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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Chemometric modeling of power conversion efficiency of organic dyes in dye sensitized solar cells for the future renewable energy

The present study reports chemometric modeling of power conversion efficiency (PCE) of dye sensitized solar cells (DSSCs) using the biggest available data set till date which comprises around 1200 dyes covering 7 chemical classes. To extract the best structural features required for higher PCE, we have developed multiple partial least squares (PLS) quantitative structure-property relationship (QSPR) models for the Triphenylamine, Phenothiazine, Indoline, Porphyrin, Coumarin, Carbazole and Diphenylamine chemical classes using descriptors derived from the best subset selection method followed by selection of best five models in each dataset based on the Mean Absolute Error (MAE) values. The models were validated both internally and externally followed by the consensus predictions employing “Intelligent Consensus Predictor” tool to examine whether the quality of predictions can be improved with the “intelligent” selection of multiple PLS models. The quality of predictions for the respective external sets showed that the consensus models (CM) are better than the individual models (IM) in most of the cases. From the insights of the developed models, we concluded that attributes like a packed structure toward higher conductivity of electrons, auxiliary donor fragment of aromatic tertiary amines, number of thiophenes inducing the bathochromic shift and augmenting the absorption, presence of additional electron donors, enhancement of electron-donating abilities, number of non-aromatic conjugated C(sp 2 ) which helps as conjugation extension units to broaden the absorption and highly conjugated $π$-systems exert positive contributions to the PCE. On the contrary, features negatively contributing to PCE are the followings: fragments which lower the tendency of localized $π–π*$ transition, fragments related to larger volume and surface area of dyes along with hydrophobicity resulting in poor adhesion, fragment RC = N causing dye hydrolysis, steric hindrance for π electronic mobility, fragments enhancing polarity, etc. Finally, the identified features from the best QSPR model of the coumarin dataset was employed in designing of ten more efficient coumarin dyes (predicted %PCE ranging from 8.93 to 10.62) than the existing ones.

14 SOLAR ENERGY↗
DOE OSTI2020

Enhanced detection of volatile organic compounds (VOCs) by caffeine modified carbon nanotube junctions

Detection of vapor phase analytes and gas molecules is primarily essential for numerous applications including medical diagnostic, environmental monitoring, chemical threat detection, food quality control, and chemical warfare agents. Here, we developed Caffeine functionalized carbon nanotubes (CNTs) random network based vapor quantum resistive sensors (vQRSs) for volatile organic compounds (VOCs) detection. The localized transmission electron microscopy (TEM) image and energy dispersive X-ray spectroscopy (EDS) confirm migration of caffeine to CNT–CNT junction (CNTj). We have recorded more than one order of magnitude higher sensitivity and unique selectivity towards selective VOCs (e.g., acetone, toluene, ethanol, methanol, etc.) with short response time (few seconds) for caffeine modified CNT junction (Caf-CNTj) vQRSs. Molecular dynamics (MD) calculations suggest that the sensitivity of the sensor is diffusion limited, with an advective contribution for ethanol. Furthermore, the designed Caf-CNTj sensors can potentially be important candidate to be a part of electronic nose used for various application such as breath analysis and food quality monitoring.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions

Here we propose a new type of neural networks, Kronecker neural networks (KNNs), that form a general framework for neural networks with adaptive activation functions. KNNs employ the Kronecker product, which provides an efficient way of constructing a very wide network while keeping the number of parameters low. Our theoretical analysis reveals that under suitable conditions, KNNs induce a faster decay of the loss than that by the feed-forward networks. This is also empirically verified through a set of computational examples. Furthermore, under certain technical assumptions, we establish global convergence of gradient descent for KNNs. As a specific case, we propose the Rowdy activation function that is designed to get rid of any saturation region by injecting sinusoidal fluctuations, which include trainable parameters. The proposed Rowdy activation function can be employed in any neural network architecture like feed-forward neural networks, Recurrent neural networks, Convolutional neural networks etc. The effectiveness of KNNs with Rowdy activation is demonstrated through various computational experiments including function approximation using feed-forward neural networks, solution inference of partial differential equations using the physics-informed neural networks, and standard deep learning benchmark problems using convolutional and fully-connected neural networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Generalist multimodal AI: A review of architectures, challenges and opportunities

