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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Measuring Gas Transport and Sorption in Large Intact Geologic Specimens via the Piezometric Method

Uptake of noble gases into heterogeneous geologic core samples was measured using a piezometric methodology. In addition to measuring accessible porosity—as with gas pycnometry—by monitoring the rate of pressure decay, this method can also be used to estimate the gas effective diffusivity in the sample. In contrast to previous applications of this method, where milligram quantities of fractured grains are characterized, here approximately kilogram core samples were left intact when tested. In doing so, a more representative sample of the heterogeneous field geology is provided. Additionally, alteration of the pore structure and connectivity during sample preparation is avoided. Furthermore, to scale the piezometric method from milligrams to kilograms, the system was designed to operate at medium vacuum (1 to 100 Pa) to restrict transport in pores less than approximately 60 µm to large Knudsen numbers. To test the system performance, two samples of interest were selected: a rhyolitic welded tuff from Blue Canyon Dome at the Energetic Materials Research and Testing Center and a zeolitized non-welded rhyolitic tuff from the Nevada National Security Site. Three noble gases were utilized in this test series; Argon and xenon as they are of direct interest to nuclear monitoring efforts and helium as it is a weakly adsorbing reference standard. Additionally, mercury intrusion porosimetry measurements were made on subsamples of the core to compare the observed porosity by the two methods and to discuss gas transport rates in the context of the measured pore distribution.

58 GEOSCIENCES↗
DOE OSTI2023

Light-trapping structures fabricated in situ for ultrathin III-V solar cells

Here, we describe a fully in situ method of fabricating light-scattering structures on III-V materials that generates a rough morphology via vapor phase etching and redeposition. Fully in situ methods support higher industrial throughput by utilizing the growth reactor to generate the light-trapping structures after device growth without removal from the reactor. We use HCl and PH 3 to etch and redeposit scattering morphologies on Ga 0.5 In 0.5 P in a dynamic hydride vapor phase epitaxy (D-HVPE) reactor. We show that the addition of PH 3 leads to redeposition during the vapor phase HCl etching of Ga 0.5 In 0.5 P and that HCl flow rate and time exposed to HCl-PH 3 each independently cause a linear increase in the redeposited feature size, indicating that redeposition proceeds by island growth in a III-Cl-limited, hydride-enhanced HVPE regime. Auger electron spectroscopy and scanning transmission electron microscopy with energy dispersive spectroscopy (STEM-EDS) reveal redeposition to be highly Ga-rich GaInP, i.e., Ga(In)P. The Ga-rich nature of the redeposition results from the higher thermodynamic driving force for Ga incorporation than for In during HVPE growth and the difference in the volatility of the III-Cl etch products. The resulting morphologies have high broadband scattering, as determined by normal specular reflectance and integrating sphere measurements, indicating effectiveness as light-scattering structures. In a 270-nm-thick GaAs photovoltaic device with a textured back surface, we achieve a 4.9% increase in short circuit current density (J SC ) without any loss in open-circuit voltage (V OC ) relative to a planar control using only a 60 s in situ texturing treatment.

14 SOLAR ENERGY↗
DOE OSTI2020

Winners are not keepers: Characterizing household engagement, gains, and energy patterns in demand response using machine learning in the United States

Demand-response programs can help utilities manage rapidly evolving electric grids, but these programs are subject to the complexities of human behavior. This paper explores a novel method for uncovering heterogeneity in households. In this work, we use a machine-learning method known as a Conditional Inference Tree (c-tree) algorithm to categorize households based on their energy behavior characteristics collected via smart meters, and explore how this translates through into heterogeneity in their real-world response to a DR program. Using data from randomized controlled trial, we generate estimates of the changes in energy use caused by the program within each household group. Our results show that the c-tree approach differentiates households by their energy-use characteristics in a way that increases the spread in enrollment rates and critical peak reduction among household groups, compared with the spreads achieved via several conventional segmentation methods. Thus, the c-tree analysis enables the most tailored targeting of major potential energy savers and could provide the greatest increase in cost-effectiveness of household recruitment into DR programs. Our results also offer fresh insights into the relationships between household energy behavior characteristics – such as peak energy use and “structural winningness” (the ability to save money under a DR program without changing energy-use behaviors) – and household decisions about enrolling in DR programs and reducing energy use. Our research also demonstrates the potential of smart meter data, combined with machine learning and econometric methods, to provide significant value to utilities, program implementers, researchers, and other stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Chemical and Optical Control of Spin Crossover: Ultrafast XUV Spectroscopy of Molecular Magnets in Native Solvation Environments

