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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Examining normal modes as fundamental heat carriers in amorphous solids: The case of amorphous silicon

Normal mode decomposition of atomic vibrations has been used to provide microscopic understanding of thermal transport in amorphous solids for decades. In normal mode methods, it is naturally assumed that atoms vibrate around their equilibrium positions, and that individual normal modes are the fundamental vibrational excitations transporting heat. With the abundance of predictions from normal mode methods and experimental measurements now available, we carefully analyze these calculations in amorphous silicon, a model amorphous solid. We find a number of discrepancies, suggesting that treating individual normal modes as fundamental heat carriers may not be accurate in amorphous solids. Furthermore, our classical and ab initio molecular dynamics simulations of amorphous silicon demonstrate a large degree of atomic diffusion, especially at high temperatures, leading to the conclusion that thermal transport in amorphous solids could be better described starting from the perspectives of liquid physics rather than from crystalline solids.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Progress in Normalizing Flows for 4d Gauge Theories

Normalizing flows have arisen as a tool to accelerate Monte Carlo sampling for lattice field theories. This work reviews recent progress in applying normalizing flows to 4-dimensional nonabelian gauge theories, focusing on two advancements: an architectural improvement referred to as learned active loops, and the application of correlated ensemble methods to QCD with N f = 2 dynamical fermions.

Abbott, Ryan [Massachusetts Institute of Technolog↗
DOE OSTI2021

Normal and anomalous self-healing mechanism of crystalline calcium silicate hydrates

The origin of different stability of crystalline calcium silicate hydrates was investigated. The tobermorite crystal has been used as an analog of cement hydrate that is being mostly manufactured material on earth. Normal tobermorite is thermally unstable and transforms to amorphous at low pressure. Meanwhile, anomalous tobermorite with high Al content does not significantly transform under high pressure or high temperature. Conducted X-ray absorption spectroscopy explains the weak stability of normal tobermorite which was originally hypothesized by the role of zeolitic Ca ions in the cavities of silicate chains. Atomic simulations reproduced the experimentally observed trend of pressure behavior once the ideal structures were modified to account for the Al content as well as the chain defects. The simulations also suggested that the stability of tobermorite under stress could be rationalized as a self-healing mechanism in which the structural instabilities were accommodated by a global sliding of the CaO layer.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quota management in dCache or making a perfectly normal file system normal

dCache (https://dcache.org) is a highly scalable storage system providing location-independent access to data. The data are stored across multiple data servers as complete files presented to the end-user via a single-rooted namespace. From its inception, dCache has been designed as a caching disk buffer to a tertiary tape storage system with the assumption that the latter has virtually unlimited capacity. dCache can also be configured as a disk-only storage system with no tape backend. Owing to the idea that a tape resource is infinite, or purely physically limited by budget considerations, the system has never provided for any restrictions on how much data can be stored on tape. Likewise, in the disk-only configuration, the capacity of the system is only limited by the aggregate disk capacity of the data servers. In a multi-user environment, however, this has become problematic. This presentation will describe the design and implementation of a user- and group-based quota system, that allows to manage tape and disk space allocations, as part of dCache namespace.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) peak intensity normalization for complex mixture analyses

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a preferred technique for analyzing complex organic mixtures. Currently, there is no consensus normalization approach, nor an objective method for selecting one, for quantitative analyses of FT-ICR-MS data. We investigate a method to evaluate and score the amount of bias various normalization approaches introduce into the data. We evaluate the ability of the Statistical Procedure for the Analysis of Normalization Strategies (SPANS) to guide selection of appropriate normalization approaches for two different FT-ICR-MS datasets. Further, we test the robustness of SPANS results to changes in SPANS parameter values and assess the impact of using various normalization approaches on downstream statistical analyses. The normalization approach identified by SPANS differed for the two datasets. Normalization methods impacted the statistical significance of peaks differently, underscoring the importance of carefully evaluating potential methods. More consistent SPANS scores resulted when at least 120 significant peaks are used, where larger sets of peaks were obtained by increasing the p-value threshold. Interestingly, we show that Total Sum Scaling and highest peak normalization, used in previous studies, underperformed relative to SPANS-recommended normalization approaches. While there is no single, best normalization method for all datasets, SPANS provides a mechanism to identify an appropriate normalization method for analyzing FT-ICR-MS data quantitatively. As a result, the number of peaks used in the background distributions of SPANS contributes more significantly to the reproducibility of results than the p-value thresholds used to obtain those peaks.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Evaluation of normalization strategies for mass spectrometry-based multi-omics datasets

