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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Enhanced Frequency Support Scheme of Generic Inverter-Based Resource Models for Renewable-Dominated Power Grids

The frequency response of SG-dominated power grids is predictable ahead of an occurrence of a frequency event because the frequency response of SGs is consistent, and it can be inferred from the swing equation [1]. However, increasing the portion of IBRs in an SG-dominated power grid might make the characteristics of the conventional power grids no longer valid because this changing resource mix affects grid dynamics and controls [2]. Thus, maintaining these characteristics greatly benefits the control and operation of the power grids with high penetration of IBRs. To maintain these characteristics in IBR-dominated power grids, IBRs should have frequency response capability similar to that of an SG. The WECC modeling validation subcommittee has developed generic IBR models for large system planning [3]-[5]. These models can represent various vendors' dynamic behavior for WTG, PV, and ESS [5]. The current generic IBR models approved by WECC can provide frequency response only from droop control loops in REPC models [6], [7]. The contribution of the loops is proportional to the frequency deviation from the nominal frequency. Thus, it presents an insufficient contribution to arrest frequency variation compared to the frequency response of SGs because it allows a high ROCOF in the early stage of frequency events. This shortfall will become greater as the PL of IBRs increases in power grids. Controller enhancement for the generic IBR models is required to secure the frequency stability under high PL of IBRs as in the SG-dominated power grids. This paper proposes a control extension for the generic IBR models to enhance the frequency support capabilities and discusses the classification of frequency support for the different types of IBR considering their operating constraints. An inertial control scheme is implemented in the REPC and REEC models of the generic IBR models to achieve these objectives. The inertial control scheme includes the following stages: Control area data acquisition, inertia time constant estimation, IBR-related constraint check, IBR contribution determination, and inertial response provision. In the scheme, a REPC acquires control area data from a system operator and estimates a total inertia time constant for the control area the applicable IBR power plant belongs. Then, the estimated inertial time constant is transferred to each IBR controller—REEC—within the power plant. Each REEC checks the availability of applicable IBR for inertial response participation. If the IBR is available, the REEC amplifies the estimated inertial time constant to utilize it for inertial response provision. In this way, the proposed inertial response scheme extends the functionality of the generic IBR models to provide SG-like frequency response within their constraints. Various scenarios considering different IBR types, IBR penetration levels, and frequency control schemes were simulated and compared in an IEEE 39-bus system using PSCAD simulator to verify the effectiveness of the proposed scheme.

Kim, Jinho↗
DOE OSTI2020

Measurement of Low-$Q^2$ Protons from Neutral Current Events in Argon with MicroBooNE

The MicroBooNE experiment is an 85 ton active mass liquid-argon time projection chamber located at the Fermilab Booster Neutrino Beamline. MicroBooNE’s ability to detect low-energy protons allows us to study single-proton events with a four-momentum transfer squared Q 2 as low as 0.10 GeV 2 . We present a differential cross-section measurement of a signal with one proton and no other particles (NC1p) in the final state. We report the flux-averaged NC1p differential cross section dσ/dT for neutrinos scattering on argon as a function of proton kinetic energy T using a subset of MicroBooNE’s data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Transfer Learning Meets Embedded Correlated Wavefunction Theory for Chemically Accurate Molecular Simulations: Application to Calcium Carbonate Ion Pairing

Achieving chemical accuracy for molecular simulations remains a central challenge in computational chemistry. Here, we present an embedded correlated wavefunction transfer learning (ECW-TL) framework for accurately simulating molecular dynamics in the condensed phase. ECW-TL incorporates high-level electron exchange and correlation effects in ECW theory while preserving the training and computational efficiency of machine-learned interatomic potentials. We demonstrate the framework on Ca 2+ –CO 3 2– ion pairing in aqueous solution, a key process underlying CO 2 mineralization in seawater. As proof of principle, we first show that fine-tuning a DFT-revPBE-D3(BJ) baseline model with embedded-DFT-SCAN data reproduces the DFT-SCAN free-energy surface within 1 kcal/mol across all solvation states. Extending the framework to embedded MP2 and localized natural-orbital CCSD(T) further refines the free-energy profile, revealing the crucial role of exact electron exchange and correlation in determining ion-pair stability and structure. The computed ion-pair association free energy is in quantitative agreement with experimental measurements, further validating the accuracy of the ECW-TL framework. ECW-TL thus provides a general, data-efficient route for transferring CW accuracy to efficient simulations of complex aqueous and interfacial chemical processes.

