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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Effect of trace amounts of added Sc on microstructure and mechanical properties of 2055 aluminum alloy

Highlights: • Effect of trace Sc on microstructure and mechanical properties in 2055 Al-alloy was investigated. • T{sub 1} is the main strengthening phase in Sc free and Sc added 2055 alloy at the aging temperature of 175°C and 200°C. • The refinement of T{sub 1} by Sc addition depends on the aging temperature. • Mechanical properties were deteriorated by Sc at the aging temperature of 175°C and improved at 200°C aging treatment. - Abstract: The effects of Sc additions and isothermal aging on the microstructure and mechanical properties of 2055 aluminum alloy have been investigated. The isothermal aging temperatures investigated were 175 °C and 200 °C. Results show that the aging temperature does not affect the type of precipitates in both Sc-free and Sc-added 2055 Al alloys. While remarkable changes in the size and number density of T{sub 1} (Al{sub 2}CuLi) precipitates have been observed. For samples aged at 175 °C for 8 h, the average length of T{sub 1} precipitates was increased from 39.9 nm to 45.6 nm, the number density decreased from 5.77 × 10{sup 22} m{sup −3} to 3.68 × 10{sup 22} m{sup −3} after Sc addition. On the contrary, when samples were aged at 200 °C for 8 h, the length decreased from 59.89 nm to 43.32 nm and number density increased from 2.13 × 10{sup 22} m{sup −3} to 3.00 × 10{sup 22} m{sup −3} by adding trace Sc. Slight deterioration of tensile strength and yield strength with higher ductility was founded at the aging temperature of 175 °C for 8 h due to the larger size and lower number density of T{sub 1} precipitates along with the formation of a W (AlCuSc) phase during the casting or homogenization processes. When aging temperature increased to 200 °C, tensile strength and yield strength were significantly improved by Sc addition without losing ductility. Highly dense fine T{sub 1} precipitates take responsible for the strength improvement, and to some extent it compensated the strength loss caused by the formation of W phase. A “vacancy-prison” mechanism was adopted to explain the effect of Sc additions on the precipitation of T{sub 1} phase as a function of aging temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nth-plant supply: corn stover supplies and costs in a fleet of biorefineries

Feedstock cost and cost variability is expected to increase with the number of biorefineries. To quantify this effect, this spatial-economic analysis simulates feedstock cost and cost variability of an industry based on corn stover as a function of the number of biorefineries. Results are reported for nine scenarios (a base case and sensitivity analysis of four variables – harvest efficiency, sustainability constraints, opportunity cost, and corn grain yield) under deterministic and stochastic simulations, assuming biorefineries using 658 000 Mg (725 000 tons) year- 1 of corn stover in 2019. The resulting supply curves are highly elastic (i.e. little change in cost) for the first 50 of the 121 biorefineries, with price increases in subsequent biorefineries depending on scenario. In the base-case deterministic scenario, weighted-average stover costs are $66 Mg -1 ($60 ton- 1 ), $69 Mg -1 ($62 ton -1 ), and $156 Mg -1 ($142 ton -1 ), at the first, 60th, and 121st biorefineries, respectively. The stochastic simulations, subject to observed 30-year corn yield variability, follow a similar pattern, with price distributions that vary by scenario. The base-case stochastic simulations illustrate minimal cost variability for the first 60 biorefineries, but rapid increases in cost variability in the second half of potential biorefineries, with similar patterns observed in the other scenarios. Of the four variables explored, price was most sensitive to harvest efficiency, followed by sustainability constraints, corn yield, and opportunity cost. Results suggest that, under conventional logistics, about half of the US corn stover resource is reliably available with minimum cost increase and variability. Interactive visualization is available at https://doi.org/10.11578/1828779.

09 BIOMASS FUELS↗
DOE OSTI2022

Insights into Methodologies and Operational Details of Resource Adequacy Assessment: A Case Study with Application to a Broader Flexibility Framework

