Search NASA⌕ Search

SEARCH · Search NASA

Results for “PATH INTEGRALS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Conceptual Basis and Techno-Economic Modeling for Integrated Algal Biorefinery Conversion of Microalgae to Fuels and Products (2019 NREL TEA Update: Highlighting Paths to Future Cost Goals via a New Pathway for Combined Algal Processing)

The report documents the conceptual basis for a new potential Combined Algal Processing design strategy which may allow more flexibility in accommodating different algal biomass feedstock compositions, by enabling upgrading of both protein and carbohydrates in a single step, without a strict requirement for either component to be in soluble or monomeric form, while maintaining effective wet lipid extraction techniques to enable high lipid recoveries. In light of previously-established constraints around algal biomass costs (which are significantly higher than lignocellulosic terrestrial biomass), the present CAP processing strategy reflects an integrated biorefinery concept producing both fuels and value-added chemical coproducts as a means to improve profitability and generate coproduct revenues to help drive down the minimum fuel selling price (MFSP) towards economically viable levels. Namely, this report highlights an integrated CAP biorefinery process and associated technical targets that would be required to achieve U.S. Department of Energy target MFSP goals of $2.5/gallon gasoline equivalent by 2030. This is accomplished by a process involving low-cost seasonal storage of algal biomass during high-growth seasons, rapid flash hydrolysis pretreatment of the biomass, solvent extraction of pretreated biomass, cleanup and fractionation of lipids into triglyceride and free fatty acid fractions, and a series of thermochemical conversion steps to upgrade carbohydrates and protein to hydrocarbon fuels. These steps include mild oxidative treatment (MOT), a process originally investigated at NREL for upgrading lignin, followed by catalytic ketonization and hydrotreating of MOT products to fuels. Isolated triglycerides are sent to a coproduct train, with the base case focused on upgrading to polyurethane foams as a high-value, high-market-volume coproduct.

09 BIOMASS FUELS↗
DOE OSTI2024

An explainable variational autoencoder model for three-dimensional acoustic emission source localization in hollow cylindrical structures

We introduce an explainable variational autoencoder for three-dimensional (3D) localization of acoustic emission sources in hollow cylindrical structures, with an unsupervised approach. This research capitalizes on multi-arrival waveforms generated by helical path propagation in cylindrical geometries to enable efficient two-receiver localization. By integrating the modal characteristics of Lamb modes under multi-path conditions, we demonstrate that two sets of time-of-arrival differences and peak amplitudes extracted from one receiver can serve as effective localization features. This initial approach identifies four potential source locations, highlighting the feasibility of two-receiver source localization using traditional feature extraction methods. However, direct extraction can be challenging when mode overlaps occur, complicating the localization process. To address this, our work proposes a novel waveform-based method. This method leverages the consistent dispersion characteristics within isotropic materials, where each unique combination of mode arrival times and peak amplitudes constructs a distinct waveform. This distinctiveness overcomes the ambiguities associated with mode overlaps, significantly enhancing the method’s precision and robustness. Our approach adopts a data-driven strategy for waveform-based localization using variational autoencoder (VAE). VAE discerns waveform patterns for localization, while also addressing data uncertainties. The VAE’s encoder and decoder networks capture the localization process and the source’s influence on waveform generation, respectively, guiding latent variables to segregate waveforms by source in the latent space. The design of the learning process focuses on specific localization characteristics to enhance result explainability. Localization predictions are generated by projecting test waveforms, not included in the training set, onto a trained latent space. The prediction is determined using a nearest-neighbor approach based on the closest latent representation of a source. Validation with pencil-lead-break tests on a metallic pipe confirmed our method’s effectiveness, achieving an averaged 3D localization accuracy of 0.84.

Lee, Guan-Wei↗
DOE OSTI2018

Hybrid Integration of III-V Solar Microcells for High Efficiency Concentrated Photovoltaic Modules

The design, fabrication and performance of InGaAs and InGaP/GaAs microcells are presented. These cells are integrated with a Si wafer providing a path for insertion in hybrid concentrated photovoltaic modules. Comparisons are made between bonded cells and cells fabricated on their native wafer. The bonded cells showed no evidence of degradation in spite of the integration process which involved significant processing including the removal of the III-V substrate. Results from a number of hybrid cell configurations were reported. These cells employed integration techniques including wafer level bonding of processed cells and solder bonding of the cells. Lastly, the cells themselves showed evidence of degradation in spite of the integration process, which involved significant processing including the removal of the III-V substrate.