cluster chemistry↗
DOE OSTI2022

Impacts of Solvent Washing on the Electrochemical Remediation of Commercial End-of-Life Cathodes

Changes to surface structure and chemistry occurring throughout the functional lifetime of lithium-ion batteries (LIBs) may impact the effectiveness of end-of-life rejuvenation methods. Solvent washing prior to electrochemical relithiation is shown to both increase relithiation efficacy and beneficially alter the interfacial chemistry of heavily degraded industrial cathode material. Four common solvents (acetone, diethyl carbonate, isopropyl alcohol, propylene carbonate) are employed to investigate the role of varying physicochemical solvent properties on the mechanism of capacity recovery. Electrochemical (dQ/dV, EIS), structural (XRD), and chemical (SPME-GC-MS) analysis techniques are employed to comprehensively analyze solvent-cathode interactions. Highly nucleophilic solvents (acetone, DEC) are found to reduce cathode charge-transfer impedance and enable stable impedance growth throughout subsequent cycling. The use of nucleophilic solvents under mechanically aggressive washing conditions may also enable the reintroduction of bulk lattice oxygen, thereby restoring anionic redox capacity. Further, the four solvents are found to selectively remove a subset of surface species from the aged cathode material, including residual electrolyte, additives, and electrolyte-additive reaction products, which are qualitatively analyzed. Surface species removal by each solvent is correlated with the electrochemical performance of the correspondingly washed cathode, highlighting the importance of an optimized washing protocol to effective remediation in the context of direct LIB recycling. For the material under study, the use of a simple acetone washing protocol prior to electrochemical relithiation enables up to 174% capacity recovery relative to unwashed/relithiated black mass.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Fourier Analysis and Design of a Shielded 120kW Inductive Wireless System

High-power inductive wireless power transfer (WPT) systems for EVs are designed to meet specifications such as stray field, power level, efficiency, misalignment tolerance, and ground clearance. These metrics are all heavily influenced by the coil geometry. Herein this paper proposes a coil design method based on the Fourier Analysis Method (FAM) which is an analytical method for directly designing coil geometries to meet stray field and power level requirements through an optimization of Fourier basis function coefficients. In this work, two 120 kW WPT proof-of-concept demonstrators with low stray field and high efficiency are built from FAM optimization results to validate the models and show the impact of the FAM design process. Experimental validation of the Gen. 2 demonstrator at 120 kW output power resulted in a measured DC/DC efficiency of 97.2% at alignment with a 125 mm airgap. At the 120 kW test point, the stray fields 80 cm away from the center of the airgap between the coil assemblies were 3.4 µT(rms) on the X-axis and 3.5 µT(rms) on the Y-axis, much lower than the 27 µT(rms) ICNIRP limit.

42 ENGINEERING↗
DOE OSTI2022

Diffusion Monte Carlo approaches for studying nuclear quantum effects in fluxional molecules

Abstract Diffusion quantum Monte Carlo (DMC) provides a powerful approach for obtaining the ground state energy and wave function of molecules, ions, and molecular clusters. The approach is uniquely well suited for studies of fluxional molecules, which undergo large amplitude vibrational motions even in their ground state. In contrast to the electronic structure problem, where the wave function must be antisymmetric with respect to exchange of any pair of electrons, the wave function for the ground vibrational state is nodeless. This greatly simplifies the application of DMC for vibrational problems. Because there is not a single potential function that can be used to describe the intramolecular and intermolecular interactions in all molecular systems, most methods that are used to describe nuclear quantum effects rely on a carefully chosen zero‐order description of the molecular vibrations. In contrast, DMC calculations can be performed in Cartesian coordinates, making the DMC algorithm easily transferable between different chemical systems. In this contribution, the theory that underlies DMC will be discussed along with important considerations for performing DMC calculations. Extensions for evaluating vibrationally excited states and molecular properties are also discussed. Insights that can be obtained from DMC calculations are illustrated in the context of the protonated water clusters. This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods Theoretical and Physical Chemistry > Spectroscopy

Chemistry↗
DOE OSTI2024

Cluster expansion by transfer learning for phase stability predictions

Recent progress towards universal machine-learned interatomic potentials holds considerable promise for materials discovery. Yet the accuracy of these potentials for predicting phase stability may still be limited. In contrast, cluster expansions provide accurate phase stability predictions but are computationally demanding to parameterize from first principles, especially for structures of low dimension or with a large number of components, such as interfaces or multimetal catalysts. We overcome this trade-off via transfer learning. Using Bayesian inference, we incorporate prior statistical knowledge from machine-learned and physics-based potentials, enabling us to sample the most informative configurations and to efficiently fit first-principles cluster expansions. Furthermore, this algorithm is tested on Pt:Ni, showing robust convergence of the mixing energies as a function of sample size with reduced statistical fluctuations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Clades of huge phages from across Earth’s ecosystems

