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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Embedding Fiber Optic Sensors in Stainless Steel using Spark Plasma Sintering for Structural Health Monitoring in Harsh Environments

Embedded fiber optic sensors such as fiber Bragg gratings (FBGs) offer a unique route for distributed real-time in-situ imaging of various engineering parameters for numerous purposes. This study advanced the current sensor embedding approaches by exploring a spark plasma sintering (SPS)-assisted technology to embed FBGs in high-temperature structural materials and demonstrated the capability of temperature measurement. In this approach, single-mode FBGs were integrated into stainless steel (SS) 316L components using SPS, followed by the evaluation of the bonding quality between the FBGs and matrix, the optical attenuation of the fibers induced by embedding, and the sensing characters of the FBGs under temperature stimuli. The results demonstrated that superior bonding was achieved between the FBGs and highly-densified SS316L. Examination of the behavior of Bragg gratings validated signal fidelity after embedding. Real-time thermal imaging under temperature cycling using the FBGs demonstrated the effectiveness of the technique for smart materials manufacturing.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

Multilevel graph embedding

The goal of the present paper is the design of embeddings of a general sparse graph into a set of points in $\mathbb{R}^d$ for appropriate d ≥ 2. The embeddings that we are looking at here aim to keep vertices that are grouped in communities together and keep the rest apart. To achieve this property, we utilize coarsening that respects possible community structures of the given graph. We employ a hierarchical multilevel coarsening approach that identifies communities (strongly connected groups of vertices) at every level. The multilevel strategy allows any given (presumably expensive) graph embedding algorithm to be made into a more scalable (and faster) algorithm. We demonstrate the presented approach on a number of given embedding algorithms and large-scale graphs and achieve speed-up over the methods in a recent paper.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Functional fiber-optic sensors embedded in stainless steel components using ultrasonic additive manufacturing for distributed temperature and strain measurements

The nuclear industry is progressing toward microreactors that can be factory assembled and deployed to remote regions for reliable, scalable power generation. However, the reduced power output requires enhanced monitoring capabilities to reduce staffing and eventually move toward autonomous control to improve the economics of microreactors. The ability to embed sensors such as fiber-optics, which can provide spatially distributed temperature and strain measurements, within microreactor components for real-time health monitoring would be particularly advantageous. Recent advances in ultrasonic additive manufacturing (UAM) have demonstrated the successful embedding of fiber-optics in soft materials such as Al and Cu by placing the sensors in machined cavities and ultrasonically welding over the top with thin foils. This article reports the first successful embedment of fiber-optic sensors and thermocouples within a common nuclear reactor material, SS304, via UAM. UAM parameters were first explored with simple plate geometries before moving to more complex geometries, such as pipes and other test articles for heat pipe–based microreactors. Select samples were sectioned for microscopy to evaluate the sensor/foil and foil/foil interfaces from samples fabricated by using 100% SS304 foils vs. foils plated with a Ni coating to improve UAM bonding. Furthermore, embedding metal-coated, low-bend loss fibers resulted in greatly reduced signal attenuation and adequate compressive residual strain in the embedded region to ensure successful strain coupling. Pipe specimen functional testing was performed by monitoring temperature and strain during transient and steady-state thermal testing.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Expanded polyglutamine embedded in the endoplasmic reticulum causes membrane distortion and coincides with Bax insertion

The endoplasmic reticulum (ER) is important in various cellular functions, such as secretary and membrane protein biosynthesis, lipid synthesis, and calcium storage. ER stress, including membrane distortion, is associated with many diseases such as Huntington's disease. In particular, nuclear envelope distortion is related to neuronal cell death associated with polyglutamine. However, the mechanism by which polyglutamine causes ER membrane distortion remains unclear. We used electron microscopy, fluorescence protease protection assay, and alkaline treatment to analyze the localization of polyglutamine in cells. We characterized polyglutamine embedded in the ER membrane and noted an effect on morphology, including the dilation of ER luminal space and elongation of ER-mitochondria contact sites, in addition to the distortion of the nuclear envelope. The polyglutamine embedded in the ER membrane was observed at the same time as Bax insertion. These results demonstrated that the ER membrane may be a target of polyglutamine, which triggers cell death through Bax. -- Highlights: •We characterized polyglutamine embedded in the ER membrane. •The polyglutamine embedded in the ER membrane was observed at the same time as Bax insertion. •The ER membrane may be a target of polyglutamine, which triggers cell death.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Failure of brittle micro-spherical shells embedded in elastomer matrix under indentation

