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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Bayesian estimations of orientation distribution functions from small-angle scattering enable direct prediction of mechanical stress in anisotropic materials

Properties of soft materials are influenced by their anisotropic structuring under nonequilibrium fields. Although anisotropic structure-property relationships have been extensively explored theoretically, comparison to experiments requires determination of the microstructural orientation probability distribution function (OPDF) of microstructural elements. Small angle scattering (SAS) measurements encode information about the OPDF, but tools to navigate this connection are incomplete. Here, we develop and validate an explicit framework to link arbitrary OPDFs to SAS measurements. Specifically, we propose, validate, and apply a method, maximum a posteriori scattering inference (MAPSI), whereby the OPDF may be obtained from SAS measurements using a Bayesian estimation method. Using this method, we obtain estimates of the full 3D OPDF for two model semidilute fd-virus (rodlike) dispersions at concentrations that are approximately equal to and twice the overlap concentration. From the OPDF, we calculate its second and fourth moments and compare these to predictions for a dilute suspension of rigid rods and to a recent theory for semidilute suspensions. Finally, we use both the theoretical and measured moments to calculate the stress, both for dilute and semidilute suspensions. These predictions are not only compared to each other, but also to measured values of the shear stress, and point to new insights into the behavior of suspensions of highly elongated particles in the transition between dilute and semidilute behavior. We also use this new framework to provide perspective on the connection between scalar parameterizations of scattering and the OPDF that have frequently been used in the past. Here, the new tools developed in this work provide an unprecedented path toward experimental validation of dynamical theories of rodlike colloids and polymers, and for measurement of nonequilibrium structures and stresses of other complex fluids and soft materials with SAS.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Collinear Three-Photon Excitation of a Strongly Forbidden Optical Clock Transition

The 1 𝑆 0 − 3 𝑃 0 clock transition in strontium serves as the foundation for the world’s best atomic clocks and for gravitational wave detector concepts in clock atom interferometry. This transition is weakly allowed in the fermionic isotope 87 Sr but strongly forbidden in bosonic isotopes. Here, we demonstrate coherent excitation of the clock transition in bosonic 88 Sr using a novel collinear three-photon process in a weak magnetic field. We observe Rabi oscillations with frequencies of up to 50 kHz using W/cm 2 laser intensities and Gauss-level magnetic field amplitudes. The absence of nuclear spin in bosonic isotopes offers decreased sensitivity to magnetic fields and optical lattice light shifts, enabling atomic clocks with reduced systematic errors. The collinear propagation of the laser fields permits the interrogation of spatially separated atomic ensembles with common laser pulses, a key requirement for dark matter searches and gravitational wave detection with next-generation quantum sensors.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Quantum-enhanced sensing of displacements and electric fields with two-dimensional trapped-ion crystals

Fully controllable ultracold atomic systems are creating opportunities for quantum sensing, yet demonstrating a quantum advantage in useful applications by harnessing entanglement remains a challenging task. Here, we realize a many-body quantum-enhanced sensor to detect displacements and electric fields using a crystal of ~150 trapped ions. The center-of-mass vibrational mode of the crystal serves as a high- Q mechanical oscillator, and the collective electronic spin serves as the measurement device. By entangling the oscillator and collective spin and controlling the coherent dynamics via a many-body echo, a displacement is mapped into a spin rotation while avoiding quantum back-action and thermal noise. We achieve a sensitivity to displacements of 8.8 ± 0.4 decibels below the standard quantum limit and a sensitivity for measuring electric fields of 240 ± 10 nanovolts per meter in 1 second. Feasible improvements should enable the use of trapped ions in searches for dark matter.

Gilmore, Kevin A.↗
DOE OSTI2025

Hybridization capture sequencing for Vibrio spp. and associated virulence factors

