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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Computational and Experimental Characterization of the Ligand Environment of a Ni-Oxo Catalyst Supported in the Metal–Organic Framework NU-1000

Heterogeneous catalysts exhibit significant changes in composition due to the influence of operating conditions, and these compositional changes can have dramatic effects on catalytic performance. For traditional bulk metal heterogeneous catalysts, relationships between composition and catalytic operating conditions are well documented. However, the influence of operating conditions on the compositions of single-site heterogeneous catalysts remains largely unresolved. To address this, we report a combined computational and experimental characterization of a Ni oxo catalyst under catalytic hydrogenation conditions. Specifically, pair distribution function (PDF) analysis is combined with ab initio thermodynamic modeling to investigate ligand environments present on a Ni oxo cluster supported in the metal–organic framework NU-1000. Comparisons of the experimentally observed and simulated Ni–O coordination numbers and Ni–O, Ni···Ni, and Ni···Zr distances provide insight into the Ni ligand environment under H 2 (g). These comparisons suggest significant OH and H 2 O content and, further, that different Ni ions within the cluster and/or NU-1000 structure may comprise subtly different numbers of these ligands. Further, the observation of significant H 2 O content under H 2 (g) suggests that the NU-1000 support supplies H 2 O to the cluster. Examples of ligand environments that could lead to the observed PDFs are provided. Furthermore, the combination of simulations and experiments provides new insights into the ligand environment for Ni-NU-1000 catalysts that will be useful for understanding the ligand environments of other single-site Ni catalysts as well.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Robustness of topological insulating phase against vacancy, vacancy cluster, and grain boundary bulk defects

One distinguished property of the topological insulator (TI) is its robust quantized edge conductance against edge defect. However, this robustness, underlined by the topological principle of bulk-boundary correspondence, is conditioned by assuming a perfect bulk. Here, we investigate the robustness of the TI phase against bulk defects, including vacancy (VA), vacancy cluster (VC), and grain boundary (GB), instead of edge defect. In this work, based on a tight-binding model analysis, we show that a two-dimensional (2D) TI phase, as characterized by a nonzero spin Bott index, will vanish beyond a critical VA concentration ($n^\text{c}_\text{v}$). Generally, $n^\text{c}_\text{v}$ decreases monotonically with the decreasing topological gap induced by spin-orbit coupling. Interestingly, the $n^\text{c}_\text{v}$ to destroy the topological order, namely, the robustness of the TI phase, is shown to be increased by the presence of VCs but decreased by GBs. As a specific example of a large-gap 2D TI, we further show that the surface-supported monolayer Bi can sustain a nontrivial topology up to $n^\text{c}_\text{v}$ ~ 17%, based on a density-functional theory–Wannier-function calculation. Our findings should provide useful guidance for future experimental studies of effects of defects on TIs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Classification of orthostatic intolerance through data analytics

Imbalance in the autonomic nervous system can lead to orthostatic intolerance manifested by dizziness, lightheadedness, and a sudden loss of consciousness (syncope); these are common conditions, but they are challenging to diagnose correctly. Uncertainties about the triggering mechanisms and the underlying pathophysiology have led to variations in their classification. This study uses machine learning to categorize patients with orthostatic intolerance. Here we use random forest classification trees to identify a small number of markers in blood pressure, and heart rate time-series data measured during head-up tilt to (a) distinguish patients with a single pathology and (b) examine data from patients with a mixed pathophysiology. Next, we use Kmeans to cluster the markers representing the time-series data. We apply the proposed method analyzing clinical data from 186 subjects identified as control or suffering from one of four conditions: postural orthostatic tachycardia (POTS), cardioinhibition, vasodepression, and mixed cardioinhibition and vasodepression. Classification results confirm the use of supervised machine learning. We were able to categorize more than 95% of patients with a single condition and were able to subgroup all patients with mixed cardioinhibitory and vasodepressor syncope. Clustering results confirm the disease groups and identify two distinct subgroups within the control and mixed groups. The proposed study demonstrates how to use machine learning to discover structure in blood pressure and heart rate time-series data. The methodology is used in classification of patients with orthostatic intolerance. Diagnosing orthostatic intolerance is challenging, and full characterization of the pathophysiological mechanisms remains a topic of ongoing research. This study provides a step toward leveraging machine learning to assist clinicians and researchers in addressing these challenges.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

