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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Perturbative unorientable JT gravity and matrix models

We consider an orthogonal polynomial formulation of the double scaling limit of multicritical matrix models in the β = 1 Dyson-Wigner class. They capture the physics of 2D quantum gravity coupled to minimal matter on unorientable surfaces, otherwise called unoriented minimal strings. We derive a formula for the density of states valid to all orders in perturbation theory. We show how to define an interpolation between the multicritical models and that a certain interpolation among an infinite number of them provides an alternative definition of unoriented JT gravity. We discuss the strengths and weaknesses of our formulation.

1/N Expansion↗
DOE OSTI2020

Phase identification using co‐association matrix ensemble clustering

Calibrating distribution system models to aid in the accuracy of simulations such as hosting capacity analysis is increasingly important in the pursuit of the goal of integrating more distributed energy resources. The recent availability of smart meter data is enabling the use of machine learning tools to automatically achieve model calibration tasks. This research focuses on applying machine learning to the phase identification task, using a co‐association matrix‐based, ensemble spectral clustering approach. The proposed method leverages voltage time series from smart meters and does not require existing or accurate phase labels. This work demonstrates the success of the proposed method on both synthetic and real data, surpassing the accuracy of other phase identification research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Neutral excitations of quantum Hall states: A density matrix renormalization group study

We use the dynamical structure factors of the quantum Hall states at ν = 1 / 3 and 1 / 2 in the lowest Landau level to study their excitation spectrum. Using the density matrix renormalization group in combination with the time-dependent variational principle on an infinite cylinder geometry, we extract the low-energy properties. At ν = 1 / 3 , a sharp magnetoroton mode and the two-roton continuum are present and the finite-size effects can be understood using the fractional charge of the quasiparticle. At ν = 1 / 2 , we find low-energy modes with linear dispersion and the static structure factor s ¯ ( q ) ~ ( q ℓ ) 3 in the limit q ℓ → 0 . The properties of these modes agree quantitatively with the predictions of the composite-fermion theory placed on the infinite cylinder.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Unveiling the Morphological and Physical Mechanism of Burn–in Loss Alleviation by Ternary Matrix Toward Stable and Efficient All–Polymer Solar Cells

All–polymer solar cells (All–PSCs) are considered the most promising candidate in achieving both efficient and stable organic photovoltaic devices, yet the field has rarely presented an in–depth understanding of corresponding device stability while efficiency is continuously boosted via the innovation of polymer acceptors. Herein, a ternary matrix is built for all–PSCs with optimized morphology, improved film ductility and importantly, boosted efficiency and better operational stability than its parental binary counterparts, as a platform to study the underlying mechanism. The target system PQM–Cl:PTQ10:PY–IT (0.8:0.2:1.2) exhibits an alleviated burn–in loss of morphology and efficiency under light soaking, which supports its promoted device lifetime. The comprehensive characterizations of fresh and light–soaked active layers lead to a clear illustration of opposite morphological and physical degradation direction of PQM–Cl and PTQ10, thus resulting in a delicate balance at the optimal ternary system. Specifically, the enlarging tendency of PQM–Cl and shrinking preference of PTQ10 in terms of phase separation leads to a stable morphology in their mixing phase; the hole transfer kinetics of PQM–Cl:PY–IT host is stabilized by incorporating PTQ10. Finally, this work succeeds in reaching a deep insight into all–PSC's stability promotion by a rational ternary design, which booms the prospect of gaining high–performance all–PSCs.