ABSTRACT Proliferation ofVibriospp. in aquatic ecosystems is associated with climate change and, concomitantly, increased incidence of vibriosis. They are autochthonous to aquatic environments globally, but traditional metagenomic methods for detecting and typing pathogenicVibriospp. are challenged by their presence in relatively low abundance and ability to persist in a viable but nonculturable state. In the study reported here, hybridization capture sequencing (HCS) was employed to profile low-abundanceVibriospp. in environmental samples. The HCS panel targeted a family of molecular chaperones (CPN60) specific to 69Vibriospp. and 162Vibrio-specific virulence factors. This approach was evaluated in parallel with traditional whole-community shotgun sequencing in a metagenomic analysis of water and oyster samples collected from the Chesapeake Bay. In addition,Vibrio parahaemolyticusandVibrio vulnificusstrains isolated from the samples were subjected to whole-genome sequencing to determine the genetic characteristics of pathogenicVibriospp. circulating in an aquatic environment. HCS, employed to determine the incidence and characterization of specificVibriospp., yielded significantly greater metagenomic insight, notably a variety of otherVibriospp., including detection ofVibrio cholerae,Vibrio fluvialis, andVibrio aestuarianus, in addition toVibrio parahaemolyticusandVibrio vulnificus, and also important virulence factors not detectable using traditional molecular methods. Thus, pathogenicVibriospp. in aquatic ecosystems may be far more common than currently understood. It is concluded that environmental surveillance should include HCS, a valuable tool for the detection and characterization of pathogenic agents in aquatic ecosystems, notably vibrios. IMPORTANCE The increasing prevalence of pathogenicVibriospp. in aquatic ecosystems, driven by climate change, is closely linked to a rise in cholera and vibriosis cases, emphasizing the need for improved environmental surveillance. Vibrios are naturally occurring in aquatic environments globally, but traditional metagenomic methods for detecting and typing pathogenicVibriospp. are challenged by their presence in relatively low abundance and ability to persist in a viable but nonculturable state. In the study reported here, hybridization capture sequencing was employed to profile low-abundanceVibriospp. in metagenomic samples, namely water and oysters collected from the Chesapeake Bay. This approach was evaluated in parallel with traditional whole-community shotgun sequencing and whole-genome sequencing ofVibrio parahaemolyticusandVibrio vulnificusstrains isolated from the samples. Results suggest pathogenicVibriospp. in aquatic ecosystems may be far more common than currently understood, when multiple methods are considered for environmental surveillance.

Microbiology↗
DOE OSTI2023

Modeling Electrochemical and Rheological Characteristics of Suspension-Based Electrodes for Redox Flow Cells

Flowable suspension-based electrodes (FSEs) have gained attention in recent years, as the integration of solid materials into electrochemical flow cells can offer improved performance and flexible operation. However, under conditions that engender favorable electrochemical properties (e.g., high particle loading, high conductivity, high surface area), FSEs can exhibit non-Newtonian characteristics that impose large pumping losses and flow-dependent transport rates. These multifaceted trade-offs motivate the use of models to broadly explore scaling relationships and better understand design rules for electrochemical devices. To this end, we present a one-dimensional model, integrating porous electrode theory with FSE rheology as well as flow-dependent electron and mass transport under pressure-driven flow. We study FSE behavior as a function of material properties and operating conditions, identifying key dimensionless groups that describe the underlying physical processes. We assess flow cell performance by quantifying electrode polarization and relative pumping losses, establishing generalized property-performance relationships for FSEs. Importantly, we expound relevant operating regimes—based on a subset of dimensionless groups—that inform practical operating envelopes, ultimately helping to guide FSE and cell engineering for electrochemical systems.

25 ENERGY STORAGE↗
DOE OSTI2023

Providing Geospatial Intelligence through a Scalable Imagery Pipeline

This chapter describes ORNL’s (Oak Ridge National Laboratory’s) contributions to imagery preprocessing for geospatial intelligence research and development (R&D) in four sections. First, we discuss challenges involved in building an effective imagery preprocessing workflow and the world-class high-performance computing (HPC) resources at ORNL available to process petabytes of imagery data. Second, we highlight how we developed imagery preprocessing tools over three decades while paving the way for our current cutting-edge machine learning and computer vision algorithms that are impacting humanitarian and disaster response efforts. Third, we discuss how PIPE modules work together to turn raw images into analysis-ready datasets. Fourth, we look toward the future and discuss planned advancements to PIPE and computing trends that will affect geospatial intelligence R&D.

Reith, Andrew↗
DOE OSTI2025

High-fidelity holographic beam shaping with optimal transport and phase diversity

A phase-only spatial light modulator (SLM) provides a powerful way to shape laser beams into arbitrary intensity patterns but at the cost of a hard computational problem of determining an appropriate SLM phase. Here, we show that optimal transport methods can generate approximate solutions to this problem that serve as excellent initializations for iterative phase retrieval algorithms, yielding vortex-free solutions with superior accuracy and efficiency. Additionally, we show that analogous algorithms can be used to measure the intensity and phase of the input beam incident upon the SLM via phase diversity imaging. These techniques furnish flexible and convenient solutions to the computational challenges of beam shaping with an SLM.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Supply Chain Sustainability Analysis of Renewable Hydrocarbon Fuels via Indirect Liquefaction, Ex Situ Catalytic Fast Pyrolysis, Hydrothermal Liquefaction, Combined Algal Processing, and Biochemical Conversion: Update of the 2019 State-of-Technology Cases