Bacteriophages typically have small genomes and depend on their bacterial hosts for replication. Here we sequenced DNA from diverse ecosystems and found hundreds of phage genomes with lengths of more than 200 kilobases (kb), including a genome of 735 kb, which is—to our knowledge—the largest phage genome to be described to date. Thirty-five genomes were manually curated to completion (circular and no gaps). Expanded genetic repertoires include diverse and previously undescribed CRISPR–Cas systems, transfer RNAs (tRNAs), tRNA synthetases, tRNA-modification enzymes, translation-initiation and elongation factors, and ribosomal proteins. The CRISPR–Cas systems of phages have the capacity to silence host transcription factors and translational genes, potentially as part of a larger interaction network that intercepts translation to redirect biosynthesis to phage-encoded functions. In addition, some phages may repurpose bacterial CRISPR–Cas systems to eliminate competing phages. We phylogenetically define the major clades of huge phages from human and other animal microbiomes, as well as from oceans, lakes, sediments, soils and the built environment. We conclude that the large gene inventories of huge phages reflect a conserved biological strategy, and that the phages are distributed across a broad bacterial host range and across Earth’s ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

An accurate and efficient Ehrenfest dynamics approach for calculating linear and nonlinear electronic spectra

Linear and nonlinear electronic spectra provide an important tool to probe the absorption and transfer of electronic energy. Here, we introduce a pure state Ehrenfest approach to obtain accurate linear and nonlinear spectra that is applicable to systems with large numbers of excited states and complex chemical environments. We achieve this by representing the initial conditions as sums of pure states and unfolding multi-time correlation functions into the Schrödinger picture. By doing this, we show that one can obtain significant improvements in accuracy over the previously used projected Ehrenfest approach and that these benefits are particularly pronounced in cases where the initial condition is a coherence between excited states. While such initial conditions do not arise when calculating linear electronic spectra, they play a vital role in capturing multidimensional spectroscopies. We demonstrate the performance of our method by showing that it is able to quantitatively capture the exact linear, 2D electronic spectroscopy, and pump–probe spectra for a Frenkel exciton model in slow bath regimes and is even able to reproduce the main spectral features in fast bath regimes.

Chemistry↗
DOE OSTI2023

Picosecond magneto-optic thermometry measurements of nanoscale thermal transport in AlN thin films

The thermal conductivity Λ of wide bandgap semiconductor thin films, such as AlN, affects the performance of high-frequency devices, power devices, and optoelectronics. However, accurate measurements of Λ in thin films with sub-micrometer thicknesses and Λ > 100 W m -1 K -1 is challenging. Widely used pump/probe metrologies, such as time–domain thermoreflectance (TDTR) and frequency–domain thermoreflectance, lack the spatiotemporal resolution necessary to accurately quantify thermal properties of sub-micrometer thin films with high Λ. In this work, we use a combination of magneto-optic thermometry and TiN interfacial layers to significantly enhance the spatiotemporal resolution of pump/probe thermal transport measurements. We use our approach to measure Λ of 100, 400, and 1000 nm AlN thin films. We coat AlN thin films with a ferromagnetic thin-film transducer with the geometry of (1 nm-Pt/0.4 nm-Co) x3 /(2 nm-TiN). This PtCo/TiN transducer has a fast thermal response time of <50 ps, which allows us to differentiate between the thermal response of the transducer, AlN thin film, and substrate. For the 100, 400, and 1000 nm thick AlN films, we determine Λ to be 200 ± 80, 165 ± 35, and 300 ± 70 W m -1 K -1 , respectively. We conclude with an uncertainty analysis that quantifies the errors associated with pump/probe measurements of thermal conductivity, as a function of transducer type, thin-film thermal conductivity, and thin-film thickness. Time resolved magneto-optic Kerr effect experiments can measure films that are three to five times thinner than is possible with standard pump/probe metrologies, such as TDTR. This advance in metrology will enable better characterization of nanoscale heat transfer in high thermal conductivity material systems like wide bandgap semiconductor heterostructures and devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Kinetic Modeling and Experimental Studies of Capacitively Coupled Macro- and Microplasmas at Microwave Frequencies