Silicone elastomer filled with glass micro balloons (GMB) is an elastomeric syntactic foam used in electronics and component packaging for encapsulation, potting, stress-relief layer, and electrical insulation purposes. Under mechanical loading, the reinforcing phase, namely the GMBs embedded in the elastomer matrix, may break or delaminate, leading to internal damage and macroscale stiffness degradation, which can alter the material's protective capacity against mechanical shock and vibration. The degree of damage is controlled by the loading history, delamination, and failure behavior of the GMBs. In this work, we investigate the GMB failure behavior in this work wherein we present an indentation experiment to measure the force required to fail individual GMBs that are either embedded in the elastomer matrix or adhered to the surface of an elastomer layer. The indentation apparatus is augmented with an inverted optical microscope to enable in situ imaging of the GMB. Failure modes for the embedded or non-embedded GMBs are discussed based on the morphology of the broken GMBs and the measured failure forces. We also measure the adhesion energy between the glass balloon and the elastomer, based on which the possibility of delamination between the GMB and the surrounding elastomer matrix during the failure process is evaluated. Our results can facilitate the development of a failure criterion of GMBs which is necessary for establishing a physics-based constitutive model to describe the macroscopic damage mechanics of elastomeric syntactic foams.

42 ENGINEERING↗
DOE OSTI2016

X-ray absorption spectroscopy characterization of embedded and extracted nano-oxides

Here, the chemistries and structures of both embedded and extracted Ysingle bondTisingle bondO nanometer-scale oxides in a nanostructured ferritic alloy (NFA) were probed by x-ray absorption spectroscopy (XAS). Y 2 Ti 2 O 7 is the primary embedded phase, while the slightly larger extracted oxides are primarily Y 2 TiO 5 . Analysis of the embedded nano-oxides is difficult partly due to the multiple Ti environments associated with different oxides and those still residing in matrix lattice sites. Thus, bulk extraction followed by selective filtration was used to isolate the larger Y 2 TiO 5 oxides for XAS, while the smaller predominant embedded phase Y 2 Ti 2 O 7 oxides passed through the filters and were analyzed using the log-ratio method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Amino-functionalized graphene quantum dots (aGQDs)-embedded thin film nanocomposites for solvent resistant nanofiltration (SRNF) membranes based on covalence interactions

Solvent resistant nanofiltration (SRNF) membranes are highly demanded in processing organic solutions especially those contain large molecules with molecular weight between 200 to 2000 Da, yet they have some drawbacks such as relatively poor solvent resistance and low solvent permeance. The current work presented an innovative class of amino-functionalized graphene quantum dots (aGQDs) embedded thin film nanocomposites (TFN) for SRNF membranes which were prepared via interfacial polymerization (IP) and subsequent steps (chemical imidization, crosslinking, and solvent activation). The prepared membranes enabled covalent interactions not only between the IP skin layer and the substrate, but also between the IP layer and the embedded aGQDs. The ethanol permeance and surface porosity increased by 44% and 69%, respectively, with the embedment of aGQDs under the optimal conditions, while the Rhodamine B (RDB, 479 Da) rejection maintained essentially stable above 99%. Furthermore, our novel membranes exhibited excellent long-term stability, with a rejection of over 99% for Rose Bengal (RB, 1017 Da) during the continuous filtration of 100 mg L -1 RB/N,N-dimethyl formamide (DMF) solution at room temperature for more than 768 h. They also exhibited good organic solvent resistance and high-temperature tolerance in both DMF and NMP solvents, with a RDB rejection of over 99% and an ethanol permeance of about 38 L m -2 h -1 MPa -1 after being immersed in DMF at 80 °C for 248 h, and a RDB rejection of over 99% and an ethanol permeance of about 41 L m -2 h -1 MPa -1 after being immersed in NMP at 80 °C for 232 h. The results demonstrated that the aGQDs-embedded TFN OSN membrane has vast potential in SRNF applications.