Introduction Data normalization is crucial for multi-omics integration, reducing systematic errors and maximizing the likelihood of discovering true biological variation. Most studies assess normalization for a single omics type or use datasets from separate experiments. Few address time-course data, where normalization might bias temporal differentiation. In this study, we compared common normalization methods and a machine learning approach, Systematical Error Removal using Random Forest (SERRF), using multi-omics datasets generated from the same experiment—even from the same cell lysate. Objectives To develop a straightforward process to assess normalization effects and identify the most robust methods across multi-omics datasets. Methods We analyzed metabolomics, lipidomics, and proteomics datasets from primary human cardiomyocytes and motor neurons exposed to acetylcholine-active compounds over time. Normalization effectiveness was evaluated based on improvement in QC features consistency and observing the change in treatment and time-related variance. Results Probabilistic Quotient Normalization (PQN) and Locally Estimated Scatterplot Smoothing (LOESS) QC were identified as optimal for metabolomics and lipidomics, while PQN, Median, and LOESS normalization excelled for proteomics. These methods consistently enhanced QC feature consistency in metabolomics and lipidomics, and preserved time-related variance or treatment-related variance in proteomics, demonstrating their effectiveness and robustness. SERRF normalization, applied only to metabolomics in this study, outperformed other methods in some datasets but inadvertently masked treatment-related variance in others. Conclusion Our evaluation identified PQN and LoessQC as the top methods for metabolomics and lipidomics, and PQN, Median, and Loess normalization for proteomics, in multi-omics integration in a temporal study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

A Pseudoreversible Normalizing Flow for Stochastic Dynamical Systems with Various Initial Distributions

Here, we present a pseudoreversible normalizing flow method for efficiently generating samples of the state of a stochastic differential equation (SDE) with various initial distributions. The primary objective is to construct an accurate and efficient sampler that can be used as a surrogate model for computationally expensive numerical integration of SDEs, such as those employed in particle simulation. After training, the normalizing flow model can directly generate samples of the SDE’s final state without simulating trajectories. The existing normalizing flow model for SDEs depends on the initial distribution, meaning the model needs to be retrained when the initial distribution changes. The main novelty of our normalizing flow model is that it can learn the conditional distribution of the state, i.e., the distribution of the final state conditional on any initial state, such that the model only needs to be trained once and the trained model can be used to handle various initial distributions. This feature can provide a significant computational saving in studies of how the final state varies with the initial distribution. Additionally, we propose to use a pseudoreversible network architecture to define the normalizing flow model, which has sufficient expressive power and training efficiency for a variety of SDEs in science and engineering, e.g., in particle physics. We provide a rigorous convergence analysis of the pseudoreversible normalizing flow model to the target probability density function in the Kullback–Leibler divergence metric. Numerical experiments are provided to demonstrate the effectiveness of the proposed normalizing flow model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Anomalous normal fluid response in a chiral superconductor UTe2

Abstract Chiral superconductors have been proposed as one pathway to realize Majorana normal fluid at its boundary. However, the long-sought 2D and 3D chiral superconductors with edge and surface Majorana normal fluid are yet to be conclusively found. Here, we report evidence for a chiral spin-triplet pairing state of UTe 2 with surface normal fluid response. The microwave surface impedance of the UTe 2 crystal was measured and converted to complex conductivity, which is sensitive to both normal and superfluid responses. The anomalous residual normal fluid conductivity supports the presence of a significant normal fluid response. The superfluid conductivity follows the temperature behavior predicted for an axial spin-triplet state, which is further narrowed down to a chiral spin-triplet state with evidence of broken time-reversal symmetry. Further analysis excludes trivial origins for the observed normal fluid response. Our findings suggest that UTe 2 can be a new platform to study exotic topological excitations in higher dimension.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

A reduced-order model for nonlinear radiative transfer problems based on moment equations and POD-Petrov-Galerkin projection of the normalized Boltzmann transport equation

