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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Performance Improvement of Lithium Metal Batteries Enabled By LiBF 3 CN as a New Electrolyte Additive

A newly synthesized electrolyte additive, lithium trifluoro(cyano) borate (LiBF 3 CN), has been investigated for electrochemical performance improvement of lithium metal batteries. The LiBF 3 CN has a structure where one fluorine atom of BF 4 – is substituted with a cyano group (–CN) prepared by the reaction of boron trifluoride etherate with lithium cyanide. The electrochemical performance in symmetric Li/Li cells and NCM523/Li cells is significantly improved upon the incorporation of LiBF 3 CN as an electrolyte additive into a carbonate-based electrolyte. Extensive characterization of the deposited lithium metal reveals that a thin (≈20 nm) and robust SEI composed of LiN x O y , Li 3 N and Li 2 O is formed by the reductive decomposition of the LiBF 3 CN additive, which plays an important role in decreasing the resistance and stabilizing lithium deposition/stripping. The insight into the substitution effect of a functional group obtained from this work provides guidance for the design of new electrolyte additives.

25 ENERGY STORAGE↗
DOE OSTI2024

NetDuid

SAND2025-00238O The NetDuid library is a software tool that can manage and manipulate DHCP Unique Identifiers (DUIDs) in .NET applications. It simplifies the process of working with DUIDs by offering functionalities such as parsing, constructing, comparing, checking equality, and formatting DUIDs. The library supports various types of DUIDs, making it easier for developers to handle these identifiers in their applications. The program fills a gap in the .NET/C# ecosystem by providing a specialized tool for managing DHCP Unique Identifiers, offering a straightforward and efficient solution for developers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Engelhardt, Robert↗
DOE OSTI2020

New perspectives on butyrate assimilation in Rhodospirillum rubrum S1H under photoheterotrophic conditions

Background: The great metabolic versatility of the purple non-sulfur bacteria is of particular interest in green technology. Rhodospirillum rubrum S1H is an α-proteobacterium that is capable of photoheterotrophic assimilation of volatile fatty acids (VFAs). Butyrate is one of the most abundant VFAs produced during fermentative biodegradation of crude organic wastes in various applications. While there is a growing understanding of the photoassimilation of acetate, another abundantly produced VFA, the mechanisms involved in the photoheterotrophic metabolism of butyrate remain poorly studied. Results: In this work, we used proteomic and functional genomic analyses to determine potential metabolic pathways involved in the photoassimilation of butyrate. We propose that a fraction of butyrate is converted to acetyl-CoA, a reaction shared with polyhydroxybutyrate metabolism, while the other fraction supplies the ethylmalonyl-CoA (EMC) pathway used as an anaplerotic pathway to replenish the TCA cycle. Surprisingly, we also highlighted a potential assimilation pathway, through isoleucine synthesis and degradation, allowing the conversion of acetyl-CoA to propionyl-CoA. We tentatively named this pathway the methylbutanoyl-CoA pathway (MBC). An increase in isoleucine abundance was observed during the early growth phase under butyrate condition. Nevertheless, while the EMC and MBC pathways appeared to be concomitantly used, a genome-wide mutant fitness assay highlighted the EMC pathway as the only pathway strictly required for the assimilation of butyrate. Conclusion: Photoheterotrophic growth of Rs. rubrum with butyrate as sole carbon source requires a functional EMC pathway. In addition, a new assimilation pathway involving isoleucine synthesis and degradation, named the methylbutanoyl-CoA (MBC) pathway, could also be involved in the assimilation of this volatile fatty acid by Rs. rubrum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

An Integrated Study of a Novel Thermal Coating for Nb-Based High Temperature Alloy

This report summarizes our recent works of ab initio density functional theory (DFT) method and molecular dynamics (MD) simulation on the interfaces between niobium substrate and coatings at atomic level. Potential oxidation barrier bond coat, Nb₂AlC and high entropy alloys, and top coat candidates were synthesized, characterized, and evaluated in our labs. The simulation methods, experimental validation techniques, achievements already reached, students and postdoc training, and future improvement are briefly introduced.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

