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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Quantifying Microstructure Variability in Laser Powder Bed Fusion 316 L Stainless Steel Microstructures with Spatial Statistics

Here, we have explored data-driven methods for material microstructure quantification that improve sensitivity to microstructural changes compared to traditional approaches. The methods integrate multiple microstructural properties, including grain morphology, crystallographic orientation, and material phase information. The simpler method employs maps of the Euclidean distance transformation metric to evaluate the morphology of grain boundary networks. The more intensive approach employs generalized spherical harmonic mapping for crystallographic orientations, per-pixel phase information, and a variational auto-encoder for dimensionality reduction and results in a multidimensional clustering of by microstructure similarity. Applied to an experimental dataset of additively manufactured steel, both methods detected slight variations in samples produced under nominally identical processing conditions. Both methods were able to distinguish between samples from multiple (nominally identical) builds, while the generalized spherical harmonics-based method could additionally cluster data samples rotated at two orientations on the build plate. The improved sensitivity of the methods, demonstrated through comparison with traditional microstructure characterization techniques, offers advantages for microstructure quantification and comparisons in advanced manufacturing applications.

SS316L↗
DOE OSTI2018

An approach based on dwindling filter method for positive definite generalized eigenvalue problem

In this paper, we present a new spectral residual method for solving large-scale positive definite generalized eigenvalue problems. The proposed algorithm is equipped with a dwindling multidimensional nonmonotone filter, in which the envelope dwindles as the step length decreases. We have also employed a relaxed nonmonotone line search technique in the structure of the algorithm which allows it to enjoy the nonmonotonicity from scratch. Under some mild and standard assumptions, the global convergence property of the proposed algorithm is established. An implementation of the new algorithm on some test problems shows the efficiency and effectiveness of the proposed algorithm in practice.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Groundwater flow and heat transport for systems undergoing freeze-thaw: Intercomparison of numerical simulators for 2D test cases

In high-elevation, boreal and arctic regions, hydrological processes and associated water bodies can be strongly influenced by the distribution of permafrost. Recent field and modeling studies indicate that a fully-coupled multidimensional thermo-hydraulic approach is required to accurately model the evolution of these permafrost-impacted landscapes and groundwater systems. However, the relatively new and complex numerical codes being developed for coupled non-linear freeze-thaw systems require verification. Here in this paper, this issue is addressed by means of an intercomparison of thirteen numerical codes for two-dimensional test cases with several performance metrics (PMs). These codes comprise a wide range of numerical approaches, spatial and temporal discretization strategies, and computational efficiencies. Results suggest that the codes provide robust results for the test cases considered and that minor discrepancies are explained by computational precision. However, larger discrepancies are observed for some PMs resulting from differences in the governing equations, discretization issues, or in the freezing curve used by some codes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Particle on a torus knot: Constrained dynamics and semi-classical quantization in a magnetic field

Kinematics and dynamics of a particle moving on a torus knot poses an interesting problem as a constrained system. In the first part of the paper we have derived the modified symplectic structure or Dirac brackets of the above model in Dirac’s Hamiltonian framework, both in toroidal and Cartesian coordinate systems. This algebra has been used to study the dynamics, in particular small fluctuations in motion around a specific torus. The spatial symmetries of the system have also been studied. In the second part of the paper we have considered the quantum theory of a charge moving in a torus knot in the presence of a uniform magnetic field along the axis of the torus in a semiclassical quantization framework. We exploit the Einstein–Brillouin–Keller (EBK) scheme of quantization that is appropriate for multidimensional systems. Embedding of the knot on a specific torus is inherently two dimensional that gives rise to two quantization conditions. This shows that although the system, after imposing the knot condition reduces to a one dimensional system, even then it has manifested non-planar features which shows up again in the study of fractional angular momentum. Finally we compare the results obtained from EBK (multi-dimensional) and Bohr–Sommerfeld (single dimensional) schemes. The energy levels and fractional spin depend on the torus knot parameters that specifies its non-planar features. Interestingly, we show that there can be non-planar corrections to the planar anyon-like fractional spin.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Ground-state and stability properties of 288-308 118 Og isotopes based on semi-microscopic calculations

