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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 73 records · Page 4

Evaluation of quantitative synchrotron radiation micro-X-ray fluorescence in rice grain

Concentrations of nutrients and contaminants in rice grain affect human health, specifically through the localization and chemical form of elements. Methods to spatially quantify the concentration and speciation of elements are needed to protect human health and characterize elemental homeostasis in plants. Here, an evaluation was carried out using quantitative synchrotron radiation microprobe X-ray fluorescence (SR-µXRF) imaging by comparing average rice grain concentrations of As, Cu, K, Mn, P, S and Zn measured with rice grain concentrations from acid digestion and ICP-MS analysis for 50 grain samples. Better agreement was found between the two methods for high-Z elements. Regression fits between the two methods allowed quantitative concentration maps of the measured elements. These maps revealed that most elements were concentrated in the bran, although S and Zn permeated into the endosperm. Arsenic was highest in the ovular vascular trace (OVT), with concentrations approaching 100 mg kg –1 in the OVT of a grain from a rice plant grown in As-contaminated soil. Quantitative SR-µXRF is a useful approach for comparison across multiple studies but requires careful consideration of sample preparation and beamline characteristics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Toward a quantitative description of solvation structure: a framework for differential solution scattering measurements

Appreciating that the role of the solute–solvent and other outer-sphere interactions is essential for understanding chemistry and chemical dynamics in solution, experimental approaches are needed to address the structural consequences of these interactions, complementing condensed-matter simulations and coarse-grained theories. High-energy X-ray scattering (HEXS) combined with pair distribution function analysis presents the opportunity to probe these structures directly and to develop quantitative, atomistic models of molecular systems in situ in the solution phase. However, at concentrations relevant to solution-phase chemistry, the total scattering signal is dominated by the bulk solvent, prompting researchers to adopt a differential approach to eliminate this unwanted background. Though similar approaches are well established in quantitative structural studies of macromolecules in solution by small- and wide-angle X-ray scattering (SAXS/WAXS), analogous studies in the HEXS regime—where sub-ångström spatial resolution is achieved—remain underdeveloped, in part due to the lack of a rigorous theoretical description of the experiment. To address this, herein we develop a framework for differential solution scattering experiments conducted at high energies, which includes concepts of the solvent-excluded volume introduced to describe SAXS/WAXS data, as well as concepts from the time-resolved X-ray scattering community. Our theory is supported by numerical simulations and experiment and paves the way for establishing quantitative methods to determine the atomic structures of small molecules in solution with resolution approaching that of crystallography.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

X-ray and Neutron Radiography for Quantitative Material Reconstructions

Radiography is a powerful tool to determine the interior structure of objects. X-ray radiography is widely used and provides high-resolution images, though X-rays have limited transmission through materials of high atomic number (Z) and density. In contrast, neutrons can penetrate many materials that are heavily attenuating to X-rays, such as metals, providing contrast in the inner layers of highly attenuating items. Past work has shown the value in using both X-ray and neutron radiography for estimating material thicknesses, though that work was limited to simulated data. Here, we demonstrate quantitative material reconstructions using experimental X-ray and neutron radiography data from lab-based systems, accurately modeling radiography system responses to within a few percent to enable quantitative measures of material thickness. We demonstrate the utility of neutron radiography and X-ray radiography for these quantitative reconstructions and introduce methods for using their complementarity to improve image quality and optimize experimental design.

Gilbert, Andrew J.↗

Quantitative Metrics for Grid Resilience Evaluation and Optimization

Power system resilience has become a critical topic in recent years because of the increasing trend of extreme events and the growing integration of intermittent renewable energy sources. To enhance grid resilience against high-impact, low-frequency events, two questions should be answered: how to quantify the resilience of a given grid and how to incorporate the quantification into power system planning, operation, and restoration. Here this paper develops a new set of quantitative metrics with clear physical interpretation to comprehensively evaluate power system resilience. Using microgrids as an example, an event-based corrective scheduling (ECS) model and an online model predictive control (OMPC) model are developed to integrate the proposed quantitative resilience metrics into power system optimization models for resilience enhancement. The ECS model employs extreme event data to investigate the optimal restoration solution and to help microgrid operators prepare to respond to similar events. The OMPC model provides online decision-making support for operators to handle ongoing outages in the most resilient fashion. The effectiveness and superiority of the proposed quantitative resilience metrics and the resilience enhancement models are demonstrated through simulations and comparative studies on an IEEE test feeder and a real distribution feeder in Southern California.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Quantitative approaches for including equity in risk and resilience infrastructure planning analyses

