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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 829 records · Page 46
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NASA NTRS2002

Spectral Re-Growth Reduction for CCSDS 8-D 8-PSK TCM

This report presents a study on the CCSDS recommended 8-dimensional 8 PSK Trellis Coded Modulation (TCM) scheme. The important steps of the CCSDS scheme include: conversion of serial data into parallel form, differential encoding, convolutional encoding, constellation mapping, and filtering the 8-PSK symbols using the square root raised cosine (SRRC) pulses. The last step, namely the filtering of the 8 PSK symbols using SRRC pulses, significantly affects the bandwidth of the signal. If a nonlinear power amplifier is used, the SRRC filtered signal creates spectral regrowth. The purpose of this report is to investigate a technique, called the smooth phase interpolated keying (SPIK), that can provide an alternative to SRRC filtering so that good spectral as well as power efficiencies can be obtained with the CCSDS encoder. The results of this study show that the CCSDS encoder does not affect the spectral shape of the SRRC filtered signal or the SPIK signal. When a nonlinear traveling wave tube amplifier (TWTA) is used, the spectral performance of the SRRC signal degrades significantly while the spectral performance of SPIK remains unaffected. The degrading effect of a nonlinear solid state power amplifier (SSPA) on SRRC is found to be less than that due to a nonlinear TWTA. However, in both cases, the spectral performance of the SRRC modulated signal is worse than that of the SPIK signal. The bit error rate (BER) performance of the SRRC signal in a linear amplifier environment is about 2.5 dB better than that of the SPIK signal when both the receivers use algorithms of similar complexity. In a nonlinear TWTA environment, the SRRC signal requires accurate phase tracking since the TWTA introduces additional phase distortion. This problem does not arise with SPIK signal due to its constant envelope property. When a nonlinear amplifier is used, the SRRC method loses nearly 1 dB in the bit error rate performance. The SPIK signal does not lose any performance. Thus the performance gap between SRRC and SPIK reduces. The BER performance of SPIK can be improved even further by using a more optimal receiver. A similar optimal receiver for SRRC is quite complex since the amplifier distorts the pulse shape. However, this requires further investigation and is not covered in this report.

Borah, Deva K.↗
DOE OSTI2024

A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. Here, the proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10 -7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10 -5 . The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios.

3D reconstruction model↗
DOE OSTI2024

Deep Learning-based Parameterization of Complex 3D CO2 Saturation Data in Large-scale Geological Carbon Storage

In deep learning (DL), dimension reduction plays a pivotal role in improving training efficiency and minimizing overfitting, especially when working with complex datasets like three-dimensional (3D) saturation data. In the context of geological carbon storage (GCS), 3D saturation data introduces unique challenges due to its sparse nature and sharp transitions at plume boundaries, known as shock fronts. To tackle these challenges, we developed a novel DL framework that combines dimension reduction with advanced 3D reconstruction techniques. Our approach utilizes latent variables derived from 2D average saturation fields to efficiently capture the essential features of high-dimensional data while reducing the number of variables. This enhances both the robustness and accuracy of DL models, making the framework more practical for real-world applications. By offering a tailored solution for modeling complex 3D saturation dynamics, this framework holds significant potential for environmental monitoring, energy storage, and other geological applications.

Wang, Hongsheng [University of Texas at Austin]↗
DOE OSTI2016

Late Side Effects After Image Guided Intensity Modulated Radiation Therapy Compared to 3D-Conformal Radiation Therapy for Prostate Cancer: Results From 2 Prospective Cohorts

