Quantitative analysis of power systems resilience: Standardization, categorizations, and challenges
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24 POWER TRANSMISSION AND DISTRIBUTION↗
SEARCH · Engineering Papers
Results for “quantitative analysis”
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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Colorimetric-Luminance Readout for Quantitative Analysis of Fluorescence Signals with a Smartphone CMOS Sensor
Smartphones have shown promise as an enabling technology for portable and distributed point-of-care diagnostic tests. The CMOS camera sensor can be used for detecting optical signals, including fluorescence for applications such as isothermal nucleic acid amplification tests. However, such analysis is typically limited mostly to end point detection of single targets. In this paper, we present a smartphone-based image analysis pipeline that utilizes the CIE xyY (chromaticity-luminance) color space to measure the luminance (in lieu of RGB intensities) of fluorescent signals arising from nucleic acid amplification targets, with a discrimination sensitivity (ratio between the positive to negative signals), which is an order of magnitude more than traditional RGB intensity based analysis. Furthermore, the chromaticity part of the analysis enables reliable multiplexed detection of different targets labeled with spectrally separated fluorophores. We apply this chromaticity-luminance formulation to simultaneously detect Zika and chikungunya viral RNA via end point RT-LAMP (Reverse transcription Loop-Mediated isothermal amplification). We also show real time LAMP detection of Neisseria gonorrhoeae samples down to a copy number of 3.5 copies per 10 μL of reaction volume in our smartphone-operated portable LAMP box. Finally, our chromaticity-luminance analysis is readily adaptable to other types of multiplexed fluorescence measurements using a smartphone camera.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data
Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.
36 MATERIALS SCIENCE↗
Quantitative Analysis and Prediction of Thermal Runaway Metrics of High-Nickel Oxide Cathodes by Machine Learning Models
The pursuit of higher energy density in lithium-ion batteries has made high-nickel (Ni) layered oxides leading cathode candidates for next-generation electric vehicles. However, their poor thermal stability, particularly at Ni contents ≥ 90%, increases the risk of cathode-initiated thermal runaway. Furthermore, we present a data-driven framework combining linear and nonlinear machine learning models to predict key thermal runaway descriptors from a high-throughput differential scanning calorimetry database. With cathode composition and state of charge (SOC) as input features, the ensemble model accurately predicts peak temperature, heat release, and peak heat flow. SHAP analysis identifies Ni content and SOC as the dominant factors controlling thermal runaway temperature, while SOC primarily governs heat release and peak heat flow. Al, Mg, and Mn improve thermal stability by strengthening metal–oxygen bonding and delaying structural transformation, whereas B mainly reduces heat release through surface passivation. Validation with a new cathode composition confirms accurate prediction of SOC-dependent thermal runaway behavior and critical SOC.
25 ENERGY STORAGE↗
Quantitative analysis of the local phase transitions induced by the laser heating
Functional imaging enabled by scanning probe microscopy (SPM) allows investigations of nanoscale material properties under a wide range of external conditions, including temperature. However, a number of shortcomings preclude the use of the most common material heating techniques, thereby limiting precise temperature measurements. Here we discuss an approach to local laser heating on the micron scale and its applicability for SPM. We applied local heating coupled with piezoresponse force microscopy and confocal Raman spectroscopy for nanoscale investigations of a ferroelectric-paraelectric phase transition in the copper indium thiophosphate layered ferroelectric. Bayesian linear unmixing applied to experimental results allowed extraction of the Raman spectra of different material phases and enabled temperature calibration in the heated region. Lastly, the obtained results enable a systematic approach for studying temperature-dependent material functionalities in heretofore unavailable temperature regimes.
36 MATERIALS SCIENCE↗
A Quantitative Analysis of Aqueous Nanofilm Rupture by Molecular Dynamic Simulation
In this study, we used molecular dynamic (MD) simulations of the rupture process for a water film to define and determine the critical rupture time (CRT). This new approach could be an important method for authentically defining and determining the rupture point of a water film and associated phenomena. We were able to generically predict the CRT and the critical thickness of the water film. Then, we studied the effect of ions on the film rupture process. Our results showed that addition of sodium chloride did not significantly affect on the stability of the water film. Results from MD simulations, when compared with results from experimental measurements, can provide insights into the film rupture process.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Quantitative analysis of EXAFS data sets using deep reinforcement learning
Not provided.