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

Harmonic Infrared and Raman Spectra in Molecular Environments Using the Polarizable Embedding Model

We present a fully analytic approach to calculate infrared (IR) and Raman spectra of molecules embedded in complex molecular environments modeled using the fragment-based polarizable embedding (PE) model. We provide the theory for the calculation of analytic second-order geometric derivatives of molecular energies and first-order geometric derivatives of electric dipole moments and dipole–dipole polarizabilities within the PE model. The derivatives are implemented using a general open-ended response theory framework, thus allowing for an extension to higher-order derivatives. The embedding-potential parameters used to describe the environment in the PE model are derived through first-principles calculations, thus allowing a wide variety of systems to be modeled, including solvents, proteins, and other large and complex molecular environments. Here, we present proof-of-principle calculations of IR and Raman spectra of acetone in different solvents. This work is an important step toward calculating accurate vibrational spectra of molecules embedded in realistic environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Projection-Based Correlated Wave Function in Density Functional Theory Embedding for Periodic Systems

In this report we present a level shift projection operator-based embedding method for systems with periodic boundary conditions—where the “active” subsystem can be described using either density functional theory (DFT) or correlated wave function (WF) methods and the “environment” is described using DFT. Our method allows for k-point sampling, is shown to be exactly equal to the canonical DFT solution of the full system under the limit that we use the full system basis to describe each subsystem, and can treat the active subsystem either with periodic boundary conditions—in what we term “periodic-in-periodic” embedding—or as a molecular cluster—in “cluster-in-periodic” embedding. We explore each of these methods and show that cluster WF-in-periodic DFT embedding can accurately calculate the absorption energy of CO on to a Si(100)-2×1 surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Polarizable Frozen Density Embedding with External Orthogonalization

In this work, we report a polarizable subsystem density functional theory to describe electronic properties of molecules embedded on a metal cluster. Interaction between the molecule and metal cluster is described using frozen density embedding (FDE). Substituting the nonadditive kinetic potential (NAKP) by approximate functionals is circumvented by enforcing external orthogonality (EO) through a projection operator. The computationally expensive freeze/thaw (FT) cycles are bypassed by including a polarization term in the embedding operator. Furthermore, the combination of polarization and EO permits supermolecular basis set calculations, which was not possible for strongly interacting systems with existing kinetic energy functionals. To test the method, we described the ground state density of pyridine, water, and benzene on a silver cluster. Performing FT on top of EO results in exact density embedding for this category of systems and is thus used for benchmarking the method. We find that the density is reproduced to within 0.15e, and the dipole and quadrupole moments are within 18% of the reference points for subsystem separations ranging from bonding to noninteracting distances. Additionally, our formalism allows the flexibility of incorporating different density functionals to the molecular and the metallic subsystems reducing the overall computational cost.

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

A graph embedding‐based approach for automatic cyber‐physical power system risk assessment to prevent and mitigate threats at scale

Abstract Power systems are facing an increasing number of cyber incidents, potentially leading to damaging consequences to both physical and cyber aspects. However, the development of analytical methods for the study of large‐scale power infrastructures as cyber‐physical systems is still in its early stages. Drawing inspiration from machine‐learning techniques, the authors introduce a method inspired by the principles of graph embedding that is tailored for quantitative risk assessment and the exploration of possible mitigation strategies of large‐scale cyber‐physical power systems. The primary advantage of the graph embedding approach lies in its ability to generate numerous random walks on a graph, simulating potential access paths. Meanwhile, it enables capturing high‐dimensional structures in low‐dimensional spaces, facilitating advanced machine‐learning applications, and ensuring scalability and adaptability for comprehensive network analysis. By employing this graph embedding‐based approach, the authors present a structured and methodical framework for risk assessment in cyber‐physical systems. The proposed graph embedding‐based risk analysis framework aims to provide a more insightful perspective on cyber‐physical risk assessment and situation awareness for power systems. To validate and demonstrate its applicability, the method has been tested on two cyber‐physical power system models: the Western System Coordinating Council (WSCC) 9‐Bus System and the Illinois 200‐Bus System , thereby showing its advantages in enhancing the accuracy of risk analysis and comprehensiveness of situational awareness.