With support from the US Department of Energy Office of Science, we have developed and utilized extreme ultraviolet (XUV) spectroscopy and sum frequency generation vibrational spectroscopy as probes of charge, spin, and solvation structure and dynamics in molecules and at interfaces. This work is crucial to advancing fundamental understanding of the processes that control the efficiency and speed of energy conversion and information processing in molecules and at interfaces. Accordingly, it has important applications for developing next generation technologies for information storage and processing with increasing data storage density and processing rates as well as developing new methods for efficient energy conversion and storage.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Towards COP27: Decarbonization patterns of residential building in China and India

As the two largest emerging emitters with the highest growth in operational carbon emissions from residential buildings, the historical emission patterns and decarbonization efforts of China and India warrant further exploration. This study aims to be the first to present a carbon intensity model considering end-use performances, assessing the operational decarbonization progress of residential building in India and China over the past two decades using the newest decomposing structural decomposition approach. Results indicate (1) the annual operational carbon intensity increased by 1.4% and 2.5% in China and India, respectively, between 2000 and 2020. Household expenditure-related energy intensity and emission factors were crucial in decarbonizing residential buildings. (2) Building electrification played a significant role in decarbonizing space cooling (–87.7 in China and – 130.2 kg of carbon dioxide (kgCO 2 ) per household in India) and appliances (~ –169.7 in China and ~ –43.4 kgCO 2 per household in India). (3) China and India collectively decarbonized 1498.3 and 399.7 M-tons of CO 2 in residential building operations, respectively. In terms of decarbonization intensity, India (164.8 kgCO 2 per household) nearly caught up with China (182.5 kgCO 2 per household) in 2020 and is expected to surpass China in the upcoming years, given the country's robust annual growth rate of 7.3%. Overall, this study provides an effective data-driven tool for investigating the building decarbonization potential in China and India, and offers valuable insights for other emerging economies seeking to decarbonize residential buildings in the forthcoming COP28 1 age.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

The molten salt tritium transport experiment: A pumped fluoride salt loop for hydrogen isotope experimentation

Molten salt reactors (MSRs) and fusion reactors propose to use molten salts as coolants and breeder blanket materials, respectively. Tritium, however, poses safety concerns in both reactor types due to its ability to permeate through reactor materials and potential for environmental release. This manuscript addresses the tritium transport phenomena in molten salts and presents the design and analysis of the Molten Salt Tritium Transport Experiment (MSTTE). MSTTE is a forced-convection fluoride salt loop intended to measure hydrogen isotope permeation through structural materials in a flowing salt system. In the first phase, MSTTE will use FLiNaK salt and deuterium as surrogates for FLiBe and tritium, with future plans to utilize tritium and FLiBe. MSTTE couples a Copenhagen Atomics pumped salt loop with an external test section that introduces hydrogen isotopes into the loop and measures transport phenomena. The Hydrogen Injection System (HIS) controls hydrogen isotope introduction into the molten salt loop. Here, the permeation test section measures the permeation rate through stainless steel tubing in contact with flowing salt. Computational fluid dynamics (CFD) analysis ensures fully developed salt flow in the permeation test section. MSTTE is modeled with MELCOR-TMAP to predict the permeation rate as a function of experimental variables such as source term, salt flow rate, and salt temperature. Results indicate that the source term is the only parameter with a significant effect on the permeation rate. Pressure drop analysis suggests that the loop should operate below 200 LPM to maintain a pressure drop below 200 kPa. Additionally, finite-element analysis assesses thermal stress during loop operation to ensure the experiment's safe design. MSTTE will provide semi-integral data on tritium transport phenomena in molten salts and serve as a testbed for advancing molten salt technology.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Catalytic reforming of methane with H 2 S via dynamically stabilized sulfur on transition metal oxides and sulfides

Reforming of methane with H 2 S is a promising path to directly utilize sour natural gas reserves, although some aspects of the mechanism and structure–function relations remain elusive. In this report we show that metal oxides of group 4–6 elements, which are inert for steam and dry methane reforming reactions, are active and stable (pre)catalysts for the H 2 S reforming of methane. The key active sites are sulfur species (S*) that are dynamically bound to metal cations during catalysis. Similar H/D isotope exchange patterns and universal rate inhibition by H 2 on representative catalysts indicate that H 2 S decomposition and recombination of surface hydrogen atoms are quasi-equilibrated, whereas CH 4 dissociation steps are reversible, yet not quasi-equilibrated. An in-depth analysis of the kinetic data and isotopic substitution effects identifies S*-mediated C–H bond cleavage as the most plausible rate-limiting step common for all catalysts, with subtle yet essential differences between 3d and 4d/5d catalysts in the thermodynamic stability of S*.