The Sagittarius stream in Gaia Early Data Release 3 and the origin of the bifurcations

The Sagittarius dwarf spheroidal (Sgr) is a dissolving galaxy being tidally disrupted by the Milky Way (MW). Its stellar stream still poses serious modelling challenges, which hinders our ability to use it effectively as a prospective probe of the MW gravitational potential at large radii. Our goal is to construct the largest and most stringent sample of stars in the stream with which we can advance our understanding of the Sgr-MW interaction, focusing on the characterization of the bifurcations. We improved on previous methods based on the use of the wavelet transform to systematically search for the kinematic signature of the Sgr stream throughout the whole sky in the Gaia data. We then refined our selection via the use of a clustering algorithm on the statistical properties of the colour-magnitude diagrams. Our final sample contains more than 700 000 candidate stars and is three times larger than previous Gaia samples. With it, we have been able to detect the bifurcation of the stream in both the northern and southern hemispheres, which requires four branches (two bright and two faint) to fully describe the system. We present the detailed proper motion distribution of the trailing arm as a function of the angular coordinate along the stream, showing, for the first time, the presence of a sharp edge (on the side of the small proper motions) beyond which there are no Sgr stars. We also characterize the correlation between kinematics and distance. Finally, the chemical analysis of our sample shows that the faint branch of the bifurcation is more metal poor than the bright. We provide analytical descriptions for the proper motion trends as well as for the sky distribution of the four branches of the stream. Based on our analysis, we interpret the bifurcations as a misaligned overlap of the material stripped at the antepenultimate pericentre (faint branches) with the stars ejected at the penultimate pericentre (bright branch), given that Sgr just went through its perigalacticon. The source of this misalignment is still unknown, but we argue that models with some internal rotation in the progenitor – at least during the time of stripping of the stars that are now in the faint branches – are worth exploring.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Catalytic, Spectroscopic, and Theoretical Studies of Fe 4 S 4 -Based Coordination Polymers as Heterogenous Coupled Proton–Electron Transfer Mediators for Electrocatalysis

Iron–sulfur clusters play essential roles in biological systems, and thus synthetic [Fe 4 S 4 ] clusters have been an area of active research. Recent studies have demonstrated that soluble [Fe 4 S 4 ] clusters can serve as net H atom transfer mediators, improving the activity and selectivity of a homogeneous Mn CO 2 reduction catalyst. Here, in this work, we demonstrate that incorporating these [Fe 4 S 4 ] clusters into a coordination polymer enables heterogeneous H atom transfer from an electrode surface to a Mn complex dissolved in solution. A previously reported solution-processable Fe 4 S 4 -based coordination polymer was successfully deposited on the surfaces of different electrodes. The coated electrodes serve as H atom transfer mediators to a soluble Mn CO 2 reduction catalyst displaying good product selectivity for formic acid. Furthermore, these electrodes are recyclable with a minimal decrease in activity after multiple catalytic cycles. The heterogenization of the mediator also enables the characterization of solution-phase and electrode surface species separately. Surface enhanced infrared absorption spectroscopy (SEIRAS) reveals spectroscopic signatures for an in situ generated active Mn–H species, providing a more complete mechanistic picture for this system. The active species, reaction mechanism, and the protonation sites on the [Fe 4 S 4 ] clusters were further confirmed by density functional theory calculations. The observed H atom transfer reactivity of these coordination polymer-coated electrodes motivates additional applications of this composite material in reductive H atom transfer electrocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Manipulating the Assembly and Architecture of Fibrillar Silk

Silk is a unique and exceptionally strong biological material. However, no synthetic method has yet come close to replicating the properties of natural silk. This shortfall is attributed to an insufficient understanding of both silk nanofibril structure and the mechanism of formation. Here in situ atomic force microscopy (AFM) and photo-induced force microscopy (PiFM) is utilized to investigate the formation process and define the basic structural paradigm of individual silk nanofibrils. By visualizing the multistage process of silk nanofibril formation, the importance of conformational transformations along the assembly pathway is revealed. Unfolded silk structures initially accumulate into amorphous clusters, which then evolve into crystal nuclei via conformational transformation into β-crystallites. Nanofibril elongation then occurs through the attachment of silk molecules at a single end of the nanofibril tip; this is facilitated through the formation of a new amorphous cluster that then repeats the aforementioned conformational transformation. However, enzymatic digestion of the amorphous regions leads to direct, rapid elongation of β-crystalline fibers. These findings imply that the energy landscape is characterized by shallow minima associated with intermediate states, which can be eliminated by introducing β-crystallites, and motivate research into the directed modification of the silk assembly pathway to select for features beneficial to specific applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantifying rupture characteristics of microearthquakes in the Parkfield Area using a high-resolution borehole network