Science & Technology - Other Topics↗
Quantitative analysis of magnetic spin and orbital moments from an oxidized iron (1 1 0) surface using electron magnetic circular dichroism
Understanding the ramifications of reduced crystalline symmetry on magnetic behavior is a critical step in improving our understanding of nanoscale and interfacial magnetism. However, investigations of such effects are often controversial largely due to the challenges inherent in directly correlating nanoscale stoichiometry and structure to magnetic behavior. Here, we describe how to use Transmission Electron Microscope (TEM) to obtain Electron Magnetic Circular Dichroism (EMCD) signals as a function of scattering angle to locally probe the magnetic behavior of thin oxide layers grown on an Fe (1 1 0) surface. Experiments and simulations both reveal a strong dependence of the magnetic orbital to spin ratio on its scattering vector in reciprocal space. We exploit this variation to extract the magnetic properties of the oxide cladding layer, showing that it locally may exhibit an enhanced orbital to spin moment ratio. This finding is supported here by both spatially and angularly resolved EMCD measurements, opening up the way for compelling investigations into how magnetic properties are affected by nanoscale features.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Quantitative analysis of hydrogen sites and occupancy in deep mantle hydrous wadsleyite using single crystal neutron diffraction
Evidence from seismological and mineralogical studies increasingly indicates that water from the oceans has been transported to the deep earth to form water-bearing dense mantle minerals. Wadsleyite [(Mg, Fe2+)2SiO4] has been identified as one of the most important host minerals incorporating this type of water, which is capable of storing the entire mass of the oceans as a hidden reservoir. To understand the effects of such water on the physical properties and chemical evolution of Earth’s interior, it is essential to determine where in the crystal structure the hydration occurs and which chemical bonds are altered and weakened after hydration. Here, we conduct a neutron time-of-flight single-crystal Laue diffraction study on hydrous wadsleyite. Single crystals were grown under pressure to a size suitable for the experiment and with physical qualities representative of wet, deep mantle conditions. The results of this neutron single crystal diffraction study unambiguously demonstrate the method of hydrogen incorporation into the wadsleyite, which is qualitatively different from that of its denser polymorph, ringwoodite, in the wet mantle. The difference is a vital clue towards understanding why these dense mantle minerals show distinctly different softening behaviours after hydration.
54 ENVIRONMENTAL SCIENCES↗
A quantitative analysis of the efficiency of solar-driven water-splitting device designs based on tandem photoabsorbers patterned with islands of metallic electrocatalysts
The trade-off between the optical obscuration and kinetic overpotentials of electrocatalyst films patterned onto the surface of tandem light-absorber structures in model photoelectrosynthetic water-splitting systems was investigated using a 0-dimensional load-line analysis and experimental measurements. The electrocatalytic performance of the catalyst at high current densities, normalized to the electrocatalyst surface area, is an important factor in the dependence of the optimal solar-to-hydrogen (STH) conversion efficiency, η STH,opt , on the filling fraction ( f c ) of the patterned catalysts, because even under conditions that produce minority-carrier current densities of ~10 mA cm -2 at the solid/liquid interface, the current density at catalyst-bearing sites can be >1–2 A cm -2 in low filling-fraction films. A universal current-density versus potential relationship, up to current densities of 10 A cm -2 , was obtained experimentally for the hydrogen-evolution reaction (HER) using patterned Pt ultramicroelectrode (UME) arrays with a range of filling fractions and disc diameters. The η STH,opt of system designs that utilize patterned electrocatalysts located on the illuminated side of tandem photoabsorbers was then evaluated systematically. The maximum STH conversion efficiency, η STH,max , using a hypothetical electrocatalyst that was optically transparent but which nevertheless exhibited a current-density versus potential behavior that is characteristic of the most active Pt films measured experimentally regardless of their optical obscuration, was 26.7%. By comparison, the maximum η STH,opt of 24.9% for real patterned Pt electrocatalyst films closely approached this ideal-case limit. The performance and materials utilization of the patterned electrocatalysts and of the uniformly coated electrocatalysts on tandem photoabsorbers were also compared in this research. Hence, patterned electrocatalysts with very low filling fractions can provide a potentially promising path to the realization of efficient large-scale photoelectrolysis systems while minimizing the use of scarce noble metals.