Purpose: Technical developments in the field of external beam radiation therapy (RT) enabled the clinical introduction of image guided intensity modulated radiation therapy (IG-IMRT), which improved target conformity and allowed reduction of safety margins. Whether this had an impact on late toxicity levels compared to previously applied three-dimensional conformal radiation therapy (3D-CRT) is currently unknown. We analyzed late side effects after treatment with IG-IMRT or 3D-CRT, evaluating 2 prospective cohorts of men treated for localized prostate cancer to investigate the hypothesized reductions in toxicity. Methods and Materials: Patients treated with 3D-CRT (n=189) or IG-IMRT (n=242) to 78 Gy in 39 fractions were recruited from 2 Dutch randomized trials with identical toxicity scoring protocols. Late toxicity (>90 days after treatment) was derived from self-assessment questionnaires and case report forms, according to Radiation Therapy Oncology Group/European Organization for Research and Treatment of Cancer (RTOG-EORTC) scoring criteria. Grade ≥2 endpoints included gastrointestinal (GI) rectal bleeding, increased stool frequency, discomfort, rectal incontinence, proctitis, and genitourinary (GU) obstruction, increased urinary frequency, nocturia, urinary incontinence, and dysuria. The Cox proportional hazards regression model was used to compare grade ≥2 toxicities between both techniques, adjusting for other modifying factors. Results: The 5-year cumulative incidence of grade ≥2 GI toxicity was 24.9% for IG-IMRT and 37.6% following 3D-CRT (adjusted hazard ratio [HR]: 0.59, P=.005), with significant reductions in proctitis (HR: 0.37, P=.047) and increased stool frequency (HR: 0.23, P<.001). GU grade ≥2 toxicity levels at 5 years were comparable with 46.2% and 36.4% following IG-IMRT and 3D-CRT, respectively (adjusted HR: 1.19, P=.33). Other strong predictors (P<.01) of grade ≥2 late toxicity were baseline complaints, acute toxicity, and age. Conclusions: Treatment with IG-IMRT reduced the risk of late grade ≥2 complications, whereas GU toxicities remained comparable. This clinically relevant observation demonstrates that IMRT and image-guidance should therefore be the preferred treatment option, provided that margin reduction is implemented with caution.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Quasi-One-Dimensional Spin Excitations in the Iron Pnictide NaFe 0.53 ⁢Cu 0.47 ⁢As

Spectroscopic measurements in model 1D correlated systems offer insights for understanding their two-dimensional counterparts, which include the cuprate and iron pnictide/chalcogenide superconductors. A major challenge is the identification of such correlated systems with dominantly 1D physics. Here, in this Letter, inelastic neutron scattering measurements on NaFe 0.53⁢ Cu 0.47 ⁢As single crystal directly reveal quasi-1D spin excitations, resulting from atomic order that leads to magnetic Fe and nonmagnetic Cu chains. The dominant exchange interaction is antiferromagnetic along the chain [𝑆⁢𝐽 ∥ ≈ 90.1⁢(3) meV], whereas the inter-chain couplings are much weaker [𝑆⁢𝐽 ⊥ ≈ −2.4⁢(1) meV and 𝑆⁢𝐽 c ≈ 0.15⁢(5) meV]. The quasi-1D spin excitations in NaFe 0.53 ⁢Cu 0.47⁢ As stem from both the Néel and stripe vectors, with Néel excitations sensitive to Fe impurities on the Cu site. The spin excitations in quasi-1D NaFe 0.53 ⁢Cu 0.47⁢ As and quasi-2D FeSe exhibit a striking resemblance, suggesting a common origin for their coexistent stripe and Néel excitations. Our findings demonstrate magnetic dilution in NaFeAs leads to dimension reduction of its magnetic degree of freedom, presenting a strategy for discovering low-dimensional quantum materials.