Risk and resilience assessments for critical infrastructure focus on myriad objectives, from natural hazard evaluations to optimizing investments. Although research has started to characterize externalities associated with current or possible future states, incorporation of equity priorities at project inception is increasingly being recognized as critical for planning related activities. However, there is no standard methodology that guides development of equity-informed quantitative approaches for infrastructure planning activities. Here, to address this gap, we introduce a logic model that can be tailored to capture nuances about specific geographies and community priorities, effectively incorporating them into different mathematical approaches for quantitative risk assessments. Specifically, the logic model uses a graded, iterative approach to clarify specific equity objectives as well as inform the development of equations being used to support analysis. We demonstrate the utility of this framework using case studies spanning aviation fuel, produced water, and microgrid electricity infrastructures. For each case study, the use of the logic model helps clarify the ways that local priorities and infrastructure needs are used to drive the types of data and quantitative methodologies used in the respective analyses. The explicit consideration of methodological limitations (e.g., data mismatches) and stakeholder engagements serves to increase the transparency of the associated findings as well as effectively integrate community nuances (e.g., ownership of assets) into infrastructure assessments. Such integration will become increasingly important to ensure that planning activities (which occur throughout the lifecycle of the infrastructure projects) lead to long-lasting solutions to meet both energy and sustainable development goals for communities.

community-based↗

Quantitative analysis method for multi-color microscopy

We developed an analysis framework for quantitatively interpreting results from multi-color fluorescence microscopy data. When the emission signal from fluorescent probes (i.e. from biological microscopy or in single-particle microscopy) is spectrally separated before detection, the resulting signals contain information about the strengths of each probe. We built a model to deconvolve the raw data into quantitative descriptions of either of the wavelength of a single probe or the relative strengths among multiple probes. This approach requires only spectrally separating the image data into two or more channels, as opposed to fully resolving the spectral profile, thus allowing other microscopy techniques to be used simultaneously. Our analysis framework incorporates the response features of the optical and imaging elements used to produce the spectral separation, yielding highly quantitative interpretations of the underlying behaviors that give rise to the data.

Ryan, Duncan↗

Assessment of an E10 gasoline surrogate: Qualitative and quantitative comparisons of in-cylinder spray morphology

A minimum-component gasoline fuel surrogate that captures both chemical and physical behaviors of a full-distillate fuel is needed for high-fidelity CFD simulations. This study evaluates gasoline spray characteristics in a direct-injection spark-ignition engine under motored operation. Two fuels are compared; PACE-20, which is a 9-component surrogate formulation of RD5-87, is compared with its target fuel RD5-87, which is a full-boiling range research grade E10 gasoline. The spray morphologies of both fuels are recorded for a centrally-located direct-injection 8-hole spray subject to intake air cross-flow during the early part of the intake stroke. High-speed imaging recorded scattered light of the side and axial projections of the liquid spray. Quantitative metrics were developed and employed to facilitate comparison of spray morphologies as well as to identify the transition in spray morphology due to flash boiling. This paper builds on a previous study of RD5-87 where coolant temperature (20°C–100°C), in-cylinder pressure (40–110 kPa), engine speed (650–1950 rpm), and injection pressure (60–180 bar) were systematically changed to span operating conditions with and without flash boiling. Images of the PACE-20 morphology are selected for a sub-set of operating conditions from the previous study where distinctive morphology changes occurred. Visual inspection of the images and quantitative metrics demonstrate that the PACE-20 spray morphology is equivalent to that of the RD5-87 in most cases. The exception was for changes in the ambient-gas pressure where the flash-boiling transition occurred at ∼5 kPa higher in-cylinder pressure for PACE-20. Three empirical metrics, Merging Index, Asymmetry, and Flash Index are proposed here and they were found to be useful both as quantitative comparisons of the fuel morphologies, and for identifying the transition in spray morphology due to flash boiling.

Kim, Namho↗

Quantitative defect analysis in MOCVD GaN-on-GaN using cathodoluminescence

Cathodoluminescence (CL) is used as a quantitative characterization technique to probe impurities at the metal-organic chemical vapor deposition (MOCVD) grown GaN-on-GaN homoepitaxial interfaces. CL intensity contrast shows a strong correlation with the interfacial impurity concentrations. Based on the analysis of recombination mechanisms of electron beam induced non-equilibrium carriers, an analytical model is proposed to quantitatively determine the impurity concentrations from CL intensity. The extracted interfacial impurity concentrations from the analytical model show a good agreement with the compensation levels obtained from capacitance-voltage measurement, signifying the potential of CL for probing the quantitative impurity levels in GaN-on-GaN structures. This approach can also be extended to be applied in other material systems.