Assessing and maintaining resource adequacy (RA) is a core pillar of power systems. However, recent changes in the physical makeup of these systems and the conditions under which these systems must operate have yielded a renewed interest in the methods, metrics, and assumptions that underpin RA assessments. In this paper, we systematically explore a wide range of RA modeling dimensions, including: the objective function and level of operational detail in the underlying model formulation; the quantity (look-ahead) and quality (accuracy) of data that is available for making operational decisions within those models; and the physical configuration of solar photovoltaics (PV) with battery storage hybrid resources. We apply a set of probabilistic RA tools and production cost modeling tools to a realistic test system based loosely on a future Electric Reliability Council of Texas power system dominated by solar PV resources. Under the assumptions of our system and models, we find that multi-stage probabilistic assessments may provide a more robust evaluation of RA by capturing a wider range of operational and system interactions, but this comes at a computational cost of 1-2 orders of magnitude longer run time depending on the specific configuration. In addition, the information on thermal generator availability impacts RA performance by an order of magnitude more than solar resource forecasts, which is driven by the comparatively larger magnitude of thermal outages than solar forecast errors within our test system. Lastly, the flexibility provided by hybrid and other resources can help reduce system load-shedding event frequencies and enable the system to be more robust to inaccurate forecast information, and alternative hybrid inverter sizes can impact RA levels by 1-2 orders of magnitude. Our results point to the importance of a broader flexibility framework to describe the interaction between (1) flexibility "supply" from both physical resource capabilities and operational constraints considered in the modeling, and (2) flexibility "demand" from forecast errors, thermal generator outages, and other sources of uncertainty, as well as their RA impacts. Results are likely sensitive to the system buildout explored; future work could consider additional system configurations and conditions.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2023

Ab initio study of tungsten-based alloys under fusion power-plant conditions

Tungsten (W) is considered a leading candidate for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield, and low long-term disposal radioactive footprint. However, tungsten also presents a very low fracture toughness, primarily associated with intergranular failure and bulk plasticity, limiting its applications. In recent years, several families of tungsten-based alloys have been explored to overcome the aforementioned limitations of pure tungsten. These include tungsten-based high-entropy alloys (W-HEAs) and tungsten-based Self-passivating Metal Alloys with Reduced Thermo-oxidation or “SMART alloys” (W-SAs). Given their proximity to the plasma, it is crucial to understand how the exposure of these candidate plasma-facing materials (PFMs) to the neutron fluxes expected in fusion reactors impacts their material behavior over time. In this work, we present a computational approach that combines inventory codes and first-principles DFT electronic structure calculations to understand the behavior of transmuting tungsten-based PFMs. In particular, we calculate the changes in the chemical composition, production uncertainties, the elastic and ductility properties, and the density of states for five tungsten-based PFMs when exposed to EU-DEMO fusion first wall conditions for ten years.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Side Chain Regioisomers that Dictate Optical Properties and Mechanofluorochromism through Crystal Packing

Designing strong interactions into $π$-conjugated materials can direct their typically uncontrolled molecular packing and is an important strategy toward tuning their technologically relevant properties in the solid state. In this paper we demonstrate unconventional control over solid-state fluorescence and mechanofluorochromism (MFC) through regiochemical substitutions in side chains of 12 three-ring phenylene ethynylenes (PEs) that employ fluoroarene–arene (ArF–ArH) interactions between tetrafluoro ArF pendants and PE main chains to direct crystal packing, with single-atom variations of the lone proton in ArF pendants between 4-hydro, 5-hydro, and 6-hydro substitution yielding in two cases dramatically different fluorescence and MFC behavior. X-ray crystal structures reveal key intermolecular interactions of ArF rings, including their lone protons, which vary as a function of substitution pattern and contribute to optical properties in solids. Rarely reported, particularly with such dramatic results, this systematic study on regiochemical effects over solid-state properties demonstrates the versatility of using discrete, directional interactions of side chains for noncovalent control in conjugated materials.

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

A First-Principles Study of Hydrogen Diffusivity and Dissociation on δ-Pu (100) and (111) Surfaces

The diffusivity and chemical reactivity of hydrogen on the δ-Pu (100) and (111) surfaces has been studied with density functional theory using both spin-polarization and spin–orbit coupling calculations. Comparison of the total electronic density of states and atomic hydrogen diffusion energies indicates that spin-polarization yields accurate results, with spin–orbit coupling yielding slightly smaller barriers to hopping between adsorption sites. On the (100) surface, both sets of calculations indicate that the dissociation reaction for molecular hydrogen is highly active at ambient conditions and results in the hydrogen ions bonded within the Pu surface, similar to hydride formation. In contrast, calculations on the (111) surface indicate a lower barrier for dissociation without the formation of the hydride-like end product. Our results help quantify the effect of spin–orbit coupling on hydrogen surface chemistry on δ-Pu. Additionally, we observe that the degree of resulting corrosion could depend on the specific geometry of the plutonium surface, which could have ramifications for future engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Machine-Learning Methods Enable Exhaustive Searches for Active Bimetallic Facets and Reveal Active Site Motifs for CO 2 Reduction