TA-I Sub-Area Plan: Overview & Summary

The Sub-Area plan recognizes that TA-I is the center of R&D for SNL and its “crown jewel.” The Plan seeks to: Maintain Research and Development (R&D), Manufacturing, and Administration as primary land use; Create a new “front door” and focus for internal and external interaction; Organize the site by nature of work / mission focus to enhance functional relationships and cost-effectiveness; Reshape the security boundary to enhance and simplify the security hierarchy, and open portions of the site for external collaboration; Preserve opportunities for growth and sustainment of mission by encouraging infill, redevelopment, and consolidation; Upgrade roadways and walkways to improve site access, circulation and internal logistics, and promote a pedestrian-oriented environment; Relocate site support activities and functions that do not require a TA-I site (“backyard activities”) to make room for program use and external collaboration.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Embedment of sensors in ceramic structures

Ceramic materials such as silicon carbide (SiC) are attractive for many nuclear applications due to their ability to withstand high temperatures, which inherently improve the thermal efficiency of the power conversion cycle and can in some cases provide high-temperature process heat. SiC is particularly attractive because of its high-temperature strength retention, stability under neutron irradiation, and low neutron absorption. The TCR program has recently demonstrated the ability to fabricate monolithic SiC components with complex geometries using a binder jet additive manufacturing technique followed by densification using chemical vapor infiltration (CVI). This technology presents an opportunity to embed sensors within ceramic components at critical locations that allow for enhanced process monitoring and control of advanced nuclear energy systems. The challenges with embedding sensors in ceramic components are to identify appropriate materials that can survive the CVI process, remain embedded after cooling to room temperature, and be suitable for operation in a high-temperature nuclear environment. This report summarizes the sensors that are being considered for embedding within ceramics, the sensor embedding process, material compatibility studies, and characterization of the embedded components. Material selection is first guided by computational thermodynamics and is confirmed by embedding coupons and examining material interactions using electron microscopy. This work shows that a wide range of refractory metals, as well as certain fiber optic sensors, can be successfully embedded in 3D-printed SiC. Future work will involve testing of functional sensors including thermocouples and optical fiber-based, spatially distributed temperature/strain sensors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Water foraging with dynamic roots in E3SM; The role of roots in terrestrial ecosystem memory on intermediate timescales (Final Technical Report)

Terrestrial ecosystems can show sustained responses to stress events that may last for years after the initial perturbation. This phenomenon is referred to as legacy or memory and it emerges from a set of ecosystem processes that are poorly captured by Earth System and Land Surface Models. Consequently, these models struggle to predict the impact that extreme climate events have on surface energy, carbon and hydrological exchange once a stressor such as drought has relaxed or in response to repeated exposure to stress. In this project, we set out to test how the addition of dynamic root profiles in land surface models impact the capacity for Earth System Models, such as the Department of Energy’s E3SM, to capture realistic legacy effects. Observations have shown that vegetation shifts their root profiles during stress events to forage for water and these altered root profiles may take years to relax back to the initial state. We hypothesized that the alteration of the belowground root structures may be a source of terrestrial ecosystem legacy that is missing from models. To test this idea we undertook three core activities. (1) We developed a global-scale analysis of the impact of dynamic roots on ecosystem legacy building from a recently developed dynamic root module. (2) We developed new root dynamics in the DOE’s Energy Land Model (ELM) that allowed not only root profiles to shift their profile but also simultaneously alter carbon allocation to fine root pools. We then tested the impact of these new dynamics with intensive sensitivity analysis at four long-term AmeriFlux sites. (3) We undertook detailed isotopic analysis of tree rings from these AmeriFlux sites to assess ecophysiological and ecohydrological legacy to stress events that can be used to benchmark the sensitivity experiments with ELM. From these core activities, we report the following key findings. Firstly, on a global scale, the addition of dynamic roots led to chronically water-stressed ecosystems recovering faster to climate stress while wetter ecosystem showed enhanced legacy. This is because across ecosystems, stress events were almost universally associated with water shortages that led to the development of deeper root profiles. These deeper root profiles proved beneficial for recovery from drought stress. While the root dynamics did not universally improve the modeled representation of legacy it showed complex transient dynamics that emerge from the addition of dynamic roots. Secondly, the sensitivity analysis illustrated long term shifts in rooting depths away from the prescribed default profile suggesting that initializing of root profiles could benefit from spin-up simulations that converge on locally optimized root profiles. In addition, by enabling dynamic allocation some of the sites predicted unrealistically low allocation to roots (and high allocation to leaves). While these changes did not dramatically alter modeled gross primary productivity, they illustrated that without more sophisticated root processes in models, there is little penalty to dramatically disinvest in roots. Thirdly, the isotopic analysis of tree rings showed highly distinct legacy responses across species and sites. For example, T. canadensis showed reduced transpiration the year after stress events illustrated by sustained elevated $\delta^{18}$O. In contrast, A saccharum displayed elevated $\delta^{13}$C associated with reduced stomatal conductance in response to the previous years’ stress event. These geochemical signatures of legacy were present despite tree growth returning to normal the year after the stress. The results show the importance of species-level dynamics in legacy that are absent in modeling that assumes common traits within plant functional types. In summary, the work here established new avenues to explore root dynamics in models while illustrating how additional root processes are needed before dynamic carbon allocation can be implemented. Lastly, this project provided mentorship to a postdoctoral fellow, training for an early career scientist and multiple undergraduate students recruited from a minority serving institution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Machine-Learned Force Field Modeling of Metal Organic Frameworks for CO2 Direct Air Capture

