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At least 37 records · Page 2

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 2

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 3

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 4

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 1

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024). Three distinct rounds of FSP experiments were performed by the experimental team, producing replicate samples utilizing across different nominal processing conditions (Condition IDs) listed in Table 1. The starting material on which FSP was applied was commercially available unprocessed stainless-steel type 316L material. Chosen processing conditions were very diverse, and some were intentionally chosen to produce defects. Several samples experienced tool breakage during experimentation, so a full set of three replicates was not produced for every nominal processing condition.

36 MATERIALS SCIENCE↗

Multi-decade high-resolution regional hindcasts for wave energy resource characterization in U.S. coastal waters

Long-term, high-resolution, regional wave hindcast datasets were generated using unstructured-grid Simulating WAves Nearshore (SWAN) models for the U.S. coastal waters to support nearshore wave energy development in the U.S. including those bordering U.S. territorial islands. The model domains resolved the entire U.S. exclusive economic zones, with a spatial resolution of approximately 200 m nearshore. The regional SWAN models were driven by the global WAVEWATCH III® model outputs and run for a 42-year period from 1979 to 2020. Extensive model validations were performed using buoy observations and altimeter data. Regional resource characterization was performed based on hindcast data points at 2 km from shore and along the 100 m isobath. Aggregations of wave resource parameters were produced, and spatial and seasonal variations were analyzed for all the regions. Wave resource metrics recommended by international standards, including a 3-hour time series of six resource parameters, hourly frequency- and directionally resolved wave spectra at selected “virtual buoy” locations, and average-annual values of omni-directional wave power, significant wave height, and energy period are publicly disseminated through an Amazon Web Service and a Marine Energy Atlas web application tool to facilitate wave energy research and a wide range of coastal ocean applications.

16 TIDAL AND WAVE POWER↗

Tidal energy resource characterization measurements at Cook Inlet’s East Foreland: Velocity and turbulence

To characterize tidal current and turbulence at a top tidal energy site off the East Foreland in Cook Inlet, Alaska, United States, three moorings were deployed for two months between July and August 2021, and a transect survey was conducted over the course of two tidal cycles at the end of the deployment period. Measurements of velocity and turbulence were then analyzed to better understand the site's hydrodynamics and power potential. Analysis reveals that swift, north-flowing flood currents peak at 4~m/s, while south-flowing ebb currents reach just over 3~m/s. Turbulence intensity ranges from 23\% at the seafloor to 8\% near the surface, and the presence of the foreland creates more intense turbulence near-shore during ebb tide than flood. Power availability at the site could be as high as 720~MW, or 13~kW/m$^2$, though the energy available to a marine energy device will be smaller than this estimate because of water-to-wire efficiency and wake losses. The results from this measurement campaign will inform the validation of a high-resolution tidal hydrodynamic model, as well as early tidal energy projects that are beginning to move beyond the prototyping and demonstration stages to full-scale deployments.

McVey, James R.↗

Characterization of mechanical deformation in aluminum by optical second harmonic generation

Second harmonic generation (SHG), a laser-based surface technique, was used to characterize near-surface defect evolution associated with mechanical deformation in 2024-T3 aluminum due to tensile loads. Electron backscatter diffraction (EBSD) measurements were also performed to determine the geometrically necessary dislocation density before and after tensile deformation. Comparison of the EBSD and SHG results found that dislocation density and SHG signal are inversely proportional; tensile deformation in the plastic regime led to an increase in dislocation density and a decrease in SHG response. A similar trend was seen in the SHG results on as-received (unpolished) Al samples; SHG response decreases with extent of plastic deformation. Furthermore, this study suggests that SHG has potential as a nondestructive evaluation technique.

