compound. The optical conductivity reveals a substantial anisotropy in the electronic structure. Renormalization of σ⁡(ω, T) occurs as a function of temperature to a coherent Kondo state with concomitant effective mass generation. Associated spectroscopic signatures were reproduced remarkably well by the combination of density functional theory and dynamical mean-field theory using a momentum-independent self-energy. The theory shows that the anisotropy for energies > 10 meV is mainly driven by the bare three-dimensional electronic structure that is renormalized by local electronic correlations. The possible influence of magnetic frustration and quantum criticality is restricted to lower energies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Partial muon capture rates in A = 3 and A = 6 nuclei with chiral effective field theory

Searches for neutrinoless-double beta decay rates are crucial in addressing questions within fundamental symmetries and neutrino physics. The rates of these decays depend not only on unknown parameters associated with neutrinos, but also on nuclear properties. In order to reliably extract information about the neutrino, one needs an accurate treatment of the complex many-body dynamics of the nucleus. Neutrinoless-double beta decays take place at momentum transfers on the order of 100 MeV/$c$ and require both nuclear electroweak vector and axial current matrix elements. Muon capture, a process in the same momentum transfer regime, has readily available experimental data to validate these currents. In this work, we present results of {\it ab initio} calculations of partial muon capture rates for $^3$He and $^6$Li nuclei using variational and Green's Function Monte Carlo computational methods. We estimate the impact of the three-nucleon interactions, the cutoffs used to regularize two-nucleon ($2N$) interactions, and the energy range of $2N$ scattering data used to fit these interactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

HPC Campaign Management: Remote data access with user-defined error bound using ADIOS and ZFP

Remote access to large-scale scientific datasets, like those generated by combustion simulations or other high-performance computing (HPC) applications, presents a significant challenge. Downloading entire datasets is often impractical due to their size and the bandwidth limitations of typical networks. To address this challenge, we propose a novel approach that enables efficient remote access to large datasets distributed across multiple facilities. Our method enables technologies to download only the data values of a select variable, in a select region of interest, to a user-defined accuracy. For this purpose, we extended the ADIOS IO library to provide read functions with user-defined accuracy, a remote data server that understands multidimensional selections of specific variables, steps and accuracy from an ADIOS dataset, and which uses lossy compression on the remote site to reduce the data to be transferred back to the client. In addition, our extension of the ADIOS library collects metadata from multiple datasets in small files called Campaign Archives, which can be shared among project participants on any HPC, cloud or laptop, and which can easily facilitate the discovery of content and pointers to the data location as well as remote access to the data by local tools as if data was local. This feature called Campaign Management, enables a group of scientists to manage related datasets stored in multiple files, across multiple facilities as if it was in a single file/database. We demonstrate the effectiveness of our approach using a 1.5 TB dataset from the S3D combustion simulation on Frontier at the Oak Ridge Leadership Facility. Even a single variable from this dataset, at 64 GB, is too large to be processed on a standard laptop. We show two different reading patterns for 2D plots and 3D visualization, with careful settings that a scientist studying combustion data would do and show that running the same Python scripts on Frontier directly takes comparable time than running them on the local laptop with remote access to the data on Frontier.

Podhorszki, Norbert [ORNL] (ORCID:000000019647542X↗