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

Filament-induced breakdown spectroscopy with structured beams

Filament-induced ablation represents an attractive scheme for long-range material identification via optical spectroscopy. However, the delivery of laser energy to the target can be severely hindered by the stochastic nature of multiple-filamentation, ionization of ambient gas, and atmospheric turbulence. In order to mitigate some of these adverse effects, we examine the utility of beam shaping for femtosecond filament-induced breakdown spectroscopy with Gaussian and structured (Laguerre-Gaussian, Airy, and Bessel-Gaussian) beams in the nonlinear regime. Interaction of filaments with copper, zinc, and brass targets was studied by recording axially-resolved broadband emission from the filament-induced plasma. The laser-solid coupling efficacy was assessed by inferring thermodynamic parameters such as excitation temperature and electron density. While under our experimental conditions the ablation rate with Gaussian- and Laguerre-Gaussian beams is found to be similar, the Airy and Bessel-Gaussian beams offer the advantage of longitudinally extended working zones. These results provide insights into potential benefits of structuring ultrafast laser beams for standoff sensing applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Network Models of Active Degradation Mechanisms and Pathways for Service Life Prediction of Indoor and Outdoor PV Modules

ct: PV service lifetime prediction (SLP) enables accurate calculation of levelized cost of energy (LCOE), which is crucial to rationalizing PV investment and installation. However, SLP is challeging since PV reliability in the field is affected by many combined factors, including various environmental stresses and module quality. In order to map out the active degradation mechanisms and pathways that best resemble real world conditions, we introduce the framework of a study protocol and use network models fitted to data, to enable analysis and SLP of complex PV systems with multiple active degradation mechanisms. The study protocol is the experimental design, including module variants and different exposure conditions, selection of evaluation methods, time-series data acquisition and training of network models to these data. We present SLP of minimodules in the lab and PV systems in the field. For lab SLP, minimodules with 8 variants based on manufacturer, architecture, and encapsulation were prepared and aged in modified damp heat with or without full spectrum light exposure. Stepwise I-V and Suns-Voc data acquisition tracks changes in electrical properties including Rs,IV, Isc,IV, Vmp,PIV providing insights into power loss of minimodules. Network structural equation modeling (netSEM) was utilized to construct degradation pathway models that identify active degradation mechanisms and predict power loss over time. For field SLP, datastreams of Pmp values and I-V curve datastreams of two types of modules installed in three distinctly different Köppen-Geiger climate zones for 9 years were acquired. With power loss modes corresponding to uniform current loss (ΔPIsc), recombination (ΔPVoc), series resistance (ΔPRs), and current mismatch (ΔPImis) determined, the performance loss rates (PLR) were determined using PVplr. We show how to establish a study protocol framework to ensure appropriate parametric variations and valid data collection from the variants of your complex systems. Then the data-driven netSEM model fitting provides a comprehensive mapping of multiple active degradation mechanisms, and accurate service life prediction.

network model, degradation, photovoltaic, solar↗
DOE OSTI2024

N-Doped Graphene (N-G)/MOF(ZIF-8)-Based/Derived Materials for Electrochemical Energy Applications: Synthesis, Characteristics, and Functionality

In recent years, graphene-type materials originating from metal–organic frameworks (MOFs) or integrated with MOFs have exhibited notable performances across various applications. However, a comprehensive understanding of these complex materials and their functionalities remains obscure. While some studies have reviewed graphene/MOF composites from different perspectives, due to their structural–functional intricacies, it is crucial to conduct more in-depth reviews focusing on specific sets of graphene/MOF composites designed for particular applications. In this review, we thoroughly investigate the syntheses, characteristics, and performances of N-G/MOF(ZIF-8)-based/derived materials employed in electrochemical energy conversion and storage systems. Special attention is given to realizing their fundamental functionalities. The discussions are divided into three segments based on the application of N-G/ZIF-8-based/derived materials as electrode materials for batteries, electrodes for electrochemical capacitors, and electrocatalysts. As electrodes for batteries, N-G/MOF(ZIF-8) materials can mitigate issues like an electrode volume expansion for Li-ion batteries and the ‘shuttle effect’ for Li-S batteries. As electrodes for electrochemical capacitors, these materials can considerably improve the ion transfer rate and electronic conductivity, thereby enhancing the specific capacitance while maintaining the structural stability. Also, it was observed that these materials could occasionally outperform standard platinum-based catalysts for the electrochemical oxygen reduction reaction (ORR). The reported electrochemical performances and structural parameters of these materials were carefully tabulated in uniform units and scales. Through a critical analysis of the present synthesis trends, characteristics, and functionalities of these materials, specific aspects were identified that required further exploration to fully utilize their inherent capabilities.