14 SOLAR ENERGY↗
DOE OSTI2023

The S-matrix of 2D type 0B string theory. Part II. D-instanton effects

We study the effect of D-instantons on closed string scattering amplitudes in the two-dimensional type 0B string theory from the worldsheet perspective. We find that the contribution from a pair of D-instanton and anti-D-instanton to the closed string reflection amplitude, with a suitable contour prescription for the integration over the D-instanton moduli space, agrees with the corresponding leading non-perturbative corrections in the proposed dual matrix quantum mechanics. This analysis is further extended to thermal observables defined at finite temperature. The infrared divergence in charged processes is understood through the measure factor for charged D-instantons, and can be treated with spacetime dimensional regularization.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Direct interpolative construction of the discrete Fourier transform as a matrix product operator

The quantum Fourier transform (QFT), which can be viewed as a reindexing of the discrete Fourier transform (DFT), has been shown to be compressible as a low-rank matrix product operator (MPO) or quantized tensor train (QTT) operator. However, the original proof of this fact does not furnish a construction of the MPO with a guaranteed error bound. Meanwhile, the existing practical construction of this MPO, based on the compression of a quantum circuit, is not as efficient as possible. We present a simple closed-form construction of the QFT MPO using the interpolative decomposition, with guaranteed near-optimal compression error for a given rank. This construction can speed up the application of the QFT and the DFT, respectively, in quantum circuit simulations and QTT applications. We also connect our interpolative construction to the approximate quantum Fourier transform (AQFT) by demonstrating that the AQFT can be viewed as an MPO constructed using a different interpolation scheme.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Melting and solidification dynamics during laser melting of reaction-based metal matrix composites uncovered by in-situ synchrotron X-ray diffraction

Laser additive manufacturing (AM) of reaction-based metal matrix composites (MMCs) involves highly complex and non-equilibrium material transformation behavior, including melting, dissolution, precipitation, and solidification. Yet, the dynamics and interplay of these phase transformation processes remain poorly understood, posing substantial challenges in identifying the microstructure formation mechanism, and predicting and controlling the microstructure in the printed parts. Here, in this study, we performed the in-situ X-ray diffraction experiment to characterize the phase evolution dynamics of the 316L + 10 vol.%TiC system during laser melting, which provides direct and quantitative insights of the complex phase reaction and evolution dynamics under rapid heating and cooling conditions relevant to additive manufacturing of reaction-based MMCs. Further in-depth thermodynamic and kinetic calculations revealed that most of the phase evolution behavior observed in the in-situ X-ray diffraction experiment cannot be solely explained by widely used equilibrium thermodynamic models, and diffusion-controlled nonequilibrium dissolution and precipitation kinetics must be considered to elucidate the complex phase evolution behavior, including incomplete TiC dissolution, and three-step TiC precipitation. The three distinct types of precipitates generate unique hierarchical TiC micro- and nanostructures, which enhances the yield strength from 513 MPa to 877 MPa by 71 %, tensile strength from 628 MPa to 1054 MPa by 68 %, and Young's modulus from 193 GPa to 221 GPa by 14 %. The findings of our research provide the knowledge foundation for the design of unique microstructures and advanced MMC materials through laser AM.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Hydrogen uptake in graphite matrix at high temperature

Tritium management is a critical challenge for the next generation of nuclear reactors, such as Fluoride Salt Cooled High Temperature Reactors (FHRs) and High Temperature Gas-cooled Reactors (HTGRs), due to the higher production rate (up to 10,000 times) than conventional Light Water Reactors (LWRs). Graphitic materials employed as moderator, reflector, and fuel pebbles offer a potential pathway for tritium recovery by serving as a sink for tritium. Prediction of uptake capacity under reactor relevant conditions remains a challenge due to a lack of low partial pressure data and significant inter-grade variability of graphite. This study addresses these gaps by providing a comprehensive characterization of hydrogen (as a tritium surrogate) uptake and release behavior in the A3-3 graphite matrix (GM) used in fuel pebbles. Uptake measurements are performed at reactor relevant temperatures of 600- 800 °C, 1-200 Torr hydrogen pressure, and 15-120 min equilibration time, followed by thermal desorption spectroscopy up to 1100 °C. Uptake experiments at different equilibration times demonstrate the role of kinetics in hydrogen uptake, which can be modeled as a diffusion-with-trapping process. In the thermodynamics limit, the Sips adsorption model is shown to capture the uptake in A3-3 GM well. Our campaign provides a set of new results for hydrogen uptake in A3-3, including limiting uptake capacity at 600 °C, apparent diffusion coefficient at 600 °C, and the first estimates of the FHR/HTGR relevant (600 °C, 20 Pa partial pressure) equilibrium uptake capacity and time to saturation. Desorption data highlights a new site for hydrogen uptake, not observed in nuclear graphite, which we attribute to the non-graphitized binder. Using the Kissinger method, we estimate activation energy for release from the desorption peaks, confirming the activation energy for release from the basal planes and providing the first estimate for the activation energy of release from the binder.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Cellular mRNA triggers structural transformation of Ebola virus matrix protein VP40 to its essential regulatory form