To cope with legacy greenhouse gas emissions and to achieve net-zero emissions by 2050, the U.S. Department of Energy (DOE) is funding efforts to develop direct air capture (DAC), a method for removing CO2 directly from air. Metal organic frameworks (MOFs) have been well studied as DAC sorbent materials due to their tunable structural and compositional properties. Thermodynamic simulations using force fields are often used to provide predictions of a material’s performance in many separations. However, these force fields often make assumptions about bonds and the physics of the adsorption process. A new class of force fields called machine-learned force fields (MLFFs) use machine learning to form quantitative relationships between a material’s chemical structure and the forces and energies predicted by more accurate quantum mechanical calculations, such as dispersion-corrected density functional theory (DFT). In this work, models were developed to achieve DFT-level accuracy for the forces and energies associated with MOF flexibility and CO2 adsorption using MLFFs. These methods were parametrized based on thousands of DFT calculations of CO2 in flexible MOFs and used to predict MOF structural properties as well as CO2 adsorption in several MOFs.

Findley, John↗
DOE OSTI2024

MxRAM (Final Report)

Sandia National Labs will provide Technical Assistance and consulting to Requester on a series of Requester’s test structures and devices to characterize and aid in the determination of optimal fabrication parameters via fabrication of functional test structures and cells. Working with previously established processes and test die modules, Sandia will construct a series of test chips with varying materials properties to allow the electrical characterization and component testing of Requester’s test structures and devices. Material variations will be selected for optimization of yield and desired target operation parameters. A deliverable in the form of a report will be written. Sandia intends to deliver testable die to the Requester.

36 MATERIALS SCIENCE↗
DOE OSTI2026

DASSH-F: Subchannel Based Thermal Analysis

The DASSH thermal analysis code is designed to rapidly allow a reactor design engineer to obtain flow rates requirements that satisfy peak temperature constraints in the domain. The advantage of using DASSH over a hand calculation is that it has a more rigorous treatment of the pin power distribution and coolant heat transfer within an assembly and between assemblies. The advantage of using DASSH over a conventional 3D subchannel code or a computational fluid dynamics code (CFD) is that it can obtain the desired solution in a matter of minutes in serial with minor computer memory needs. The DASSH methodology for pin lattice models is virtually identical to SUPERENERGY-2 with additional functionalities taken from follow on work to SUPERENERGY-2 done at ANL in the 1980s. DASSH today is an integral component of the Argonne Fast Reactor analysis suite for reactor design work. DASSH obtains the power distribution from a coupled neutron-gamma heating calculation in GAMSOR (including DIF3D) at each time point of a companion fuel cycle analysis calculation with REBUS. The domain in DASSH assumes a hexagonal grid typical for fast reactors with much of the geometry information taken from the DIF3D model. DASSH assumes the assemblies that are loaded into each grid position are ducted to control the coolant flow. The user can alternatively provide their own geometry and power profile instead of inheriting it from DIF3D. Considerable detail is given on the subchannel formulation of DASSH in this document. Much of the formulation and design of the code builds upon research done by previous authors with little new investigation. Thus the decisions made in developing the subchannel model used in DASSH have their origins over 50 years ago. Much of the heat transfer methodology in DASSH is built upon correlations for both the coolant mixing and heat transfer coefficients for pins and ducts. DASSH is thus not a rigorous treatment of a given problem, but a rapid assessment of the temperature field that has known limitations with respect to an experimental measurement or CFD calculation. The DASSH input and output are detailed along with usage of the software. The DASSH output provides tables of evaluated material properties and key coolant and pin temperature results. DASSH can create Python scripts that generate domain summary pictures. DASSH can also generate assembly temperature maps and VTK output files which allow the DASSH solution to be visualized. As the primary purpose of the DASSH software is to compute the coolant and fuel pin temperature distribution for a given model of a reactor, much of the output focus is giving the user quick summary tables needed to assess the performance of a given orifice flow specification. The present version of DASSH has a crude orifice search capability and a sufficient orifice flow search capability. The flow search tries to meet user specified constraints for 1) peak 2-sigma clad temperature, 2) peak coolant temperature, and 3) desired bulk outlet temperature. This document serves as the manual for the Fortran based DASSH software that was developed to replace the Python version of DASSH developed as part of the VTR program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