Bimetallic catalysts are promising for the most difficult thermal and electrochemical reactions, but modeling the many diverse active sites on polycrystalline samples is an open challenge. Here, we present a general framework for addressing this complexity in a systematic and predictive fashion. Active sites for every stable low-index facet of a bimetallic crystal are enumerated and cataloged, yielding hundreds of possible active sites. The activity of these sites is explored in parallel using a neural-network-based surrogate model to share information between the many density functional theory (DFT) relaxations, resulting in activity estimates with an order of magnitude fewer explicit DFT calculations. Sites with interesting activity were found and provide targets for follow-up calculations. This process was applied to the electrochemical reduction of CO 2 on nickel gallium bimetallics and indicated that most facets had similar activity to Ni surfaces, but a few exposed Ni sites with a very favorable on-top CO configuration. This motif emerged naturally from the predictive modeling and represents a class of intermetallic CO 2 reduction catalysts. These sites rationalize recent experimental reports of nickel gallium activity and why previous materials screens missed this exciting material. Most importantly these methods suggest that bimetallic catalysts will be discovered by studying facet reactivity and diversity of active sites more systematically.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Catalytic chemoselective functionalization of methane in a metal-organic framework

Methane constitutes the largest fraction of natural gas reserves and is a low-cost abundant starting material for the synthesis of value-added chemicals and fuel. Selective catalytic functionalization of methane remains a vital goal in the chemical sciences due to its low intrinsic reactivity. Borylation has recently emerged as a promising route for the catalytic functionalization of methane. A major challenge in this regard is selective borylation towards the monoborylated product that is more active than methane and can easily lead to over-functionalization. Herein, we report a highly selective microporous metal-organic framework- supported iridium(III) catalyst for methane borylation that exhibits a chemoselectivity of > 99% (mono versus bis at 19.5% yield; turnover number = 67) for monoborylated methane, with bis(pinacolborane) as the borylation reagent in dodecane, at 150 °C and 34 atm of methane, employing as little as 1.8 wt% of iridium. The preference for the monoborylated product is ascribed to the shape-selective effect of the metal-organic framework pore structures.

Zhang, Xuan (ORCID:0000000182147265)↗
DOE OSTI2023

A coarse-grained simulation model for colloidal self-assembly via explicit mobile binders

Colloidal particles with mobile binding molecules constitute a powerful platform for probing the physics of self-assembly. Binding molecules are free to diffuse and rearrange on the surface, giving rise to spontaneous control over the number of droplet–droplet bonds, i.e., valence, as a function of the concentration of binders. This type of valence control has been realized experimentally by tuning the interaction strength between DNA-coated emulsion droplets. Optimizing for valence two yields droplet polymer chains, termed ‘colloidomers’, which have recently been used to probe the physics of folding. To understand the underlying self-assembly mechanisms, here we present a coarse-grained molecular dynamics (CGMD) model to study the self-assembly of this class of systems using explicit representations of mobile binding sites. Further, we explore how valence of assembled structures can be tuned through kinetic control in the strong binding limit. More specifically, we optimize experimental control parameters to obtain the highest yield of long linear colloidomer chains. Subsequently tuning the dynamics of binding and unbinding via a temperature-dependent model allows us to observe a heptamer chain collapse into all possible rigid structures, in good agreement with recent folding experiments. Our CGMD platform and dynamic bonding model (implemented as an open-source custom plugin to HOOMD-Blue) reveal the molecular features governing the binding patch size and valence control, and opens the study of pathways in colloidomer folding. This model can therefore guide programmable design in experiments.

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

Optimizing dicyandiamide pretreatment conditions for enhanced structure and electronic properties of polymeric graphitic carbon nitride

Graphitic carbon nitride, a polymeric semiconductor, possesses a distinctive electronic band structure and exceptional chemical stability, making it a highly promising material for various catalytic applications such as electrocatalysis, photocatalysis, and photo-electrocatalysis. However, its practical applications remain limited due to its low active site density and poor electrical conductivity. In this study, to overcome such limitations, we have conducted a thorough investigation to explore the impact of dicyandiamide (DCDA) precursor pretreatment prior to thermal polymerization to graphitic carbon nitride. The DCDA precursor was subjected to various pretreatment methods including grinding using mortar and pestle, recrystallization through stirring or probe sonication after dissolving in deionized water, and freeze drying, prior to thermal polymerization at 550 °C for 2 hours. The structural and morphological properties of the catalysts prepared were compared and characterized by X-ray diffraction (XRD), attenuated total reflectance–Fourier transform infrared (ATR-IR) spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS) analysis while the electronic band gap properties were determined based on density functional theory (DFT) calculations for a set of crystalline systems having C/N ratios similar to those identified experimentally. In comparison to direct thermal polymerization, pretreated samples rendered the same product yield, diverse morphologies with flat or wrinkle structures, and reduced electrochemical resistance, making them suitable for use in various catalytic processes.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Spontaneous driving forces give rise to protein-RNA condensates with coexisting phases and complex material properties