In this study, we present theoretical predictions on the stability properties of the yet unknown {sup 276−293,295−308}{sub 118}Og isotopes using the Skyrme-SLy4 nucleon–nucleon interaction and the deformed Woods–Saxon single-particle potential in a semi-microscopic approach. The ground-state masses, binding energy, deformations and fission barriers are calculated from the total energy surfaces produced in a multidimensional deformation space using the dynamical differential evolution optimization method. Besides, the Q-values of the different decay modes and the nucleon separation energies for each isotope, and its α-decay (T{sub α}) and spontaneous fission half-lives are also calculated. Our study revealed the {sub 290−296}Og elements to be the most bound Oganesson isotopes, among which {sup 302,304,306}Og elements are predicted to be spherical nuclei, and {sup 299,300,301,303,305}Og elements are shown to be almost spherical. The predicted ground-state and decay properties successfully reproduced the available data of the solely known Oganesson isotope {sup 294}Og. In addition to the principle α-decay modes, we studied the rival decay modes that challenge the stability of nuclei in the superheavy regions, namely the electron capture β{sup +} decays and the spontaneous fission. An overall oscillating increasing behavior of T{sub α} with the mass number is obtained, which obviously reverses the hesitating decreasing behavior of Q{sub α} and follows increasing trend of the corresponding change in the neutron-skin thickness after α-decays. The {sub 291,294−296,299−302}Og isotopes are expected to have relatively long half-lives, T{sub α} ≈ 1–45 ms, while {sup 295}Og is found to have the longest half-life between the considered nuclei. The {sub 291−300}Og isotopes exhibited relatively high fission barriers and small branching ratios for their spontaneous fission modes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Three differential expression profiles of miRNAs as potential biomarkers for lung adenocarcinoma

Highlights: • To identify the differential miRNAs expression between lung cancer and normal tissues. • Data analysis was based on a computational approach to detect survival-associated signatures. • Three-miRNA signature could be used as a prognostic marker in LACA. Owing to the poor prognosis, novel biomarkers for lung adenocarcinoma (LACA) are needed nowadays. The aim of the study was to identify the differential miRNAs expression between lung cancer and normal tissues and evaluate the prognostic values of the miRNAs. Multidimensional data of 528 samples were retrieved from The Cancer Genome Atlas archive. Data analysis was based on a computational approach to detect survival-associated molecular signatures. A total of 191 differentially expressed miRNAs were identified between LACA tissues and normal tissues, including 88 up-regulated and 103 down-regulated miRNAs. The Kaplan-Meier survival method revealed the prognostic function of the three miRNAs (miR-1293, miR-873 and miR-1914). Cox regression analysis showed that the three-miRNA signature was an independent prognostic factor in LACA. The functional enrichment analysis suggested that the target genes of three miRNAs may be involved in various pathways related to the cancer. This study demonstrated that the three-miRNA signature (miR-1293, miR-873 and miR-1914) could be used as a prognostic marker in LACA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Editorial overview: Omics

The great complexity of biological systems and their environment poses similarly vast challenges for accurate analytical evaluations of their identity, structure and quantity. Post genomic science, has predicted much regarding the static populations of biological systems, but a further challenge for analysis is to test the accuracy of these predictions, as well as provide a better representation of the transient nature of the molecules of life. Accurate measurements of biological systems have wide applications for biological, forensic, biotechnological and healthcare fields. Therefore, the holy grail is to find a technique which can identify and quantify biological molecules with high throughput, sensitivity and robustness, as well evaluate molecular structure(s) in order to understand how the specific molecules interact and function. While wrapping all of these characteristics into one platform may sound difficult, ion mobility spectrometry (IMS) is addressing all of these challenges. Over the last decade, the number of analytical studies utilizing IMS for the evaluation of complex biological and environmental samples has greatly increased. In most cases IMS is coupled with mass spectrometry (IM-MS), but even alone IMS provides the unique capability of rapidly assessing a molecule’s structure, which can be extremely difficult with other techniques. The robustness of the IMS measurement is bourne out by its widespread use in security, environmental and military applications. The multidimensional IM-MS measurements however have been proven to be ever more powerful, as applied to complex mixtures as they enable the evaluation of both the structure and mass of every molecular component in a sample during a single measurement, without the need for continual reference calibration.

Barran, Perdita↗
DOE OSTI2021

Empirical estimation of densities in NaCl-KCl-UCl 3 and NaCl-KCl-YCl 3 molten salts using Redlich-Kister expansion

Densities of molten KCl-NaCl-UCl 3 and KCl-NaCl-YCl 3 ternary systems have been estimated using a multidimensional Redlich-Kister model. Temperature and composition dependent Redlich-Kister functions have been used to generate binary interaction parameters in the outlined ternary salt systems. These binary interactions have been used in the extrapolation to ternary system densities. The results of the density extrapolations by Muggianu interpolation scheme provide agreement within 2–3% for the NaCl-KCl-YCl 3 liquids and 11% in NaCl-KCl-UCl 3 liquids compared to the available experimental data. Modeling NaCl-KCl-UCl 3 molten phase density with a ternary interaction parameter improved the agreement within 4%. Thermophysical modeling used in this study has shown promising results for use in other material properties, such as viscosity, thermal conductivity, and heat capacity of the molten salts. Lastly, the outlined modeling method applied in these specific molten salt ternaries can be used for quaternary or higher multicomponent molten salt systems.