14 SOLAR ENERGY↗
DOE OSTI2015

Jumpstarting commercial-scale CO 2 capture and storage with ethylene production and enhanced oil recovery in the US Gulf

CO 2 capture, utilization, and storage (CCUS) technology has yet to be widely deployed at a commercial scale despite multiple high-profile demonstration projects. We suggest that developing a large-scale, visible, and financially viable CCUS network could potentially overcome many barriers to deployment and jumpstart commercial-scale CCUS. To date, substantial effort has focused on technology development to reduce the costs of CO 2 capture from coal-fired power plants. Here, we propose that near-term investment could focus on implementing CO 2 capture on facilities that produce high-value chemicals/products. These facilities can absorb the expected impact of the marginal increase in the cost of production on the price of their product, due to the addition of CO 2 capture, more than coal-fired power plants. A financially viable demonstration of a large-scale CCUS network requires offsetting the costs of CO 2 capture by using the CO 2 as an input to the production of market-viable products. As a result, we demonstrate this alternative development path with the example of an integrated CCUS system where CO 2 is captured from ethylene producers and used for enhanced oil recovery in the U.S. Gulf Coast region.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Predicting Melt Curves of Energetic Materials Using Molecular Models

Here, in this work, the solid–liquid coexistence curves of classical fully flexible atomistic models of α-RDX and β-HMX were calculated using thermodynamically rigorous methodologies that identify where the free energy difference between the phases is zero. The free energy difference between each phase at a given state point was computed using the pseudosupercritical path (PSCP) method, and Gibbs–Helmholtz integration was used to evaluate the solid–liquid free energy difference as a function of temperature. This procedure was repeated for several pressures to determine points along the coexistence curve, which were then fit to the Simon–Glatzel functional form. While effective, this method is computationally expensive. An alternative approach is to compute the melting point at a single pressure via the PSCP method, and then use the Gibbs–Duhem integration technique to trace out the coexistence curve in a more computationally economical manner. Both approaches were used to determine the coexistence curve of α-RDX. The Gibbs–Duhem integration method was shown to generate a melt curve that is in good agreement with the PSCP-derived melt curve, while only costing ~10 % of the computational resources used for the PSCP method. For α-RDX, the predicted melting temperature increases significantly more for a given increase in pressure when compared to available experimental data.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2018

Improved Sensitivity and Separations for Phosphopeptides using Online Liquid Chromotography Coupled with Structures for Lossless Ion Manipulations Ion Mobility–Mass Spectrometry

Phosphoproteomics greatly augments proteomics and holds tremendous potential for insights into the modulation of biological systems for various disease states, etc. However, numerous challenges hinder conventional methods in terms of measurement sensitivity, throughput, and capabilities for confident phosphopeptide and phosphosite identification. In this work, we report the first example of integrating structures for lossless ion manipulations ion mobility (SLIM) IM-MS with online reversed-phase liquid chromatography (LC) to evaluate its potential for addressing the aforementioned challenges. A mixture of 51 heavy-labeled phosphopeptides was analyzed with a SLIM IM module having integrated ion accumulation and long-path separation regions. The SLIM IM-MS provided improved sensitivity over an established LC-SRM method, with limits of detection as low as 50 pM (50 amol/µl) for several peptides. Conventionally problematic phosphopeptide isomers could be resolved following an 18 m SLIM IM separation. The 2-D peak capacity was estimated as ~9000 for 90 min LC separation coupled to an 18 m SLIM IM separation, considerably higher than LC alone and providing a basis for both improved identification and quantification, with additional gains projected with the future use of longer path SLIM IM separations. Thus, LC-SLIM IM-MS offers great potential for improving the sensitivity, separation, and throughput of phosphoproteomics analyses.