Phase separation of multivalent protein and RNA molecules underlies the biogenesis of biomolecular condensates such as membraneless organelles. In vivo, these condensates encompass hundreds of distinct types of molecules that typically organize into multilayered structures supporting the differential partitioning of molecules into distinct regions with distinct material properties. The interplay between driven (active) versus spontaneous (passive) processes that are required for enabling the formation of condensates with coexisting layers of distinct material properties remains unclear. Here, we deploy systematic experiments and simulations based on coarse-grained models to show that the collective interactions among the simplest, biologically relevant proteins and archetypal RNA molecules are sufficient for driving the spontaneous emergence of multilayered condensates with distinct material properties. These studies yield a set of rules regarding homotypic and heterotypic interactions that are likely to be relevant for understanding the interplay between active and passive processes that control the formation of functional biomolecular condensates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Targeted modulation of pennycress lipid droplet proteins impacts droplet morphology and seed oil content

SUMMARY Lipid droplets (LDs) are unusual organelles that have a phospholipid monolayer surface and a hydrophobic matrix. In oilseeds, this matrix is nearly always composed of triacylglycerols (TGs) for efficient storage of carbon and energy. Various proteins play a role in their assembly, stability and turnover, and even though the major structural oleosin proteins in seed LDs have been known for decades, the factors influencing LD formation and dynamics are still being uncovered mostly in the “model oilseed” Arabidopsis. Here we identified several key LD biogenesis proteins in the seeds of pennycress, a potential biofuel crop, that were correlated previously with seed oil content and characterized here for their participation in LD formation in transient expression assays and stable transgenics. One pennycress protein, the lipid droplet associated protein‐interacting protein (LDIP), was able to functionally complement the Arabidopsis ldip mutant, emphasizing the close conservation of lipid storage among these two Brassicas. Moreover, loss‐of‐function ldip mutants in pennycress exhibited increased seed oil content without compromising plant growth, raising the possibility that LDIP or other LD biogenesis factors may be suitable targets for improving yields in oilseed crops more broadly.

Guzha, Athanas↗
DOE OSTI2026

Juvenile Salmon and Their Habitats in the Columbia River Estuary: A Review and Synthesis of Knowledge Development 2000–2025

[This is a 90% discussion draft.] This is the third Synthesis Memorandum funded by the U.S. Army Corps of Engineers and developed for the Columbia Estuary Ecosystem Restoration Program (CEERP) on the topic of habitat restoration in the Columbia River Estuary (CRE) from Bonneville Dam to the river mouth. While the first two were developed by PNNL and NOAA without the benefit of stakeholder participation, for the current memo, two key activities were initiated: (1) review, by the Expert Regional Technical Group (ERTG), of status and trends monitoring and action effectiveness monitoring funded by CEERP, and (2) a workshop including representatives of the Bonneville Power Administration and the U.S. Army Corps of Engineers (the action agencies [AAs]), the National Oceanic and Atmospheric Administration (NOAA), major research agencies contributing to CEERP, and sponsors who implement CEERP restoration actions. A systematic literature review was conducted using ClarivateTM Web of ScienceTM database. The topics of interest for CRE relevant research included salmon ecology, physical processes, and wetland habitats, and therefore required the use of broad search terms. Our final search criteria included a combination of Boolean operators and an approach to combine different sets of search terms. The final search result yielded 669 records. The records were classified by groups and assigned to the relevant disciplinary expert for review. The review identified substantive advances in understanding the provision of salmon habitat functions through spatiotemporally dynamic physical and ecological processes, and the use of CRE habitats by numerous stocks of juvenile salmon. It also uncovered heretofore unincorporated historical documentation of riparian habitats across the CRE. The characterization of the structural components of floodplain habitat including plant associations and channel networks has advanced considerably, together with the understanding of seasonal changes and long-term trends. The relative influence of salmon-habitat location in the CRE as compared with temporal factors, mainly season, has been well described, which affects the prioritization of restoration. Stressors on the ecosystem and fish, and the drivers of these stressors, have been more carefully elucidated and predictive models are in various stages of development. The vision, aims, and design of restoration projects have advanced together with methods of data collection, analysis, and modeling that have seen substantial improvements. Experiments intended to inform the design of restoration projects are underway or have been completed. An important outstanding area of research that has lagged behind the advances in fundamental understanding of the ecosystem and salmon habitat functions remains the peer-reviewed documentation of the outcomes of restoration for both habitats and fish functions.