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

Multimodal hyperspectral optical microscopy

We describe a unique and convenient approach to multimodal hyperspectral optical microscopy, herein achieved by coupling a portable and transferable hyperspectral imager to various optical microscopes. The experimental and data analysis schemes involved in recording spectrally and spatially resolved fluorescence, dark field, and optical absorption micrographs are illustrated through prototypical measurements targeting selected model systems. Namely, hyperspectral fluorescence micrographs of isolated fluorescent beads are employed to ensure spectral calibration of our detector and to gauge the attainable spatial resolution of our measurements; the recorded images are diffraction-limited. Moreover, spatially over-sampled absorption spectroscopy of a single lipid (18:1 Liss Rhod PE) layer reveals that optical densities on the order of 10-3 may be resolved by spatially averaging the recorded optical signatures. We also briefly illustrate two applications of our setup in the general areas of plasmonics and cell biology. Most notably, we deploy hyperspectral optical absorption microscopy to identify and image algal pigments within a single live Tisochrysis lutea cell. Overall, this work paves the way for multimodal multidimensional spectral imaging measurements spanning the realms of several scientific disciples.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

An antibody-free platform for multiplexed, sensitive quantification of protein biomarkers in complex biomatrices

Sensitive, multiplexed protein quantification remains challenging despite recent advancements in LC-MS assays for targeted protein biomarker quantification. High-sensitivity protein biomarker measurements usually require immuno-affinity enrichment of target protein; a process which is highly dependent on capture reagent and limited in capability to measure multiple analytes. Herein, we report a novel antibody-free platform, which measures multiple biomarkers from complex matrices employing a strategically optimized solid-phase extraction cleanup and orthogonal multidimensional LC-MS. Eight human protein biomarkers with different specifications were spiked into canine plasma as a model investigation system. The developed strategy achieved the desired sensitivity, robustness, and throughput via the following steps: (1) post digestion mixed-mode cation exchange-reverse phase SPE enrichment cleaned up the sample initially; (2) rapid, high-pH peptide fractionation further eliminated background components efficiently while selectively enriched signature peptides (SP) to provide sufficient sensitivity for multiple targets; and (3) trapping-micro-LC-MS analysis delivered high sensitivity comparable to a nano-LC-MS method but with much better robustness and throughput for the final analysis. Compared with a conventional LC-MS assay with direct protein digestion and limited clean-up, analysis with this antibody-free platform improved the LLOQ by 1–2 orders of magnitude for the eight protein biomarkers, reaching as low as 5 ng/mL in plasma, with feasible robustness and throughput. In conclusion, this platform was applied for the quantification of biomarkers of respiratory conditions in patients with various lung diseases, demonstrating real-world applicability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Hydrogen shift isomerizations in the kinetics of the second oxidation mechanism of alkane combustion. Reactions of the hydroperoxypentylperoxy OOQOOH radical

Hydroperoxyalkylperoxy species are important intermediates that are generated during the autoignition of transport fuels. In combustion, the fate of hydroperoxyalkylperoxy is important for the performance of advanced combustion engines, especially for autoignition. A key fate of the hydroperoxyalkylperoxy is a 1,5 H-shift, for which kinetics data are experimentally unavailable. In the present work, we study 1-hydroperoxypentan-3-yl)dioxidanyl (CH 3 CH 2 CH(OO)CH 2 CH 2 OOH) as a model compound to clarify the kinetics of 1,5 H-shift of hydroperoxyalkylperoxy species, in particular α-H isomerization and alternative competitive pathways. With a combination of electronic structure calculations, we determine previously missing thermochemical data, and with multipath variational transition state theory (MP-VTST), a multidimensional tunneling (MT) approximation, multiple-structure anharmonicity, and torsional potential anharmonicity, we obtained much more accurate rate constants than the ones that can computed by conventional single-structure harmonic transition state theory (TST) and than the empirically estimated rate constants that are currently used in combustion modeling. The roles of various factors in determining the rates are elucidated. The pressure-dependent rate constants for these competitive reactions are computed using system-specific quantum RRK theory. The calculated temperature range is 298–1500 K, and the pressure range is 0.01–100 atm. The accurate thermodynamic and kinetics data determined in this work are indispensable in the detailed understanding and prediction of ignition properties of hydrocarbons and alternative fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

