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At least 271 records · Page 15

Liquid Interfacial Electron Microscopy Identifies Nanogalvanic Corrosion in Pearlitic Steel

The nanoscale mechanisms of localized corrosion in low carbon steels have remained elusive due to the complexity of studying the degradative material behavior at nanoscale solid-liquid interfaces. We identified various steps in the nanogalvanic corrosion processes using in-situ liquid-cell scanning transmission electron microscopy (STEM) using a microfluidic holder by Hummingbird Scientific. Initial work, performed at low magnification, identified the initiation point on a 1018 low-carbon steel surface. This initiation point was determined to be a triple junction of two ferrite grains bridging a cementite grain in contact with a baseline electrolyte of 6 uM CO2 dissolved in a buffered (2.78 uM Na2SO4) aqueous solution, pH 6.1. The pre-etched low-carbon steel surface was prepared using focused ion beam lift-out procedures to extract a cross-section of the low-carbon steel surface, which then was thinned to about 150 nm and transferred to a SiN membrane microfluidic window. The transfer was made using a lift-out needle to attach the low-carbon steel lamella to the corner of the SiN window, and then Pt/C deposition held the lamella in contact with the window while it was released from the lift out needle. To identify the triple point on the low carbon steel lamella, prior to attachment on the SiN window, the sample was characterized for compositional variations with energy dispersive x-ray spectroscopy mapping, grain orientation and phase mapping with precession electron diffraction, and thickness mapping with energy filtered transmission electron microscopy. This pre-characterization prior to the in-situ experiment provided a map of the multiphase and multigrain structure, where the in-situ liquid cell imaging provided a clear understanding of the initiation point on the sample. These data were cross-correlated to paint a holistic picture of the triple junction site, enabling low electron-fluence in-situ snapshot imaging to avoid dominating the native corrosion reactions with effects from the incident electron beam. This initial result identified that localized, nanogalvanic corrosion at the phase interface was the dominant corrosion process in the low-carbon steel, so we next targeted the observation of an array of these nanogalvanic features phase boundaries in a pearlite grain. Near-surface ferrite/cementite phase interfaces that typify pearlitic low-carbon steel were extracted, pre-characterized, and imaged for the in-situ corrosion processes. The sample was a cross-section from a pearlite grain, with alternating ferrite and cementite grains that extended microns down from the pre-etched low-carbon steel pipe surface. After contact with a buffered aqueous solution, the phase boundaries between the ferrite and cementite began to dissolve, with observable material loss and thickness changes in the dark-field and bright-field STEM images. Within minutes, the corrosion front proceeded deeper into the material, claiming a thin layer of ferrite around all exposed phase boundaries before progressing laterally into the ferrite matrix, converting the ferrite to corrosion product normal to each buried cementite grain. Formation of the corrosion product causes a volumetric expansion, creating a lateral wedging force that mechanically ejects the cementite grains from their grooves and leaves behind percolation channels into the steel substructure. Rapid and deleterious, this nanogalvanic corrosion pathway represents an important target for understanding and preventing run-away degradation in this common building material. Observation of this corrosion mechanism was enabled by the combination of pre-characterization using standard structural, grain, and compositional analysis in the TEM, which provides maps for understanding the reaction propagation captured in low-dose, in-situ, liquid-cell STEM.

corrosion↗

Presentation on the INL Remote-Handled Low-Level Waste Disposal Facility FY-2024 Annual Summary Report

The abstract below is from the report INL/RPT-24-82600. The powerpoint presentation contains information taken from the report. This Fiscal Year (FY) 2024 annual summary report (ASR) documents the continued adequacy of the performance assessment (PA), the composite analysis (CA), and associated operating disposal authorization statement (ODAS) technical basis documents for the Remote Handled Low Level Waste (RHLLW) Disposal Facility at Idaho National Laboratory (INL). Annual review of the adequacy of the PA and CA for RHLLW Disposal Facility ensures that conclusions of the analyses remain valid in accordance with requirements of the U.S. Department of Energy (DOE) Order 435.1, “Radioactive Waste Management.” In FY 2024, no significant operational changes or other activities occurred that would cause deviation from the assumptions in the PA and CA pertaining to disposal geometry, verification of waste characteristics, tracking disposal inventories against total limits, facility closure design, or institutional controls. Nineteen waste canister shipments were received at the RHLLW Disposal Facility, and all nineteen waste canisters were emplaced in disposal vaults.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗

Presentation on the INL Remote-Handled Low-Level Waste Disposal Facility FY-2023 Annual Summary Report

The abstract below is from the report INL/RPT-24-76103. The powerpoint presentation contains information taken from the report. This Fiscal Year (FY) 2023 annual summary report (ASR) documents the continued adequacy of the performance assessment (PA), the composite analysis (CA) and associated operating disposal-authorization statement (ODAS) technical basis documents for the Remote Handled (RH) Low-Level Waste (LLW) Disposal Facility at Idaho National Laboratory. Annual review of the adequacy of the PA and CA for the RHLLW Disposal Facility ensures that conclusions of the analyses remain valid in accordance with requirements of Department of Energy (DOE) Order 435.1, “Radioactive Waste Management.” In FY 2023, no significant operational changes or other activities occurred that would cause deviation from the assumptions in the PA and CA pertaining to disposal geometry, verification of waste characteristics, tracking disposal inventories against total limits, facility closure design, or institutional controls. Sixteen total waste-canister shipments were received at the RHLLW Disposal Facility, and 15 total waste canisters were emplaced.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗

Reliability, biological variability, and accuracy of multi-frequency bioelectrical impedance analysis for measuring body composition components

Introduction Bioelectrical impedance analysis (BIA) systems are gaining popularity for use in research and fitness assessments as the technology improves and becomes more affordable and easier to use. Multifrequency BIA (MF-BIA) may improve accuracy and precision using octopolar contacts for segmental analyses. Purpose Evaluate reliability, biological variability, and accuracy of component measures (total body water, mass, and composition) of commercially available MF-BIA system (InBody 770, Cerritos, California, USA). Methods Fourteen healthy military-age adults were assessed by MF-BIA in duplicate on five laboratory visits across 3 weeks (10 measures each). Participants were evaluated at the same time of day after refraining from strenuous exercise (> 48 h), alcohol consumption (> 24 h), and caffeine, nicotine, and food (> 10 h). Systematic error (test–retest reliability) and biological variability (day-to-day reliability) were summarized by intraclass correlation coefficient (ICC) values determined for body mass (fat, fat-free, total) and body water (extracellular, intracellular, total). Body composition measurements derived from BIA on the second visit were also tested for accuracy compared to dual-energy x-ray absorptiometry (DXA). Results Test–retest reliability was very high for all measurements of whole-body water and mass (ICC ≥ 0.999) and high for regional body water and mass (ICC 0.973–1.000). Biological variability was observable with very minor differences between tests (same day) for total and regional body water (0.0–0.2 L) and total and regional body mass measurements (0.0–0.2 kg); while between day differences were slightly higher (0.0–0.5 L and 0.1–0.7 kg). Compared to DXA, the MF-BIA whole-body measures showed an offset in %BF (Bias −4.0 ± 2.8%; Standard error of the estimate (SEE), 2.6%), an overprediction for total body fat-free mass (Bias 2.8 ± 2.1 kg; SEE 2.2 kg) and an underprediction of total body fat mass (Bias −2.9 ± 2.0 kg; SEE 1.9 kg). Conclusion Under controlled conditions with fit and healthy men and women, this MF-BIA system has high methodological reliability and demonstrates stable day-to-day measurements of major body composition components. Previously reported ~3% body fat offset compared to criterion methods was again confirmed. Precision of the InBody 770 shows consistency and supports further testing of this specific device as a new military standards method and suitability across a wider range of %BF.

