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At least 937 records · Page 52

A CFD Study Assisted with Experimental Confirmation for Liquid Shape Control of Electromagnetically Levitated Bulk Materials

Two types of optimized electromagnetic levitators were designed to achieve the free surface shape control of metallic melts as the combined results of the Lorentz force, sample gravity, and surface tension. The levitation behavior of bulk melts was investigated using computational fluid dynamics (CFD) modeling coupled with high-frequency electromagnetic field analysis and the arbitrary Lagrangian–Eulerian (ALE) method. The difference in the oscillation behavior between the solid and molten samples was explained by the damping of the electromagnetic induction and liquid viscosity. The motion of the mass center, melt shape, flow pattern, and Lorentz force in the levitated melt were determined within a wide excitation current range. With the increase in the applied current, the melt’s centroid position rose sharply in the area with low current but displayed a slow increase in the area with high current. Meanwhile, the stable shape of the bulk melt showed the typical transition from a long taper through a short taper and then into a rhombus. The internal flow pattern transformed from a simple double-loop structure to a complex configuration with three or four loops. The dependence of the deformation on the Bond number was analyzed in the two types of levitators. In addition, the stable shape and swing process of the bulk Al melt within the two types of electromagnetic levitation (EML) systems were quantitatively studied under protective inert gas conditions. The melt contour could be well described by the 10th Legendre polynomial function with a deviation of less than 0.5 pct.

36 MATERIALS SCIENCE↗

HPHT synthesis, structure and electrical properties of type-I clathrates Ba{sub 8}Al{sub x}Si{sub 46−x}

Clathrate compounds Ba{sub 8}Al{sub x}Si{sub 46−x} were successfully synthesized using the method of high-pressure and high-temperature (HPHT). In this process, we used BaSi{sub 2} as one of the starting materials in place of Ba metals, which reduces the complexity of the program caused by the extremely high chemical reactivity. By using this method, the processing time was reduced from few days to an hour. X-ray diffraction and structural refinement indicated this composition crystallized in type-I clathrate phase. Bond length analysis showed the Ba atoms in small dodecahedron had spherical thermal ellipsoids while those in large tetrakaidecahedron displayed anisotropic thermal ellipsoids. The negative Seebeck coefficient indicated transport processes were dominated by electrons as carriers, and increased with the increasing temperature. The electrical properties, including Seebeck coefficient and Power factor, were greatly enhanced by Al substitution. - Graphical abstract: Left: The cavity structure diagram of a China-type large volume cubic high-pressure apparatus, and the Type-I clathrate structure of sample synthesized using HPHT. Middle: X-ray Rietveld refinement profile for Ba{sub 8}Si{sub 46} and element mapping for Ba{sub 8}Al{sub 16}Si{sub 30}. Right: Temperature dependence of Seebeck coefficient for Ba{sub 8}Al{sub x}Si{sub 46−x} prepared by HPHT. - Highlights: • HPHT is a simple and rapid synthetic approach. • We use BaSi{sub 2} as one of the starting materials replacing Ba metals. • The processing time reduces from few days to an hour. • Structure determination is refined by Rietveld analysis of XRD data. • Variable temperature electrical properties are characterized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selection and characterization of ssDNA aptamers specifically recognizing pathogenic Vibrio alginolyticus

Abstract Vibrio alginolyticus ( V. alginolyticus ) is a major opportunistic pathogen to both marine animals and humans, which has also caused heavy economic losses to mariculture. The aim of this study was to develop highly specific aptamers for V. alginolyticus . Single‐stranded DNA (ssDNA) aptamers with high binding affinity to viable V. alginolyticus were generated by Systematic Evolution of Ligands by Exponential Enrichment (SELEX) and identified by flow cytometric analysis in this study. The selected aptamers showed high specificity for V. alginolyticus and low apparent binding for other bacteria. The aptamers formed distinct stem‐loop structures, which could form the basis of aptamers’ specific binding to the target V. alginolyticus . Aptamer VA2 and VA8 showed particularly high binding affinity constant (K d ) of 14.31 ± 4.26 and 90.00 ± 13.51 nM, respectively. The aptamers produced no cytotoxic effects in vitro and in vivo. ssDNA aptamers were successfully selected against the viable bacteria pathogen V. alginolyticus by SELEX. The aptamers selected in this study could be not only applied as specific chemical molecular probes for studying V. alginolyticus pathogenesis to Trachinotus ovatus , but also developing rapid convenient diagnosis assay for V. alginolyticus infection, even when applied to the complex sample matrix, such as food and environment samples.

