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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

The Data Transfer Kit: A geometric rendezvous-based tool for multiphysics data transfer

The Data Transfer Kit (DTK) is a software library designed to provide parallel data transfer services for arbitrary physics components based on the concept of geometric rendezvous. The rendezvous algorithm provides a means to geometrically correlate two geometric domains that may be arbitrarily decomposed in a parallel simulation. By repartitioning both domains such that they have the same geometric domain on each parallel process, efficient and load balanced search operations and data transfer can be performed at a desirable algorithmic time complexity with low communication overhead relative to other types of mapping algorithms. With the increased development efforts in multiphysics simulation and other multiple mesh and geometry problems, generating parallel topology maps for transferring fields and other data between geometric domains is a common operation. The algorithms used to generate parallel topology maps based on the concept of geometric rendezvous as implemented in DTK are described with an example using a conjugate heat transfer calculation and thermal coupling with a neutronics code. In addition, we provide the results of initial scaling studies performed on the Jaguar Cray XK6 system at Oak Ridge National Laboratory for a worse-case-scenario problem in terms of algorithmic complexity that shows good scaling on 0(1 x 104) cores for topology map generation and excellent scaling on 0(1 x 105) cores for the data transfer operation with meshes of O(1 x 109) elements. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Super-resolution imaging of non-fluorescent reactions via competition

Super-resolved fluorescence microscopy techniques have enabled substantial advances in the chemical and biological sciences. However, they can only interrogate entities that fluoresce, and most chemical or biological processes do not involve fluorescent species. Here we report a competition-enabled imaging technique with super-resolution (COMPEITS) (a COMPetition-Enabled Imaging Technique with Super-resolution) that enables quantitative super-resolution imaging of non-fluorescent processes. It is based on the incorporation of competition into a single-molecule fluorescence-detection scheme. We demonstrate COMPEITS by investigating a photoelectrocatalytic reaction; we map, with nanometre precision, a non-fluorescent surface reaction that is important for water decontamination on single photocatalyst particles. The subparticle-level quantitative information of reactant adsorption affinities unambiguously decouples size- and shape-scaling laws on specific particle facets and uncovers a surprising biphasic shape dependence, leading to catalyst design principles for optimal reactant adsorption efficacy. With its ability to provide spatially resolved information on the behaviours of unlabelled, non-fluorescent entities under operando conditions, COMPEITS could interrogate a variety of surface processes in fields ranging from heterogeneous catalysis and materials engineering to nanotechnology and energy sciences.

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

The carbon nanotube formation parameter space: data mining and mechanistic understanding for efficient resource use

Carbon nanotube (CNT) synthesis via catalytic chemical vapor deposition is relatively energy consumptive and among the least efficient reactions with respect to carbon conversion efficiency. Interestingly, these processes can be fed using a diverse set of hydrocarbon starting materials, including methane, ethylene, and acetylene, over a wide range of operating temperatures and carbon-to-hydrogen feedstock ratios. Mapping the parameter space for successful CNT growth through data extraction from published literature illuminated the most energy- and material- efficient synthetic pathways in practice to date and provided insights on thermodynamic limitation of CNT growth (i.e., the fundamental mechanisms of CNT formation). Further experimental investigations confirmed that emergent trends in the literature were the result of physicochemical constraints on the process rather than behavioral inertia in the community. The initiation temperatures for CNT growth from acetylene, ethylene, and methane feedstocks via direct experimentation were 550, 700, and 950 °C, respectively, consistent with the trend in literature-extracted mean optima (642 ± 128, 739 ± 82, and 858 ± 125 °C, respectively). These relative temperatures are consistent with a universal CNT growth mechanism, wherein all carbon feedstocks are converted to alkyne-containing species that serve as direct precursors for CNT growth. Mitigating this step with rational carbon precursor delivery, rather than relying on heat to generate the most reactive precursors in situ, could largely reduce the environmental burdens in CNT manufacturing. Indeed, manipulating the starting gas-phase composition and minimizing the thermal treatment through the use of C 2 H 2 increased carbon conversion yield by a factor of more than 10 compared to C 2 H 4 , and, consequently, should minimize hazardous volatile organic compound and polycyclic aromatic hydrocarbon emissions. Finally, the methodology utilized in this study is transferrable to guide the green synthesis of other materials and should be automated in the future for high-throughput screening of the vast process chemistry literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Advanced Characterization of Rare Earth Elements in Coal Utilization Byproducts