Nutrition & Dietetics↗

3D printing of packaging inserts from biomass-fungi composites: Environmental sustainability analysis

In this study, a comprehensive Life cycle assessment (LCA) is conducted on molded packaging inserts from expanded polystyrene (EPS) foam, molded packaging inserts from biomass-fungi composite, and 3D-printed packaging inserts from biomass-fungi composite under the low mix / high volume (LMHV) scenario and molded and machined packaging inserts from EPS foam, molded and machined packaging inserts from biomass-fungi composite, and 3D-printed packaging inserts from biomass-fungi composite under the high mix / low volume (HMLV) scenario. Six environmental impact categories—climate change, acidification, eutrophication, fossil resource scarcity, land use, and water consumption—are analyzed to evaluate the environmental trade-offs associated with each type of packaging inserts. Under the LMHV scenario, molded packaging inserts from biomass-fungi composite emerge as the best option due to their lower impact on climate change, acidification and water consumption compared to other types of packaging inserts. Conversely, molded packaging inserts from biomass-fungi composite face challenges in land use and eutrophication, primarily due to raw material production. LCA also reveals that 3D-printed packaging inserts from biomass-fungi composite are the most environmentally favorable option under the HMLV scenario, due to significantly lower contributions to climate change, eutrophication, and water consumption compared to other types of packaging inserts. Conversely, 3D-printed packaging inserts from biomass-fungi composite face challenges in acidification and land use, primarily due to raw material production. As part of the LCA, sensitivity analyses show that sourcing energy from 100% renewable sources substantially lowers climate change impacts across all packaging types, while varying transportation distances results in only minor changes, indicating the dominant role of upstream material and manufacturing processes. Additional sensitivity analysis is conducted under the HMLV scenario to assess the impact of material removal during machining on the environment. The amount of material removal is varied from 10 to 70% for the sensitivity analysis and it highlights that the amount of material removed during machining has no significant impact on climate change for packaging inserts from EPS foam. However, molded and machined packaging inserts from biomass-fungi composite show an increasing trend in climate change with higher amount of material removal, while 3D-printed packaging inserts from biomass-fungi composite exhibit a decreasing trend, driven by reduced raw material usage and energy consumption.

09 BIOMASS FUELS↗

ToF-SIMS Analysis of Chemical Composition of Atmospheric Aerosols in Beijing

Atmospheric aerosols collected from each season in urban Beijing have been studied using time-of-flight secondary ion mass spectrometry (ToF-SIMS). The chemical composition of atmospheric aerosol particles during various atmospheric pollution levels were analyzed and distinguished by principal component analysis (PCA). The differences and sources of the components of the aerosol particles were explored. The results showed that the fine particulate matter from heavily polluted days mainly consists of inorganic salts and organic compounds, such as hydrocarbons, nitrogen- or sulfur-containing hydrocarbons, and their oxides. Samples collected from clean days in the four seasons were also analyzed. Only the samples collected in spring showed a significant difference from the other three seasons. We concluded that the main source of pollution in the Beijing urban area was fossil fuel combustion from motor vehicles.

ToF-SIMS, principal component analysis↗

HPTLC Analysis and Chemical Composition of Selected Melaleuca Essential Oils

Tea tree oil (TTO) is a volatile essential oil obtained by distillation, mainly from the Australian native plant Melaleuca alternifolia (Maiden & Betche) Cheel (Myrtaceae). In this study, a comparative analysis of the chemical constituents of seven tea tree oils (M. alternifolia) and four other Melaleuca spp. oils (M. cajuputi, (M Ca ), two chemotypes of M. quinquenervia, (M Ne and M Ni ), and M. ericifolia (M Ro )) was carried out using gas chromatography–mass spectrometry (GC-MS) and high-performance thin-layer chromatography (HPTLC). Among the seven TTOs, terpinen-4-ol (37.66–44.28%), γ-terpinene (16.42–20.75%), α-terpinene (3.47–12.62%), α-terpineol (3.11–4.66%), and terpinolene (2.75–4.19%) were the most abundant compounds. On the other hand, the most abundant compounds of the other Melaleuca oils varied, such as 1,8-cineole (64.63%) in M Ca oil, (E)-nerolidol (48.40%) and linalool (33.30%) in M Ne oil, 1,8-cineole (52.20%) in M Ni oil, and linalool (38.19%) and 1,8-cineole (27.57%) in M Ro oil. HPTLC fingerprinting of Melaleuca oils enabled the discrimination of TTO oils from other Melaleuca spp. oils. Variation was observed in the profile of the R f values among EOs. The present study shows that HPTLC is one of the best ways to identify and evaluate the quality control in authenticating TTOs, other Melaleuca EOs, or EOs from other species within the Myrtaceae.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Composition-Nanoarchitecture-Performance Analysis of High Energy Density Electrodeposited Silicon for Lithium-Ion Battery Anodes