Yu, Qing↗

Autotrophic biofilms sustained by deeply sourced groundwater host diverse bacteria implicated in sulfur and hydrogen metabolism

Abstract Background Biofilms in sulfide-rich springs present intricate microbial communities that play pivotal roles in biogeochemical cycling. We studied chemoautotrophically based biofilms that host diverse CPR bacteria and grow in sulfide-rich springs to investigate microbial controls on biogeochemical cycling. Results Sulfide springs biofilms were investigated using bulk geochemical analysis, genome-resolved metagenomics, and scanning transmission X-ray microscopy (STXM) at room temperature and 87 K. Chemolithotrophic sulfur-oxidizing bacteria, including Thiothrix and Beggiatoa , dominate the biofilms, which also contain CPR Gracilibacteria, Absconditabacteria, Saccharibacteria, Peregrinibacteria, Berkelbacteria, Microgenomates, and Parcubacteria. STXM imaging revealed ultra-small cells near the surfaces of filamentous bacteria that may be CPR bacterial episymbionts. STXM and NEXAFS spectroscopy at carbon K and sulfur L 2,3 edges show that filamentous bacteria contain protein-encapsulated spherical elemental sulfur granules, indicating that they are sulfur oxidizers, likely Thiothrix . Berkelbacteria and Moranbacteria in the same biofilm sample are predicted to have a novel electron bifurcating group 3b [NiFe]-hydrogenase, putatively a sulfhydrogenase, potentially linked to sulfur metabolism via redox cofactors. This complex could potentially contribute to symbioses, for example, with sulfur-oxidizing bacteria such as Thiothrix that is based on cryptic sulfur cycling. One Doudnabacteria genome encodes adjacent sulfur dioxygenase and rhodanese genes that may convert thiosulfate to sulfite. We find similar conserved genomic architecture associated with CPR bacteria from other sulfur-rich subsurface ecosystems. Conclusions Our combined metagenomic, geochemical, spectromicroscopic, and structural bioinformatics analyses of biofilms growing in sulfide-rich springs revealed consortia that contain CPR bacteria and sulfur-oxidizing Proteobacteria, including Thiothrix , and bacteria from a new family within Beggiatoales. We infer roles for CPR bacteria in sulfur and hydrogen cycling.

59 BASIC BIOLOGICAL SCIENCES↗

Rapid simulations of hyperspectral near-field images of three-dimensional heterogeneous surfaces – part II

The modeling of the near-field interaction in the scattering-type scanning near-field optical microscope (s-SNOM) is rapidly advancing, although an accurate yet versatile modeling framework that can be easily adapted to various complex situations is still lacking. In this work, we propose a time-efficient numerical scheme in the quasi-electrostatic limit to capture the tip-sample interaction in the near field. This method considers an extended tip geometry, which is a significant advantage compared to the previously reported method based on the point-dipole approximation. Using this formalism, we investigate, among others, nontrivial questions such as uniaxial and biaxial anisotropy in the near-field interaction, the relationship between various experimental parameters (e.g. tip radius, tapping amplitude, etc.), and the tip-dependent spatial resolution. The demonstrated method further sheds light on the understanding of the contrast mechanism in s-SNOM imaging and spectroscopy, while also representing a valuable platform for future quantitative analysis of the experimental observations.

Chen, Xinzhong (ORCID:0000000261033848)↗

Catalytic Aquathermolysis of High-Viscosity Oil Using Iron, Cobalt, and Copper Tallates

The results of a study of the composition of active forms of the catalyst formed upon degradation of the precursor, based on the results of physical modeling of a sample of high-viscosity oil having high asphaltene and resin contents, are presented. Oil-soluble iron, cobalt, and copper tallates were used as the objects of the study. The composition of the separated powder of the active form of the catalyst was determined by X-ray diffraction analysis, and the catalyst particle size was determined by scanning electron microscopy. The SARA (saturate, aromatic, resin and asphaltene) analysis data revealed a marked decrease in high-molecular-weight oil components due to thermocatalytic cracking. The basic transformation mechanism is breakdown of the high-molecular-weight compounds along the sulfur-bearing bonds, as indicated by elemental CHNS (carbon, hydrogen, nitrogen and sulfur) analysis data. It is shown that the cobalt- and copper-based oil-soluble complexes turn are converted to sulfide forms and the iron-based complex is converted to the oxide form. According to the results of scanning electron microscopic analysis of the catalyst, the particle size is about 60 nm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Correlating inter-particle forces and particle shape to shear-induced aggregation/fragmentation and rheology for dilute anisotropic particle suspensions: A complementary study via capillary rheometry and in-situ small and ultra-small angle X-ray scattering