Rare earth elements (REE) in various forms (e.g., crystalline mineral phases; adsorbed/absorbed state on and into organic macerals, neoformed glass from flyash or bottom ash) from domestic feedstocks such as coal deposits to coal utilization byproducts (CUB) have the potential to reduce foreign REE dependence and increase domestic resource security. Characterization is critical for understanding environmental risks related to their fate and transport as well as determining the most practical and economical techniques for concentrating the REE and converting them into chemical stocks for manufacturing. Several complementary electron microscopy (SEM-EDS, EPMA-WDS, FIB-SEM, cathodoluminescence, and XRD) and post image processing techniques were used to understand REE transition from coal to CUB. Sites of interest were identified and imaged and respective elemental x-ray maps acquired and montaged. Pixel classification of SEM imagers was completed using image analysis techniques to quantify the distribution of REE associated features. Quantitative elemental analysis of phases were completed using EMPA-WDS followed by FIB-SEM. The FIB-SEM results were reconstructed into 3D volumes and features of interest (e.g. monazite) were analyzed to determine the structure and volumetric estimation of REEs and thus predict detrital REE phases to ICP-MS results. Trace minerals were identified as pyrite, zircon, REE-phosphates' (monazite, xenotime), and barite within the coal tailings. In CUB, amorphous aluminosilicates, iron oxide cenospheres, and calcium oxides were present; monazite appear to be unaltered and unaffected by the combustion process in these samples. Thermal decomposition may have occurred due to presence of detrital zircon and xenotime and subsequent thin Ca-oxide coating enriched in trace REEs.

Verba, Circe↗
DOE OSTI2021

Tightly-coupled camera/LiDAR integration for point cloud generation from GNSS/INS-assisted UAV mapping systems

Unmanned aerial vehicles (UAVs) equipped with integrated global navigation satellite systems/inertial navigation systems (GNSS/INS) together with cameras and/or LiDAR sensors are being widely used for topographic mapping in a variety of applications such as precision agriculture, coastal monitoring, and archaeological documentation. Integration of image-based and LiDAR point clouds can provide a comprehensive 3D model of the area of interest. For such integration, ensuring a good alignment between data from the different sources is critical. Although many works have been conducted on this topic, there is still a need for a rigorous integration approach that minimizes the discrepancy between camera and LiDAR data caused by inaccurate system calibration parameters and/or trajectory artifacts. This study proposes an automated tightly-coupled camera/LiDAR integration workflow for GNSS/INS-assisted UAV systems. The proposed strategy is conducted in three main steps. First, an image-based point cloud is generated using a LiDAR/GNSS/INS-assisted structure from motion (SfM) strategy. Then, feature correspondences between image-based and LiDAR point clouds are automatically identified. Finally, an integrated-bundle adjustment procedure including image points, LiDAR raw measurements, and GNSS/INS information is conducted to minimize the discrepancy between point clouds from different sensors while estimating system calibration parameters and refining the trajectory information. The proposed SfM strategy and integration framework are evaluated using five datasets. The SfM results show that using LiDAR data can facilitate feature matching and further increase the number of reconstructed 3D points. The experimental results also illustrate that the developed automated camera/LiDAR integration strategy is capable of accurately estimating system calibration parameters to achieve good alignment among camera/LiDAR data from single/multiple systems. Finally, an absolute accuracy in the range of 3–5 cm is achieved for the image/LiDAR point clouds after the integration process.

42 ENGINEERING↗
DOE OSTI2013

Systematic mapping of occluded genes by cell fusion reveals prevalence and stability of cis-mediated silencing in somatic cells

Both diffusible factors acting in trans and chromatin components acting in cis are implicated in gene regulation, but the extent to which either process causally determines a cell’s transcriptional identity is unclear. We recently used cell fusion to define a class of silent genes termed ‘‘cis-silenced’’ (or ‘‘occluded’’) genes, which remain silent even in the presence of transacting transcriptional activators. We further showed that occlusion of lineage-inappropriate genes plays a critical role in maintaining the transcriptional identities of somatic cells. Here, we present, for the first time, a comprehensive map of occluded genes in somatic cells. Specifically, we mapped occluded genes in mouse fibroblasts via fusion to a dozen different rat cell types followed by whole-transcriptome profiling. We found that occluded genes are highly prevalent and stable in somatic cells, representing a sizeable fraction of silent genes. Occluded genes are also highly enriched for important developmental regulators of alternative lineages, consistent with the role of occlusion in safeguarding cell identities. Alongside this map, we also present whole-genome maps of DNA methylation and eight other chromatin marks. These maps uncover a complex relationship between chromatin state and occlusion. Furthermore, we found that DNA methylation functions as the memory of occlusion in a subset of occluded genes, while histone deacetylation contributes to the implementation but not memory of occlusion. Our data suggest that the identities of individual cell types are defined largely by the occlusion status of their genomes. The comprehensive reference maps reported here provide the foundation for future studies aimed at understanding the role of occlusion in development and disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A phenology- and trend-based approach for accurate mapping of sea-level driven coastal forest retreat