Wang, Yifan [Zhejiang Univ., Hangzhou (China)]↗
DOE OSTI2015

Electronic, structural, and substrate effect properties of single-layer covalent organic frameworks

Recently synthesized two-dimensional covalent organic frameworks (COFs) exhibit high surface area, large pore size, and unique structural architectures, making them promising materials for various energy applications. Here, a total of nine COFs structures, including two deposited on a hexagonal boron nitride substrate, are investigated using density functional theory, quasi-particle many-body theory within the GW approximation, and an image charge model. The structures considered belong to two major families (thiophene-based COF-n (T-COF-n) and tetrakis (4-aminophenyl) porphyrin-x (TAPP-x)) differing from the presence of B—O or C=N linkers. While T-COF-n structures are shown to constitute planar networks, TAPP-x systems can display non-negligible corrugation due to the out-of-plane rotation of phenyl rings. We find that the electronic properties do not differ significantly when altering the chain molecules within each family. Many-body effects are shown to lead to large band-gap increase while the presence of the substrate yields appreciable reductions of the gaps, due to substrate polarization effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Nitrogen and Fluorine-Codoped Carbon Nanowire Aerogels as Metal-Free Electrocatalysts for Oxygen Reduction Reaction

The development of active, durable, and low-cost catalysts to replace noble metal-based materials is highly desirable to promote the sluggish oxygen reduction reaction in fuel cells. Herein, nitrogen and fluorine-codoped three-dimensional carbon nanowire aerogels, composed of interconnected carbon nanowires, were synthesized for the first time by a hydrothermal carbonization process. Owing to their porous nanostructures and heteroatom-doping, the as-prepared carbon nanowire aerogels, with optimized composition, present excellent electrocatalytic activity that is comparable to commercial Pt/C. Remarkably, the aerogels also exhibit superior stability and methanol tolerance. This synthesis procedure paves a new way to design novel heteroatomdoped catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Rholography, black holes and Scherk-Schwarz

We present a construction of a class of near-extremal asymptotically flat black hole solutions in four (or five) dimensional gauged supergravity with R-symmetry gaugings obtained from Scherk-Schwarz reductions on a circle. The entropy of these black holes is counted holographically by the well known MSW (or D1/D5) system, with certain twisted boundary conditions labeled by a twist parameter ρ. Here, we find that the corresponding (0, 4) (or (4, 4)) superconformal algebras are exactly those studied by Schwimmer and Seiberg, using a twist on the outer automorphism group. The interplay between R-symmetries, ρ-algebras and holography leads us to name our construction “Rholography”.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Modeling rarefied gas chemistry with QuiPS, a novel quasi-particle method

The goal of this work is to build up the capability of quasi-particle simulation (QuiPS), a novel flow solver, such that it can adequately model the rarefied portion of an atmospheric reentry trajectory. Direct simulation Monte Carlo (DSMC) is the conventional solver for such conditions, but struggles to resolve transient flows, trace species, and high-level internal energy states due to stochastic noise. Quasi-particle simulation (QuiPS) is a novel Boltzmann solver that describes a system with a discretized, truncated velocity distribution function. The resulting fixed-velocity, variable weight quasi-particles enable smooth variation of macroscopic properties. The distribution function description enables the use of a variance-reduced collision model, greatly minimizing expense near equilibrium. This work presents the addition of a neutral air chemistry model to QuiPS and some demonstrative 0D simulations. The explicit representation of internal distributions in QuiPS reveals some of the flaws in existing physics models. Overall, variance reduction, a key feature of QuiPS, can greatly reduce expense of multi-dimensional calculations, but is only cheaper when the gas composition is near chemical equilibrium.

42 ENGINEERING↗
DOE OSTI2024

Exploring Ion Mobility Mass Spectrometry Data File Conversions to Leverage Existing Tools and Enable New Workflows

Ion mobility (IM) is often combined with LC-MS experiments to provide an additional dimension of separation for complex sample analysis. While highly complex samples are better characterized by the full dimensionality of LC-IM-MS experiments to uncover new information, downstream data analysis workflows are often not equipped to properly mine the additional IM dimension. For many samples the data acquisition benefits of including IM separations are all that is necessary to uncover sample information and the full dimensionality of the data is not required for data analysis. Post-acquisition reduction and adaptation of the dimensions of LC-IM-MS and IM-MS experiments into an LC-MS format opens the possibility to use a plethora of existing software tools. In this work, we developed data file conversion tools to reduce the complexity of IM data analysis. Three data file transformations are introduced in the PNNL PreProcessor software: 1) mapping the IM axis to the LC axis for IM-MS data, 2) converting the drift time vs. m/z space to CCS/z vs m/z space, and 3) transforming All Ions IM/MS mobility aligned fragmentation data to a standard LC-MS DDA data file format. Finally, these new data file conversions are demonstrated with corresponding lipidomics and proteomics workflows that leverage existing LC-MS data analysis software to highlight the benefits of the data transformations.