The Electrochemical Sodiation of Sb Investigated by Operando X-ray Absorption and 121 Sb Mössbauer Spectroscopy: What Does One Really Learn?

In this study, we want to highlight the assets and restrictions of X-ray absorption spectroscopy (XAS) and Mössbauer spectroscopy for investigating the mechanism of the electrochemical reaction of antimony electrode materials vs. Na. For this, operando XAS was carried out during the first one and a half cycles, and the whole set of measured data was analysed using a statistical-chemometric approach, while low temperature Mössbauer spectroscopy measurements were carried out ex situ on selected samples stopped at different points of the electrochemical reaction. Complementary ab initio calculations were performed to support the experimental findings. Both techniques show that, upon the first sodiation, most Sb reacts with Na to form disordered Na 3 Sb. This step is accompanied by the formation of amorphous Sb as an intermediate. Upon inversion of the current Na 3 Sb is desodiated and an amorphous Sb phase, distinct from the pristine bulk Sb state, is gradually formed. However, both XAS and Mössbauer spectroscopy were unable to spot the formation of intermediate Na x Sb phases, which were evinced in previous works by operando Pair Distribution Function analyses. The results shown here clearly assign such failure to the intrinsic inability of both techniques to identify these intermediates.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Ion-Selective Scattering Studied Using the Variable-Energy Electron Irradiation in the Ba 0.2 K 0.8 Fe 2 As 2 Superconductor

Low-temperature variable-energy electron irradiation was used to induce non-magnetic disorder in a single crystal of a hole-doped iron-based superconductor, Ba $1-x$ K $x$ Fe 2 As 2 , $x$ = 0.80. To avoid systematic errors, the beam energy was adjusted non-consequently for five values between 1.0 and 2.5 MeV when sample resistance was measured in situ at 22 K. For all energies, the resistivity raises linearly with the irradiation fluence suggesting the creation of uncorrelated dilute point-like disorder (confirmed by simulations). The rate of the resistivity increase peaks at energies below 1.5 MeV. Comparison with calculated partial cross-sections points to the predominant creation of defects in the iron sublattice. Simultaneously, superconducting $T_c$, measured separately between the irradiation runs, is monotonically suppressed as expected, since it depends on the total scattering rate, hence on the total cross-section, which is a monotonically increasing function of the energy. Our work experimentally confirms an often-made assumption of the dominant role of the iron sub-lattice in iron-based superconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Quantum Mechanical Modeling of the Vibrational Spectra of Minerals with a Focus on Clays

We present an overview of how to use quantum mechanical calculations to predict vibrational frequencies of molecules and materials such as clays and silicates. Other methods of estimating vibrational frequencies are mentioned, such as classical molecular dynamics simulations; references are given for additional information on these approaches. Herein, we discuss basic vibrational theory, calculating Raman and infrared intensities, steps for creating realistic models, and applications to spectroscopy, thermodynamics, and isotopic fractionation. There are a wide variety of programs and methods that can be employed to model vibrational spectra, but this work focuses on hybrid density functional theory (DFT) approaches. Many of the principles are the same when used in other programs and DFT methods, so a novice can benefit from simple examples that illustrate key points to consider when modeling vibrational spectra. Other methods and programs are listed to give the beginner a starting point for exploring and choosing which approach will be best for a given problem. The modeler should also be aware of the numerous analytical methods available for obtaining information on vibrations of atoms in molecules and materials. In addition to traditional infrared and Raman spectroscopy, sum-frequency generation (SFG) and inelastic neutron scattering (INS) are also excellent techniques for obtaining vibrational frequency information in certain circumstances.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

The Dynamic Socket: A Better Prosthesis

The issues that amputees experience with current prosthetic devices are discussed and how Sandia National Laboratory is working to make them both functional and comfortable to wear.