Chen, Zhaoying↗

Deep learning classification of lipid droplets in quantitative phase images

We report the application of supervised machine learning to the automated classification of lipid droplets in label-free, quantitative-phase images. By comparing various machine learning methods commonly used in biomedical imaging and remote sensing, we found convolutional neural networks to outperform others, both quantitatively and qualitatively. We describe our imaging approach, all implemented machine learning methods, and their performance with respect to computational efficiency, required training resources, and relative method performance measured across multiple metrics. Overall, our results indicate that quantitative-phase imaging coupled to machine learning enables accurate lipid droplet classification in single living cells. As such, the present paradigm presents an excellent alternative of the more common fluorescent and Raman imaging modalities by enabling label-free, ultra-low phototoxicity, and deeper insight into the thermodynamics of metabolism of single cells.

59 BASIC BIOLOGICAL SCIENCES↗

Quantitative Performance Assessment of Proxy Apps and Parents (Report for ECP Proxy App Project Milestone ADCD-504-28)

The ECP Proxy Application Project has an annual milestone to assess the state of ECP proxy applications and their role in the overall ECP ecosystem. Our FY22 March/April milestone (ADCD- 504-28) proposed to: Assess the fidelity of proxy applications compared to their respective parents in terms of kernel and I/O behavior, and predictability. Similarity techniques will be applied for quantitative comparison of proxy/parent kernel behavior. MACSio evaluation will continue and support for OpenPMD backends will be explored. The execution time predictability of proxy apps with respect to their parents will be explored through a carefully designed scaling study and code comparisons. Note that in this FY, we also have quantitative assessment milestones that are due in September and are, therefore, not included in the description above or in this report. Another report on these deliverables will be generated and submitted upon completion of these milestones. To satisfy this milestone, the following specific tasks were completed: Study the ability of MACSio to represent I/O workloads of adaptive mesh codes. Re-define the performance counter groups for contemporary Intel and IBM platforms to better match specific hardware components and to better align across platforms (make cross-platform comparison more accurate). Perform cosine similarity study based on the new performance counter groups on the Intel and IBM P9 platforms. Perform detailed analysis of performance counter data to accurately average and align the data to maintain phases across all executions and develop methods to reduce the set of collected performance counters used in cosine similarity analysis. Apply a quantitative similarity comparison between proxy and parent CPU kernels. Perform scaling studies to understand the accuracy of predictability of the parent performance using its respective proxy application. This report presents highlights of these efforts.

97 MATHEMATICS AND COMPUTING↗

Front-end engineering design (FEED) studies: a quantitative analysis

NETL has devised a methodology for normalizing FEED study metrics of interest and allowing cautious quantitative comparison across FEED studies. This presentation introduces the novel quantitative comparison methodology and presents results from utilizing this methodology to examine data presented in recent FEED study reports. The quantitative methodology developed for the examination of FEED study performance and cost also allows comparison of real-world performance and costs against NETL TEA model predicted performance and cost. Learnings from examining NETL model predicted performance and cost versus real world reported values are highlighted. These learnings provide insight into NETL TEA model uncertainty and highlight opportunities for further model development.

FEED Studies↗

Quantitative Risk Assessment for Fuel Cell Electric Bus Hydrogen Storage and Refueling Facility