It is well known that large earthquakes often exhibit significant rupture complexity such as well separated subevents. With improved recording and data processing techniques, small earthquakes have been found to exhibit rupture complexity as well. Studying these small earthquakes offers the opportunity to better understand the possible causes of rupture complexities. Specifically, if they are random or are related to fault properties. We examine microearthquakes (M < 3) in the Parkfield, California, area that are recorded by a high-resolution borehole network. We quantify earthquake complexity by the deviation of source time functions and source spectra from simple circular (omega-square) source models. We establish thresholds to declare complexity, and find that it can be detected in earthquakes larger than magnitude 2, with the best resolution above M2.5. Comparison between the two approaches reveals good agreement (>90 per cent), implying both methods are characterizing the same source complexity. For the two methods, 60–80 per cent (M 2.6–3) of the resolved events are complex depending on the method. The complex events we observe tend to cluster in areas of previously identified structural complexity; a larger fraction of the earthquakes exhibit complexity in the days following the M w 6 2004 Parkfield earthquake. Ignoring the complexity of these small events can introduce artefacts or add uncertainty to stress drop measurements. Focusing only on simple events however could lead to systematic bias, scaling artefacts and the lack of measurements of stress in structurally complex regions.

58 GEOSCIENCES↗
DOE OSTI2020

Machine learning analysis of perovskite oxides grown by molecular beam epitaxy

Reflection high-energy electron diffraction (RHEED) is a ubiquitous in situ molecular beam epitaxial (MBE) characterization tool. Although RHEED can be a powerful means for crystal surface structure determination, it is often used as a static qualitative surface characterization method at discrete intervals during a growth. A full analysis of RHEED data collected during the entirety of MBE growths is made possible using principle component analysis (PCA) and $\textit{k}$-means clustering to examine significant boundaries that occur in the temporal clusters grouped from RHEED data and identify statistically significant patterns. This process is applied to data from homoepitaxial SrTiO 3 growths, heteroepitaxial SrTiO 3 grown on scandate substrates, BaSnO 3 films grown on SrTiO 3 substrates, and LaNiO 3 films grown on SrTiO 3 substrates. We report this analysis may provide additional insights into the surface evolution and transitions in growth modes at precise times and depths during growth, and that video archival of an entire RHEED image sequence may be able to provide more insight and control overgrowth processes and film quality.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Q-BEEP: Quantum Bayesian Error Mitigation Employing Poisson Modeling over the Hamming Spectrum

Quantum computing technology has grown rapidly in recent years, with new technologies being explored, error rates being reduced, and quantum processor’s qubit capacity growing. However, near-term quantum algorithms are still unable to be induced without compounding consequential levels of noise, leading to non-trivial erroneous results. Quantum Error Correction (in-situ error mitigation) and Quantum Error Mitigation (post-induction error mitigation) are promising fields of research within the quantum algorithm scene, aiming to alleviate quantum errors, increasing the overall fidelity and hence the overall quality of circuit induction. Earlier this year, a pioneering work, namely HAMMER, published in ASPLOS-22 demonstrated the existence of a latent structure regarding post-circuit induction errors when mapping to the Hamming spectrum. However, they intuitively assumed that errors occur in local clusters, and that at higher average Hamming distances this structure falls away. In this work, we show that such a correlation structure is not only local but extends certain non-local clustering patterns which can be precisely described by a Poisson distribution model taking the input circuit, the device run time status (i.e., calibration statistics) and qubit topology into consideration. Using this quantum error characterizing model, we developed an iterative algorithm over the generated Bayesian network state-graph for post-induction error mitigation. Thanks to more precise modeling of the error distribution latent structure and the new iterative method, our Q-Beep approach provides state of the art performance and can boost circuit execution fidelity by up to 234.6% on Bernstein-Vazirani circuits and on average 71.0% on QAOA solution quality, using 16 practical IBMQ quantum processors. For other benchmarks such as those in QASMBench, the fidelity improvement is up to 17.8%. Q-Beep is a light-weight post-processing technique that can be performed offline and remotely, making it a useful tool for quantum vendors to integrate and provide more reliable circuit induction results.