42 ENGINEERING↗
DOE OSTI2015

Order-to-Disorder Transitions in BECN1 Regulate Autophagy

Autophagy, an essential conserved, cell survival pathway in eukaryotes is responsible for degradation and recycling of unwanted, damaged or harmful cytoplasmic components. Our pathway-wide bioinformatics analysis shows that intrinsically disordered regions (IDRs) are the most common structural feature of autophagy proteins and these IDRs may be responsible for many regulatory interactions. BECN1 is a critical component of the autophagy nucleation complex. Aberrant or reduced autophagy, due to BECN1 defects or low levels is implicated in many diseases. Over 20 cellular or viral proteins appear to interact with BECN1 to modulate autophagy. We are also using a multi-faceted experimental approach encompassing bioinformatics, computational, structural, biophysical, biochemical, cell biology and molecular biology methods to understand the mechanism by which BECN1 mediates autophagy, and how partners bind to BECN1 to modulate autophagy. This work reveals a structural and functional dichotomy within the 450-residue human BECN1: residues 42-132 constitute a poorly conserved IDR that includes a BECN1 BH3 domain (BH3D) responsible for binding Bcl-2 proteins, while the highly-conserved C-terminal residues 133-450 comprise three conformationally-flexible domains: the helical domain (HD), the coiled-coil domain and the b-a-repeat in autophagy domain. Finally, our structural and biophysical results show that the BH3D and HD undergo binding-associated disorder-to-structure transitions and have identified residues important for regulating autophagy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Artificial Neural Network-Based Monitoring of the Fuel Assembly Temperature Sensor and FPGA Implementation

Numerous methods have been developed around the world to model the dynamic behavior and detect a faulty operating mode of a temperature sensor. In this context, we present in this study a new method based on the dependence between the fuel assembly temperature profile on control rods positions, and the coolant flow rate in a nuclear reactor. This seems to be possible since the insertion of control rods at different axial positions and variations in flow rate of the reactor coolant results in different produced thermal power in the reactor. This is closely linked to the instant fuel rod temperature profile. In a first step, we selected parameters to be used and confirmed the adequate correlation between the chosen parameters and those to be estimated by the proposed monitoring system. In the next step, we acquired and de-noised the data of corresponding parameters, the qualified data is then used to design and train the artificial neural network. The effective data denoising was done by using the wavelet transform to remove a various kind of artifacts such as inherent noise. With the suitable choice of wavelet level and smoothing method, it was possible for us to remove all the non-required artifacts with a view to verify and analyze the considered signal. In our work, several potential mother wavelet functions (Haar, Daubechies, Bi-orthogonal, Reverse Bi-orthogonal, Discrete Meyer and Symlets) were investigated to find the most similar function with the being processed signals. To implement the proposed monitoring system for the fuel rod temperature sensor (03 wire RTD sensor), we used the Bayesian artificial neural network 'BNN' technique to model the dynamic behavior of the considered sensor, the system correlate the estimated values with the measured for the concretization of the proposed system we propose an FPGA (field programmable gate array) implementation. The monitoring system use the correlation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

SymPLe 1131: A novel architectural solution for the realization of verifiable digital I and C systems and embedded digital devices - 387

One of the main reasons for the increasing popularity of FPGAs in embedded systems and digital I and C systems is that they provide many of the advantages from both hardware and software components. FPGAs provide configurability approaching that of SW, while at the same time delivering deterministic behavior of pure hardware solutions. However, with regard to Software Common Cause Failures (CCF), the use of FPGAs in digital I and C platforms should not be seen as plug-in remedy for reduction or elimination of CCF. To address CCF, we argue that it is not enough to manage the complexity of an I and C device or system, but we must also have the ability to constrain complexity (as needed) and rigorously reason about execution and device functionality. This paper presents the work done regarding an FPGA overlay architecture called SymPLe. SymPLe is designed to reduce the gap between software and hardware approaches for digital I and C systems and increases deterministic behavior and verifiability of the application, architecture and safety-critical system while reasoning about CCF. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