It is necessary to understand the safety implications and risk mitigation options for fuel cell electric bus fleet deployment, especially for related facilities responsible for operations such as production, storage, compression, and dispensing of hydrogen for use by the buses. In this report, we present a quantitative risk assessment for a potential fuel cell electric bus fleet that was motivated by efforts to improve resilience at the Portland International Airport but can be applicable to a range of hydrogen case studies and use cases. We estimated risk for a facility that produces, stores, compresses, and dispenses hydrogen for the fleet of buses, with a focus on individual risk to people in terms of annual frequency of fatality. We considered the frequency of hydrogen leaks that could result in harmful physical outcomes like jet fires or explosions, and the consequences of those outcomes for people. We created customized fault trees to calculate the frequencies of different sizes of leaks and event sequence diagrams to calculate ignition probabilities for the various leak sizes. We also leveraged the HyRAM+ toolkit to use these inputs to calculate overall risk for the facility, which we separated into one section responsible for producing, storing, and compressing hydrogen, and one section responsible for dispensing the hydrogen to the buses. We found that the dispensing area seemed to have a higher risk than the production/storage/compression area of the facility, largely because of the inclusion of a component with a high leak frequency (the heat exchanger used to cool the hydrogen before entering the vehicle, to prevent overheating and expansion of hydrogen in the onboard tank). For the example production and refueling facility we evaluated and the data we used for the analysis, the leak frequency had a larger impact on the risk differences between the two sections on the facility, compared to the physical outcome consequence, which was slightly different due to the varying fuel conditions, but not substantially different. Actions can be taken to prevent these hazards (e.g., lowering leak frequencies in system components) or to mitigate the consequences if they do occur (e.g., installing barriers to protect people if ignition events occur). The choice of which actions to take depends not only on safety considerations but also on space, time, staffing, feasibility, and financial constraints. Therefore, the quantitative risk assessment approach can help understand relative risk contributions from different components, leak sizes, consequences, and human actions, to prioritize risk reduction strategies and balance these parameters. The outcomes of this report may be useful for a variety of stakeholders working in the hydrogen, transportation, vehicle, and aviation sector, including those responsible for aspects like facility design, operations, and regulations. There is not a single value of risk that determines whether a hypothetical system is “safe” or not. The insights about risk mitigations may be leveraged, and the quantitative risk assessment approach can be applied to other case studies to understand risk priorities and contributions specific to different FCEB and hydrogen facility uses.

08 HYDROGEN↗

Quantitative measurements of dislocations in metals for advancing predictive simulations

LLNL applications require scientists to predict how materials evolve under various thermomechanical conditions. While this is achieved through physics-based simulations, uncertainty in the predictions of mechanical properties remains a serious challenge that limits the predictive capabilities of models because we lack methods to compare predictions of atomic-scale defects (dislocations) with experimental measurements. High energy X-ray diffraction (HEXRD) is the most relevant technique that can provide the necessary statistical information on dislocations. However, this technique is not yet quantitative because we lack a precise understanding of the relationship between X-ray diffraction patterns and the underlying material dislocation content and arrangements. To address this need, we used our novel computational X-ray diffraction method to simulate the effect of dislocations on the diffraction patterns. We compared virtual and experimental diffraction patterns. Results allowed us to clearly establish the relationship between X-ray diffraction patterns and the underlying dislocation structures, proving that it is feasible to quantitatively measure dislocation statistics with HEXRD. This project delivered a method that can provide the missing piece to LLNL’s mechanical property simulations in advanced metals by obtaining experimentally long-needed quantitative dislocation data, which could fully enable predictive capabilities.

36 MATERIALS SCIENCE↗

Quantitation of olefins in sustainable aviation fuel intermediates using principal component analysis coupled with vacuum ultraviolet spectroscopy

Olefins, a common intermediate from biomass conversion processes, are undesirable in jet fuel because of their poor thermal stability. This paper presents an approach for olefin quantitation using 2D gas chromatography coupled with vacuum ultraviolet spectroscopy. Principal component analysis was used to reduce the dimensionality of the spectroscopic data from a highly olefinic fuel intermediate. A principal component template was created that enabled olefin quantitation, which was compared to the existing GCxGC-VUV approach from the literature. The principal component method was able to identify and quantify trace amounts of cyclodienes, which were present at only 0.01 wt% in the fuel sample. The principal component approach also identifies species that fall outside of the GCxGC template. For instance, quantitation with the literature method resulted in an olefin concentration of 0.95 times that of the principal component method due to olefins falling outside of the expected GCxGC regions. The principal component results were compared with 13 C and 1 H NMR data, which confirmed that the fuel had a high concentration of olefins and alkanes with little aromatic content.

Kosir, Shane↗

From Qualitative to Quantitative AOP: A Case Study of Neurodegeneration

Adverse outcome pathways (AOPs) include a sequence of events that connect a molecular-level initiating event with an adverse outcome at the cellular level for human health endpoints, or at the population level for ecological endpoints. When there is enough quantitative understanding of the relationships between key events in an AOP, a mathematical model may be developed to connect key events in a quantitative AOP (qAOP). Ideally, a qAOP will reduce the time and resources spent for chemical toxicity testing and risk assessment and enable the extrapolation of data collected at the molecular-level by in vitro assays, for example, to predict whether an adverse outcome may occur. Here, we review AOPs in the AOPWiki, an AOP repository, to determine best practices that would facilitate conversion from AOP to qAOP. Then, focusing on a particular case study, acetylcholinesterase inhibition leading to neurodegeneration, we describe specific methods and challenges. Examples of challenges include the availability and collection of quantitative data amenable to model development, the lack of studies that measure multiple key events, and model accessibility or transferability across platforms. We conclude with recommendations for improving key event and key event relationship descriptions in the AOPWiki that facilitate the transition of qualitative AOPs to qAOPs.