The Ebola virus matrix protein VP40 forms distinct structures linked to distinct functions in the virus life cycle. Dimeric VP40 is a structural protein associated with virus assembly, while octameric, ring-shaped VP40 is associated with transcriptional control. In this study, we show that suitable nucleic acid is sufficient to trigger a dynamic transformation of VP40 dimer into the octameric ring. Deep sequencing reveals a binding preference of the VP40 ring for the 3' untranslated region of cellular mRNA and a guanine- and adenine-rich binding motif. Complementary analyses of the nucleic-acid-induced VP40 ring by native mass spectrometry, electron microscopy, and X-ray crystal structures at 1.8 and 1.4 Å resolution reveal the stoichiometry of RNA binding, as well as an interface involving a key guanine nucleotide. The host factor-induced structural transformation of protein structure in response to specific RNA triggers in the Ebola virus life cycle presents unique opportunities for therapeutic inhibition.

3′ UTR↗
DOE OSTI2023

Experimental and numerical investigation of flame stabilization and pollutant formation in matrix stabilized ammonia-hydrogen combustion

Ammonia (NH 3 ) is a carbon-free fuel that offers an attractive alternative for reducing greenhouse gas emissions. However, the slow flame speed, low heating value, and emissions of nitrogen-containing pollutants present significant issues for practical combustion applications. To address these issues, we investigate the use of matrix stabilized combustion. In this type of burner, combustion is performed within an inert porous ceramic foam, heat is recirculated by solid conduction and radiation, which enhances flame speed and combustion stabilization, thereby permitting combustion over a wide range of equivalence ratio conditions. We present a new porous media burner (PMB) capable of stabilizing NH 3 /air flames at ambient conditions. An extensive experimental characterization of the stability of this burner is conducted with up to 30% by volume of hydrogen (H 2 ) in the fuel stream. A 15:1 turndown ratio is demonstrated, with a high thermal power density of 62 MW m -3 . Concentrations of NO, unburnt NH 3 , and H 2 in the exhaust stream are measured. Two regimes are identified for low NO operation: rich and very lean. For rich conditions, NO emissions decrease with increasing equivalence ratio and decreasing H 2 blending. Unburnt NH 3 emissions follow opposite trends. These measurements are complemented by simulations in which the burner is represented by a coupled solid-gas reactor network. In conclusion, this model captures the burner’s pollutant emissions to good accuracy and is used to analyze the mechanisms of pollutant formation.

42 ENGINEERING↗
DOE OSTI2021

Effect of curvature on extensional stiffness matrix of 2-D braided composite tubes

In the micromechanical analysis of braided composite tubes, the effects of curvature are often ignored. This approach is acceptable for thin-walled tubes with a large radius. However, in case of small diameter thick-walled tubes, such an approach may lead to inaccurate results. Therefore, it is of interest to determine when the curvature effects of tubular geometry become important in micromechanics. In this study, the extensional stiffness matrix of 2-D braided composite tubes was calculated using a curved unit-cell. The periodicity was imposed in circumferential and longitudinal directions of the tube. The extensional stiffness coefficients were calculated by simulating an internal pressure test, uniaxial tensile test, and torsion test. The obtained stiffness coefficients were compared to those obtained using a flat unit-cell. The results of curved unit-cell were different from that of flat unit-cell. The differences in stiffness coefficients, calculated using curved and flat unit cells were as high as 13%.

