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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 631 records · Page 35

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DOE OSTI2015

Nanotag-enabled photonic crystal fiber as quantitative surface-enhanced Raman scattering optofluidic platform

Core-shell nanotags that are active in surface-enhanced Raman scattering (SERS) and entrapped with thiocyanate (SCN) label molecules were immobilized in the air channels of suspended-core photonic crystal fiber (PCF) to impart quantitative capacity to SERS-based PCF optofluidic sensing platform. The Raman intensity of Rhodamine 6G increases with concentration, whereas the intensity of SCN remains constant when measured using this platform. The signal from the SCN label can be used as an internal reference to establish calibration for quantitative measurements of analytes of unknown concentrations. The long optical path-length PCF optofluidic platform integrated with SERS-active core-shell nanotags holds significant promise for sensitive quantitative chem/bio measurements with the added benefit of small sampling volume. The dependence of SERS intensity on the nanotag coverage density and PCF length was interpreted based on numerical-analytical simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

State-specific tunneling lifetimes from classical trajectories: H-atom dissociation in electronically excited pyrrole

A trajectory method of calculating tunneling probabilities from phase integrals along straight line tunneling paths, originally suggested by Makri and Miller [J. Chem. Phys. 91, 4026 (1989)] and recently implemented by Truhlar and co-workers [Chem. Sci. 5, 2091 (2014)], is tested for one- and two-dimensional ab initio based potentials describing hydrogen dissociation in the {sup 1}B{sub 1} excited electronic state of pyrrole. The primary observables are the tunneling rates in a progression of bending vibrational states lying below the dissociation barrier and their isotope dependences. Several initial ensembles of classical trajectories have been considered, corresponding to the quasiclassical and the quantum mechanical samplings of the initial conditions. It is found that the sampling based on the fixed energy Wigner density gives the best agreement with the quantum mechanical dissociation rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

FRIB Cryogenic Distribution System and Status

The MSU-FRIB cryogenic distribution system supports the 2 K primary, 4 K primary, and 35 - 55 K shield operation of more than 70 loads in the accelerator and the experimental areas. It is based on JLab and SNS experience with bayonet-type disconnects between the loads and the distribution system for phased commissioning and maintenance. The linac transfer line, which features three separate transfer line segments for additional independence during phased commissioning at 4 K and 2 K, connects the folded arrangement of 49 cryomodules and 4 superconducting dipole magnets and a fourth transfer line supports the separator area cryo loads. The pressure reliefs for the transfer line process lines, located in the refrigeration room outside the tunnel/accelerator area, are piped to be vented outdoors. The transfer line designs integrate supply and return flow paths into a combined vacuum space. The main linac distribution segments are produced in a small number of standard configurations; a prototype of one such configuration has been fabricated at Jefferson Lab and has been installed at MSU to support testing of a prototype FRIB cryomodule.

Ganni, Venkatarao↗

DOE OSTI2017

First-principles and model simulation of all-optical spin reversal

All-optical spin switching is a potential trailblazer for information storage and communication at an unprecedented fast rate free of magnetic fields. However, the current wisdom is largely based on semiempirical models of effective magnetic fields and heat pulses, so it is difficult to provide high-speed design protocols for actual devices. In this paper we carry out a massively parallel first-principles and model calculation for 13 spin systems and magnetic layers, free of any effective field, to establish a simpler and alternative paradigm of laser-induced ultrafast spin reversal and to point out a path to a full-integrated photospintronic device. It is the interplay of the optical selection rule and sublattice spin orderings that underlines seemingly irreconcilable helicity-dependent and -independent switchings. Using realistic experimental parameters, we predict that strong ferrimagnets, in particular, Laves phase C15 rare-earth alloys, meet the telecommunication energy requirement of 10 fJ, thus allowing a cost-effective subpicosecond laser to switch spin in the gigahertz region.