Sinitsyn, Dennis↗

Quantitative Proteomic Analysis of the Senescence-Associated Secretory Phenotype by Data-Independent Acquisition

Cellular senescence is a complex stress response that induces an essentially permanent cell cycle arrest and a complex secretory phenotype termed the senescence-associated secretory phenotype (SASP), which drives numerous aging pathologies. Characterization of the SASP can provide insights into aging and disease mechanisms, aging biomarker candidates, and targets for counteracting the deleterious effects of senescent cells. Here we describe a mass spectrometry (MS)-compatible protocol to (1) generate senescent cells using different stimuli, (2) collect conditioned medium containing proteins secreted by senescent cells (i.e., SASP), and (3) prepare the SASP for quantitative proteomic analysis using data-independent acquisition (DIA) MS. Basic Protocol 1: Generating ionizing radiation-induced senescent and control cells Alternate Protocol 1: Generating doxorubicin-induced senescent and control cells Alternate Protocol 2: Generating oncogenic RAS-induced senescent and control cells Alternate Protocol 3: Generating mitochondrial dysfunction-induced senescent and control cells Alternate Protocol 4: Generating atazanavir/ritonavir-induced senescent and control cells Support Protocol: A multiple-assay approach to confirm the phenotype of senescent cells Basic Protocol 2: Generating conditioned medium from senescent cells cultured in low serum and quiescent control cells Alternate Protocol 5: Generating conditioned medium from senescent cells cultured in complete medium and quiescent control cells Basic Protocol 3: Quantitative proteomic analysis of the SASP.

60 APPLIED LIFE SCIENCES↗

A quantitative and holistic circular economy assessment framework at the micro level

Circular Economy (CE) aims to solve resource, waste, and emission challenges by creating a production-to-consumption supply chain that is restorative and environmentally benign. A variety of metrics has been developed with the focus mainly on the macro and meso levels. This work introduces a micro level CE assessment framework that provides i) a set of indicators and metrics with sector-specific dimensions, ii) quantitative and holistic CE overall and category-based metrics, iii) media for data visualization and analysis of CE indicators, and iv) an analytical tool to assess multi-national businesses and the multi-scale and interconnected CE supply chains. Using this quantitative tool, companies are able to track their transition towards CE, conduct temporal analysis, and benchmark their performance against their peers and industry’s standards. The applicability and the capabilities of the developed CE assessment framework is demonstrated through three case studies, with the results demonstrating a clear trend towards circularity.

42 ENGINEERING↗

Cyanobacterial Phycobilisome Allostery as Revealed by Quantitative Mass Spectrometry

Phycobilisomes (PBSs) are the major photosynthetic light-harvesting complexes in cyanobacteria and red algae. PBS, a multisubunit protein complex, has two major interfaces that comprise intrinsically disordered regions (IDRs): rod–core and core-membrane. IDRs do not form regular, three-dimensional structures on their own. Their presence in the photosynthetic pigment–protein complexes portends their structural and functional importance. A recent model suggests that PB-loop, an IDR located on the PBS subunit ApcE and C-terminal extension (CTE) of the PBS subunit ApcG, forms a structural protrusion on the PBS core-membrane side, facing the thylakoid membrane. Here, the structural synergy between the rod–core region and the core-membrane region was investigated using quantitative mass spectrometry (MS). The AlphaFold-predicted CpcG-CTE structure was first modeled onto the PBS rod–core region, guided and justified by the isotopically encoded structural MS data. Quantitative cross-linking MS analysis revealed that the structural proximity of the PB-loop in ApcE and ApcG-CTE is significantly disturbed in the absence of six PBS rods, which are attached to PBS via CpcG-CTE, indicative of drastic conformational changes and decreased structural integrity. Furthermore, these results suggest that CpcG-rod attachment on the PBS rod–core side is essentially required for the PBS core-membrane structural assembly. The hypothesized long-range synergy between the rod–core interface (where the orange carotenoid protein also functions) and the terminal energy emitter of PBS must have important regulatory roles in PBS core assembly, light-harvesting, and excitation energy transmission. These data also lend strategies that genetic truncation of the light-harvesting antennas aimed for improved photosynthetic productivity must rely on an in-depth understanding of their global structural integrity.

59 BASIC BIOLOGICAL SCIENCES↗