36 MATERIALS SCIENCE↗

Ligand and Linkage Isomers of Bis(ethylthiocarbamato) Copper Complexes with Cyclic C 6 H 8 Backbone Substituents: Synthesis, Characterization, and Antiproliferation Activity

Abstract A series of isomeric bis(alkylthiocarbamate) copper complexes have been synthesized, characterized, and evaluated for antiproliferation activity. The complexes were derived from ligand isomers with 3‐methylpentyl (H 2 L 2 ) and cyclohexyl (H 2 L 3 ) backbone substituents, which each yield a pair of linkage isomers. The thermodynamic products CuL 2a/3a have two imino N and two S donors resulting in three five‐member chelate rings (555 isomers). The kinetic isomers CuL 2b/3b have one imino and one hydrazino N donor and two S donors resulting in four‐, six‐, and five‐member rings (465 isomers). The 555 isomers have more accessible Cu II/I potentials (E 1/2 =−811/−768 mV vs. ferrocenium/ferrocene) and lower energy charge transfer bands than their 465 counterparts (E 1/2 =−923/‐854 mV). Antiproliferation activities were evaluated against the lung adenocarcinoma cell line (A549) and nonmalignant lung fibroblast cell line (IMR‐90) using the MTT assay. CuL 2a was potent ( A549 EC 50 =0.080 μM) and selective ( IMR‐90 EC 50 / A549 EC 50 =25) for A549. Its linkage isomer CuL 2b had equivalent A549 activity, but lower selectivity ( IMR‐90 EC 50 / A549 EC 50 =12.5). The isomers CuL 3a and CuL 3b were less potent with A549 EC 50 values of 1.9 and 0.19 M and less selective with IMR‐90 EC 50 / A549 EC 50 ratios of 2.3 and 2.65, respectively. There was no correlation between reduction potential and A549 antiproliferation activity/selectivity.

Chemistry↗

A deep learning-guided automated workflow in LipidOz for detailed characterization of fungal fatty acid unsaturation by ozonolysis

Understanding fungal lipid biology and metabolism is critical for antifungal target discovery as lipids play central roles in cellular processes. Nuances in lipid structural differences can significantly impact their functions, making it necessary to characterize lipids in detail to enable and understanding of their roles in these complex systems. In particular, lipid double bond (DB) locations are an important component of lipid structure that can only be determined using a few specialized analytical techniques. Ozone-induced dissociation mass spectrometry (OzID-MS) is one such technique that uses ozone to break lipid DBs, producing pairs of characteristic fragments that allow the determination of DB positions. In this work we apply OzID-MS and LipidOz software to analyze the complex lipids of Saccharomyces cerevisiae yeast strains transfected with different fatty acid desaturases from Histoplasma capsulatum to determine the specific unsaturated lipids produce. The automated data analysis in LipidOz made the determination of DB positions from this large dataset more practical, but manual verification for all targets was still time-consuming. The DL model reduces manual involvement in data analysis, but since it was trained using mammalian lipid extracts, the prediction accuracy on yeast-derived data was reduced. We addressed both shortcomings by retraining the DL model to act as a pre-filter to prioritize targets for automated analysis, providing confident manually verified results but requiring less computational time and manual effort. Our workflow resulted in the determination of novel DB positions and enzymatic specificity.

mass spectrometry, deep learning, Lipidomics, doub↗

Direct observations and characterization of crack closure during microstructurally small fatigue crack growth via in-situ high-energy X-ray characterization

This study provides direct observation of the crack closure mechanism of a naturally occurring, tortuous, 3D microstructurally small fatigue crack (SFC) in additively manufactured Inconel 718. In-situ non-destructive characterization is performed using high-energy X-ray diffraction techniques to capture the evolution of the 3D microstructure and micromechanical response in the vicinity of the crack front. Based on the stress state of twelve grains analyzed at the crack tip, the crack closure events of the SFC front was found to be spatially heterogeneous with respect to loading progression governed by the local stress state of the grains (specifically the stress reversal from compression to tension). From this analysis, three grains that displayed different degrees of crack closure were further investigated, based on the orientation of the crack relative to the grains and the associated modality of crack growth. The stress normal to the crack plane and the associated degree of Mode I crack behavior were correlated with events of the crack opening earlier during the loading cycle. This was further corroborated by diffraction spot spreading analysis that quantified the crystallographic lattice distortion caused by the opening crack. Additionally, the detailed characterization of the opening behavior of the grains located at the crack tip and their associated states of stress elucidates the mechanism governing crack closure and will inform future modeling efforts of this phenomenon.