36 MATERIALS SCIENCE↗

DOE OSTI2025

ATcT — Active Thermochemical Tables Python Interface

SF-25-140 atct is a lightweight, Python client for the ATcT v1 API that enables programmatic access to high-accuracy thermochemical data and turnkey reaction-enthalpy analysis. The package implements full v1 endpoint coverage (species lookup by ATcT ID, name, formula, SMILES, InChI, CAS RN; covariance queries; health checks) with robust error handling, retries, and environment-based configuration for local/production endpoints. Beyond data retrieval, atct provides rigorously implemented reaction calculators that propagate uncertainties via either (i) a conventional independent-errors method (0 K or 298.15 K) or (ii) covariance-aware propagation using provided covariances at 298.15 K. Typed data classes ensure transparent, reproducible data structures and carry ATcT Thermochemical Network (TN) version identifiers for provenance. Dual import paths and comprehensive examples facilitate integration into research pipelines, enabling reproducible thermochemical calculations, automated validation, and downstream method development.

Bross, DavidHamilton [Argonne National Laboratory ↗

DOE OSTI2015

Analysis of Modeling Parameters on Threaded Screws

Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation properties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connection. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.

42 ENGINEERING↗

DOE OSTI2015

A Reduced Order Model of Force Displacement Curves for the Failure of Mechanical Bolts in Tension.

Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry causes issues when generating a mesh of the model. This report will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.

42 ENGINEERING↗

DOE OSTI2015

Lignocellulosic Biomass for Advanced Biofuels and Bioproducts: Workshop Report, Washington, DC, June 23-24, 2014

Multiple societal benefits underlie the U.S. Department of Energy’s (DOE) support for a viable and sustainable domestic lignocellulosic advanced biofuels and bioproducts industry. These benefits include ensuring future energy security, lowering greenhouse gases to mitigate climate impacts, diversifying the range of available products, producing less toxic chemicals and byproducts, creating jobs in rural areas, and improving the trade balance. A DOE workshop sought ways to realize these benefits by accelerating the emergence of a robust, new cellulosic ethanol industry. The resulting report, Breaking the Biological Barriers to Cellulosic Ethanol (U.S. DOE 2006), outlined a path toward this future, emphasizing integrated research from feedstock development to conversion technologies. Since then, DOE’s Office of Biological and Environmental Research (BER), operating within the Office of Science, has supported transformational bioenergy research through the vertically integrated DOE Bioenergy Research Centers and development of biomass feedstocks and biofuels-relevant microbes. A number of important breakthroughs have resulted from this fundamental research and include the (1) demonstration that lignin composition and deposition can be genetically engineered to reduce plant cell wall recalcitrance without impacting plant viability; (2) development of effective pretreatments that can be adapted commercially to lower costs; (3) discoveries of novel microbes and enzymatic pathways for more efficient deconstruction of lignocellulosic biomass; (4) proof-of-concept research for consolidated bioprocessing (CBP; i.e., production of ethanol and other biofuels by naturally cellulolytic microbes); (5) metabolic engineering of microorganisms and plants for biological production of numerous advanced biofuels or their immediate precursors; and (6) identification of hundreds of new plant genes and developing an understanding of their role in cell wall biosynthesis.

09 BIOMASS FUELS↗

DOE OSTI2021

Leveraging Spin-Orbit Coupling in Ge/SiGe Heterostructures for Quantum Information Transfer

Hole spin qubits confined to lithographically - defined lateral quantum dots in Ge/SiGe heterostructures show great promise. On reason for this is the intrinsic spin - orbit coupling that allows all - electric control of the qubit. That same feature can be exploited as a coupling mechanism to coherently link spin qubits to a photon field in a superconducting resonator, which could, in principle, be used as a quantum bus to distribute quantum information. The work reported here advances the knowledge and technology required for such a demonstration. We discuss the device fabrication and characterization of different quantum dot designs and the demonstration of single hole occupation in multiple devices. Superconductor resonators fabricated using an outside vendor were found to have adequate performance and a path toward flip-chip integration with quantum devices is discussed. The results of an optical study exploring aspects of using implanted Ga as quantum memory in a Ge system are presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

Making Steppingstones out of Stumbling Blocks: A Bayesian Model Evidence Estimator with Application to Groundwater Transport Model Selection