The rapid replacement of upland forest by encroaching marshland is a striking manifestation of global sea-level rise (SLR). Timely and high-resolution information on the location and extent of transition forest (the ecotone between upland forest and marsh where tree mortality due to seawater intrusion begins) is fundamental to understanding the processes and patterns of SLR-driven landscape reorganization. Despite its significance, accurate characterization of salt-impacted transition forest remains challenging due to the complexity of coastal environments, scarcity of ground-truth data, and the lack of effective mapping algorithms. Here we use the full archive of Landsat images between 1984 and 2021 to investigate the spectral, temporal, and phenological characteristics of transition forest, and develop a robust framework for monitoring coastal vegetation shifts in the mid-Atlantic U.S., a global SLR hotspot. Here, we found that transition forest exhibits strong negative NDVI trends and a deviation of land surface phenology from marsh and upland forest that distinguishes itself from surrounding vegetation. By integrating temporal trends and land surface phenology, our results demonstrate superior discrimination between marsh and coastal forests to existing map products (e.g. NOAA Coastal Change Analysis Program, National Land Cover Database) that allows a reliable identification of the coastal treeline. We applied the approach to map regional land cover in 1985, 2000 and 2020 (overall classification accuracy >92%) and found that the area of coastal forest decreased by 22.0% from 1985 to 2020, the majority of which transitioned to marshland (92.3%, 5.3 × 10 3 ha). Based upon fine-scale patterns of coastal transgression, we created a practical workflow for spatially explicit quantification of forest retreat rates. Concurrent with rising sea level, coastal forests migrated upslope from 0.63 (± 0.27) m above sea level in 1985 to 0.78 (± 0.32) m above sea level in 2020, and horizontal forest retreat rates accelerated from 3.1 (range of 0–36) m yr -1 during 1985–2000 to 4.7 (0–55) m yr -1 during 2001–2020. As SLR continues to accelerate, our study may serve as a scalable solution for consistent tracking of coastal landscape evolution that is urgently needed for sustainable forest and wetland management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Laser‐ablation electrospray ionization mass spectrometry with ion mobility separation reveals metabolites in the symbiotic interactions of soybean roots and rhizobia

Summary Technologies enabling in situ metabolic profiling of living plant systems are invaluable for understanding physiological processes and could be used for rapid phenotypic screening (e.g., to produce plants with superior biological nitrogen‐fixing ability). The symbiotic interaction between legumes and nitrogen‐fixing soil bacteria results in a specialized plant organ (i.e., root nodule) where the exchange of nutrients between host and endosymbiont occurs. Laser‐ablation electrospray ionization mass spectrometry ( LAESI ‐ MS ) is a method that can be performed under ambient conditions requiring minimal sample preparation. Here, we employed LAESI ‐ MS to explore the well characterized symbiosis between soybean ( Glycine max L. Merr.) and its compatible symbiont, Bradyrhizobium japonicum . The utilization of ion mobility separation ( IMS ) improved the molecular coverage, selectivity, and identification of the detected biomolecules. Specifically, incorporation of IMS resulted in an increase of 153 differentially abundant spectral features in the nodule samples. The data presented demonstrate the advantages of using LAESI – IMS – MS for the rapid analysis of intact root nodules, uninfected root segments, and free‐living rhizobia. Untargeted pathway analysis revealed several metabolic processes within the nodule (e.g., zeatin, riboflavin, and purine synthesis). Compounds specific to the uninfected root and bacteria were also detected. Lastly, we performed depth profiling of intact nodules to reveal the location of metabolites to the cortex and inside the infected region, and lateral profiling of sectioned nodules confirmed these molecular distributions. Our results established the feasibility of LAESI – IMS – MS for the analysis and spatial mapping of plant tissues, with its specific demonstration to improve our understanding of the soybean‐rhizobial symbiosis.