Multimodal models are expected to be a critical component to future advances in artificial intelligence. Here, this field is starting to grow rapidly with a surge of new design elements motivated by the success of foundation models in natural language processing (NLP) and vision. It is widely hoped that further extending the foundation models to multiple modalities (e.g., text, image, video, sensor, time series, graph, etc.) will ultimately lead to generalist multimodal models, i.e. one model across different data modalities and tasks. However, there is little research that systematically analyzes recent multimodal models (particularly the ones that work beyond text and vision) with respect to the underling architecture proposed. Therefore, this work provides a fresh perspective on generalist multimodal models (GMMs) via a novel architecture and training configuration specific taxonomy. This includes factors such as Unifiability, Modularity, and Adaptability that are pertinent and essential to the wide adoption and application of GMMs. The review further highlights key challenges and prospects for the field and guide the researchers into the new advancements.

Artificial intelligence (AI)↗
DOE OSTI2025

A compact electromagnetic neutron nutator for precise neutron spin manipulation

A superconducting electromagnetic nutator (EMN) capable of generating a magnetic field vector along an arbitrary direction on a 2D plane has been designed. Its performance in precisely manipulating the neutron polarization vector has been tested at the HB2-D polarized development beamline at the High Flux Isotope Reactor. Unlike mechanical nutators that require physical handling or motor-driven actuation to rotate the magnetic field, the magnitude and orientation of the magnetic field produced by the EMN can be controlled electromagnetically. Further, the compact design (~15 mm depth, not including cryogenic housing) of this device ensures ease of coupling within existing superconducting neutron spin manipulation devices, such as magnetic Wollaston prisms (MWP), resonant radio frequency (RF) flippers, spherical neutron polarimetry (SNP) devices, etc.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Simulation studies for beam commissioning at FRIB Advanced Rare Isotope Separator

The Facility for Rare Isotope Beams (FRIB) includes a powerful superconducting driver accelerator and an Advanced Rare Isotope Separator (ARIS). The ARIS collects and purifies the rare isotope fragments of interest for experiments in nuclear physics, nuclear astrophysics, fundamental symmetries, etc. ARIS consists of a vertical pre-separator and downstream horizontal separator section (C-Bend). Each section can provide a high-resolution separation alternatively. The resolution reduction due to the emittance induced by momentum compression can be avoided by isotope separation in different dispersive planes. Beam commissioning of ARIS for the first experiments was completed and demonstrated particle identification of fragments. The beam tuning in ARIS largely relies on numerical simulations since the limited space for diagnostics. Here, we report the result of the beam trajectory correction, transverse matching, and beam-based misalignment studies at ARIS.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Limitations of traditional tools for beyond design basis external hazard PRA

Probabilistic risk assessment (PRA) is being used increasingly by the nuclear industry for safety during normal operations as well as for the protection against external hazards. Computation of total risk in an external hazard PRA is dependent on hazard assessment, fragility assessment, and systems analysis. A systems analysis for propagation of component fragilities is conducted using event and fault trees. The event and fault trees for an actual power plant can be fairly large in size, which imposes computational challenges. Hence, certain assumptions are employed for computational efficiency. These assumptions typically represent the conditions imposed during the design basis (DB) scenario. The traditional PRA tools based on these assumptions are also widely applied to perform risk assessment in the context of beyond design basis (BDB) scenarios. However, some of these assumptions may not be valid for certain BDB scenarios. In addition, the probability of dependent failures also increases in BDB scenarios due to common cause failures (CCF) which usually results from design modifications, human errors, etc. In this manuscript, a simple and a relatively more complex illustrative examples are used to show the limitation of these assumptions in the numerical quantification of risk for the case of BDB conditions. Case studies with CCF events across multiple fault trees are also presented to illustrate the effect of these assumptions when traditional approach is used in BDB risk assessment. It is shown that the assumptions are valid for the case of DB conditions but may lead to excessively conservative risk estimates in the case of BDB conditions. Finally, a Bayesian network based top-down algorithm is proposed as an alternative tool for accurate numerical quantification of total risk in systems analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