estuary↗
DOE OSTI2016

Return to [log-]normalcy: rethinking quenching, the star formation main sequence, and perhaps much more

Knowledge of galaxy evolution rests on cross-sectional observations of different objects at different times. Understanding of galaxy evolution rests on longitudinal interpretations of how these data relate to individual objects moving through time. The connection between the two is often assumed to be clear, but we use a simple “physics-free” model to show that it is not and that exploring its nuances can yield new insights. Comprising nothing more than 2094 loosely constrained lognormal star formation histories (SFHs), the model faithfully reproduces the following data it was not designed to match: stellar mass functions at z⩽8; the slope of the star formation rate/stellar mass relation (the SFR “Main Sequence”) at z⩽6; the mean sSFR(≡SFR/M{sub ∗}) of low-mass galaxies at z⩽7; “fast-” and “slow-track” quenching; downsizing; and a correlation between formation timescale and sSFR(M{sub ∗},t) similar to results from simulations that provides a natural connection to bulge growth. We take these findings—which suggest that quenching is the natural downturn of all SFHs affecting galaxies at rates/times correlated with their densities—to mean that: (1) models in which galaxies are diversified on Hubble timescales by something like initial conditions rival the dominant grow-and-quench framework as good descriptions of the data; or (2) absent spatial information, many metrics of galaxy evolution are too undiscriminating—if not inherently misleading—to confirm a unique explanation. We outline future tests of our model but stress that, even if ultimately incorrect, it illustrates how exploring different paradigms can aid learning and, we hope, more detailed modeling efforts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The Extended Northern ROSAT Galaxy Cluster Survey (NORAS II). I. Survey Construction and First Results

As the largest, clearly defined building blocks of our universe, galaxy clusters are interesting astrophysical laboratories and important probes for cosmology. X-ray surveys for galaxy clusters provide one of the best ways to characterize the population of galaxy clusters. We provide a description of the construction of the NORAS II galaxy cluster survey based on X-ray data from the northern part of the ROSAT All-Sky Survey. NORAS II extends the NORAS survey down to a flux limit of 1.8 × 10{sup −12} erg s{sup −1} cm{sup −2} (0.1–2.4 keV), increasing the sample size by about a factor of two. The NORAS II cluster survey now reaches the same quality and depth as its counterpart, the southern REFLEX II survey, allowing us to combine the two complementary surveys. The paper provides information on the determination of the cluster X-ray parameters, the identification process of the X-ray sources, the statistics of the survey, and the construction of the survey selection function, which we provide in numerical format. Currently NORAS II contains 860 clusters with a median redshift of z = 0.102. We provide a number of statistical functions, including the log N –log S and the X-ray luminosity function and compare these to the results from the complementary REFLEX II survey. Using the NORAS II sample to constrain the cosmological parameters, σ {sub 8} and Ω{sub m}, yields results perfectly consistent with those of REFLEX II. Overall, the results show that the two hemisphere samples, NORAS II and REFLEX II, can be combined without problems into an all-sky sample, just excluding the zone of avoidance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Data‐driven variational method for discrepancy modeling: Dynamics with small‐strain nonlinear elasticity and viscoelasticity

Abstract The effective inclusion of a priori knowledge when embedding known data in physics‐based models of dynamical systems can ensure that the reconstructed model respects physical principles, while simultaneously improving the accuracy of the solution in the previously unseen regions of state space. This paper presents a physics‐constrained data‐driven discrepancy modeling method that variationally embeds known data in the modeling framework. The hierarchical structure of the method yields fine scale variational equations that facilitate the derivation of residuals which are comprised of the first‐principles theory and sensor‐based data from the dynamical system. The embedding of the sensor data via residual terms leads to discrepancy‐informed closure models that yield a method which is driven not only by boundary and initial conditions, but also by measurements that are taken at only a few observation points in the target system. Specifically, the data‐embedding term serves as residual‐based least‐squares loss function, thus retaining variational consistency. Another important relation arises from the interpretation of the stabilization tensor as a kernel function, thereby incorporating a priori knowledge of the problem and adding computational intelligence to the modeling framework. Numerical test cases show that when known data is taken into account, the data driven variational (DDV) method can correctly predict the system response in the presence of several types of discrepancies. Specifically, the damped solution and correct energy time histories are recovered by including known data in the undamped situation. Morlet wavelet analyses reveal that the surrogate problem with embedded data recovers the fundamental frequency band of the target system. The enhanced stability and accuracy of the DDV method is manifested via reconstructed displacement and velocity fields that yield time histories of strain and kinetic energies which match the target systems. The proposed DDV method also serves as a procedure for restoring eigenvalues and eigenvectors of a deficient dynamical system when known data is taken into account, as shown in the numerical test cases presented here.