Stopka, Sylwia A.↗
DOE OSTI2025

Unfolding of the Villin Headpiece Domain: Revealing Structural Heterogeneity with Time‐Resolved X‐Ray Solution Scattering and Markov State Modeling

Understanding protein folding pathways is crucial to deciphering the principles of protein structure and function. Here, the unfolding dynamics of the 35‐residue villin headpiece (HP35) and a norleucine‐substituted variant (2F4K) using a combination of experimental and computational techniques is investigated. Time‐resolved X‐ray solution scattering coupled with equilibrium molecular dynamics simulations and Markov state modeling reveals distinct unfolding mechanisms between the two variants: HP35 and 2F4K. Specifically, HP35 exhibits a two‐state unfolding process, whereas an intermediate state is identified for the 2F4K mutant. A Markov state model constructed from simulations is used to map atomic‐level transitions to experimental observations, providing insights into the role of sequence variations in modulating folding pathways. The findings underscore the importance of integrating experimental and computational approaches to unravel protein unfolding mechanisms between heterogenous structural ensembles.

Nijhawan, Adam K. [Department of Chemistry Northwe↗
DOE OSTI2023

Toward accurate measurement of electromagnetic field by retrieving and refining the center position of non-uniform diffraction disks in Lorentz 4D-STEM

Recent advancement in scanning transmission electron microscopy (STEM) allows the use of 4D-STEM, a technique that captures an electron diffraction pattern at each scan point in STEM, to measure electrostatic and magnetic potential and field in materials. However, accurate measurement, separation of the magnetic and electric signals, and removal of artifacts remain challenging, especially in the presence of complex non-uniform diffraction contrast within the disks. In this work, based on dynamic simulations of 4D-STEM patterns built upon superstructures consisting of millions of atoms to account for different sample thickness and edge geometries, we show how the shape and intensity distribution of the central disk are affected by multiple scattering. We propose a robust refinement procedure through iteration of the spin-sensitive peak position of the disk-center in the circular Hough transform filtered images from experimental Lorentz 4D-STEM dataset after minimizing the possible artifacts, such as those due to the change of thickness, dynamic scattering, and scanning process. We verify that caution must be taken as in practice the rigid-disk-shift model used to reconstruct induction maps can easily break down due to disk-protrusion when there exists a nonconstant phase gradient or thickness within the width of the probe. Through quantitative analysis and comparing experiment with calculation the effect of the non-spin-related intensity distribution inside the disk as well as that causes the disk shift due to the intensity-protrusion can be removed, and high-quality magnetic field mapping is possible.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Carbon Coating Influence on the Formation of Percolating Electrode Networks for Silicon Anodes

Previous studies have demonstrated that chemical vapor deposition carbon coating on silicon (Si@C) can enhance the electrochemical performance of lithium-ion batteries with Si-based anodes. However, the underlying mechanisms contributing to this improvement have not been fully explored. Here, we address this knowledge gap by applying a suite of characterization methods to evaluate Si@C anodes prepared by reducing acetylene on ball-milled Si particles. Raman mapping measurements show that the C coating (<5 nm thick) enables a homogeneous Si and carbon distribution during the slurry casting process, thereby promoting Si utilization during cycling. The coating’s microstructure and morphology were evaluated using X-ray photoelectron spectroscopy (XPS), scanning transmission electron microscopy, and neutron reflectivity experiments. Electrochemical impedance spectroscopy measurements upon cycling indicate that carbon coating also reduces the overall resistance as benchmarked against bare Si anodes. Galvanostatic cycling in half-cell studies revealed higher initial Coulombic efficiency and specific capacities with increasing carbon coating time. However, solid electrolyte interphase (SEI) investigations using XPS showed that the coated and uncoated samples have very similar characteristics, suggesting that the SEI may only play a minor role in enhancing the performance of Si@C. Full-cell evaluation of the Si electrodes was consistent with half-cell results relating to performance and SEI properties, further supporting the conclusion that electronic and ionic percolation, enabled by effective electrode manufacturing, are the dominant factors contributing to the favorable performance of Si@C.