36 MATERIALS SCIENCE↗

Microstructure and water absorption of ancient concrete from Pompeii: An integrated synchrotron microtomography and neutron radiography characterization

There is renewed interest in using advanced techniques to characterize ancient Roman concrete due to its exceptional durability and low-carbon footprint. In the present work, samples were drilled from the “Hospitium” in Pompeii and were analyzed by synchrotron microtomography (μCT) and neutron radiography to study how the microstructure, including the presence of induced cracks, affects their water adsorption. The water distribution and absorptivity were quantified by neutron radiography. The 3D crack propagation, pore size distribution and orientation, tortuosity, and connectivity were analyzed from μCT results using advanced imaging methods. Porosity was also measured by mercury intrusion porosimetry (MIP) as a reference. Ductile fracture patterns were observed once cracks were introduced. Compared to Portland cement mortar/concrete, the Pompeii samples had relatively high porosity, low connectivity, and a similar coefficient of capillary penetration. In addition, permeability was predicted from models based on percolation theory and pore structure data to evaluate the fluid transport properties. Understanding the microstructure of ancient Pompeii concrete is important because it could inspire the development of modern concrete with high durability.

36 MATERIALS SCIENCE↗

Detector Characterization for Quantitative Spectral Radiography of Uranium Powder Samples

Pacific Northwest National Laboratory (PNNL) is developing a prototype spectral x-ray radiography (SpecX) non-destructive assay system for noninvasive material mass quantification of uranium-bearing powders. The SpecX system uses a custom material estimation algorithm, which requires a high-fidelity pixel-by-pixel detector response model for accurate quantification. We performed a detailed characterization and built a model of a High-Energy X-ray Imaging Technology (HEXITEC) CdTe pixelated spectral detector. Here we present the detector characterization which led to that model, including a determination of the pixel-wise energy calibration, the detection efficiency, the detector uniformity, the detector stability, and a comparison of methods to remove charge-shared events.

spectral X-ray radiography, pixelated detector, ca↗

Geospatial characterization of low-temperature heating and cooling demand in residential, commercial, manufacturing, agricultural, and data center sectors for potential geothermal applications in the United States

Thermal demand for heating and cooling has been predominantly supplied by fossil fuel combustion in the United States, although low-carbon alternatives are extensively available including geothermal, solar thermal, and waste heat. Here, this study analyzed end-use energy consumption, fuel expenditure, and data center commissioned power data to geospatially characterize the U.S. low-temperature heating and cooling demand at the county level in residential, commercial, manufacturing, agricultural, and data center sectors and understand potential opportunities for geothermal applications. In the analysis, the regional-scale energy consumption data was incorporated with system efficiencies to address actual demand and was then disaggregated with weighting factors to the county level. The results indicated that total low-temperature heating and cooling demand is 16.7 EJ, combining heating demand of 10.8 EJ and cooling demand of 5.9 EJ. Overall, 59.9 % (10 EJ) of the low-temperature heating and cooling demand occurred in the residential sector. The heating and cooling demand visualized in maps represented that the geospatial distribution of heating and cooling demand in the residential and commercial sectors is governed by the number of housing units and climate zone designations, while heating and cooling demand in the manufacturing, agricultural, and data center sectors is dependent on the number and location of facilities. The results also demonstrated that geothermal heat pumps are broadly used in the residential and commercial sectors for heating and cooling in the U.S. Midwest, South, and Northeast regions but are limited in the West, implying great decarbonization potential in the future.

15 GEOTHERMAL ENERGY↗