Masud, Arif↗
DOE OSTI2018

Structural and Electrochemical Characteristics of Ca-Doped “Flower-like” Li 4 Ti 5 O 12 Motifs as High-Rate Anode Materials for Lithium-Ion Batteries

Doped motifs offer an intriguing structural pathway toward improving conductivity for battery applications. Specifically, Ca-doped, three-dimensional “flower-like” Li 4–x Ca x Ti 5 O 12 (“x” = 0, 0.1, 0.15, and 0.2) micrometer-scale spheres have been successfully prepared for the first time using a simple and reproducible hydrothermal reaction followed by a short calcination process. The products were experimentally characterized by means of X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) mapping, inductively coupled plasma optical emission spectrometry (ICP-OES), X-ray photoelectron spectroscopy (XPS), cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and galvanostatic charge–discharge testing. Calcium dopant ions were shown to be uniformly distributed within the LTO structure without altering the underlying “flower-like” morphology. The largest lattice expansion and the highest Ti 3+ ratios were noted with XRD and XPS, respectively, whereas increased charge transfer conductivity and decreased Li + -ion diffusion coefficients were displayed in EIS for the Li 4–x Ca x Ti 5 O 12 (“x” = 0.2) sample. The “x” = 0.2 sample yielded a higher rate capability, an excellent reversibility, and a superior cycling stability, delivering 151 and 143 mAh/g under discharge rates of 20C and 40C at cycles 60 and 70, respectively. In addition, a high cycling stability was demonstrated with a capacity retention of 92% after 300 cycles at a very high discharge rate of 20C. In addition, first-principles calculations based on density functional theory (DFT) were conducted with the goal of further elucidating and understanding the nature of the doping mechanism in this study. The DFT calculations not only determined the structure of the Ca-doped Li 4 Ti 5 O 12 , which was found to be in accordance with the experimentally measured XPD pattern, but also yielded valuable insights into the doping-induced effect on both the atomic and electronic structures of Li 4 Ti 5 O 12 .

25 ENERGY STORAGE↗
DOE OSTI2022

How to Obtain the Redshift Distribution from Probabilistic Redshift Estimates

Abstract A reliable estimate of the redshift distribution n ( z ) is crucial for using weak gravitational lensing and large-scale structures of galaxy catalogs to study cosmology. Spectroscopic redshifts for the dim and numerous galaxies of next-generation weak-lensing surveys are expected to be unavailable, making photometric redshift (photo- z ) probability density functions (PDFs) the next best alternative for comprehensively encapsulating the nontrivial systematics affecting photo- z point estimation. The established stacked estimator of n ( z ) avoids reducing photo- z PDFs to point estimates but yields a systematically biased estimate of n ( z ) that worsens with a decreasing signal-to-noise ratio, the very regime where photo- z PDFs are most necessary. We introduce Cosmological Hierarchical Inference with Probabilistic Photometric Redshifts ( CHIPPR ), a statistically rigorous probabilistic graphical model of redshift-dependent photometry that correctly propagates the redshift uncertainty information beyond the best-fit estimator of n ( z ) produced by traditional procedures and is provably the only self-consistent way to recover n ( z ) from photo- z PDFs. We present the chippr prototype code, noting that the mathematically justifiable approach incurs computational cost. The CHIPPR approach is applicable to any one-point statistic of any random variable, provided the prior probability density used to produce the posteriors is explicitly known; if the prior is implicit, as may be the case for popular photo- z techniques, then the resulting posterior PDFs cannot be used for scientific inference. We therefore recommend that the photo- z community focus on developing methodologies that enable the recovery of photo- z likelihoods with support over all redshifts, either directly or via a known prior probability density.

79 ASTRONOMY AND ASTROPHYSICS↗