42 ENGINEERING↗
DOE OSTI2024

Multi deep learning-based stochastic microstructure reconstruction and high-fidelity micromechanics simulation of time-dependent ceramic matrix composite response

A multi deep learning-based framework is developed for efficient, automated microstructure reconstruction and generation of stochastic representative volume elements (SRVEs) with periodic boundary conditions (PBCs) for accurate modeling of ceramic matrix composite (CMC) response. The methodology comprises a convolutional neural network coupled with regression layers to act as a vanilla regression network for semantic segmentation of the microstructure, allowing accurate characterization of the phases and their distributions at the microscale. Scanning electron microscope and confocal microscope are used to obtain C/SiNC and SiC/SiNC CMCs micrographs for vanilla regression testing. Microstructure variability in terms of fiber volume fraction and porosity are quantified through the output regression layer, ensuring accurate representation of material variability in SRVE construction. Generative adversarial network (GAN) and its variants are designed to produce high-fidelity SRVE, spanning CMCs microstructure variability space. A circular padding algorithm is developed to generate SRVEs with PBCs during training of GANs. The accuracy of the generated SRVEs is established through micromechanics simulations, where an efficient formulation of the high-fidelity generalized methods of cells (HFGMC) approach is used to compute the effective mechanical properties. Furthermore, an iterative algorithm is implemented in the HFGMC solver to simulate time-dependent deformation of SiC/SiNC subjected to creep loading conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Advanced measurement techniques in quantum Monte Carlo: The permutation matrix representation approach

In a typical finite temperature quantum Monte Carlo (QMC) simulation, estimators for simple static observables such as specific heat and magnetization are known. With a great deal of system-specific manual labor, one can sometimes also derive more complicated non-local or even dynamic observable estimators. In contrast, we show that arbitrary static observables can be estimated within the permutation matrix representation (PMR) flavor for any Hamiltonian. We then generalize these results to general imaginary-time correlation functions and non-trivial integrated susceptibilities thereof. Finally, we demonstrate the practical versatility of our method by estimating various non-local, random observables for the transverse-field Ising model on a square lattice and a toy random model.

Permutation matrix representation↗
DOE OSTI2022

Discovering hidden geothermal signatures using non-negative matrix factorization with customized k-means clustering

Discovery of hidden geothermal resources is challenging. It requires the mining of large datasets with diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used play fairway analysis approach typically incorporates subject-matter expertise to analyze regional data to estimate geothermal characteristics and favorability. We demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset from southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. Several of these systems are not well characterized because of insufficient existing data and limited past explorative work. This study discovers hidden patterns and relations in the SWNM geothermal dataset to improve our understanding of the regional hydrothermal conditions and energy-production favorability. This understanding is obtained by applying an unsupervised ML algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden signatures characterizing analyzed datasets, (2) the optimal number of these signatures, (3) the dominant data attributes associated with each signature, and (4) the spatial distribution of the extracted signatures. Here, in this study, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, and geothermal attributes at 44 locations in SWNM. Using NMFk, we find data patterns and identify the spatial associations of hydrothermal signatures within two physiographic provinces (Colorado Plateau and Basin and Range) and two sub-regions of these provinces (the Mogollon-Datil volcanic field and the Rio Grande rift) in SWNM. The ML algorithm extracted five hydrothermal signatures in the SWNM datasets that differentiate between low (<90°C) and medium (90-150°C)-temperature hydrothermal systems. The algorithm also suggests that the Rio Grande rift and northern Mogollon-Datil volcanic field are the most favorable regions for future geothermal resource discovery. NMFk also identified critical attributes to identify medium-temperature hydrothermal systems in the study area. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored regions. The code to execute the performed analyses as well as the corresponding data can be found at https://github.com/SmartTensors/GeoThermalCloud.jl.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Structural characterization of HIV-1 matrix mutants implicated in envelope incorporation