Electrochemistry↗
DOE OSTI2025

Development and Validation of MALAMUTE model for Electric Field Assisted Sintering of Structural Materials

Fusion power plant designs feature extreme material performance requirements for structural material candidates. In addition to conventional alloys, more advanced composites and oxide dispersion strengthened (ODS) alloys are being explored, however, achieving the desired microstructures to maximize performance using traditional manufacturing methods can be challenging. The advanced manufacturing (AM) electric field-assisted sintering (EFAS) technique offers improved control over the final microstructure through higher heating and cooling rates and moderate pressures. Modeling and simulation tools show promise in elucidating the process-structure-property-performance (PSPP) correlation for AM-produced parts, including the EFAS process. An inherently multiscale process, the EFAS technique aligns well with the multiscale modeling capability of the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE)[cite]. We present here an electro-thermo-mechanical approach to modeling the EFAS process using the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) code. Prediction of the field and gradient distributions across the EFAS tooling is required to accurately describe the conditions for the lower-scale microstructural evolution models. In this work we present the MALAMUTE model developed to predict the electrical potential, temperature, and mechanical stress distribution across the EFAS graphite tooling and part at the larger engineering-scale. Validation of the MALAMUTE engineering-scale model is completed using data from experimental densification and pre-densified runs of iron powder via EFAS at 1000oC. These runs were conducted using a Thermal Technology DCS-5 EFAS system. Data collected during the experiment runs include the direct current (DC) supplied to the graphite tooling, the temperature of the graphite tooling as measured with a pyrometer, and the force applied to the top of the graphite tooling stack, and the data were recorded every 10 seconds. Our validation approach used the current and force data from the EFAS run as boundary condition inputs to the MAMALUTE simulation; the temperature data were used to evaluate the MALAMUTE EFAS model prediction. Results of the MALAMUTE simulations are employed to connect the external pyrometer temperature measurement to the temperature profile across the part undergoing consolidation. We investigate the impact of material property variation and mesh deformation on the temperature profile as predicted by MALAMUTE. We conclude by highlighting projects where the MALAMUTE EFAS modeling and simulation capabilities will be used to assist experimental design.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Use of Lignin-Based Admixture as Water Reducer (WRA) for Tailoring the Rheological Properties of Mortars for 3D-Printing

Efforts towards decarbonizing construction materials and industrial processes related to cement and concrete can be aided via multifaceted approaches that target alternative admixtures as well as precision control of fabrication. Chemical admixtures for water reduction have played a crucial role in the development of advanced mortar and concrete mixtures. Newer biomass processing techniques developed for aviation fuel production from corn stover biomass produce a highly reactive lignin byproduct that is suitable for chemical modifications to mimic the properties of commonly used polycarboxylate ethers (PCEs) with a smaller carbon footprint. These lignin-based plasticizers developed at NREL can be used in place of petrochemical-derived superplasticizers to tailor the rheological properties of cement-based systems for applications such as additive manufacturing while reducing the carbon intensity of the concrete mix. Lignosulfonates derived from paper pulping were historically used as water reducers only to be displaced with the rise of PCEs. The present study examines the use of a NREL produced lignin-based water reducing admixture (WRA), in cement pastes and mortar mixtures for 3D-printing at small- (mm) scale. The experimental program consisted of different formulations of oxidized lignin-based WRAs added in variable dosages to cement pastes with a fixed water-to-cement ratio. The objective is to achieve an appropriate workability, extrudability and buildability of mortar mixtures to produce 3D-printed specimens. The rheological characterization was performed to compare the initial yield stress and viscosity of the different mixtures with lignin-based admixture with respect to conventional PCE superplasticizers. The rheological characterization shows that the proposed material act as an effective water-reducer in cement systems, affecting the yield stress, plastic viscosity, and structuration rate of the mixtures evaluated. On the other hand, the effect on early hydration process of the cement pastes containing lignin-based admixtures is comparable to conventional superplasticizers.