Bayesian model evidence (BME) is a measure of the average fit of a model to observation data given all the parameter values that the model can assume. By accounting for the trade-off between goodness-of-fit and model complexity, BME is used for model selection and model averaging purposes. For strict Bayesian computation, the theoretically unbiased Monte Carlo based numerical estimators are preferred over semi-analytical solutions. This study examines five BME numerical estimators and asks how accurate estimation of the BME is important for penalizing model complexity. The limiting cases for numerical BME estimators are the prior sampling arithmetic mean estimator (AM) and the posterior sampling harmonic mean (HM) estimator, which are straightforward to implement, yet they result in underestimation and overestimation, respectively. We also consider the path sampling methods of thermodynamic integration (TI) and steppingstone sampling (SS) that sample multiple intermediate distributions that link the prior and the posterior. Although TI and SS are theoretically unbiased estimators, they could have a bias in practice arising from numerical implementation. For example, sampling errors of some intermediate distributions can introduce bias. We propose a variant of SS, namely the multiple one-steppingstone sampling (MOSS) that is less sensitive to sampling errors. We evaluate these five estimators using a groundwater transport model selection problem. SS and MOSS give the least biased BME estimation at an efficient computational cost. If the estimated BME has a bias that covariates with the true BME, this would not be a problem because we are interested in BME ratios and not their absolute values. On the contrary, the results show that BME estimation bias can be a function of model complexity. Thus, biased BME estimation results in inaccurate penalization of more complex models, which changes the model ranking. This was less observed with SS and MOSS as with the three other methods.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

NNSA Strategic Integrated Roadmap 2020-2044

The agency’s Strategic Integrated Road Map illustrates the path to achieving goals now and into the future. NNSA’s mission priorities include maintaining the stockpile, countering proliferation threats, keeping the nuclear Navy moving, applying world-class scientific and technological discoveries to real-world problems, and modernizing the infrastructure of the enterprise.

Source record↗

DOE OSTI2021

NNSA Strategic Integrated Roadmap 2020-2045

Source record↗

DOE OSTI2023

Direct measurement of the electron turbulence-broadening edge transport barrier to facilitate core–edge integration in tokamak fusion plasmas

Abstract The integration of a high-performance core and a dissipative divertor, or the so-called ‘core–edge integration,’ has been widely identified as a critical gap in the design of future fusion reactors. In this letter, we report, for the first time, direct experimental evidence of electron turbulence at the DIII-D H-mode pedestal that correlates with the broadening of the pedestal and thus facilitates core–edge integration. In agreement with gyrokinetic simulations, this electron turbulence is enhanced by high η e ( η e = L n / L T e , where L n is the density scale length and L T e is the electron temperature scale length), which is due to a strong shift between the density and temperature pedestal profiles associated with a closed divertor. The modeled turbulence drives significant heat transport with a lower pressure gradient that may broaden the pedestal to a greater degree than the empirical and theoretically predicted pedestal width scalings. Such a wide pedestal, coupled with a closed divertor, enables us to achieve a good core–edge scenario that integrates a high-temperature low-collisionality pedestal (pedestal top temperature T e,ped > 0.8 keV and a pedestal top collisionality ν * ped < 1) under detached divertor conditions. This paves a new path toward solving the core–edge integration issue in future fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

SALSA3D: A Tomographic Model of Compressional Wave Slowness in the Earth’s Mantle for Improved Travel-Time Prediction and Travel-Time Prediction Uncertainty

The task of monitoring the Earth for nuclear explosions relies heavily on seismic data to detect, locate, and characterize suspected nuclear tests. In this study, motivated by the need to locate suspected explosions as accurately and precisely as possible, we developed a tomographic model of the compressional wave slowness in the Earth’s mantle with primary focus on the accuracy and precision of travel-time predictions for P and Pn ray paths through the model. Path-dependent travel-time prediction uncertainties are obtained by computing the full 3D model covariance matrix and then integrating slowness variance and covariance along ray paths from source to receiver. Path-dependent travel-time prediction uncertainties reflect the amount of seismic data that was used in tomography with very low values for paths represented by abundant data in the tomographic data set and very high values for paths through portions of the model that were poorly sampled by the tomography data set. The pattern of travel-time prediction uncertainty is a direct result of the off-diagonal terms of the model covariance matrix and underscores the importance of incorporating the full model covariance matrix in the determination of travel-time prediction uncertainty. In addition, the computed pattern of uncertainty differs significantly from that of 1D distance-dependent travel-time uncertainties computed using traditional methods, which are only appropriate for use with travel times computed through 1D velocity models.