A data-driven projection-based reduced-order model (ROM) for nonlinear thermal radiative transfer (TRT) problems is presented. The TRT ROM is formulated by (i) a hierarchy of low-order quasidiffusion (aka variable Eddington factor) equations for moments of the radiation intensity and (ii) the normalized Boltzmann transport equation (BTE). The multilevel system of moment equations is derived by projection of the BTE onto a sequence of subspaces which represent elements of the phase space of the problem. Exact closure for the moment equations is provided by the Eddington tensor. A Petrov-Galerkin (PG) projection of the normalized BTE is formulated using a proper orthogonal decomposition (POD) basis representing the normalized radiation intensity over the whole phase space and time. The Eddington tensor linearly depends on the solution of the normalized BTE. By linear superposition of the POD basis functions, a low-rank expansion of the Eddington tensor is constructed with coefficients defined by the PG projected normalized BTE. The material energy balance (MEB) equation is coupled with the effective gray low-order equations which exist on the same dimensional scale as the MEB equation. The resulting TRT ROM is structure and asymptotic preserving. A detailed analysis of the ROM is performed on the classical Fleck-Cummings (F-C) TRT multigroup test problem in 2D geometry. Numerical results are presented to demonstrate the ROM's effectiveness in the simulation of radiation wave phenomena. Importantly, the ROM is shown to produce solutions with sufficiently high accuracy while using low-rank approximation of the normalized BTE solution. Essential physical characteristics of supersonic radiation wave are preserved in the ROM solutions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Frictional properties of Opalinus Clay: influence of humidity, normal stress and grain size on frictional stability

SUMMARY The Opalinus Clay (OPA) is a clay-rich formation considered as a potential host rock for radioactive waste repositories and as a caprock for carbon storage in Switzerland. Its very low permeability (10−19 to 10−21 m2) makes it a potential sealing horizon, however the presence of faults that may be activated during the lifetime of a repository project can compromise the long-term hydrological confinement, and lead to mechanical instability. Here, we have performed laboratory experiments to test the effect of relative humidity (RH), grain size (g.s.) and normal stress on rate-and-state frictional properties and stability of fault laboratory analogues corresponding to powders of OPA shaly facies. The sifted host rock powders at different grain size fractions (<63 μm and 63 < g.s. < 125 μm), at room (∼25 per cent) and 100 per cent humidity, were slid in double-direct shear configuration, under different normal stresses (5–70 MPa). We observe that peak friction, μpeak and steady-state friction, μss, depend on water vapour content and applied normal stress. Increasing relative humidity from ∼25 per cent RH (room humidity) to 100 per cent RH causes a decrease of frictional coefficient from 0.41 to 0.35. The analysis of velocity-steps in the light of rate-and-state friction framework shows that the stability parameter (a–b) is always positive (velocity-strengthening), and it increases with increasing sliding velocity and humidity. The dependence of (a–b) on slip rate is lost as normal stress increases, for each humidity condition. By monitoring the variations of the layer thickness during the velocity steps, we observe that dilation (Δh) is directly proportional to the sliding velocity, decreases with normal stress and is unaffected by humidity. Microstructural analysis shows that most of the deformation is accommodated within B-shear zones, and the increase of normal stress (σn) promotes the transition from strain localization and grain size reduction to distributed deformation on a well-developed phyllosilicate network. These results suggest that: (1) the progressive loss of velocity dependence of frictional stability parameter (a–b) at σn > 35 MPa is dictated by a transition from localized to distributed deformation and (2) water vapour content does not affect the deformation mechanisms and dilation, whereas it decreases steady-state friction (μss), and enhances fault stability.

58 GEOSCIENCES↗
DOE OSTI2022

Neutrino mass and mass ordering: no conclusive evidence for normal ordering

The extraction of the neutrino mass ordering is one of the major challenges in particle physics and cosmology, not only for its implications for a fundamental theory of mass generation in nature, but also for its decisive role in the scale of future neutrinoless double beta decay experimental searches. It has been recently claimed that current oscillation, beta decay and cosmological limits on the different observables describing the neutrino mass parameter space provide robust decisive Bayesian evidence in favor of the normal ordering of the neutrino mass spectrum. We further investigate these strong claims using a rich and wide phenomenology, with different sampling techniques of the neutrino parameter space. Contrary to the findings of Jimenez et al., no decisive evidence for the normal mass ordering is found. Neutrino mass ordering analyses must rely on priors and parameterizations that are ordering-agnostic: robust results should be regarded as those in which the preference for the normal neutrino mass ordering is driven exclusively by the data, while we find a difference of up to a factor of 33 in the Bayes factors among the different priors and parameterizations exploited here. An ordering-agnostic prior would be represented by the case of parameterizations sampling over the two mass splittings and a mass scale, or those sampling over the individual neutrino masses via normal prior distributions only. In this regard, we show that the current significance in favor of the normal mass ordering should be taken as 2.7σ (i.e. moderate evidence), mostly driven by neutrino oscillation data. Let us stress that, while current data favor NO only mildly, we do not exclude the possibility that this may change in the future. Eventually, upcoming oscillation and cosmological data may (or may not) lead to a more significant exclusion of IO.

79 ASTRONOMY AND ASTROPHYSICS↗