3D-printing↗
DOE OSTI2025

ThO 2 and Th 1– x U x O 2 Nanoscale Materials and Thin Films for Nuclear Science Applications

This study investigates the dynamics and mechanisms of solution combustion synthesis (SCS) for the preparation of nanoscale ThO 2 and Th 1–x U x O 2 materials, utilizing metal nitrates (Th(NO 3 ) 4 and UO 2 (NO 3 ) 2 ) and acetylacetone (C 5 H 8 O 2 ) as reactants dissolved in a 2-methoxyethanol (C 3 H 8 O 2 ) solvent. By combining thermodynamic calculations, dynamic time–temperature profile measurements with differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA), this research reveals how variations in acetylacetone concentration and uranium content influence the structural parameters of the synthesized oxides. The time–temperature measurements show that the heating rate and maximum combustion temperatures are sensitive to acetylacetone concentration. DSC-TGA results indicate shifts in exothermic peak temperatures as the uranium content changes. The complexation between thorium and acetylacetone emerges as a critical factor, impacting combustion parameters and the structural characteristics of the final products. The uniform distribution of Th and U in the Th 1–x U x O 2 solid solution and the formation of nanoscale particles with strained crystallites are considered essential for the low-temperature densification of these materials for nuclear fuel pellet applications. Additionally, high-quality ThO 2 and Th 1–x U x O 2 thin (100–150 nm) films are successfully synthesized via electrospray deposition of combustible solutions followed by a brief period of heat treatment. Furthermore, these films exhibit excellent structural and morphological uniformity, making them ideal candidates for nuclear measurements, irradiation damage studies, and investigations into the physical properties of both pure and mixed oxides.

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

EVI-EnSitePy (Electric Vehicle Infrastructure – Energy Estimation and Site Optimization Tool in Python) [EVI-X Modeling Suite] [SWR-25-07]

EVI-EnSitePy is a comprehensive agent-based tool designed for the analysis and design of high-power charging sites, encompassing a wide array of site agents including Electric Vehicles (EVs), chargers, energy storage units (ESS), renewable energy resources (DER), and loads. This versatile tool offers diverse functionalities and a modular modeling approach, allowing detailed configuration of agents based on power ratings, port numbers, energy capacities, demand requirements, charger interfaces, and flexibility to customize the tool for project specific goals. By simulating agent interactions and employing various metrics, EVI-EnSitePy enables the assessment of site performance, exploration of energy management systems (EMS), and implementation of innovative EV charging policies. Utilizing EV charge schedules and arrival states, the tool performs thorough charging site simulations, with outputs consisting of agent and site-level power profiles and statistical metrics. Employing a tree graph structure, EVI-EnSitePy supports nested site structures and power distribution modeling. The tool's ability to generate charging schedules deterministically or via stochastic analysis further enhances its versatility. Through its features and capabilities, EVI-EnSitePy offers a powerful platform for informed decision-making in the realm of high-power charging site design and operation.

Jackson, Derek [National Renewable Energy Laborato↗
DOE OSTI2023

Nonthermal plasma synthesis of silicon carbonitride

Abstract The use of a low‐temperature plasma for the synthesis of amorphous silicon carbonitride (SiCN) nanoparticles enables the realization of sintered bulk samples with high thermal stability. Amorphous SiCN nanoparticles are produced from a mixture of silane, methane, and ammonia utilizing a mid‐pressure, radio‐frequency, continuous flow reactor. Particle characterization shows that the nanoparticles are largely amorphous with some crystalline silicon and silicon carbide domains <10 nm in size. Compositional tuning, controlled by varying the precursor flow rates, coupled with the uniform mixing of elements at the nanoscale, results in samples that resist crystallization even when sintered at temperatures as high as 2000°C. This study suggests that the low‐temperature plasma synthesis of nanoparticles has great potential to produce bulk structural materials for application in harsh environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Development & Validation of Low-Cost, Highly-Durable, Spinel-Based Materials for SOFC Cathode-Side Contact (Final Report)