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

Multi-objective goal-directed optimization of de novo stable organic radicals for aqueous redox flow batteries

Abstract Advances in the field of goal-directed molecular optimization offer the promise of finding feasible candidates for even the most challenging molecular design applications. One example of a fundamental design challenge is the search for novel stable radical scaffolds for an aqueous redox flow battery that simultaneously satisfy redox requirements at the anode and cathode, as relatively few stable organic radicals are known to exist. To meet this challenge, we develop a new open-source molecular optimization framework based on AlphaZero coupled with a fast, machine-learning-derived surrogate objective trained with nearly 100,000 quantum chemistry simulations. The objective function comprises two graph neural networks: one that predicts adiabatic oxidation and reduction potentials and a second that predicts electron density and local three-dimensional environment, previously shown to be correlated with radical persistence and stability. With no hard-coded knowledge of organic chemistry, the reinforcement learning agent finds molecule candidates that satisfy a precise combination of redox, stability and synthesizability requirements defined at the quantum chemistry level, many of which have reasonable predicted retrosynthetic pathways. The optimized molecules show that alternative stable radical scaffolds may offer a unique profile of stability and redox potentials to enable low-cost symmetric aqueous redox flow batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Controlled plasma–droplet interactions: a quantitative study of OH transfer in plasma–liquid interaction

Plasmas in contact with liquids are a rich source of OH radicals and have been extensively studied in the last decade to leverage the ability to generate chemically reactive species in gas phase plasmas to decompose organics. Multiphase transfer of OH radicals is highly transport limited and to overcome transport limits, the plasma activation of aerosols, small liquid droplets, interspersed in the plasma has been proposed. In this work, we report a combined experimental and modeling study of a controlled plasma–droplet interaction experiment using a diffuse RF glow discharge in He + 0.2% H 2 O with detailed plasma diagnostics, ex situ analysis of the plasma-induced chemistry in the droplet containing formate, droplet trajectory and size measurements. This enables a quantitative study of the reactivity transfer of OH from the gas phase plasma to the liquid phase and how its diffusion limitations impact formate decomposition in the water droplet. For a droplet with a diameter of 36 μm, we observed 50% reduction in formate concentration in the droplets after plasma treatment for droplet residence times in the plasma of ~10 ms. These short droplet residence times in the plasma allow in some cases for droplet size reductions of ~5% in spite gas temperatures of 360 K. A one-dimensional reaction–diffusion model was used to calculate the OH transport and formate oxidation inside the droplet and was able to predict the conversion of formate by plasma in a droplet without any fitting parameters. The model further shows that formate conversion is dominated by near-interfacial reactions with OH radicals and is limited by diffusion of formate in the droplet. Here, the results show that a controlled plasma–micro-droplet reactor as reported in this study might be an excellent tool for detailed quantitative plasma–liquid interaction studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Spontaneous Valley Polarization of Itinerant Electrons