Predicting the stability of suspensions composed of anisotropic particles is difficult due to the complexity and interplay of hydrodynamic and colloidal forces. For example, it is not well understood how non-spherical particle shapes affect suspension-rheological responses. This study presents evidence showing how the stacking of boehmite platelets dispersed in aqueous solution leads to moderate shear thinning, even at low boehmite mass fractions. Wide angle X-ray, small angle X-ray, and ultra-small angle X-ray scattering were used to simultaneously monitor changes to the size and fractal dimensions of boehmite aggregates from 6 – 10,000 Å as the sample was recirculated through an in situ capillary rheometer. The latter also provided simultaneous measurements of the viscosity of the suspensions. Computational fluid dynamics modeling of the apparatus was used to provide a more rigorous analysis of the fluid flow. In addition to shear-induced aggregation/fragmentation correlated to a complicated balance between hydrodynamic and colloidal forces, the results indicate that orientationally-dependent interactions, arising from non-spherical boehmite aggregate sub-units, may explain the relatively large experimental viscosity when the hydrodynamic force is small compared to colloidal forces. Ultimately, the results from this study can provide a foundation for future work investigating particle shape effects on colloidal and hydrodynamics forces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bayesian inference in band excitation scanning probe microscopy for optimal dynamic model selection in imaging

The universal tendency in scanning probe microscopy (SPM) over the last two decades is to transition from simple 2D imaging to complex detection and spectroscopic imaging modes. The emergence of complex SPM engines brings forth the challenge of reliable data interpretation, i.e., conversion from detected signals to descriptors specific to tip–surface interactions and subsequently to material’s properties. In this work, we implemented a Bayesian inference approach for the analysis of the image formation mechanisms in band excitation SPM. Compared to the point estimates in classical functional fit approaches, Bayesian inference allows for the incorporation of extant knowledge of materials and probe behavior in the form of corresponding prior distribution and return the information on the material functionality in the form of readily interpretable posterior distributions. We explore the nonlinear mechanical behaviors spatially in a classical ferroelectric material, PbTiO 3 . We observe the non-trivial evolution of the Duffing stiffness term and the nonlinearity of the sample surface, determine spatial clustering of the nonlinear response, and perform a Landau analysis on predicting the nonlinear coefficient, which indicates that ferroelectric behavior can be a cause of the observed results. These observations suggest that the spectrum of anomalous behaviors at the ferroelectric domain walls may be broader than previously believed and can extend to non-conventional mechanical properties in addition to static and microwave conductance.

36 MATERIALS SCIENCE↗

First comprehensive identification of cardiac proteins with putative increased O-GlcNAc levels during pressure overload hypertrophy

Protein posttranslational modifications (PTMs) by O-GlcNAc globally rise during pressure-overload hypertrophy (POH). However, a major knowledge gap exists on the specific proteins undergoing changes in O-GlcNAc levels during POH primarily because this PTM is low abundance and easily lost during standard mass spectrometry (MS) conditions used for protein identification. Methodologies have emerged to enrich samples for O-GlcNAcylated proteins prior to MS analysis. Accordingly, our goal was to identify the specific proteins undergoing changes in O-GlcNAc levels during POH. We used C57/Bl6 mice subjected to Sham or transverse aortic constriction (TAC) to create POH. From the hearts, we labelled the O-GlcNAc moiety with tetramethylrhodamine azide (TAMRA) before sample enrichment by TAMRA immunoprecipitation (IP). We used LC-MS/MS to identify and quantify the captured putative O-GlcNAcylated proteins. We identified a total of 700 putative O-GlcNAcylated proteins in Sham and POH. Two hundred thirty-three of these proteins had significantly increased enrichment in POH over Sham suggesting higher O-GlcNAc levels whereas no proteins were significantly decreased by POH. We examined two MS identified metabolic enzymes, CPT1B and the PDH complex, to validate by immunoprecipitation. We corroborated increased O-GlcNAc levels during POH for CPT1B and the PDH complex. Enzyme activity assays suggests higher O-GlcNAcylation increases CPT1 activity and decreases PDH activity during POH. In summary, we generated the first comprehensive list of proteins with putative changes in O-GlcNAc levels during POH. Our results demonstrate the large number of potential proteins and cellular processes affected by O-GlcNAc and serve as a guide for testing specific O-GlcNAc-regulated mechanisms during POH.