The effect of driving frequency in the range of 13.56 MHz to 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 eV to 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 OSTI2026

Power Electronics Module with Integrated Ceramic Heat Exchanger

NREL, in partnership with Synteris and Packet Digital, has developed a 3D-printable ceramic package for power electronic modules to improve their thermal management, power density, performance, and lifetime. Existing power modules contain flat ceramic substrates that serve as both the electrically insulating component and thermal conductor that transfer the large heat outputs of these devices. The team has developed an additive manufacturing process that replaces the traditional insulating metalized substrate, substrate attach, and baseplate/heat exchanger with an additively-manufactured ceramic packaging that acts as both an electrical insulator and heat exchanger for better thermal management. The design, manufacturability, and function of this power module will be discussed.

25 ENERGY STORAGE↗
DOE OSTI2022

How a Formate Dehydrogenase Responds to Oxygen: Unexpected O 2 Insensitivity of an Enzyme Harboring Tungstopterin, Selenocysteine, and [4Fe–4S] Clusters

The reversible two-electron interconversion of formate and CO 2 is catalyzed by both nonmetallo- and metallo-formate dehydrogenases (FDHs). The latter group comprises molybdenum- or tungsten-containing enzymes with the metal coordinated by two equivalents of a pyranopterin cofactor, a cysteinyl or selenocysteinyl (Sec) ligand supplied by the polypeptide, and a catalytically essential terminal sulfido ligand. In addition, these biocatalysts incorporate one or more [4Fe–4S] clusters for facilitating long-distance electron transfer. However, an interesting dichotomy arises when attempting to understand how the metallo-FDHs react with O 2 . Whereas existing scholarship portrays these enzymes as being unable to perform in air due to extreme O 2 lability of their metal centers, studies dating as far back as the 1930s emphasize that some of these systems exhibit formate oxidase (FOX) activity, coupling formate oxidation to O 2 reduction. Therefore, to reconcile these conflicting views, we explored context-dependent functional linkages between metallo-FDHs and their cognate electron acceptors within the same organism vis-à-vis catalysis under atmospheric O 2 . Here, we report the discovery and characterization of an O 2 -insensitive FDH2 from the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough (DvH) that ligates tungsten, Sec, and four [4Fe–4S] clusters. By advancing a robust expression platform for its recombinant production, we eliminate both the requirement of nitrate or azide during purification and reductive activation with thiols and/or formate prior to catalysis. Because the distinctive spectral signatures of formate-reduced DvH-FDH2 remain invariant under anaerobic and aerobic conditions, we benchmarked the enzyme activity in air, identifying CO 2 as the catalytic product. Full reaction progress curve analysis discloses a high catalytic efficiency when probed with a high-potential artificial electron acceptor. Furthermore, we show that DvH-FDH2 enables near-stoichiometric hydrogen peroxide production without superoxide release to achieve O 2 insensitivity. Notably, simultaneous electron transfer to cytochrome c and O 2 reveals that metal-based electron bifurcation is operational in this system. Taken together, our work proves the co-occurrence of redox bifurcated FDH and FOX activities within a metalloenzyme scaffold. These findings set the stage for uncovering previously unknown O 2 -insensitive flavin-based electron bifurcation mechanisms, as well as for developing authentic formate/air biofuel cells, engineering O 2 -stable FDHs and biohybrid metallocatalysts, and discerning formate bioenergetics of gut microbiota.

13C NMR↗
DOE OSTI2021

Davis Computational Spectroscopy Workflow—From Structure to Spectra

Here, we describe an automated workflow that connects a series of atomic simulation tools to investigate the relationship between atomic structure, lattice dynamics, materials properties, and inelastic neutron scattering (INS) spectra. Starting from the atomic simulation environment (ASE) as an interface, we demonstrate the use of a selection of calculators, including density functional theory (DFT) and density functional tight binding (DFTB), to optimize the structures and calculate interatomic force constants. We present the use of our workflow to compute the phonon frequencies and eigenvectors, which are required to accurately simulate the INS spectra in crystalline solids like diamond and graphite as well as molecular solids like rubrene. We have also implemented a machine-learning force field based on Chebyshev polynomials called the Chebyshev interaction model for efficient simulation (ChIMES) to improve the accuracy of the DFTB simulations. We then explore the transferability of our DFTB/ChIMES models by comparing simulations derived from different training sets. We show that DFTB/ChIMES demonstrates ~100× reduction in computational expense while retaining most of the accuracy of DFT as well as yielding high accuracy for different materials outside of our training sets. The DFTB/ChIMES method within the workflow expands the possibilities to use simulations to accurately predict materials properties of increasingly complex structures that would be unfeasible with ab initio methods.