Sun, Shining↗
DOE OSTI2014

Memory functions of nanocrystalline cadmium selenide embedded ZrHfO high-k dielectric stack

Metal-oxide-semiconductor capacitors made of the nanocrystalline cadmium selenide nc-CdSe embedded Zr-doped HfO{sub 2} high-k stack on the p-type silicon wafer have been fabricated and studied for their charge trapping, detrapping, and retention characteristics. Both holes and electrons can be trapped to the nanocrystal-embedded dielectric stack depending on the polarity of the applied gate voltage. With the same magnitude of applied gate voltage, the sample can trap more holes than electrons. A small amount of holes are loosely trapped at the nc-CdSe/high-k interface and the remaining holes are strongly trapped to the bulk nanocrystalline CdSe site. Charges trapped to the nanocrystals caused the Coulomb blockade effect in the leakage current vs. voltage curve, which is not observed in the control sample. The addition of the nanocrystals to the dielectric film changed the defect density and the physical thickness, which are reflected on the leakage current and the breakdown voltage. More than half of the originally trapped holes can be retained in the embedded nanocrystals for more than 10 yr. The nanocrystalline CdSe embedded high-k stack is a useful gate dielectric for this nonvolatile memory device.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Effect of embedded metal nanocrystals on the resistive switching characteristics in NiN-based resistive random access memory cells

The metal nanocrystals (NCs) embedded-NiN-based resistive random access memory cells are demonstrated using several metal NCs (i.e., Pt, Ni, and Ti) with different physical parameters in order to investigate the metal NC's dependence on resistive switching (RS) characteristics. First, depending on the electronegativity of metal, the size of metal NCs is determined and this affects the operating current of memory cells. If metal NCs with high electronegativity are incorporated, the size of the NCs is reduced; hence, the operating current is reduced owing to the reduced density of the electric field around the metal NCs. Second, the potential wells are formed by the difference of work function between the metal NCs and active layer, and the barrier height of the potential wells affects the level of operating voltage as well as the conduction mechanism of metal NCs embedded memory cells. Therefore, by understanding these correlations between the active layer and embedded metal NCs, we can optimize the RS properties of metal NCs embedded memory cells as well as predict their conduction mechanisms.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Structural and electronic properties of GaN nanowires with embedded In{sub x}Ga{sub 1−x}N nanodisks

In the present study, the effects of various types of strain and indium concentration on the total energy and optoelectronic properties of GaN nanowires (NWs) with embedded In{sub x}Ga{sub 1−x}N nanodisks (NDs) are examined. In particular, the bi-axial, hydrostatic, and uniaxial strain states of the embedded In{sub x}Ga{sub 1−x}N NDs are investigated for multiple In concentrations. Density functional theory is employed to calculate the band structure of the NWs. The theoretical analysis finds that the supercell-size-dependent characteristics calculated for our 972-atom NW models are very close to the infinite supercell-size limit. It is established that the embedded In{sub x}Ga{sub 1−x}N NDs do not induce deep states in the band gap of the NWs. A bowing parameter of 1.82 eV is derived from our analysis in the quadratic Vegard's formula for the band gaps at the various In concentrations of the investigated In{sub x}Ga{sub 1−x}N NDs in GaN NW structures. It is concluded that up to ∼10% of In, the hydrostatic strain state is competitive with the bi-axial due to the radial absorption of the strain on the surfaces. Above this value, the dominant strain state is the bi-axial one. Thus, hydrostatic and bi-axial strain components coexist in the embedded NDs, and they are of different physical origin. The bi-axial strain comes from growth on lattice mismatched substrates, while the hydrostatic strain originates from the lateral relaxation of the surfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Exploring packaging strategies of nano-embedded thermoelectric generators