FEA-aided investigation of the effective thermal conductivity in a medium with embedded spheres

For multiple applications in nuclear energy, the ability to accurately represent material behavior with a simplified model is important to facilitate practical engineering-scale simulations. Here, we focus on the homogenized thermal response of a medium containing spherical inclusions, similar to a fuel form (compact or pebble) containing (TRISO) particles. A review on effective thermal conductivity (ETC) modeling is performed considering a random distribution of mono-sized spherical inclusions in a continuous matrix, with a primary focus on the analytical models. Finite element simulations are performed to evaluate each analytical model in varying material conditions. The model predictions are compared with the expected results obtained from the finite element predictions in addition to the Wiener and Hashin-Shtrikman bounds. Lastly, we included a practical discussion on the homogenization applied to a TRISO fuel pebble.

42 ENGINEERING↗
DOE OSTI2023

Coregistered positron emission particle tracking (PEPT) and X-ray computed tomography (CT) for engineering flow measurements

Increasingly, fully 3D experimental measurements of flow in complex engineering geometries are required to validate computational fluid dynamics models that support and inform reactor design and licensing. One barrier to such measurements is the complexity of typical reactor components and subsequent lack of optical access in these systems. To overcome this, the deployment of coregistered positron emission particle tracking (PEPT) and X-ray computed tomography (CT) is explored for flow measurement in reactor thermal hydraulic components and model (scaled) systems. Through this methodology, fully 3D flow information (via PEPT) and detailed internal geometry (via CT) are captured in opaque systems such as pipes, rod bundles, packed beds, etc. The reconstructed flow field and geometry can then be overlain to reveal detailed flow features around internal structures within a given test section. This is enabled through the use of a combined preclinical PET/CT scanner with overlapping PET and CT fields of view. Such measurements are useful for characterizing flow inside such intricate nuclear thermal hydraulic components as core geometries and heat exchangers, among others, and providing valuable 3D validation data for CFD models. In this work, basic tests of this 3D flow/geometry mapping are presented, and the implications of such measurements are discussed. Further, preliminary measurements are made with both point sources and flow in a simple pipe flow geometry to evaluate the capabilities of this technique. PEPT and CT features are coregistered with up to 0.1 mm precision, and pipe flow mean velocity and Reynolds stresses are reconstructed with similar accuracy to previous PEPT demonstrations. The utility of PEPT/CT is shown herein, and suggestions for future measurements are made.

3D flow measurement↗
DOE OSTI2023

Characterization of the Fast-Neutron Irradiator and the Fast-Flux Tube Irradiation Fixtures at the Pennsylvania State Breazeale Reactor

Accurate knowledge of the neutron spectrum at a nuclear research reactor is a prerequisite for planning irradiation experiments, as well as for evaluating irradiation exposure results. The neutron-flux spectrum in the fast-neutron irradiator (FNI) and the fast-flux tube (FFT) irradiation fixtures at the Pennsylvania State Breazeale Reactor (PSBR) were characterized using the multi-foil neutron activation method. These irradiation fixtures make use of graded shielding to produce unique neutron fields. Multiple foil sets were irradiated in the fixtures with different exposure times and reactor powers to understand the stability over a wide range of operating conditions. Measured results were evaluated against a MCNP6 simulation to produce a measurement-informed neutron flux-energy spectrum for each fixture using STAYSL_PNNL. Simulated estimates of the FNI fixture, a newer fixture (~25 years old), demonstrated excellent agreement with measured results; the FFT did not. Thermal neutron measurements from the FFT suggest there is additional thermal leakage not captured in the simulation model. In conclusion, possible explanations for the discrepancy include burn-out or degradation (i.e., micro-cracking, gaps, etc.) in the boral and cadmium liners over the lifetime of the fixture (~40 years old).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Glassy polymers: Historical findings, membrane applications, and unresolved questions regarding physical aging

