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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology

Background: An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. Results: We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for path way and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. Conclusions: The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Wavelength conversion for single-photon polarization qubits through continuous-variable quantum teleportation

A quantum internet connects remote quantum processors that need to interact and exchange quantum signals over a long distance through photonic channels. However, these quantum nodes operate at the wavelength ranges unsuitable for long-distance transmission. Therefore, quantum wavelength conversion to telecom bands is crucial for long-distance quantum networks based on optical fiber. Here, we propose wavelength conversion devices for single-photon polarization qubits using continuous-variable quantum teleportation that can efficiently convert qubits between near-infrared (780–795 nm suitable for interacting with atomic quantum nodes) and telecom wavelength (1300–1500 nm suitable for long-distance transmission). The teleportation uses entangled photon fields (i.e., nondegenerate two-mode squeezed state) that can be generated by four-wave mixing in a rubidium atomic gas using a diamond configuration of atomic transitions. The entangled fields can be emitted in two orthogonal polarizations with locked relative phase, making them especially suitable for interfacing with single- photon polarization qubits. Furthermore, our work may pave the way for the realization of long-distance quantum networks.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2002

Aeronautical Satellite-Assisted Process for Information Exchange Through Network Technologies (Aero-SAPIENT) Conducted

Broadband satellite communications for aeronautics marries communication and network technologies to address NASA's goals in information technology base research and development, thereby serving the safety and capacity needs of the National Airspace System. This marriage of technology increases the interactivity between airborne vehicles and ground systems. It improves decision-making and efficiency, reduces operation costs, and improves the safety and capacity of the National Airspace System. To this end, a collaborative project called the Aeronautical Satellite Assisted Process for Information Exchange through Network Technologies, or Aero-SAPIENT, was conducted out of Tinker AFB, Oklahoma, during November and December 2000.

Zernic, Michael J.↗
DOE OSTI2024

Tetris-inspired detector with neural network for radiation mapping

Abstract Radiation mapping has attracted widespread research attention and increased public concerns on environmental monitoring. Regarding materials and their configurations, radiation detectors have been developed to identify the position and strength of the radioactive sources. However, due to the complex mechanisms of radiation-matter interaction and data limitation, high-performance and low-cost radiation mapping is still challenging. Here, we present a radiation mapping framework using Tetris-inspired detector pixels. Applying inter-pixel padding for enhancing contrast between pixels and neural networks trained with Monte Carlo (MC) simulation data, a detector with as few as four pixels can achieve high-resolution directional prediction. A moving detector with Maximum a Posteriori (MAP) further achieved radiation position localization. Field testing with a simple detector has verified the capability of the MAP method for source localization. Our framework offers an avenue for high-quality radiation mapping with simple detector configurations and is anticipated to be deployed for real-world radiation detection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

A mechanistic study explaining the synergistic viscosity increase obtained from polyethylene oxide (PEO) and {beta}-naphthalene sulfonate (BNS) in shotcrete

In shotcrete, a combination of polyethylene oxide (PEO) and {beta}-naphthalene sulfonate (BNS) is commonly applied to reduce rebound. Here, the mechanism for the synergistic viscosity increase resulting from this admixture combination was investigated via x-ray diffraction (XRD), infrared and nuclear magnetic resonance (NMR) spectroscopy. It was found that the electron-rich aromatic rings present in BNS donate electrons to the alkyl protons of PEO and thus increase the electron density there. This rare interaction is known as CH-{pi} interaction and leads to the formation of a supramolecular structure whereby PEO chains bind weakly to BNS molecules. Through this mechanism a polymer network exhibiting exceptionally high molecular weight and thus viscosity is formed. Among polycondensates, sulfanilic acid-phenol-formaldehyde (SPF) provides even higher synergy with PEO than BNS while melamine (PMS), acetone (AFS) or polycarboxylate (PCE) based superplasticizers do not work at all. Effectiveness of lignosulfonates is dependent on their degree of sulfonation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