Embedding nanostructures within a bulk matrix is an important practical approach towards the electronic engineering of high performance thermoelectric systems. For power generation applications, it ideally combines the efficiency benefit offered by low dimensional systems along with the high power output advantage offered by bulk systems. In this work, we uncover a few crucial details about how to embed nanowires and nanoflakes in a bulk matrix so that an overall advantage over pure bulk may be achieved. First and foremost, we point out that a performance degradation with respect to bulk is inevitable as the nanostructure transitions to a multi moded one. It is then shown that a nano embedded system of suitable cross-section offers a power density advantage over a wide range of efficiencies at higher packing fractions, and this range gradually narrows down to the high efficiency regime, as the packing fraction is reduced. Finally, we introduce a metric - the advantage factor, to elucidate quantitatively, the enhancement in the power density offered via nano-embedding at a given efficiency. In the end, we explore the maximum effective width of nano-embedding which serves as a reference in designing generators in the efficiency range of interest.

42 ENGINEERING↗
DOE OSTI2018

Even-handed subsystem selection in projection-based embedding

Projection-based embedding offers a simple framework for embedding correlated wavefunction methods in density functional theory. Partitioning between the correlated wavefunction and density functional subsystems is performed in the space of localized molecular orbitals. However, during a large geometry change—such as a chemical reaction—the nature of these localized molecular orbitals, as well as their partitioning into the two subsystems, can change dramatically. This can lead to unphysical cusps and even discontinuities in the potential energy surface. In this work, we present an even-handed framework for localized orbital partitioning that ensures consistent subsystems across a set of molecular geometries. We illustrate this problem and the even-handed solution with a simple example of an S N 2 reaction. Applications to a nitrogen umbrella flip in a cobalt-based CO 2 reduction catalyst and to the binding of CO to Cu clusters are presented. In both cases, we find that even-handed partitioning enables chemically accurate embedding with modestly sized embedded regions for systems in which previous partitioning strategies are problematic.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Stochastic embedding DFT: Theory and application to p -nitroaniline in water

Over this past decade, we combined the idea of stochastic resolution of identity with a variety of electronic structure methods. In our stochastic Kohn-Sham density functional theory (DFT) method, the density is an average over multiple stochastic samples, with stochastic errors that decrease as the inverse square root of the number of sampling orbitals. Here in this paper, we develop a stochastic embedding density functional theory method (se-DFT) that selectively reduces the stochastic error (specifically on the forces) for a selected subsystem(s). The motivation, similar to that of other quantum embedding methods, is that for many systems of practical interest, the properties are often determined by only a small subsystem. In stochastic embedding DFT, two sets of orbitals are used: a deterministic one associated with the embedded subspace and the rest, which is described by a stochastic set. The method agrees exactly with deterministic calculations in the limit of a large number of stochastic samples. We apply se-DFT to study a p-nitroaniline molecule in water, where the statistical errors in the forces on the system (the p-nitroaniline molecule) are reduced by an order of magnitude compared with nonembedding stochastic DFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Huzinaga projection embedding for efficient and accurate energies of systems with localized spin-densities

We demonstrate the accuracy and efficiency of the restricted open-shell and unrestricted formulation of the absolutely localized Huzinaga projection operator embedding method. Restricted open-shell and unrestricted Huzinaga projection embedding in the full system basis is formally exact to restricted open-shell and unrestricted Kohn–Sham density functional theory, respectively. By utilizing the absolutely localized basis, we significantly improve the efficiency of the method while maintaining high accuracy. Furthermore, the absolutely localized basis allows for high accuracy open-shell wave function methods to be embedded into a closed-shell density functional theory environment. The open-shell embedding method is shown to calculate electronic energies of a variety of systems to within 1 kcal/mol accuracy of the full system wave function result. For certain highly localized reactions, such as spin transition energies on transition metals, we find that very few atoms are necessary to include in the wave function region in order to achieve the desired accuracy. This extension further broadens the applicability of our absolutely localized Huzinaga level-shift projection operator method to include open-shell species. Here, we apply our method to several representative examples, such as spin splitting energies, catalysis on transition metals, and radical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