59 BASIC BIOLOGICAL SCIENCES↗

Multi-Fidelity Stochastic Economic Dispatch for Operating Low Carbon Power Grids

Grid operators can address the inherently stochastic nature of renewables by solving a two-stage stochastic programming model that minimizes the cost of dispatch decisions while accounting for the complex grid dynamics. It is common to use a sample average approximation to estimate the expectation of the second stage costs in this model. However, the large sample count needed for numerical accuracy makes effective modeling large-scale electric grids computationally intractable. We introduce a control variate multi-fidelity estimator for the second-stage recourse that enables high quality dispatch decisions in real-time with a reduced computational burden. We obtain a hierarchy of model fidelities by linearizing the AC power flow system representation to DC power flow, and by relaxing transmission and voltage network constraints. We evaluate the performance of our proposed method on a synthetic grid with 73 buses against a deterministic baseline with persistence forecast and a high-fidelity reference. Our analysis shows a computational speed-up of 7.62x with a minimal loss in accuracy. The multi-fidelity method is well suited to fidelity combinations that use a simplified network topology in their lower fidelity model and is an attractive option for applications where accurate grid modeling needed on a limited computational budget.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Isotopic composition of a sample enriched in 93 Zr

A project to determine the neutron-capture cross section of long lived fission products and minor actinides has been started by using a beam-line at Japan Proton Accelerator Research Complex (J-PARC). We prepared one of the target nuclides is Zr-93, which in Oak Ridge National Laboratory. Qualitative and quantitative analyses on the sample were performed at Kyoto University. The isotopic composition of (m) Zr (m 90, 91, 92, 93, 94, and 96) was precisely determined by multi-collector thermal ionization mass spectrometry with < 0.1 % of 2 sigma uncertainty. We determined that the atomic abundance of Zr-93 in the sample to be 18.86 ± A 0.05 %.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Sensitivity and Limitations of Structures from X-ray and Neutron-Based Diffraction Analyses of Transition Metal Oxide Lithium-Battery Electrodes

Lithium transition metal oxides are an important class of electrode materials for lithium-ion batteries. Binary or ternary (transition) metal doping brings about new opportunities to improve the electrode’s performance and often leads to more complex stoichiometries and atomic structures than the archetypal LiCoO 2 . Rietveld structural analyses of X-ray and neutron diffraction data is a widely-used approach for structural characterization of crystalline materials. But, different structural models and refinement approaches can lead to differing results, and some parameters can be difficult to quantify due to the inherent limitations of the data. Here, through the example of LiNi 0.8 Co 0.15 Al 0.05 O 2 (NCA), we demonstrated the sensitivity of various structural parameters in Rietveld structural analysis to different refinement approaches and structural models, and proposed an approach to reduce refinement uncertainties due to the inexact X-ray scattering factors of the constituent atoms within the lattice. Furthermore, this refinement approach was implemented for electrochemically-cycled NCA samples and yielded accurate structural parameters using only X-ray diffraction data. The present work provides the best practices for performing structural refinement of lithium transition metal oxides.

25 ENERGY STORAGE↗

Comparing residential contamination in a Houston environmental justice neighborhood before and after Hurricane Harvey