VTAnDeM: A python toolkit for simultaneously visualizing phase stability, defect energetics, and carrier concentrations of materials

Phase stability, defect formation energies, and carrier concentrations are closely interrelated features of semiconductors. Due to their joint dependence on the multidimensional chemical potential space, it is challenging to quantitatively establish patterns between these quantities in a given semiconductor, especially when the semiconductor is comprised of multiple elements. To enable synchronous visualization and analysis of these complementary material properties and their interdependence, we developed the Visualization Toolkit for Analyzing Defects in Materials (VTAnDeM). This python-based toolkit allows users to interactively explore how defect formation energies and carrier concentrations vary across the composition and chemical potential spaces of multicomponent semiconductors. Here, we illustrate the computational workflow that employs VTAnDeM as a post-processing tool for first-principles calculations and describe the data organization and theory underlying the visualization scheme. Furthermore, we believe that this software will serve as a useful tool for simultaneously visualizing the often complex and non-intuitive chemical potential – defect – carrier concentration phase space of semiconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A parallel and performance portable implementation of a full-field crystal plasticity model

We have developed a parallel implementation of an Elasto-Viscoplastic Fast Fourier Transform-based (EVPFFT) micromechanical solver to enable computationally efficient crystal plasticity modeling for polycrystalline materials. Our primary focus lies in achieving performance portability, allowing a single EVPFFT implementation to run optimally on various homogeneous architectures, including multi-core Central Processing Units (CPUs), as well as on heterogeneous computer architectures comprising multi-core CPUs and Graphics Processing Units (GPUs) from different vendors. To accomplish this goal, we have leveraged MATAR, a C++ software library that simplifies the creation and utilization of multidimensional dense or sparse matrix and array data structures. These data structures are designed to be portable across diverse architectures through the use of Kokkos, a performance-portable library. Additionally, we have employed the Message Passing Interface (MPI) to efficiently distribute the computational workload among processors. The heFFTe (Highly Efficient FFT for Exascale) library is used to facilitate the performance portability of the fast Fourier transforms (FFTs) computation. The computational performance of EVPFFT is evaluated and presented in terms of parallel scalability and simulation runtime on different high-performance computing (HPC) architectures. As a result, the utility of the developed framework to efficiently simulate the micro-mechanical fields in polycrystalline microstructures in engineering applications is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2016

The social impacts of dams: A new framework for scholarly analysis

No commonly used framework exists in the scholarly study of the social impacts of dams. This hinders comparisons of analyses and thus the accumulation of knowledge. The aim of this paper is to unify scholarly understanding of dams' social impacts via the analysis and aggregation of the various frameworks currently used in the scholarly literature. For this purpose, we have systematically analyzed and aggregated 27 frameworks employed by academics analyzing dams' social impacts (found in a set of 217 articles). A key finding of the analysis is that currently used frameworks are often not specific to dams and thus omit key impacts associated with them. The result of our analysis and aggregation is a new framework for scholarly analysis (which we call ‘matrix framework’) specifically on dams' social impacts, with space, time and value as its key dimensions as well as infrastructure, community and livelihood as its key components. Building on the scholarly understanding of this topic enables us to conceptualize the inherently complex and multidimensional issues of dams' social impacts in a holistic manner. If commonly employed in academia (and possibly in practice), this framework would enable more transparent assessment and comparison of projects.

13 HYDRO ENERGY↗
DOE OSTI2018

Ranking the importance of Wildfires' human drivers through a multi-model regression approach

Highlights: • Spatial variability of wildfire regimes is closely related to human activities. • Fire variables have different correlation structures with socioeconomic variables. • Rural poverty, economic disparities and social conflicts are associated to high fire risk. • Landscape structure, land-use and cropping systems influence local-scale fire regimes. • Local unemployment rates discriminate among different wildfire regimes. - Abstract: Wildfires are a major ecological disturbance in Mediterranean environments, and affect together natural resources, ecosystem services and human activities. The impact of socioeconomic forces on wildfire regimes is generally less investigated than the effects of biophysical drivers. Being grounded on a multi-model regression analysis of socioeconomic and territorial indicators, the present study identifies relevant factors influencing local-scale wildfires' regimes in Italy. An economically-disadvantaged context with persistent unemployment, rural poverty, social inequalities and population aging proved to be associated to more frequent fire events. Additionally, our analysis points out that occurrence, average size and density of wildfires reflect different correlation profiles with the local-scale socioeconomic context. Along with the socioeconomic profile of local communities, the empirical outcomes of our study show the importance of landscape structure, land-use and cropping systems in local-scale fire regimes. The empirical results of this study justify a multidimensional analysis of relevant socioeconomic dimensions in fire risk assessment and contribute to an informed approach to wildfire management. Moreover, our study provides basic knowledge advancing research on fire prevention, and informing spatial planning and developmental policies aimed at increasing preparedness to large fires.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Environmental impact assessment of online advertising