Memory or transistor devices based on an electron’s spin rather than its charge degree of freedom offer certain distinct advantages and comprise a cornerstone of spintronics. Recent years have witnessed the emergence of a new field, valleytronics, which seeks to exploit an electron’s valley index rather than its spin. An important component in this quest would be the ability to control the valley index in a convenient fashion. Here we show that the valley polarization can be switched from zero to 1 by a small reduction in density, simply tuned by a gate bias, in a two-dimensional electron system. This phenomenon, which is akin to Bloch spin ferromagnetism, arises fundamentally as a result of electron-electron interaction in an itinerant, dilute electron system. Essentially, the kinetic energy favors an equal distribution of electrons over the available valleys, whereas the interaction between electrons prefers single-valley occupancy below a critical density. The gate-bias-tuned transition we observe is accompanied by a sudden, twofold change in sample resistance, making the phenomenon of interest for potential valleytronic transistor device applications. Finally, our observation constitutes a quintessential demonstration of valleytronics in a very simple experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Converting three-space matrices to equivalent six-space matrices for Delone scalars in S 6

The transformations from the primitive cells of the centered Bravais lattices to the corresponding centered cells have conventionally been listed as three-by-three matrices that transform three-space lattice vectors. Using those three-by-three matrices when working in the six-dimensional space of lattices represented as Selling scalars as used in Delone (Delaunay) reduction, one could transform to the three-space representation, apply the three-by-three matrices and then back-transform to the six-space representation, but it is much simpler to have the equivalent six-by-six matrices and apply them directly. The general form of the transformation from the three-space matrix to the corresponding matrix operating on Selling scalars (expressed in space S 6 ) is derived, and the particular S 6 matrices for the centered Delone types are listed. (Note: in his later publications, Boris Delaunay used the Russian version of his surname, Delone.)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Crystal Growth and Structural Characterization of a Thiocyanato-Bridged Copper(I/II) Mixed-Valence Coordination Polymer

A new mixed-valence coordination polymer [Cu{sub 3}(SCN){sub 4}(DMSO){sub 2}]{sub n} (SCN{sup –} = thiocyanato and DMSO = dimethyl sulfoxide) was prepared and characterized by single crystal X-ray diffraction method. The in situ formation of thiocyanate during the synthesis induces reduction of a part of Cu(II) to Cu(I). The three-dimensional structure of the binuclear thiocyanato bridged compound provided an example of pseudohalide materials containing two different environments for both copper centers.

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

Cylindrical Damped Solitary Propagation in Superthermal Plasmas

Wave properties of damped solitons in a collisional unmagnetized four-components dusty fluid plasma system contains superthermal distributed electrons, mobile ions, and negative-positive dusty grains have been examined. To study dissipative DIA mode properties, a reductive perturbation (RP) analysis is used under convenient geometrical coordinate transformation, three-dimensional damped Kadomtsev–Petviashvili (3D-CDKP) equation in cylindrical coordinates is obtained. Effects of collisional parameters on damped soliton pulse structures are studied. More specifically, the impact of axial, radial, and polar coordinates with the time on solitary propagation are examined. This investigation may be viable in plasma of the Earth’s mesosphere.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Leveraging Intrinsic Principal Directions for Multifidelity Uncertainty Quantification

In this work we propose an approach for accelerating Uncertainty Quantification (UQ) analysis in the context of Multifidelity applications. In the presence of complex multiphysics applications, which often require a prohibitive computational cost for each evaluation, multifidelity UQ techniques try to accelerate the convergence of statistics by leveraging the in- formation collected from a larger number of a lower fidelity model realizations. However, at the-state-of-the-art, the performance of virtually all the multifidelity UQ techniques is related to the correlation between the high and low-fidelity models. In this work we proposed to design a multifidelity UQ framework based on the identification of independent important directions for each model. The main idea is that if the responses of each model can be represented in a common space, this latter can be shared to enhance the correlation when the samples are drawn with respect to it instead of the original variables. There are also two main additional advantages that follow from this approach. First, the models might be correlated even if their original parametrizations are chosen independently. Second, if the shared space between models has a lower dimensionality than the original spaces, the UQ analysis might benefit from a dimension reduction standpoint. In this work we designed this general framework and we also tested it on several test problems ranging from analytical functions for verification purpose, up to more challenging application problems as an aero-thermo-structural analysis and a scramjet flow analysis.

42 ENGINEERING↗