Polycyclic aromatic hydrocarbons (PAHs) are complex environmental toxicants; exposure to them has been linked to adverse health outcomes including cancer, as well as diseases of the skin, liver, and immune system. Based on an ongoing community engagement partnership with stakeholder groups and residents, we conducted a small longitudinal study to assess domestic exposure to PAHs among residents of Manchester, an environmental justice neighborhood located in the East End of Houston, TX. In December, 2016, we used fiber wipes to collect samples of household dust from 25 homes in Manchester. Following Hurricane Harvey, in September 2017, we revisited 24 of the 25 homes to collect soil samples from the front yards of the same homes. Wipes and soil were analyzed for the presence of PAHs using gas chromatography–mass spectrometry (GC-MS) methods. Principle component analysis plots, heatmaps, and PAH ratios were used to compare pre- and post-Hurricane Harvey samples. While direct comparison is difficult, we present three methods for comparing PAHs found in pre-hurricane fiber wipes and post-hurricane soil samples. The methods demonstrate that the PAHs found before and after Hurricane Harvey are likely from similar sources and that those sources are most likely to be associated with combustion. We also found evidence of redistribution of PAHs due to extreme flooding associated with Hurricane Harvey. Residents of the Manchester neighborhood of Houston, TX, are exposed to a range of PAHs in household dust and outdoor soil. While difficult to compare directly, we were able to use several methods to assess detected concentrations, changes in site-specific PAH allocations, and PAH origination. Additional research is needed to identify specific sources of domestic PAH exposure in these communities and continued work involving community members and policy makers should aim to develop interventions to reduce domestic exposure to and prevent negative health outcomes from PAHs.

54 ENVIRONMENTAL SCIENCES↗

Mechanisms of interfacial reactivity in near surface and extreme environments

The local water structure surrounding ions in aqueous solutions greatly affects their chemical properties such as reaction rates, ion association, and proton and electron transport. These properties result in the behavior of ions in natural aqueous environments. For example ore transport is facilitated by chloride ion pair formation and the reaction of ions in an interface is strongly dependent on the dehydration of the ion hydration shell. We are developing the use of high-­resolution XAFS observations and 1st principles based MD-­XAFS analysis (spectra simulated using 1st principle methods with no adjustable parameters, AIMD) to interpret the solution properties of strongly interacting aqueous solutes under arbitrary pressure and temperature conditions. In the 1st principle MD-­XAFS method density functional theory (DFT) based MD simulations(Car and Parrinello, 1985) are used to generate a large ensemble of structural snap shots of the hydration region. These are then used to generate scattering intensities. I emphasize three points about this novel approach to analyzing XAFS data. 1st: As illustrated in Figure 1, the level of agreement between the calculated and observed intensities is considerably higher than has been obtained by any XAFS analysis to date (note 2nd shell region, R> 2 Å). 2nd: This result was obtained from a parameter free simulation with no fitting of the interaction potentials to any data. This supports the use of these methods for more difficult environments and more complex solutes (polyions). 3rd: New information about the shell structure (Figure 1) is now available because of this more detailed agreement. We note also that both multiple scattering and second shell features are well represented in the analysis. As far as we know this is the 1st analysis of second shell structure and multiple scattering. Excellent agreement has been obtained for most of the third row metal ions: Ca 2+ , Zn 2+ , Cu 2+ , Ni 2+ , Co 2+ , Mn 2+ , Fe 3+ , Cr 3+ . Calculations on these systems are demanding because of their open electronic shells, and high ionic charge. Principal Investigator: Professor John Weare (University of California, San Diego) The prediction of the interactions of geochemical fluids with minerals, nanoparticles, and colloids under extreme near surface conditions of temperature (T) and pressure (P) is a grand challenge research need in geosciences (U.S. DOE 2007, Basic Research Needs for Geosciences: Facilitating the 21st Energy Systems.). To evaluate the impact of these processes on energy production and management strategies it is necessary to have a high level of understanding of the interaction between complex natural fluids and mineral formations. This program emphasizes 1st principle parameter free simulations of complex chemical processes in solutions, in the mineral phase, and in the interfaces between these phases The development of new computational tools (with emphasis on oxide materials and reaction dynamics) tailored to treat wide range of conditions and time scales experienced in such geochemical applications is has been developed. Because of the sensitivity of the interaction in these systems to electronic structure and local bonding environments, and of the need to describe bond breaking/formation, our simulations are based on interactions calculated at the electronic structure level (ab-initio molecular dynamics, AIMD). The progress in the computational aspects of program may be summarized in terms of the following themes (objectives); Development of efficient parameter free dynamical simulation technology based on 1st principles force and energy calculations especially adapted for geochemical applications (e.g., mineral, interfaces and aqueous solutions) (continuing program); Calculation of the dynamics of water structure of in the surface-water interface of transition metal oxides and oxihydroxides; and Development of improved (beyond DFT+GGA) electronic structure calculations for minerals and the interface region that more accurately calculate electron correlation, spin density, and localization. The focus of the program is also on the iron oxide and oxihydroxide minerals and Fe 2+ (aq)/Fe 3+ (cr) oxidation in the mineral solution interface region. These methods included the development of model Hamilitonian methods that can be solved to near convergence for single site models (DMFT) and many-body perturbation methods (MP2, GW); Development of time decomposition methods to extend time scales of molecular dynamics (MD) simulations and support the use of high complexity electronic structure calculations (MP2, CCSD(T)) of forces for use in dynamical simulations where very high chemical accuracy is required (microsolvated reactions in absorbed surface layers); and The development of a new linear scaling finite element solver for eigenvalue problem that supports solution of quantum problems with unusual potential and boundary values. Application progress of the above new simulation technology to problems of geochemical interests includes; The prediction of metal oxide surface structure and the reduction/oxidation of Fe 3+ (cr)/Fe 2+ (aq) in metal oxide (hematite, goethite)/solution interfaces. Result: water interacts strongly with the 001 Hematite surface; interaction of water with the 100 goethite is weak; The study of ion solvation and the composition of ion hydration shells under extreme conditions (focus on Fe 3+/2+ , Al 3+ and Mg 2+ and their hydroxide speciation). Result: Ion association in water solutions can be calculated from 1st principle methods. Efficient sampling of the free energy requires more development; The continued development of new high resolution analysis of XAFS scattering of disordered systems (particularly Al, Mg) and of XANES calculations for aqueous ions. Result: EXAFS spectra can be calculated to high accuracy with DFT level dynamic simulations; The exploration of electron localization and electron transport in metal oxides (highly correlated materials). Result: Proper description of electron localization requires levels of calculation beyond DFT; and Localization of electrons in DFT type Hamiltonians was studied. Result: For very Dirac high exchange new solutions (New unphysical bifrucations) to the eigenvalue problem are found. The program was highly collaborative involving faculty and students in mathematics, physics and computer science departments as well as coworkers at the Pacific Northwest National Laboratories (PNNL). The students in this program had the opportunity to develop skills in the development of methods, the implementation of method on high performance parallel computers and the application of these methods to problem in geochemical science. Much of the software that was developed was incorporated in the NWchem software package maintained by PNNL.