25 ENERGY STORAGE↗
DOE OSTI2021

Single Nanoflake Photoelectrochemistry Reveals Intrananoflake Doping Heterogeneity That Explains Ensemble-Level Photoelectrochemical Behavior

Transition metal dichalcogenide (TMD) nanoflake thin films are attractive electrode materials for photoelectrochemical (PEC) solar energy conversion and sensing applications, but their photocurrent quantum yields are generally lower than those of bulk TMD electrodes. The poor PEC performance has been primarily attributed to enhanced charge carrier recombination at exposed defect and edge sites introduced by the exfoliation process. Here, a single nanoflake PEC approach reveals how an alternative effect, doping heterogeneity, limits ensemble-level PEC performance. Photocurrent mapping and local photocurrent–potential (i–E) measurements of MoS 2 nanoflakes exfoliated from naturally occurring bulk crystals revealed the presence of n- and p-type domains within the same nanoflake. Interestingly, the n- and p-type domains in the natural MoS 2 nanoflakes were equally efficient for iodide oxidation and tri-iodide reduction (IQE values exceed 80%). At the single domain-level, the natural MoS 2 nanoflakes were nearly as efficient as nanoflakes exfoliated from synthetic n-type MoS 2 crystals. Single domain-level i–E measurements explain why natural MoS 2 nanoflakes exhibit an n-type to p-type photocurrent switching effect in ensemble-level measurements: the n- and p-type diode currents from individual domains oppose each other upon illuminating the entire nanoflake, resulting in zero photocurrent at the switching potential. Furthermore, the doping heterogeneity effect is likely due to nonideal stoichiometry, where p-type domains are S-rich according to XPS measurements. Although this doping heterogeneity effect limits photoanode or photocathode performance, these findings open the possibility to synthesize efficient TMD nanoflake photocatalysts with well-defined lateral p- and n-type domains for enhanced charge separation.

14 SOLAR ENERGY↗
DOE OSTI2018

Chemical Evolution in Silicon–Graphite Composite Anodes Investigated by Vibrational Spectroscopy

Silicon–graphite composites are under development for the next generation of high-capacity lithium-ion anodes, and vibrational spectroscopy is a powerful tool to identify the different mechanisms that contribute to performance loss. With alloy anodes, the underlying causes of cell failure are significantly different in half-cells with lithium metal counter electrodes compared to full cells with standard cathodes. However, most studies which take advantage of vibrational spectroscopy have only examined half-cells. In this work, a combination of FTIR and Raman spectroscopy describes several factors that lead to degradation in full pouch cells with LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC532) cathodes. The spectroscopic signatures evolve after longer term cycling compared to the initial formation cycles. Several side-reactions that consume lithium ions have clear FTIR signatures, and comparison to a library of reference compounds facilitates identification. Raman microspectroscopy combined with mapping shows that the composite anodes are not homogeneous but segregate into graphite-rich and silicon-rich phases. Lithiation does not proceed uniformly either. A basis analysis of Raman maps identifies electrochemically inactive regions of the anodes. In conclusion, the spectroscopic results presented here emphasize the importance of improving electrode processing and SEI stability to enable practical composite anodes with high silicon loadings.

25 ENERGY STORAGE↗
DOE OSTI2021

Absolute contrast estimation for soft X-ray photon fluctuation spectroscopy using a variational droplet model

Abstract X-ray photon fluctuation spectroscopy using a two-pulse mode at the Linac Coherent Light Source has great potential for the study of quantum fluctuations in materials as it allows for exploration of low-energy physics. However, the complexity of the data analysis and interpretation still prevent recovering real-time results during an experiment, and can even complicate post-analysis processes. This is particularly true for high-spatial resolution applications using CCDs with small pixels, which can decrease the photon mapping accuracy resulting from the large electron cloud generation at the detector. Droplet algorithms endeavor to restore accurate photon maps, but the results can be altered by their hyper-parameters. We present numerical modeling tools through extensive simulations that mimic previous x-ray photon fluctuation spectroscopy experiments. By modification of a fast droplet algorithm, our results demonstrate how to optimize the precise parameters that lift the intrinsic counting degeneracy impeding accuracy in extracting the speckle contrast. These results allow for an absolute determination of the summed contrast from multi-pulse x-ray speckle diffraction, the modus operandi by which the correlation time for spontaneous fluctuations can be measured.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Nanoscale mapping of plasmon and exciton in ZnO tetrapods coupled with Au nanoparticles