Chouinard, Christopher D.↗
DOE OSTI2019

Heteroepitaxial vertical perovskite hot-electron transistors down to the monolayer limit

Two-dimensional heterostructures combined with vertical geometries are candidates to probe and utilize the physical properties of atomically-thin materials. The vertical configuration enables a unique form of hot-carrier spectroscopy as well as atomic-scale devices. Here, we present the room-temperature evolution of heteroepitaxial perovskite hot-electron transistors using a SrRuO 3 base down to the monolayer limit ( ~ 4 Å). As a fundamental electronic probe, we observe an abrupt transition in the hot-electron mean free path as a function of base thickness, coinciding with the thickness-dependent resistive transition. As a path towards devices, we demonstrate the integrated synthesis of perovskite one-dimensional electrical edge contacts using water-soluble and growth-compatible Sr 3 Al 2 O 6 hard masks. Edge-contacted monolayer-base transistors exhibit on/off ratios reaching ~ 10 8 , complete electrostatic screening by the base manifesting pure hot-electron injection, and excellent scaling of the output current density with device dimensions. These results open new avenues for incorporating emergent phenomena at oxide interfaces and in heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Synthetic magnetoelectric coupling in a nanocomposite multiferroic

Given the paucity of single phase multiferroic materials (with large ferromagnetic moment), composite systems seem an attractive solution to realize magnetoelectric coupling between ferromagnetic and ferroelectric order parameters. Despite having antiferromagnetic order, BiFeO₃ (BFO) has nevertheless been a key material due to excellent ferroelectric properties at room temperature. We studied a superlattice composed of 8 repetitions of 6 unit cells of La₀.₇Sr₀.₃MnO₃ (LSMO) grown on 5 unit cells of BFO. Significant net uncompensated magnetization in BFO, an insulating superlattice, is demonstrated using polarized neutron reflectometry. Remarkably, the magnetization enables magnetic field to change the dielectric properties of the superlattice, which we cite as an example of synthetic magnetoelectric coupling. Importantly, controlled creation of magnetic moment in BFO is a much needed path toward design and implementation of integrated oxide devices for next generation magnetoelectric data storage platforms.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Compositional dependence of linear and nonlinear optical response in crystalline hafnium zirconium oxide thin films

Composition dependence of second harmonic generation, refractive index, extinction coefficient, and optical bandgap in 20 nm thick crystalline Hf 1– x Zr x O 2 (0 ≤ x ≤ 1) thin films is reported here. The refractive index exhibits a general increase with increasing ZrO 2 content with all values within the range of 1.98–2.14 from 880 nm to 400 nm wavelengths. A composition dependence of the indirect optical bandgap is observed, decreasing from 5.81 eV for HfO 2 to 5.17 eV for Hf 0.4 Zr 0.6 O 2 . The bandgap increases for compositions with x > 0.6, reaching 5.31 eV for Hf 0.1 Zr 0.9 O 2 . Second harmonic signals are measured for 880 nm incident light. The magnitude of the second harmonic signal scales with the magnitude of the remanant polarization in the composition series. Film compositions that display near zero remanent polarizations exhibit minimal second harmonic generation while those with maximum remanent polarization also display the largest second harmonic signal. The results are discussed in the context of ferroelectric phase assemblage in the hafnium zirconium oxide films and demonstrate a path toward a silicon-compatible integrated nonlinear optical material.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A model of spatio-temporal regulation within biomaterials using DNA reaction–diffusion waveguides

In multi-cellular organisms, cells and tissues coordinate biochemical signal propagation across length scales spanning micrometres to metres. Designing synthetic materials with similar capacities for coordinated signal propagation could allow these systems to adaptively regulate themselves across space and over time. Here, we combine ideas from cell signalling and electronic circuitry to propose a biochemical waveguide that transmits information in the form of a concentration of a DNA species on a directed path. The waveguide could be seamlessly integrated into a soft material because there is virtually no difference between the chemical or physical properties of the waveguide and the material it is embedded within. We propose the design of DNA strand displacement reactions to construct the system and, using reaction–diffusion models, identify kinetic and diffusive parameters that enable super-diffusive transport of DNA species via autocatalysis. Finally, to support experimental waveguide implementation, we propose a sink reaction and spatially inhomogeneous DNA concentrations that could mitigate the spurious amplification of an autocatalyst within the waveguide, allowing for controlled waveguide triggering. Chemical waveguides could facilitate the design of synthetic biomaterials with distributed sensing machinery integrated throughout their structure and enable coordinated self-regulating programmes triggered by changing environmental conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Energy Flow in Thin Shell Implosions and Explosions