New interaction potentials for alkaline earth silicate and borate glasses

New interaction potentials were developed for molecular dynamics simulations to study the role of Mg and Ca in modifying the structure and properties of alkaline earth silicates and borates. Competition between the depolymerization of the silica network and the formation of new bonds between oxygen atoms and modifiers leads to the enhancement of the elastic moduli with increasing modifier content in alkaline earth silicate glasses. Compared with calcium silicate, the higher elastic moduli of magnesium silicate result from a higher connectivity of the overall glass network due to the incorporation of fourfold coordinated magnesium and a more rigid connection between oxygen atoms and modifiers. In contrast to the silicates, the effect of modifier on the elastic moduli of alkaline earth borates is dominated by the formation of fourfold coordinated boron (N 4 ). Calcium borate with higher N 4 shows a more rigid network structure and higher elastic moduli.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Species interactions differ in their genetic robustness

Conflict and cooperation between bacterial species drive the composition and function of microbial communities. Stability of these emergent properties will be influenced by the degree to which species' interactions are robust to genetic perturbations. We use genome-scale metabolic modeling to computationally analyze the impact of genetic changes when Escherichia coli and Salmonella enterica compete, or cooperate. We systematically knocked out in silico each reaction in the metabolic network of E. coli to construct all 2583 mutant stoichiometric models. Then, using a recently developed multi-scale computational framework, we simulated the growth of each mutant E. coli in the presence of S. enterica . The type of interaction between species was set by modulating the initial metabolites present in the environment. We found that the community was most robust to genetic perturbations when the organisms were cooperating. Species ratios were more stable in the cooperative community, and community biomass had equal variance in the two contexts. Additionally, the number of mutations that have a substantial effect is lower when the species cooperate than when they are competing. In contrast, when mutations were added to the S. enterica network the system was more robust when the bacteria were competing. These results highlight the utility of connecting metabolic mechanisms and studies of ecological stability. Cooperation and conflict alter the connection between genetic changes and properties that emerge at higher levels of biological organization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

On the Generalizability of Time-of-Flight Convolutional Neural Networks for Noninvasive Acoustic Measurements

Bulk wave acoustic time-of-flight (ToF) measurements in pipes and closed containers can be hindered by guided waves with similar arrival times propagating in the container wall, especially when a low excitation frequency is used to mitigate sound attenuation from the material. Convolutional neural networks (CNNs) have emerged as a new paradigm for obtaining accurate ToF in non-destructive evaluation (NDE) and have been demonstrated for such complicated conditions. However, the generalizability of ToF-CNNs has not been investigated. In this work, we analyze the generalizability of the ToF-CNN for broader applications, given limited training data. We first investigate the CNN performance with respect to training dataset size and different training data and test data parameters (container dimensions and material properties). Furthermore, we perform a series of tests to understand the distribution of data parameters that need to be incorporated in training for enhanced model generalizability. This is investigated by training the model on a set of small- and large-container datasets regardless of the test data. We observe that the quantity of data partitioned for training must be of a good representation of the entire sets and sufficient to span through the input space. The result of the network also shows that the learning model with the training data on small containers delivers a sufficiently stable result on different feature interactions compared to the learning model with the training data on large containers. To check the robustness of the model, we tested the trained model to predict the ToF of different sound speed mediums, which shows excellent accuracy. Furthermore, to mimic real experimental scenarios, data are augmented by adding noise. We envision that the proposed approach will extend the applications of CNNs for ToF prediction in a broader range.

47 OTHER INSTRUMENTATION↗
NASA NTRS1999

Atmospheric Science Experiment for Mars: ATMIS for the Netlander 2005 Mission

ATMIS (Atmospheric and Meteorological Instrumentation System) is a versatile suite of atmospheric instrumentation to be accommodated onboard the Netlander Mission slated for launch in 2005. Four Netlanders are planned to form a geophysical measurement network on the surface of Mars. The atmospheric sciences are among the scientific disciplines benefiting most of the network concept. The goal of the ATMIS instrument is to provide new data on the atmospheric vertical structure, regional and global circulation phenomena, the Martian Planetary Boundary Layer (PBL) and atmosphere-surface interactions, dust storm triggering mechanisms, as well as the climatological cycles of H2O, dust and CO2. To reach the goal of characterization of a number of phenomena exhibiting both spatial and temporal variations, simultaneous observations of multiple variables at spatially displaced sites Deforming a network D are required. The in situ observations made by the ATMIS sensors will be supported by extensive modeling efforts. Additional information is contained in the original extended abstract.