Stein, Samuel A.↗
DOE OSTI2022

Fusion Blanket and Fuel Cycle Research at PNNL: FY22 Year-end Report

During the reporting period, research at PNNL focused on two tasks within the DOE Fusion Blanket and Fuel Cycle Program. Research on Task 1, Tritium Extraction from Pb-Li and He Using a Vacuum Permeator, focused on atomistic modeling to better understand tritium transport in Pd-coated V vacuum permeators. As a lower cost alternative to Pd permeators, thin coatings of Pd (or other noble metals) can be deposited over a substrate like V. However, the permeation performance of composite metal membranes degrades over time, due to the formation of intermetallics at the coating-substrate interface. Computational studies were performed to better understand tritium transport through these Pd-V intermetallics. The results of the FY22 Pd-V modeling study were recently submitted for publication in Computational Materials Science and presented at the Technology of Fusion Energy conference. Future work in this area will focus on interdiffusion barriers to prevent intermetallic formation that is deleterious to tritium transport. There are opportunities for collaboration with researchers at the Colorado School of Mines, who are manufacturing and testing candidate interdiffusion barriers. Research on Task 3, Solid Breeder Materials, included ion irradiation and post-irradiation characterization of lithium orthosilicate (Li 4 SiO 4 ) and lithium metasilicate (Li 2 SiO 3 ) to improve fundamental understanding of irradiation effects, in combination with atomistic modeling focused on the energetics of He clustering in these two ceramic phases. The results of the study suggested that the Li 4 SiO 4 phase, which is more desirable as a solid breeder due to its higher Li density, was amorphized during ion irradiation while the Li 2 SiO 3 phase appeared to be more resistant to irradiation damage. It is possible that Li loss contributed to the poor irradiation performance of the Li 4 SiO 4 , and some thoughts are provided regarding coatings that could be applied to solid breeders like this to prevent Li loss at elevated temperature while not hindering tritium diffusion. The results of the FY22 ion irradiation study were recently submitted for publication in Journal of Nuclear Materials and presented at the 22nd International Conference on Ion Beam Modification of Materials. Future work in this area will focus on Li-rich ceramics such as Li 5 AlO 4 and Li 8 ZrO 6 that have high Li density and should provide rapid tritium release based on previous work with less Li-rich ceramics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Vacancy-mediated transport and segregation tendencies of solutes in FCC Ni under diffusional creep

Nickel-based alloys are known for their excellent corrosion resistance and high-temperature strength. However, at high temperatures, polycrystals experience grain boundary-stress-driven vacancy diffusion leading to diffusion-driven creep. Understanding the fundamentals of defect migration is essential to predict diffusion creep behavior. In this talk, we explore the Nabarro-Herring diffusion creep and the associated solute segregation that is likely to result from the different diffusivities of the solute and solvent elements. Density functional theory calculations are performed to determine the formation, migration and binding energies of the solute and vacancy defects in stress-free and stressed states. The dilute-limit transport coefficients are then calculated using the self-consistent mean field theory as implemented in the Kinetic Cluster Expansion (KineCluE) code. Predictions of diffusion creep strain rates and solute segregation are then presented for various solutes, stress and temperatures. This work opens research avenues for exploration of diffusion creep via characterization of elemental segregation to grain boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Gamma radiation-induced defects in KCl, MgCl 2 , and ZnCl 2 salts at room temperature

Room temperature post-irradiation measurements of diffuse reflectance and electron paramagnetic resonance spectroscopies were made to characterize the long-lived radiation-induced species formed from the gamma irradiation of solid KCl, MgCl 2 , and ZnCl 2 salts up to 100 kGy. The method used showed results consistent with those reported for electron and gamma irradiation of KCl in single crystals. Thermal bleaching of irradiated KCl demonstrated accelerated disaggregation of defect clusters above 400 K, due to decomposition of Cl 3 - . The defects formed in irradiated MgCl 2 comprised a mixture of Cl 3 - , F-centers, and Mg + associated as M-centers. Further, Mg metal cluster formation was also observed at 100 kGy, in addition to accelerated destruction of F-centers above 20 kGy. Irradiated ZnCl 2 afforded the formation of Cl 2 - due to its high ionization potential and crystalline structure, which decreases recombination. The presence of aggregates in all cases indicates the high diffusion of radicals and the predominance of secondary processes at 295 K. Additionally, thermal bleaching studies showed that chloride aggregates’ stability increases with the ionization potential of the cation present. The characterization of long-lived radiolytic transients of pure salts provides important information for the understanding of complex salt mixtures under the action of gamma radiation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Characterizing Spatial and Temporal Variability of California’s Coastal Upwelling Using a Satellite-Derived CUTI Index