Polymers below their glass transition temperature (Tg) are non-equilibrium glasses because excess free volume “frozen” between kinetically-restricted polymer chains slowly relaxes over time towards equilibrium via local, segmental chain motion. This process, known as physical aging, is observed through time-dependent decreases in a polymer's specific volume, enthalpy, etc. This article focuses on the history of glassy polymers in membrane separation applications. Open questions regarding the influence of thickness (e.g., membrane geometry) and temperature on physical aging in glassy polymers are highlighted.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ordinary and exotic mesons in the extended Linear Sigma Model

The extended Linear Sigma Model (eLSM) is a hadronic model based on the global symmetries of QCD and the corresponding explicit, anomalous, and spontaneous breaking patterns. In its basic three-flavor form, its mesonic part contains the dilaton/glueball as well as the nonets of pseudoscalar, scalar, vector, and axial–vector mesons, thus chiral symmetry is linearly realized. In the chiral limit and neglecting the chiral anomaly, only one term – within the dilaton potential – breaks dilatation invariance, and all terms are chirally symmetric. Spontaneous symmetry breaking is implemented by a generalization of the Mexican-hat potential, with explicit symmetry breaking responsible for its tilting. The overall mesonic phenomenology up to ~2 GeV is in agreement with the PDG compilation of masses and partial and total decay widths. The eLSM was enlarged in a straightforward way to include other conventional quark–antiquark nonets (pseudovector and orbitally excited vector mesons, tensor and axial-tensor mesons, radially excited (pseudo)scalar mesons, etc.), as well as two nonets of hybrid mesons, the lightest one with exotic quantum numbers J $\mathscr{PC}$ = 1 -+ not allowed for $\bar{q}q$ objects, such as the resonance π 1 (1600) and the recently discovered η 1 (1855) . In doing so, different types of chiral multiplets are introduced: heterochiral and homochiral multiplets, which differ in the way they transform under chiral transformations. Moreover, besides the scalar glueball that is present from the beginning as dilaton, other glueballs, the tensor, the pseudoscalar and the vector glueballs were coupled to the eLSM: the scalar resonance ƒ 0 (1710) turns out to be mostly gluonic, the tensor glueball couples strongly to vector mesons, and the pseudoscalar glueball couples sizably to $ππη'$ and can be assigned to X (2370) or X (2600). In all cases above, masses and decays can be analyzed allowing for a better understanding of both conventional and non-conventional mesons: whenever data are available, a comparison is performed and, when this is not the case, predictions of decay widths and decay ratios are outlined. The eLSM contains chiral partners on an equal footing and is therefore well suited for studies of chiral symmetry restoration at nonzero temperature and densities: this is done by coupling it to the Polyakov loop. Finally, the QCD phase diagram and the location of the critical endpoint were investigated within this framework.