This technical report describes the supply chain sustainability analysis (SCSAs) for the production of renewable hydrocarbon transportation fuels via a range of conversion technologies: (1) renewable high octane gasoline (HOG) via indirect liquefaction (IDL) of woody lignocellulosic biomass (note that the IDL pathway in this SCSA represents the syngas conversion design in the 2019 SOT); (2) renewable gasoline (RG) and diesel (RD) blendstocks via ex situ catalytic fast pyrolysis of woody lignocellulosic biomass; (3) RD via hydrothermal liquefaction (HTL) of wet sludge from a wastewater treatment plant; (4) renewable hydrocarbon fuels via biochemical conversion of herbaceous lignocellulosic biomass; (5) renewable diesel via HTL of a blend of algae and woody biomass; and (6) renewable diesel via combined algae processing (CAP). This technical report focuses on the environmental performance of these six biofuel production pathways in their 2019 SOT cases. The results of these renewable hydrocarbon fuel pathways in these SCSA analyses update those for the respective 2018 SOT cases. They also provide an opportunity to examine the impact of technology improvements in both biomass feedstock production and biofuel production that have been achieved in 2019 SOTs on the sustainability performance of these renewable transportation fuels, and they reflect updates to Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model, which was released in October 2019. These GREET updates include the production of natural gas, electricity, and petroleum-based fuels that can influence biofuels’ supply chain greenhouse gas (GHG) (CO₂, CH₄, and N₂O) emissions, water consumption, and air pollutant emissions. GHG emissions, water consumption, and nitrogen oxides (NO x ) emissions are the main sustainability metrics assessed in this analysis. In this analysis, we define water consumption as the amount of water withdrawn from a freshwater source that is not returned (or returnable) to a freshwater source at the same level of quality. Life-cycle fossil energy consumption and net energy balance, which is the life-cycle fossil energy consumption deducted from the renewable biofuel energy produced, are also assessed.

09 BIOMASS FUELS↗
DOE OSTI2020

Wet Waste Hydrothermal Liquefaction and Biocrude Upgrading to Hydrocarbon Fuels (2019 State of Technology)

Each year, the DOE Bioenergy Technologies Office (BETO) assesses progress in their research and development efforts toward sustainable production of renewable fuels. Technical and cost targets were previously established for the wet waste hydrothermal liquefaction and biocrude upgrading pathway and summarized in a design report. The present report summarizes the research and associated techno-economic analysis (TEA) in support of the 2019 state of technology (SOT) assessment for this pathway. Data from Pacific Northwest National Laboratory’s Conversion hydrothermal liquefaction (HTL) program for wet waste was used to update the pathway techno-economic analysis (TEA) for the fiscal year 2019 State of Technology (2019 SOT). An overview of the current process model, experimental data and plant economics for the SOT is presented.

09 BIOMASS FUELS↗
DOE OSTI2020

Integrated Strategies to Enable Lower-Cost Biofuels

This report summarizes the findings of a qualitative analysis to identify integrated strategies needed for more affordable biofuels. It outlines five key strategies needed to achieve lower fuel production costs in an integrated biorefinery and provides high-level research needs across the biofuel supply chain.

09 BIOMASS FUELS↗
DOE OSTI2020

Techno-Economic Analysis of Synthetic Fuels Pathways Integrated with Light Water Reactors

The purpose of this work is to identify, model, and compare two possible synfuel production routes utilizing CO 2 as the feedstock. Heat from an LWR nuclear plant is integrated wherever possible as a means to positively affect the economics of the LWR. Process and economic modeling for a conceptual synfuel production plant co-located (or in near proximity) with an LWR is presented, including the cost of CO 2 captured from an ethanol plant, compressed, and transported to the LWR hybrid plant, co-electrolysis of the CO 2 with water in a solid oxide electrolyzing cell (SOEC) system to produce syngas, and thermo-catalytic conversion of the syngas to transportation fuel. The hybrid LWR/synfuels plant is assumed to be located within 50-150 miles of an ethanol plant, e.g., located in the Midwest region of the United States. Performance and nth plant economics for the co-electrolysis-based processes are evaluated and compared with biomass-gasification-based technology for the synfuel routes considered. Sensitivity analysis around the price of CO 2 and electricity, two of the major cost drivers, is presented for each case. Consideration of a carbon credit is also included in the sensitivity analysis.