14 SOLAR ENERGY↗
Development and testing of a novel micro-Raman probe and application of calibration transfer method for the quantitative analysis of microfluidic nitric acid streams
To simplify and improve the safety of reprocessing used nuclear fuel, an initial assessment was made of Raman microscopy applied to microfluidic volumes with a view toward the on-line spectroscopic measurement of highly radioactive solutions. This study compares a microscopic Raman probe (excitation focal point diameter 70 µm) to a larger, well studied probe (excitation focal point diameter 125 µm) used in prior investigations. This was done by chemometrically modeling and predicting concentrations of HNO3 solutions (0 M to 8 M) as they flowed through microfluidic cells based upon spectra from each probe. Spectra recorded for each probe using the same static HNO3 solution set contained in 2 dram glass vials were used as training sets to produce models for the respective probes. Modeling required baseline, normalization and smoothing preprocessing to compensate for a reduced path length between the static glass vial training set (4 cm) and the reduced path length flow cell (1 cm), wide ranging solution concentrations, and the associated non-linear spectral changes, and abrupt and uneven concentration changes of flowing solutions. The micro-Raman probe is able to produce spectra that may be analyzed chemometrically to accurately predict the concentration of flowing HNO3 solutions down to microliter volumes. Based upon RMSECV and RMSEP modeling statistics concentration predictions of the micro-Raman probe are comparable to those obtained for a macro-Raman on identical samples.
microscopic Raman probe, MicroRaman, nitric acid, ↗
Rapid quantitative analysis of trace elements in plutonium alloys using a handheld laser-induced breakdown spectroscopy (LIBS) device coupled with chemometrics and machine learning
Here, we present the first reported quantification of trace elements in plutonium via a portable laser-induced breakdown spectroscopy (LIBS) device and demonstrate the use of chemometric analysis to enhance the handheld device's sensitivity and precision. Quantification of trace elements such as iron and nickel in plutonium metal via LIBS is a challenging problem due to the complex nature of the plutonium optical emission spectra. While rapid analysis of plutonium alloys has been demonstrated using portable LIBS devices, such as the SciAps Z300, their detection limits for trace elements are severely constrained by their achievable pulse power and length, light collection optics, and detectors. In this paper, analytical methods are evaluated as a means to circumvent the detection constraints. Three chemometric methods often used in analytical spectroscopy are evaluated; principal component regression, partial least-squares regression, and artificial neural networks. These models are evaluated based on goodness-of-fit metrics, root mean-squared error, and their achievable limits of detection (LoDs). Partial least squares proved superior for determining content of iron and nickel in plutonium metal, yielding LoDs of 15 and 20 ppm, respectively. These results of identifying the undesirable trace elements in plutonium components are critical for applications such as fabricating radioisotope thermoelectric generators or nuclear fuel.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
A Quantitative Analysis of Room Temperature Recrystallization Kinetics in Electroplated Copper Films using High Resolution X-ray Diffraction
Time-resolved in situ x-ray diffraction measurements were used to study the room-temperature recrystallization kinetics of electroplated copper thin films with thicknesses between 400 and 1000 nm. The thinnest films exhibited limited recrystallization and subsequent growth of grains, while recrystallized grains in the thicker films grew until all as-plated microstructure was consumed. For all films, recrystallized grains that belonged to the majority texture component, <111>, started growing after the shortest incubation time. These grains exhibited volumetric growth until they achieved the film thickness. After this point the growth mode became planar, with the <111>-type grains growing in the plane of the film. Grains with the <111> direction normal to the film surface started growing after the <111>-type grains switched to planar growth. However, the planar growth of this texture component finished at the same time as the growth of the <111> grains. Profile fitting of the 111 peak permitted the separation of the diffraction signals from recrystallized and as-plated grain populations. The average strains in these two populations, calculated from the peak position of the corresponding {l_brace}111{r_brace} reflections, were different, indicating a heterogeneous stress state within this texture component. The increasing volume fraction of recrystallized <111> grains with time was monitored via the variation in the diffracted intensity. This variation could be represented by the Johnson-Mehl-Avrami-Kolmogorov model.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