Metallic nanoparticles can be used to enhance optical absorption or emission in semiconductors, thanks to a strong interaction of collective excitations of free charges (plasmons) with electromagnetic fields. Herein we present direct imaging at the nanoscale of plasmon-exciton coupling in Au/ZnO nanostructures by combining scanning transmission electron energy loss and cathodoluminescence spectroscopy and mapping. The Au nanoparticles (~30 nm in diameter) are grown in-situ on ZnO nanotetrapods by means of a photochemical process without the need of binding agents or capping molecules, resulting in clean interfaces. Interestingly, the Au plasmon resonance is localized at the Au/vacuum interface, rather than presenting an isotropic distribution around the nanoparticle. Moreover, on the contrary, a localization of the ZnO signal has been observed inside the Au nanoparticle, as also confirmed by numerical simulations.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Tracking ion intercalation into layered Ti 3 C 2 MXene films across length scales

Enhancing the energy stored and power delivered by layered materials relies strongly on improved understanding of the intricate interplay of electrolyte ions, solvents, and electrode interactions as well as the role of confinement. Here we report a highly integrated study with multiscale theory/modelling and experiments to track the intercalation of aqueous Li + , Na + , K + , Cs + , and Mg 2+ ions into Ti 3 C 2 MXene. The integrated analysis of experiments assisted by theory/modelling allows for a deep understanding of energy storage processes highlighting the importance of the dynamics of cations, their positionings between MXene sheets, their effects on mechanical properties and capacitive energy storage. Computational simulations and operando calorimetry measurements prove the processes involving cation dehydration and H+ rehydration, showing a good correlation for heat variations between experiments and theory. Operando liquid AFM mapped energy dissipation of ions appears non-uniformly across the MXene surface, indicating heterogeneities of ions inside the MXene and confirming partially the ion behaviour obtained in theory. We directly demonstrate that the average distance between the cation and MXene surface follows a modified two-sided Helmholtz model when plotted versus the open circuit potential capacitance, revealing a different electrical double layer mechanism in confinement. This new fundamental understanding lays the foundation for improved functional devices utilizing electrodes and membranes made of two-dimensional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Thermoelectric transport properties of diamond-like Cu{sub 1−x}Fe{sub 1+x}S{sub 2} tetrahedral compounds

Polycrystalline samples with the composition of Cu{sub 1−x}Fe{sub 1+x}S{sub 2} (x = 0, 0.01, 0.03, 0.05, 0.1) were synthesized by a melting-annealing-sintering process. X-ray powder diffraction reveals all the samples are phase pure. The backscattered electron image and X-ray map indicate that all elements are distributed homogeneously in the matrix. The measurements of Hall coefficient, electrical conductivity, and Seebeck coefficient show that Fe is an effective n-type dopant in CuFeS{sub 2}. The electron carrier concentration of Cu{sub 1−x}Fe{sub 1+x}S{sub 2} is tuned within a wide range leading to optimized power factors. The lattice phonons are also strongly scattered by the substitution of Fe for Cu, leading to reduced thermal conductivity. We use Debye approximation to model the low temperature lattice thermal conductivity. It is found that the large strain field fluctuation introduced by the disordered Fe ions generates extra strong phonon scatterings for lowered lattice thermal conductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Spatially resolved and observer-free experimental quantification of spatial resolution in tomographic images

We present a novel framework and experimental method for the quantification of spatial resolution of a tomography system. The framework adopts the “black box” view of an imaging system, considering only its input and output. The tomography system is locally stimulated with a step input, viz., a sharp edge. The output, viz., the reconstructed images, is analysed by Fourier decomposition of their spatial frequency components, and the local limiting spatial resolution is determined using a cut-off threshold. At no point is an observer involved in the process. The framework also includes a means of translating the quantification region in the imaging space, thus creating a spatially resolved map of objectively quantified spatial resolution. As a case-study, the framework is experimentally applied using a gaseous propane phantom measured by a well-established chemical species tomography system. A spatial resolution map consisting of 28 regions is produced. In isolated regions, the indicated performance is 4-times better than that suggested in the literature and varies by 57% across the imaging space. A mechanism based on adjacent but non-interacting beams is hypothesised to explain the observed behaviour. The mechanism suggests that, as also independently concluded by other methods, a geometrically regular beam array maintains maximum objectivity in reconstructions. We believe that the proposed framework, methodology, and findings will be of value in the design and performance evaluation of tomographic imaging arrays and systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