Ocean upwelling off California is a wind-driven coastal process with complex interactions between spatial wind patterns and sea surface temperatures. Large-scale spatial and temporal upwelling characterizations are traditionally based on numerical models, while quantifying upwelling with direct observations is not straightforward. To complement model-based upwelling characterizations, here we use satellite estimates of winds, sea surface temperatures, and ocean currents along the California coast to calculate the coastal upwelling transport index (CUTI), originally calculated from a numerical ocean model. The CUTI framework accounts for both Ekman and geostrophic offshore-directed ocean transport, the latter of which is often neglected in satellite-based upwelling assessments. The approach yields the CUTI over a 30-yr period at a daily temporal and 0.25° spatial resolution to analyze upwelling patterns, with focus on potential Morro Bay and Humboldt wind energy areas. Morro Bay (CUTI median of 0.63 m 2 s −1 ) exhibits stronger, more consistent upwelling throughout the year, whereas Humboldt (CUTI median of 0.45 m 2 s −1 ) exhibits a pronounced seasonal cycle with strongest upwelling in the summer and occasional downwelling in winter. The cluster analysis of 1993–2022 satellite maps of CUTI identifies four characteristic spatial upwelling patterns along the coast, corresponding to distinct spatial distributions of sea surface temperature anomalies, Ekman transport, and geostrophic ocean water transport. This dataset provides an observation-based foundation for characterizing natural coastal upwelling off the California coast, showing good agreement with the original model CUTI while being based on satellite data and offering increased spatial resolution.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Genesis of Active Pt/CeO 2 Catalyst for Dry Reforming of Methane by Reduction and Aggregation of Isolated Platinum Atoms into Clusters

Atomically dispersed metal catalysts offer the advantages of efficient metal utilization and high selectivities for reactions of technological importance. Such catalysts have been suggested to be strong candidates for dry reforming of methane (DRM), offering prospects of high selectivity for synthesis gas without coke formation, which requires ensembles of metal sites and is a challenge to overcome in DRM catalysis. However, investigations of the structures of isolated metal sites on metal oxide supports under DRM conditions are lacking, and the catalytically active sites remain undetermined. Data characterizing the DRM reaction-driven structural evolution of a cerium oxide- supported catalyst, initially incorporating atomically dispersed platinum, and the corresponding changes in catalyst performance are reported. X-ray absorption and infrared spectra show that the reduction and agglomeration of isolated cationic platinum atoms to form small platinum clusters/nanoparticles are necessary for DRM activity. Density functional theory calculations of the energy barriers for methane dissociation on atomically dispersed platinum and on platinum clusters support these observations. Here the results emphasize the need for in-operando experiments to assess the active sites in such catalysts. The inferences about the catalytically active species are suggested to pertain to a broad class of catalytic conversions involving the rate-limiting dissociation of light alkanes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Kinetics and Reaction Mechanisms of Acetic Acid Hydrodeoxygenation over Pt and Pt–Mo Catalysts