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

Enhancing Nitrogen Activation in Electrochemical Reduction: The Role of Rare Earth Oxide Surface Configurations

The pursuit of sustainable ammonia synthesis has prompted the exploration of ambient electrochemical nitrogen reduction reaction (e-NRR) as an alternative to the energy-intensive Haber-Bosch process. Here, this study conducted a theoretical investigation into the use of rare earth oxide materials, specifically dysprosium oxide (Dy 2 O 3 ), as potential electrocatalysts for NRR. Utilizing spin-polarized density functional theory calculations, we explored the interaction between Dy 2 O 3 surfaces and nitrogen (N 2 ) molecules, examining the capability of Dy 2 O 3 to adsorb and activate N 2 under ambient conditions. The results indicate that Dy 2 O 3 surfaces exhibit diverse configurations and bonding environments, providing a variety of reactive sites that display different behaviors in N 2 adsorption and activation. The distinctive electronic structure and surface chemistry of a particular Dy 2 O 3 surface configuration were found to significantly enhance the activation of N 2 by promoting charge transfer, which facilitates the NRR process. This research provides deep insights into the mechanistic pathways of N 2 reduction over Dy 2 O 3 , highlighting the surface properties as pivotal in catalysis. These theoretical insights serve as a foundation for the development of novel rare earth-based electrocatalytic materials for efficient ambient e-NRR, potentially transforming ammonia production into a greener and more energy-efficient process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Process intensification of CO 2 capture by low-aqueous solvent

Low-energy solvent-based CO 2 absorption processes have drawn attention as a next-generation post-combustion CO 2 capture technology to reduce CO2 emissions from fossil fuel– or biomass-fired power generation and industrial flue gas streams. A low-aqueous (or water-lean) solvent process may substantially reduce the thermal energy consumption for solvent regeneration. Low-aqueous solvent–based processes are thermally sensitive, requiring a delicate temperature control within the absorber because of the fast exothermic amine-CO 2 reaction and low heat capacity organic diluent. This reaction may result in heat accumulation in a packed absorption column and undesirable CO 2 desorption occurring as the solvent moves through the column, reducing the solvent’s CO 2 capture efficiency if its temperature is not controlled. Using a 3D printed intensified packing device, enhanced heat and mass transfer were demonstrated in an amine-CO 2 scrubbing process using low-aqueous solvent. The multifunctional intensified device facilitates contact of the reactive solvent and gas phases in a single stage and heat removal by a cooling fluid flowing through channels in the interior of the corrugated plates of the device. These functionalities led to effective thermal management along the column via intrastage cooling and significant improvement in CO 2 uptake under a wide range of operating conditions. Intrastage cooling effectively reduced the solvent average temperature along the column by ~10 °C and, as a result, the solvent’s capture efficiency improved by up to 25%.

42 ENGINEERING↗
DOE OSTI2020

Insights into Mechanisms of Screw Feeder Plugging by Heated Pine Forestry Residues Using in-situ and Correlative Microscopy

Increasing concerns about global carbon emissions due to fossil fuel use has created interest in renewable fuel alternatives, such as lignocellulosic biomass. With an estimated global biomass production probability ten-fold higher than projected need, functionalizing and scaling biomass conversion processes, like pyrolysis, is a promising component of a diverse sustainable energy program (Kan, Strezov, & Evans, 2016). Pyrolysis reactors employed in biomass conversion often encounter the known problem of screw feeder plugging, halting work and reducing efficiency of biorefineries. Although the screw feeder is not heated directly, conductive heat transfer from the fluidized bed pyrolysis reactor creates a temperature gradient, where particles experience temperatures between 22°C and 500°C from the time they enter the feeder to being emptied into the reactor (Digman, Joo, & Kim, 2009; Nieminen & Folke, 1982). The impact of unintentional heating on this highly variable feedstock may result in particle morphology modification, surface texture transformation, and the evolution of viscous compounds and may contribute to screw feeder plugging (Haas, Nimlos, & Donohoe, 2009; Ingram et al., 2008). We hypothesized that particles of various anatomical fractions (including needles, branches, bark, cambium, and whitewood) will experience dramatic changes during this heating regime, which will be characterized by decreased particle size, increased surface roughness, degradation of key structural macromolecules, and generation of viscous compounds that would result in increased particle friction and cohesion, contributing to screw feeder plugging.

biofuels↗