During the late phase of HIV-1 infection, viral Gag polyproteins are targeted to the plasma membrane (PM) for assembly. Gag localization at the PM is a prerequisite for the incorporation of the envelope protein (Env) into budding particles. Gag assembly and Env incorporation are mediated by the N-terminal myristoylated matrix (MA) domain of Gag. Nonconservative mutations in the trimer interface of MA (A45E, T70R, and L75G) were found to impair Env incorporation and infectivity, leading to the hypothesis that MA trimerization is an obligatory step for Env incorporation. Conversely, Env incorporation can be rescued by a compensatory mutation in the MA trimer interface (Q63R). The impact of these MA mutations on the structure and trimerization properties of MA is not known. In this study, we employed NMR spectroscopy, X-ray crystallography, and sedimentation techniques to characterize the structure and trimerization properties of HIV-1 MA A45E, Q63R, T70R, and L75G mutant proteins. NMR data revealed that these point mutations did not alter the overall structure and folding of MA but caused minor structural perturbations in the trimer interface. Analytical ultracentrifugation data indicated that mutations had a minimal effect on the MA monomer–trimer equilibrium. The high-resolution X-ray structure of the unmyristoylated MA Q63R protein revealed hydrogen bonding between the side chains of adjacent Arg-63 and Ser-67 on neighboring MA molecules, providing the first structural evidence for an additional intermolecular interaction in the trimer interface. These findings advance our knowledge of the interplay of MA trimerization and Env incorporation into HIV-1 particles.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Siloxane-modified polycarbosilane flexible Prepregs for fabrication of ceramic matrix composites via compression molding and PIP densification

For this work, the development of ceramic matrix composites (CMCs) using 5 harness satin carbon fiber fabric impregnated with commercial polycarbosilane precursor plasticized by siloxane copolymer was investigated aiming to improve wetting behavior and shape conformability. The polycarbosilane precursor and polysiloxane plasticizer were mixed at varying weight ratios to obtain flexible preceramic resin prepreg cloths. 13 plies of preceramic polymer prepreg cloths were stacked in 0/90° layup and cured by compression molding, followed by densified via PIP process. The CMCs were densified with eight PIP cycles followed by final crystallization at 1600 °C. The CMCs made with 10 wt% polysiloxane loading showed lower viscosity of the prepreg resin as well as higher strength and displacement to failure compared to those fabricated from unplasticized polycarbosilane prepolymer. In contrast, at higher concentration of plasticizer, viscosity of the prepreg resin increased, and the CMC became more brittle; however, it exhibited considerably higher thermal conductivity.

Carbosilane↗
DOE OSTI2023

Accelerating matrix-centric graph processing on GPUs through bit-level optimizations

Even though it is well known that binary values are common in graph applications (e.g., adjacency matrix), how to leverage the phenomenon for efficiency has not yet been adequately explored. This paper presents a systematic study on how to unlock the potential of the bit-level optimizations of graph computations that involve binary values. It proposes a two-level representation named Bit-Block Compressed Sparse Row (B2SR) and presents a series of optimizations to the graph operations on B2SR by the intrinsics of modern GPUs. It additionally introduces Deep Reinforcement Learning (DRL) as an efficient way to best configure the bit-level optimizations on the fly. Additionally, the DQN-based adaptive tile size selector with dedicated model training can reach 68% prediction accuracy. Evaluations on NVIDIA Pascal and Volta GPUs show that the optimizations bring up to 40× and 6555× for essential GraphBLAS kernels SpMV and SpGEMM, respectively, making GraphBLAS-based BFS accelerate up to 433×, SSSP, PR, and CC up to 35×, and TC up to 52×.

79 ASTRONOMY AND ASTROPHYSICS↗