58 GEOSCIENCES↗

DOE OSTI2024

Integration of Concentrating Solar Power with High Temperature Electrolysis for Hydrogen Production: Preprint

Hydrogen (H2) has been identified as a leading sustainable contender to replace fossil fuels in transportation and electricity generation. H2 production can be achieved by concentrating solar thermal power (CSP) systems collecting thermal energy from the sun to various chemical processes for fuel production. Fuel production via solar thermal chemical processes integrated with CSP uses the full spectrum of sunlight compared with photovoltaic power conversion and stores solar energy directly and efficiently [1]. The solar fuel production can be realized by thermochemical processes (e.g., water splitting for H2 production, carbon dioxide reduction, or methane reforming) or thermal electrochemical methods (e.g., integration with solid oxide electrolysis cell). Technology development for CSP-integrated solar fuel production requires broad technological bases from solar energy collection to chemical energy conversion. H2 generated from renewable sources can be an energy carrier for a carbon-free economy. Integrating CSP with high temperature electrolysis (HTE) using solid oxide electrolysis cells (SOEC) provides a renewable path for H2 generation. The CSP-HTE integration approach provides the benefit of thermal energy storage (TES) for continuous operation, improved capacity, and SOEC life. H2 gas has low energy density for transportation, pipeline networks are expensive, and H2 liquefaction is energy intensive. However, an alternative method for H2 distribution is to use carbon dioxide (CO2) capture and liquid hydrocarbon synthesis to convert solar energy into liquid fuels that are compatible with the existing fossil fuel infrastructure.

concentrating solar thermal power↗

DOE OSTI2016

Compact CH 4 sensor system based on a continuous-wave, low power consumption, room temperature interband cascade laser

A tunable diode laser absorption spectroscopy-based methane sensor, employing a dense-pattern multi-pass gas cell and a 3.3 µm, CW, DFB, room temperature interband cascade laser (ICL), is reported. The optical integration based on an advanced folded optical path design and an efficient ICL control system with appropriate electrical power management resulted in a CH 4 sensor with a small footprint (32 x 20 x 17 cm 3 ) and low-power consumption (6 W). Polynomial and least-squares fit algorithms are employed to remove the baseline of the spectral scan and retrieve CH 4 concentrations, respectively. An Allan-Werle deviation analysis shows that the measurement precision can reach 1.4 ppb for a 60 s averaging time. Continuous measurements covering a seven-day period were performed to demonstrate the stability and robustness of the reported CH 4 sensor system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Autonomous aerial flight path inspection using advanced manufacturing techniques

Robotic systems have shown capabilities to perform inspection tasks in dangerous and difficult-to-access environments, such as those found in different components of power plants. However, most of the current robotic inspection technology is designed for specific components. Aerial robots, commonly termed as Drones, have raised an option to inspect a wider range of structural components. Nevertheless, current aerial inspecting technology still relies on a human pilot with limited line of sight, field of view and a reduced perception as the drone flies away, which prevents performing close-quarter inspection in intricate, structurally complex and GPS-denied environments. This work introduces offline inspection path generation methods based on robotics-integrated to manufacturing techniques. One method uses computer-aided manufacturing (CAM) techniques and the other an additive manufacturing (AM) approach to generate the flight path. That is to say, the drone would fly along the path described by a 3D (Three Dimensional) printer’s extruder or a CNC (Computer Numerical Control) machining tool, enabling to fly very close the structure even in physical structures with a complex geometry. Once the trajectories are generated, they are introduced for its validation in the Gazebo robotics simulator. Simulation results demonstrate the proper performance of the method and confirm that this approach can be used for close inspection of structural components.

42 ENGINEERING↗

DOE OSTI2019

Modeling the Grid Integration of Variable Renewable Energy (VRE) Resources

The presentation was given at the November 21-23, 2018 'CEM Days - Integration of Renewables in the Electric Sector: Paths and Challenges to Energy Planning' in Rio de Janeiro, Brazil. It provides a summary of NREL's current modeling approaches, datasets, and considerations for integrating renewables into the power system. It also covers current model method improvement efforts, including our vision for a truly integrated modeling approach.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