Highlights: • A practical framework for assessing the environmental impact of any Internet service • Online advertising consumed between 20.38 to 282.75 TWh of energy and 11.53 – 159.93 million tons of CO{sub 2}e was emitted to produce the electricity consumed. • Invalid traffic associated with online advertising resulted in 2.65 – 36.78 million tons of CO{sub 2}e emissions. • The energy burden of online advertising is considerable and urgently requires attention from researchers and industries. - Abstract: There are no commonly agreed ways to assess the total energy consumption of the Internet. Estimating the Internet's energy footprint is challenging because of the interconnectedness associated with even seemingly simple aspects of energy consumption. The first contribution of this paper is a common modular and layered framework, which allows researchers to assess both energy consumption and CO{sub 2}e emissions of any Internet service. The framework allows assessing the energy consumption depending on the research scope and specific system boundaries. Further, the proposed framework allows researchers without domain expertise to make such an assessment by using intermediate results as data sources, while analyzing the related uncertainties. The second contribution is an estimate of the energy consumption and CO{sub 2}e emissions of online advertising by utilizing our proposed framework. The third contribution is an assessment of the energy consumption of invalid traffic associated with online advertising. The second and third contributions are used to validate the first. The online advertising ecosystem resides in the core of the Internet, and it is the sole source of funding for many online services. Therefore, it is an essential factor in the analysis of the Internet's energy footprint. As a result, in 2016, online advertising consumed 20–282 TWh of energy. In the same year, the total infrastructure consumption ranged from 791 to 1334 TWh. With extrapolated 2016 input factor values without uncertainties, online advertising consumed 106 TWh of energy and the infrastructure 1059 TWh. With the emission factor of 0.5656 kg CO{sub 2}e/kWh, we calculated the carbon emissions of online advertising, and found it produces 60 Mt CO{sub 2}e (between 12 and 159 Mt of CO{sub 2}e when considering uncertainty). The share of fraudulent online advertising traffic was 13.87 Mt of CO{sub 2}e emissions (between 2.65 and 36.78 Mt of CO{sub 2}e when considering uncertainty). The global impact of online advertising is multidimensional. Online advertising affects the environment by consuming significant amounts of energy, leading to the production CO{sub 2}e emissions. Hundreds of billions of ad dollars are exchanged yearly, placing online advertising in a significant role economically. It has become an important and acknowledged component of the online-bound society, largely due to its integration with the Internet and the amount of revenue generated through it.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Deconvolving distribution of relaxation times, resistances and inductance from electrochemical impedance spectroscopy via statistical model selection: Exploiting structural-sparsity regularization and data-driven parameter tuning

The distribution of relaxation times (DRT) has drawn increasing attention for interpreting electrochemical impedance spectroscopy (EIS). Deconvolution of DRT from EIS is a challenging ill-posed problem that requires regularization methods. In this work, we formulate DRT reconstruction task as a statistical model selection problem with structural-sparsity penalties. We utilize the Elastic net regularization that simultaneously benefits from Ridge and Lasso regularizations with optimal tuning parameter automatically determined by the information criteria. We benchmark our approach on four synthetic experiments (a ZARC element, ZARC mixtures, a RC circuit and a Fractal element) and two real EIS datasets of a Lithium ion battery and an organic-inorganic halide class of perovskites in oxygen environment at different gas pressures. We demonstrate the superiority of proposed model selection procedure, that is capable of eliminating pseudo peaks and representing asymmetries in DRT as well as precisely estimating resistances. Here, we highlight our approach is robust to reducing and subsampling EIS frequency range, making it a promising tool for timing-resolved, localized and large scale EIS data analysis. For the Lithium ion battery data analysis, we extend the classical DRT model to incorporate the inductive effect and illustrate DRT as a guidance for equivalent circuit modeling to refine impedance reconstruction at low risks of overfitting. Furthermore, the structural-sparsity regularization could be extended for multidimensional and Bayesian EIS data analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