In this work, kinetic measurements for silica-supported Pt and Pt-Mo catalysts were collected in vapor-phase acetic acid hydrodeoxygenation by varying the hydrogen partial pressure between 18 and 72 kPa and acetic acid partial pressure between 7 and 18 kPa at 423-473 K. At all testing conditions, the Pt-Mo catalyst was more active and selective. In addition, the apparent activation energy for Pt-Mo of 76±3 kJ/mol was lower than that of 84±4 kJ/mol for Pt. The apparent reaction orders were also different. The order in hydrogen of 0.8±0.1 for Pt-Mo changed to zero at higher hydrogen partial pressures while that for Pt remained constant at 0.6±0.1. A near-zero order in acetic acid for Pt-Mo changed to -2.1 at higher acetic acid pressures while that for Pt remained constant at -2.9±0.3. These differences in reaction kinetics as well as in selectivity trends with changes in temperature and feed composition indicated a change in the reaction mechanism for Pt-Mo. The catalysts were characterized with hydrogen temperature programmed desorption, oxygen temperature programmed oxidation and transmission electron microscopy with energy-dispersed X-ray spectroscopy elemental mapping. Mo was present in the form of subnanometer-size clusters on the surface of Pt nanoparticles. Both Pt and Pt-Mo catalysts were stable under the reaction conditions for 10 h, and the size and structure of Pt and Pt-Mo particles remained mostly unchanged, without coke accumulation. Density functional theory calculations show that surface acetate is not a major reaction intermediate on both Pt and Pt-Mo and, instead, C-OH bond splitting with the formation of acetyl is the first reaction step in hydrodeoxygenation. The activation energy for this step is dramatically lower on Pt-Mo. Furthermore, the activity of acetyl on Pt-Mo is different. Unlike on pure Pt, the reaction of C-O bond splitting becomes exothermic with a lower activation energy on Pt-Mo, and the reaction of C-C bond splitting, in contrast, becomes endothermic with a higher activation energy, explaining the experimentally observed higher activities and selectivities of Pt-Mo. In addition, the calculations demonstrate that a pair of Pt-Mo surface atoms acts as a single active site where Mo serves as a preferential binding anchor for O atoms. The presence of Mo atoms changes the structure and energy of adsorbed and reacting surface species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Understanding the chemical contribution to the enhancement mechanism in SERS: Connection with Hammett parameters

The enhancement mechanism due to the molecule-surface chemical interaction in surface-enhanced Raman scattering (SERS) has been characterized using a theoretical approach based on time dependent density functional theory. This includes a systematic study of the chemical mechanism (CM) to the SERS enhancement for halogen substituted benzenethiols interacting with a silver cluster. Changing the halogen on benzenethiol enables us to systematically modulate interactions between the benzenethiol ring and the metal cluster. We observe a decrease in the CM enhancement factor with an increase in atomic number of the halogen for para- substitutions. For meta- substitutions, there is no such trend. However, the results scale linearly with the Hammett parameters for both meta and para halogens, which provides an important predictive tool for interpreting chemical enhancements. We also study the effect of solvation on the CM, showing that there is a systematic increase in enhancement with increasing solvent dielectric constant. As a result, the correlation of CM with other properties, such as the amount of charge transfer between adsorbate and metal, or the excitation energies of charge transfer states, is much less predictive than the Hammett parameter correlation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The impact of tomographic redshift bin width errors on cosmological probes

ABSTRACT Systematic errors in the galaxy redshift distribution n(z) can propagate to systematic errors in the derived cosmology. We characterize how the degenerate effects in tomographic bin widths and galaxy bias impart systematic errors on cosmology inference using observational data from the Deep Lens Survey. For this we use a combination of galaxy clustering and galaxy–galaxy lensing. We present two end-to-end analyses from the catalogue level to parameter estimation. We produce an initial cosmological inference using fiducial tomographic redshift bins derived from photometric redshifts, then compare this with a result where the redshift bins are empirically corrected using a set of spectroscopic redshifts. We find that the derived parameter S8 ≡ σ8(Ωm/.3)1/2 decreases from $0.841^{+0.062}_{-0.061}$ to $0.781^{0.061}_{0.054}$ upon correcting the n(z) errors in the second method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Novel Technique for Developing Linearized Convex System Models from Experimentally Derived Data

This paper presents a novel technique for generating a convex system model from an experimentally derived data set which features variance among repeated measurements. The convex system model developed as a test case characterizes the dynamic system losses of a vanadium redox flow battery as a function of the active power output and the battery state of charge. The technique hinges on a pre-cleaning via clustering procedure which precedes the formation of a planar convex hull comprised of triangular simplices. The clustering procedure efficiently reduces the experimental data set while mitigating variance among repeated measurements and removes outliers. Ultimately, the lower evelope of the planar convex hull serves as the desired convex system model. The proposed technique reduces systematic model error which is otherwise present when directly developing a planar convex hull model based on an unreduced data set.

24 POWER TRANSMISSION AND DISTRIBUTION↗