Harri, A.-M.↗
NASA NTRS2018

Phenolic Polymer Interactions with Water and Ethylene Glycol Solvents

Interactions between pre-cured phenolic polymer chains and a solvent have a significant impact on the structure and properties of the final post-cured phenolic resin. Developing an understanding of the nature of these interactions is important and will aid in the selection of the proper solvent that will lead to the desired final product. Here, we investigate the role of the phenolic chain structure and the solvent type on the overall solvation performance of the system through ab initio techniques and molecular dynamics simulations. Two types of solvents are considered: ethylene glycol (EGL) and H2O. Three phenolic chain structures are considered, including two novolac-type chains with either an ortho-ortho (OON) or an ortho-para (OPN) backbone network and a resole-type (RES) chain with an ortho-ortho network. Each system is characterized through a structural analysis of the solvation shell and the hydrogen-bonding environment as well as through a quantification of the solvation free energy along with partitioned interaction energies between specific molecular species. The combination of simulations and the analyses indicate that EGL provides a higher solvation free energy than H2O due to more energetically favorable hydrophilic interactions as well as favorable hydrophobic interactions between CH element groups. In addition, the phenolic chain structure significantly affects the solvation performance, with OON having limited intermolecular hydrogen-bond formations, while OPN and RES interact more favorably with the solvent molecules. The results suggest that a resole-type phenolic chain with an ortho-para network should have the best solvation performance in EGL, H2O, and other similar solvents.

Haskins, Justin B.↗
DOE OSTI2025

Oscillation Risks of Grid-Following and Grid-Forming Inverter-Based Resources in Series-Compensated Networks

Here, this paper investigates the dynamic behavior of a grid-connected inverter-based resource (IBR) when connected radially to a series compensated line. Potential interactions between the series compensation and the IBR have been identified for both types: grid-following (GFL) or grid-forming (GFM). The study begins with electromagnetic transient (EMT) simulations to demonstrate stability issues. Subsequently, nonlinear analytical models are formulated in the dq frame, validated against the EMT simulation, and leveraged to assess eigenvalues and participation factors. Influencing factors of the dominant oscillation modes have been identified. The analysis results show that series compensation may make a mode associated with the synchronization unit unstable. Furthermore, customized feedback systems are built for the synchronizing loop. Series compensation can increase the sensitivity of the voltage phase angle towards the synchronizing angle, and introduce phase lag in the real power response towards the synchronizing angle. These factors may cause interactions with the phase-locked loop in GFL-IBR systems and with power-based synchronization in GFM-IBR systems, potentially leading to instability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2011

Correctness Proof of a Self-Stabilizing Distributed Clock Synchronization Protocol for Arbitrary Digraphs

This report presents a deductive proof of a self-stabilizing distributed clock synchronization protocol. It is focused on the distributed clock synchronization of an arbitrary, non-partitioned digraph ranging from fully connected to 1-connected networks of nodes while allowing for differences in the network elements. This protocol does not rely on assumptions about the initial state of the system, and no central clock or a centrally generated signal, pulse, or message is used. Nodes are anonymous, i.e., they do not have unique identities. There is no theoretical limit on the maximum number of participating nodes. The only constraint on the behavior of the node is that the interactions with other nodes are restricted to defined links and interfaces. We present a deductive proof of the correctness of the protocol as it applies to the networks with unidirectional and bidirectional links. We also confirm the claims of determinism and linear convergence.

Malekpour, Mahyar R.↗
DOE OSTI2026

Reactive Transport Modeling with Physics-Informed Machine Learning for Critical Minerals Applications

This study presents a physics-informed neural network (PINN) framework for reactive transport modeling for simulating fast bimolecular reactions in porous media. Accurate characterization of cAhemical interactions and product formation in surface and subsurface environments is essential for advancing critical mineral extraction and related geoscience applications. The proposed methodology sequentially addresses the flow and diffusion–reaction subproblems. The flow field is computed using a mixed formulation, while the diffusion–reaction system is modeled via two uncoupled tensorial diffusion equations reformulated in terms of chemical invariants. PINNs are employed to solve the governing equations, enabling data-efficient, mesh-free prediction of chemical concentration fields. The framework is validated through a series of benchmark problems involving flow in heterogeneous porous media. Initial verification is conducted using patch tests for the flow field, followed by validation of the transport problem with emphasis on preserving non-negativity of concentrations. The complete fast bimolecular reaction scenario is then solved, yielding spatial distributions of reactants and product species. Results demonstrate that the PINNs-based approach effectively captures sharp, mixing-limited reaction fronts and dispersive mixing behavior, offering reliable predictions of reactive plume evolution. These capabilities are crucial for evaluating long-term subsurface behavior in applications such as fluid storage, energy extraction, and efficient extraction of critical minerals.