58 GEOSCIENCES↗

Thermodynamics of radiation induced amorphization and thermal annealing of Dy 2 Sn 2 O 7 pyrochlore

Thermodynamics and annealing behavior of swift heavy ion amorphized Dy 2 Sn 2 O 7 pyrochlore were studied. Its amorphization enthalpy, defined as the total energetic difference between the irradiation amorphized and undamaged Dy 2 Sn 2 O 7 states, was determined to be 283.6 ± 6.5 kJ/mol by high temperature oxide melt drop solution calorimetry. It has been an enigma that stannate and some other pyrochlores do not follow the general r A /r B -radiation resistance relation seen in most pyrochlore systems. In this paper, we use the amorphization enthalpy, which reflects all the complex chemical and structural characteristics, as a more effective parameter to correlate the radiation damage resistance of pyrochlores with their compositions. It successfully explains the superior radiation damage resistance of the stannate pyrochlores compared with titanate pyrochlores. Differential scanning calorimetry (DSC) reveals a strong exothermic event starting at 978 K, which is attributed to long-range recrystallization based on X-ray diffraction (XRD) analysis, similar to the effect previously observed in Dy 2 Ti 2 O 7 . A second pronounced heat event beginning at ~1148 K, which results from local structural rearrangement, is clearly decoupled from the first event for irradiated Dy 2 Sn 2 O 7 . Both the heat releases measured by DSC on heating to 1023 and 1473 K, and the excess enthalpies of the annealed samples indicate that the recovery to the original, ordered state was not fully achieved up to even 1473 K, despite XRD showing the apparent restoration of crystalline pyrochlore structure. The remaining metastability may be attributed to local disorder in the form of weberite-like short-range domains in the recrystallized material. Intriguingly, the second event for different pyrochlores generally starts at similar temperatures while the onset of the long range recrystallization is compositionally dependent. Finally, the amorphization and thermal annealing behavior observed in irradiated Dy 2 Sn 2 O 7 may provide insights into the general mechanisms of radiation damage and recovery of pyrochlores relevant to their nuclear applications.

36 MATERIALS SCIENCE↗

Report on PTT Imaging of Defects in AM Metallic Materials-Part 2

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study.

36 MATERIALS SCIENCE↗

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.

36 MATERIALS SCIENCE↗