Energy flow and balance in convergent systems beyond petapascal energy densities controls the fate of late-stage stars and the potential for controlling thermonuclear inertial fusion ignition. Time-resolved x-ray self-emission imaging combined with a Bayesian inference analysis is used to describe the energy flow and the potential information stored in the rebounding spherical shock at 0.22 PPa (2.2 Gbar or billions of atmospheres pressure). This analysis, together with a simple mechanical model, describes the trajectory of the shell and the time history of the pressure at the fuel-shell interface, ablation pressure, and energy partitioning including kinetic energy of the shell and internal energy of the fuel. Here, the techniques used here provide a fully self-consistent uncertainty analysis of integrated implosion data, a thermodynamic-path independent measurement of pressure in the petapascal range, and can be used to deduce the energy ow in a wide variety of implosion systems to petapascal energy densities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

High-resolution magnetic microscopy applications using nitrogen-vacancy centers in diamond

Magnetic microscopy with high spatial resolution helps to solve a variety of technical problems in condensed-matter physics, electrical engineering, biomagnetism, and geomagnetism. In this work we used quantum diamond magnetic microscope (QDMM) setups, which use a dense uniform layer of magnetically-sensitive nitrogen-vacancy (NV) centers in diamond to image an external magnetic field using a fluorescence microscope. We used this technique for imaging few-micron ferromagnetic needles used as a physically unclonable function (PUF) and to passively interrogate electric current paths in a commercial 555 timer integrated circuit (IC). As part of the QDMM development, we also found a way to calculate ion implantation recipes to create diamond samples with dense uniform NV layers at the surface. This work opens the possibility for follow-up experiments with 2D magnetic materials, ion implantation, and electronics characterization and troubleshooting.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Allometric Trophic Networks From Individuals to Socio-Ecosystems: Consumer–Resource Theory of the Ecological Elephant in the Room

A well-known parable is that of the blind men studying an elephant each of which assert the elephant is the part they first hold in their hands, e.g., “rope!” says the tail holder while the leg holder asserts “tree!” The various subdisciplines of ecology appear similar in that we each engage in our enthusiastic but at least somewhat myopic study with remarkably limited agreement or even discussion about the overall system which we all study. Allometric trophic network (ATN) theory offers a path out of this dilemma by integrating across scales, taxa, habitats and organizational levels from physiology to ecosystems based on consumer-resource interactions among co-existing organisms. The network architecture and the metabolic and behavioral processes that determine the structure and dynamics of these interactions form the first principles of ATN theory, which in turn provides a synthetic overview and powerfully predictive framework for ecology from organisms to ecosystems. Beyond ecology, ATN theory also synthesizes eco-evolutionary and socio-ecological research still largely based on consumer-resource mechanisms but respectively integrated with different processes including natural selection and market mechanisms. This paper briefly describes foundations, advances, and future directions of ATN theory including predicting an ecosystem’s phenotype from its community’s genotype in order to accelerate more predictive and unified understanding of the complex systems studied by ecologists and other environmental scientists.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Statistical Relations among Solid Precipitation, Atmospheric Moisture and Cloud Parameters in the Arctic