42 ENGINEERING↗
DOE OSTI2026

Agentic traffic intelligence: Augmented human-in-the-loop scenario generation for microscopic traffic simulation

Traditional microscopic traffic simulation generation often relies on static datasets and manual design, limiting its ability to simulate complex conditions easily. This paper presents a novel framework, Agentic Traffic Intelligence, which combines human approval large language models (LLMs), the Real-Twin tool, and multi-agent systems to perform realistic microscopic traffic simulation scenario generation. The proposed framework incorporates human-in-the-loop (HIL) control, retrieval-augmented generation (RAG), and multi-agent control mechanisms. HIL mechanisms are used to guide multiple LLMs focused on attributes for microscopic simulation generation and to improve the interpretability and transparency of LLM execution for users. RAG enhances context extraction by dynamically integrating external knowledge sources for traffic scenario generation foundations. A multi-agent architecture with supervisory control coordinates the interaction of simulation components, including traffic simulators, control logic, and calibration tools. This enables the synthesis of simulation-ready scenarios that reflect dynamic demand profiles and behavior controls. Furthermore, the framework fuses multisource traffic data with unstructured context and supports iterative refinement through interactive user feedback. Validated through microscopic simulation using Simulation of Urban Mobility, the generated scenarios demonstrate high-fidelity network generation with inflow and turn movement and behavioral calibration, offering a robust and efficient tool for stress-testing and optimizing urban mobility systems.

Hierarchical multi-agent control↗
DOE OSTI2018

Comprehensive analysis of long noncoding RNA-associated competing endogenous RNA network in cholangiocarcinoma

Highlights: • LncRNAs as a ceRNA can regulate the expression of target genes, which can influence on tumorigenesis and tumor progression. • We firstly developed novel lncRNAs as well as their action mechanisms in CCA. • We identified a total of 1411 differentially expressed lncRNAs, 3494 mRNAs, and 64 miRNAs. • A ceRNA network consisting of 116 lncRNAs, 14 miRNAs and 59 mRNAs was established. Long non-coding RNAs (lncRNAs) can interact with microRNAs (miRNAs) as a competing endogenous RNA (ceRNA) to regulate the expression of target genes, which can largely influence on tumorigenesis and tumor progression. However, the role of lncRNA-mediated ceRNAs in cholangiocarcinoma (CCA) remains unknown. This study aimed to develop novel lncRNAs as well as their action mechanisms in CCA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Utilization of mixed ligands to construct two new coordination polymers: Syntheses, structures and properties

The use of triazine and aromatic carboxylic acid as mixed chelating ligands in preparing two coordination polymers is described. Two new transition-metal coordination polymers, namely, [Co{sub 2}(bpdc){sub 4}(phdat){sub 2}] (1) and [Zn(bpdc)]{sub n} (2) (H{sub 2}bpdc=2,4-biphenyldicarboxylic acid, phdat=2,4-diamine-6-phenyl-1,3,5-triazine), have been hydrothermally synthesized and structurally characterized by IR, elemental analyses, X-ray single-crystal diffraction and TGA. Compound 1 is a 0D structure and extends to a 3D network by two different N–H···O and N–H···N hydrogen bonds. Compound 2 exhibits a 2D network with 4{sup 4}.6{sup 2} topological net, which contains two kinds of single helical chains. The interactions within each Co(II)–Co(II) pair of compound 1 are antiferromagnetic (g=2.19, J=−22 K, zj′=−0.00351 K). Furthermore, the photoluminescence property of 2 was also investigated in the solid state at room temperature. - Graphical abstract: Two polymeric metal compounds based on mixed-ligands were synthesized and characterized. The use of different metal ions results in distinct structures. The magnetic and fluorescent properties were also studied. - Highlights: • The first bpdc{sup 2−}/phdat-based 0D discrete coordination complex. • A new 2D architecture with two kinds of helical chains. • The structure-dependent magnetism and photoluminescence properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