08 HYDROGEN↗
DOE OSTI2020

The future of the NPT: REVCON and beyond

The Treaty on the Nonproliferation of Nuclear Weapons (NPT), with its quinquennial review conferences (RevCons), has become the foundation of the international nonproliferation regime over the course of its 50-year history. With more states parties than any other arms control agreement (currently 191), the Treaty provides a legally binding framework for all states parties, constraining proliferation of nuclear weapons and committing the five recognized states who possess nuclear weapons to work toward disarmament. The NPT has enjoyed wide success in constraining the spread of nuclear weapons. Only one state party has left the agreement and gone on to acquire these weapons, and the overall track record of compliance with IAEA safeguards has been robust. However, for all its effectiveness in the area of nonproliferation, its achievements on the disarmament front have been relatively unimpressive. While the NWS – most notably the United States and the Soviet Union/Russia – have decreased the overall size of their nuclear arsenals significantly since 1970, these arsenals have remained an important feature of NWS security policies. The limited progress towards disarmament has created friction between the NNWS and NWS and has been the source of mounting tension within the NPT regime. The 2020 RevCon, the 50th anniversary of the NPT and 25th anniversary of its indefinite extension, faces a range of contentious challenges, old and new, which call into question the Treaty’s future viability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A Bayesian Neural Network Ensemble Approach for Improving Large-Scale Streamflow Predictability

Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g.,AI driven model/component/parameterization selection). We propose a Bayesian neural network ensemble approach for improving large-scale streamflow predictability and understanding in a changing environment that combines multiple Earth system land model predictions by calculating spatiotemporally varying model weights and biases while accounting for various types of observations at multiple scales with uncertainty.

58 GEOSCIENCES↗
DOE OSTI2020

Techno-Economic Analysis of Synthetic Fuels Pathways Integrated with Light Water Reactors

The purpose of this work is to identify, model, perform techno-economic analysis, and compare two possible synfuel production routes utilizing CO 2 as the feedstock. Heat from an LWR nuclear plant is integrated wherever possible to positively affect the economics of the LWR by converting power to fuels during times of low grid electricity demand. Process and economic modeling for a conceptual synfuel production plant co-located (or in near proximity) with an LWR is presented, including the cost of CO 2 captured from an ethanol plant, compressed, and transported to the LWR hybrid plant, co-electrolysis of the CO 2 with water in a solid oxide electrolyzing cell (SOEC) system to produce syngas, and thermocatalytic conversion of the syngas to transportation fuel. The hybrid LWR/synfuels plant is assumed to be located within 50–150 miles of an ethanol plant (e.g., located in the midwest region of the United States). Performance and nth-plant economics for the co-electrolysis-based processes are evaluated and compared with biomass-gasification-based technology for the synfuel routes considered. Sensitivity analysis around the price of CO 2 and electricity, two of the major cost drivers, is presented for each case. Consideration of a carbon credit is also included in the sensitivity analysis.

10 SYNTHETIC FUELS↗
DOE OSTI2021

Microalgae Conversion to Biofuels and Biochemical via Sequential Hydrothermal Liquefaction (SEQHTL) and Bioprocessing: 2020 State of Technology

A preliminary techno-economic analysis (TEA) was developed for the fiscal year 2020 state of technology (SOT) assessment to evaluate the benefits and risks for a large-scale microalga hydrothermal liquefaction (HTL) system based on most recent testing results. The focus of the study is directed toward the conversion system, which consists of five processes: two-stage sequential HTL (SEQHTL), biocrude upgrading to final fuels, bioprocessing for co-product generation, hydrogen generation, and steam cycle. In this system, algae biomass with corn stover supplement during the lower algae productivity seasons (winter, fall, and spring) to match the maximum algae seasonal production rate in summer is employed to maintain a constant plant capacity in all the seasons. Algae only (summer season) or algae/corn stover blended feedstock (other seasons) are sent to a two-stage SEQHTL process. In stage I, the carbohydrates in the feedstock are extracted and separated from the residual solid. The residual solid from stage I is further converted to biocrude in the SEQHTL stage II step. The biocrude is upgraded to final fuel products in an upgrading process. The extract stream from HTL stage I is sent to the bioprocessing section for co-product generation via fermentation of carbohydrate. Lactic acid (LA) is assumed to be the co-product based on current bioprocessing testing results.

09 BIOMASS FUELS↗