Observations collected during cold-season precipitation periods at Utquagvik, Alaska and at the multidisciplinary drifting observatory for the study of Arctic climate (MOSAiC) are used to statistically analyze the relations among the atmospheric water cycle parameters including the columnar supercooled liquid and ice amounts (expressed as liquid-water and ice-water paths, i.e., LWP and IWP), the integrated water vapor (IWV) and the near-surface snowfall rate. Data come from radar and radiometer-based retrievals and from optical precipitation sensors. While the correlation between snowfall rate and LWP is rather weak, correlation coefficients between radar-derived snowfall rate and IWP are high (~0.8), which is explained, in part, by the generally low LWP/IWP ratios during significant precipitation. Correlation coefficients between snowfall rate and IWV are moderate (~0.45). Correlations are generally weaker if snowfall is estimated by optical sensors, which is, in part, due to blowing snow. Correlation coefficients between near-surface temperature and snowfall rates are low (r < 0.3). The results from the Alaska and MOSAiC sites are generally similar. These results are not very sensitive to the amount of time averaging (e.g., 15 min averaging versus daily averages). Observationally based relations among the water cycle parameters are informative about atmospheric moisture conversion processes and can be used for model evaluations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Energy Flow in Thin Shell Implosions and Explosions

Energy flow and balance in convergent systems beyond petapascal energy densities controls the fate of late-stage stars and the potential for controlling thermonuclear inertial fusion ignition. Timeresolved x-ray self-emission imaging combined with a Bayesian inference analysis is used to describe the energy flow and the potential information stored in the rebounding spherical shock at 0.22 petaPascal (2.2 Gbar or billions of atmospheres pressure). This analysis, together with a simple mechanical model, describes the trajectory of the shell and the time history of the pressure at the fuel-shell interface, ablation pressure, and energy partitioning including kinetic energy of the shell and internal energy of the fuel. The techniques used here provide a fully self-consistent uncertainty analysis of integrated implosion data, a thermodynamic-path independent measurement of pressure in the petaPascal range, and can be used to deduce the energy flow in a wide variety of implosion systems to petapascal energy densities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Assembly for directing combustion gas

An arrangement is provided for delivering gases from a plurality of combustors of a can-annular gas turbine combustion engine to a first row of turbine blades including a first row of turbine blades. The arrangement includes a gas path cylinder, a cone and an integrated exit piece (IEP) for each combustor. Each IEP comprises an inlet chamber for receiving a gas flow from a respective combustor, and includes a connection segment. The IEPs are connected together to define an annular chamber extending circumferentially and concentric to an engine longitudinal axis, for delivering the gas flow to the first row of blades. A radiused joint extends radially inward from a radially outer side of the inlet chamber to an outer boundary of the annular chamber, and a flared fillet extends radially inward from a radially inner side of the inlet chamber to an inner boundary of the annular chamber.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Retrieval Augmented Generation for Robust Cyber Defense

In cybersecurity, the ability to efficiently analyze and respond to vulnerabilities, weaknesses, attack patterns, and threat tactics is critical for effective defense strategies. With the increasing complexity and volume of cybersecurity data, traditional methods of querying and retrieving information are often inadequate. To address this challenge, we implemented Retrieval-Augmented Generation (RAG) systems—CyRAG and GraphCyRAG—that integrate large language models (LLMs) with both structured data from relational databases and knowledge graphs such as Neo4j. CyRAG is designed to handle structured data, focusing on CVE (Common Vulnerabilities and Exposures) and CWE (Common Weakness Enumeration) entities to generate accurate and context-rich responses. In contrast, GraphCyRAG leverages Neo4j knowledge graphs to retrieve interconnected information from CVE, CWE, CAPEC (Common Attack Pattern Enumeration and Classification), and ATT&CK (Adversarial Tactics, Techniques, and Common Knowledge) datasets. By utilizing Neo4j’s graph-based framework, GraphCyRAG enables deeper traversal of relationships between vulnerabilities and attack patterns, providing cybersecurity analysts with more comprehensive insights into potential attack vectors and mitigation strategies. Our preliminary results demonstrate that integrating knowledge graphs with RAG significantly enhances both the accuracy and depth of threat analysis, allowing for the retrieval of dynamic, real-time data and the generation of contextually aware responses. This approach helps analysts uncover hidden relationships between cyber entities, predict exploit paths, and prioritize mitigation efforts effectively. The integration of RAG with cybersecurity knowledge graphs represents a significant advancement in cybersecurity threat intelligence, enabling more informed decision-making and stronger defense strategies.

97 MATHEMATICS AND COMPUTING↗