A cathode-side contact layer is required to provide and maintain stable electrical conduction paths between the interconnect and cathode in a solid oxide fuel cell (SOFC) stack assembly and thus minimize the ohmic resistance and stack power loss. Current cathode-interconnect contact materials are based on noble metals, electrically-conductive perovskites, their composite materials, etc. These materials are either too expensive or do not possess the overall balanced performance required for the cathode-side contact application. To achieve the DOE SOFC system cost and performance stability goals, a new generation of low-cost, high-performance contact materials needs to be developed. In this project, spinel-based materials thermally converted from the Fe-Ni and Co-Mn based alloy precursors were developed and validated for the cathode-side contact application. The precursor alloy compositions were optimized via a combination of composition screening in the (Ni,Fe) 3 O 4 and (Mn,Co) 3 O 4 spinel system, alloy design using physical metallurgy principles, and cost considerations. The alloy powders with the desired composition and particle size were manufactured via gas atomization. The optimal process parameters for thermal conversion of these alloy precursor layers to a spinel-based layer were identified, i.e., 900°C x 2h in air, which is close to the initial stack firing condition. The area-specific resistances (ASRs) of the interconnect/contact/cathode test assemblies with the developed contact layer were determined for various durations (up to 5000 h) under simulated cathodic operation conditions. Some of the alloy-derived spinel contacts exhibited the lowest ASR and ASR degradation rate. The in-stack performance of the most promising alloy-derived contact layer is currently being evaluated via stack testing. To reduce the stack cost, the Co-Mn based alloy powders were utilized as the precursor for synthesis of dense spinel-based interconnect coating. By optimizing both the initial powder size/distribution and the alloy powder composition, a dense (Mn,Co) 3 O 4 -based spinel coating was achieved. Furthermore, co-sintering of the coating/contact dual-layer structure under the initial stack firing condition was realized by utilizing the tailored Co-Mn alloy precursors. Cost analysis of the developed technology indicated a total stack cost reduction of around 10.6% with the implementation of co-sintering of the interconnect coating and the contact layer during initial stack firing. Since low-cost processes such as screen printing is utilized in the precursor application and no reduction heat treatment is needed for the coating formation, the developed technology can be readily implemented at the industrial partner’s manufacturing facilities with no additional capital investment needed.

08 HYDROGEN↗
DOE OSTI2022

Possibilities and Limitations of Kinematically Identifying Stars from Accreted Ultra-faint Dwarf Galaxies

Abstract The Milky Way has accreted many ultra-faint dwarf galaxies (UFDs), and stars from these galaxies can be found throughout our Galaxy today. Studying these stars provides insight into galaxy formation and early chemical enrichment, but identifying them is difficult. Clustering stellar dynamics in 4D phase space ( E , L z , J r , J z ) is one method of identifying accreted structure that is currently being utilized in the search for accreted UFDs. We produce 32 simulated stellar halos using particle tagging with the Caterpillar simulation suite and thoroughly test the abilities of different clustering algorithms to recover tidally disrupted UFD remnants. We perform over 10,000 clustering runs, testing seven clustering algorithms, roughly twenty hyperparameter choices per algorithm, and six different types of data sets each with up to 32 simulated samples. Of the seven algorithms, HDBSCAN most consistently balances UFD recovery rates and cluster realness rates. We find that, even in highly idealized cases, the vast majority of clusters found by clustering algorithms do not correspond to real accreted UFD remnants and we can generally only recover 6% of UFDs remnants at best. These results focus exclusively on groups of stars from UFDs, which have weak dynamic signatures compared to the background of other stars. The recoverable UFD remnants are those that accreted recently, z accretion ≲ 0.5. Based on these results, we make recommendations to help guide the search for dynamically linked clusters of UFD stars in observational data. We find that real clusters generally have higher median energy and J r , providing a way to help identify real versus fake clusters. We also recommend incorporating chemical tagging as a way to improve clustering results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Adaptive 3D convolutional neural network-based reconstruction method for 3D coherent diffraction imaging

We present a novel adaptive machine-learning based approach for reconstructing three-dimensional (3D) crystals from coherent diffraction imaging. We represent the crystals using spherical harmonics (SH) and generate the corresponding synthetic diffraction patterns. We utilize 3D convolutional neural networks (CNNs) to learn a mapping between 3D diffraction volumes and the SH, which describe the boundary of the physical volumes from which they were generated. We use the 3D CNN-predicted SH coefficients as the initial guesses, which are then fine-tuned using adaptive model-independent feedback for improved accuracy. We also adaptively tune the locations, intensities, and decay rates of collections of radial basis functions in order to reproduce the non-uniform internal structure of 3D objects and demonstrate the method for a synthetic volume that has an internal void and a density ramp.

36 MATERIALS SCIENCE↗