Chiral symmetry↗
DOE OSTI2022

Understanding the role of flow dynamics in thermoacoustic combustion instability

Thermoacoustic combustion instability is one of the most challenging operational issues in several high-performance, low-emissions combustion technologies, including gas turbines, aircraft engines, rockets, and industrial boilers. Driven by the coupling between combustor acoustics and flame heat release rate fluctuations, thermoacoustic combustion instability can lead to reduced operability, increased emissions, and, in the most extreme cases, catastrophic failure of combustor components. The feedback loop between acoustics and combustion is often facilitated by fluid mechanic oscillations, referred to as “velocity coupling,” whereby acoustic oscillations drive flow fluctuations, which in turn create fluctuations in the flame. The character of these fluid mechanic oscillations is highly dependent on the structure of the flow field and the receptivity of the flow to external excitation. Combustor flow fields use features like fluid recirculation and shear to enhance flame holding and reduce emissions, but these are also the same features that can make the flow receptive to acoustic excitation or even drive self-excited oscillations. Here, in this paper, we discuss the basics of thermoacoustic instability with a focus on the role of hydrodynamic oscillations in typical combustor flows. To facilitate this discussion, we explore the hydrodynamic instability characteristics of several key combustor unit flows (wakes, swirling jets, etc.) and show how the hydrodynamic stability of a flow is an important consideration in determining a combustor’s propensity for thermoacoustic oscillations. Several examples of coupling between hydrodynamics and thermoacoustics are discussed to illustrate this important link. The paper concludes by discussing the potential for designing flow fields that are thermoacoustic instability resistant, either through a reduction in the receptivity of the flow or through nonlinear coupling mechanisms by which self-excited flow instabilities can suppress velocity-coupled combustion oscillations.

42 ENGINEERING↗
DOE OSTI2024

Comparison of volatiles evolving from selected highland and mare lunar regolith simulants during vacuum sintering

Volatiles evolving from JSC-1A, NU-LHT-4M and CSM-LHT-1G lunar regolith simulants during in vacuo thermal processing were analyzed using mass spectrometry as a function of temperature. Two high-fidelity simulants, JSC-1A (mare) and NU-LHT-4M (highland), were compared to a newly developed CSM-LHT-1G highland simulant, modified to closely match lunar geochemistry. Large autogenous gas loads were observed for all investigated materials. Mineralogical knowledge was used to identify and attribute individual volatile species to reacting, transforming, or decomposing constituents (hydrates, carbonates, sulfates, sulfides, clays, etc.) of the respective regolith simulant in the self-generated gas environment. Cumulative mass losses for individual simulant components as a function of temperature were quantified using mass spectrometry in conjunction with thermogravimetric analysis. Investigation of the four components of CSM-LHT-1G – anorthosite, basalt, augite, and glass – aided the attribution of volatile species to specific compounds and their respective sources. The results showed significant decomposition of non-lunar phases present in the man-made regolith simulants below the typical glass crystallization temperatures, which paves the way to devising methods for enhancing the fidelity of the simulants. Finally, high gas loads and corrosive gases (HF and HCl) were recognized as potential hazards, pertaining to the development of large testbed facilities.

42 ENGINEERING↗
DOE OSTI2022

Holocene paleoclimate change in the western US: The importance of chronology in discerning patterns and drivers

We report sediment in lakes and meadows forms a powerful archive that can be used to reconstruct environmental change through time. Reconstructions of lake level, of chemical, biological, and hydrological conditions, and of surrounding vegetation provide detailed information about past climate conditions, both locally and regionally. Indeed, most of our current knowledge of centennial- to millennial-scale climate variability in the arid western United States, where information about past hydroclimate is particularly important, comes from such sediment-based reconstructions. The pressing need for robust, precise predictions of future conditions is a significant motivation for paleoclimate science, and current research questions frequently require Holocene reconstructions to be resolved at sub-centennial timescales. Increasingly, regional syntheses seek to identify synoptic-scale patterns similar to those defined from modern observations (seasonal, interannual, multi-decadal, etc.) or to compare with the output of climate model simulations. However, the age control on existing records, especially those more than about 20 years old, is often sufficient only for millennial-scale interpretation. Here we assess the age control for 84 published and unpublished records from lakes and meadows in the Great Basin, California, and desert southwest, and use Bayesian modeling to evaluate the 95% uncertainty ranges for the 42 best-dated records. In the Late Holocene, about half of the 42 records have <400-year mean uncertainty ranges; however, high-precision age control is especially critical for young records, used to develop an accurate understanding of a proxy’s response to known climate variations. In the Middle Holocene, records vary from 400 to >800-year mean uncertainty and records of the Early Holocene have 600- to >1400-year mean uncertainty ranges. We find that the largest control on modeled uncertainties is dating density, with at least 2 dates/kyr being optimal and suggest obtaining “range-finder” dates at the onset of a study to better predict the total number of dates needed for an adequate age model. Such a density avoids a commonly observed phenomenon of significant peaks in uncertainty arising in gaps between age control points. Analysis of the uncertainties associated with proxy shifts reveal that more than half are >400 years. Although such large uncertainties currently prevent sub-centennial interpretations in most cases, increased dating density, strategic use of limited funds (including budgeting for a 2 date/kyr minimum at the proposal stage), construction of age-depth models with Bayesian methods, and critical evaluation of chronological uncertainty will shed light on past climate variability at finer timescales, enhancing our understanding of global and regional drivers of western U.S. climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

DRiFT current mode, trigger settings and flexible detector specifications applied to scintillator arrays

MCNP radiation transport output is post-processed by DRiFT, a Detector Response Function Toolkit to simulate detailed nuclear instrumentation response. DRiFT can be used to assess the performance and potential limitations of scintillator, gas, and semiconductor detectors under a variety of simulated conditions not easily achievable in a laboratory setting. This work describes new updates in DRiFT for scintillator simulations which focus on the capability to simulate scintillators in current mode, an expansion of trigger options, and the ability to customize individual detector properties in a simulation. These improvements are designed to facilitate the ability to model large arrays of scintillator detectors with higher fidelity than was previously possible and are demonstrated in three examples. The first shows the difference between operating DRiFT in current and pulse mode. In the second example, which is intended to demonstrate deviations in individual detector performance, each detector has properties (PMT gain, optical transport, scintillation yield, etc.) that vary between detectors and are specified in DRiFT. A final example examines how DRiFT could be used to optimize digitizer settings in high rate measurements with split signals using the new common trigger option.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Life-cycle analysis of battery metal recycling with lithium recovery from a spent lithium-ion battery

Demand for critical materials (nickel, cobalt, manganese [NCM], and lithium) for use in batteries is increasing rapidly due to the expansion of the battery-electric vehicles market. Battery metal recycling (BMR) is an important technology that can potentially realize environmental and economic benefits in cathode active material (LiNi x Mn y Co z O 2 ) production using recycled materials. While current major battery recycling technologies recover cathode materials (NCM) and other metals (steel, aluminum, copper, etc.) from the spent battery, the lithium (Li) recovery rate is less than 1% in the world. In this study, we analyze the environmental benefits of a BMR process that recovers lithium in the form of lithium hydroxide monohydrate (LiOH∙H 2 O) along with other cathode materials. Using life-cycle analysis (LCA), we evaluate the life-cycle greenhouse gas (GHG) emissions, criteria air pollutant emissions, and water consumption of the new BMR technology in terms of lithium hydroxide production and cathode active material production. The LCA results show that the life-cycle GHG emissions recycled LiOH are 37–72% lower than those of virgin LiOH production from Chilean brine and Australian ore, respectively. In addition, the life-cycle GHG emissions of NCM811 produced using the recycled materials are 40–48% lower compared to virgin cathode active material production. Furthermore, recovering lithium from the spent batteries reduces associated air pollutant emissions and water consumption relative to using the virgin materials or materials from other recycling technologies without LiOH recovery.

25 ENERGY STORAGE↗
DOE OSTI2021

Battery asset management with cycle life prognosis

We report Battery Asset Management problem determines the minimum cost replacement schedules for each individual asset in a group of battery assets that operate in parallel. Battery cycle life varies under different operating conditions including temperature, depth of discharge (DOD), charge rate, etc., and a battery deteriorates due to usage, which cannot be handled by current asset management models. This paper presents a new battery asset management methodology where battery cycle life prognosis is integrated with parallel asset management to reduce lifecycle cost of the Battery Energy Storage Systems (BESS). For the battery failure time prognosis, a nonlinear physics-based battery capacity fade model is developed and incorporated in parallel asset management model to update battery capacity over time. Experiment results have shown that the developed battery asset management methodology can be conveniently used to facilitate BESS asset management decision making thereby decreasing asset lifecycle costs.

25 ENERGY STORAGE↗