Electrodeposition of silicon (Si) was previously demonstrated as a promising method for fabricating 3D-structured lithium-ion battery anodes. However, the relationship between the electrochemical performance and chemical composition of the relatively impure electrodeposited silicon is not well understood. Here, we report the electrodeposition of a Si-dominant active material (EDEP-Si) onto 3D-structured nickel (Ni) scaffolds and systematically compare the electrochemical properties, elemental composition, atomistic Si coordination, and molecular structure of EDEP-Si with high-purity amorphous Si grown via static chemical vapor deposition. Despite the considerable amount of carbon (9–11 at %) and oxygen (42–44 at %) present in EDEP-Si, the cycling stability and high reversible specific capacity are remarkably similar to those of CVD-Si on a silicon basis (~2400 mA h/g-Si after 100 cycles). The primary difference is that EDEP-Si exhibits reduced cycling efficiency over the first 10–20 cycles. Reactions between carbon and, more importantly, oxygen in EDEP-Si with lithium are likely responsible for the reduced early cycle performance and lower capacity of the total deposit. Finally, our observations suggest ultrapure Si is not necessary for high electrochemical access to reversible charge storage, although limiting the presence of incorporated impurity species would improve energy density and first cycle efficiency.

25 ENERGY STORAGE↗

A robust clustering algorithm for analysis of composition-dependent organic aerosol thermal desorption measurements

Abstract. One of the challenges of understanding atmospheric organic aerosol (OA) particles stems from its complex composition. Mass spectrometry is commonly used to characterize the compositional variability of OA. Clustering of a mass spectral dataset helps identify components that exhibit similar behavior or have similar properties, facilitating understanding of sources and processes that govern compositional variability. Here, we developed an algorithm for clustering mass spectra, the noise-sorted scanning clustering (NSSC), appropriate for application to thermal desorption measurements of collected OA particles from the Filter Inlet for Gases and AEROsols coupled to a chemical ionization mass spectrometer (FIGAERO-CIMS). NSSC, which extends the common density-based special clustering of applications with noise (DBSCAN) algorithm, provides a robust, reproducible analysis of the FIGAERO temperature-dependent mass spectral data. The NSSC allows for the determination of thermal profiles for compositionally distinct clusters of mass spectra, increasing the accessibility and enhancing the interpretation of FIGAERO data. Applications of NSSC to several laboratory biogenic secondary organic aerosol (BSOA) systems demonstrate the ability of NSSC to distinguish different types of thermal behaviors for the components comprising the particles along with the relative mass contributions and chemical properties (e.g., average molecular formula) of each mass spectral cluster. For each of the systems examined, more than 80 % of the total mass is clustered into 9–13 mass spectral clusters. Comparison of the average thermograms of the mass spectral clusters between systems indicates some commonality in terms of the thermal properties of different BSOA, although with some system-specific behavior. Application of NSSC to sets of experiments in which one experimental parameter, such as the concentration of NO, is varied demonstrates the potential for mass spectral clustering to elucidate the chemical factors that drive changes in the thermal properties of OA particles. Further quantitative interpretation of the thermograms of the mass spectral clusters will allow for a more comprehensive understanding of the thermochemical properties of OA particles.

54 ENVIRONMENTAL SCIENCES↗

A User-Friendly GUI Tool for Automated Microstructural Analysis of Fiber-Reinforced Composites and Porous Structures

Understanding and quantifying microstructural features such as fiber orientation and porosity is critical for predicting the mechanical behavior and performance of fiber-reinforced polymer composites. Traditional manual analysis is time-consuming, subjective, and unsuitable for high-throughput datasets. We present a graphical user interface (GUI) application that automates the analysis of microscopy images to extract key microstructural metrics, including fiber orientation tensors, fiber orientation distribution, porosity and pore size distribution. The app integrates multiple image segmentation techniques including global and local thresholding, clustering, and region-based approaches, offering flexibility for different types of image qualities and features. Users can load microstructural images, select regions of interest and segmentation techniques tailored to their image dataset. It also addresses a critical challenge in fiber orientation analysis: the ambiguities caused by touching, overlapping, or partially cut fibers. It supports autorun examples for standardized workflows, enabling reproducible analysis and facilitating training and benchmarking. This tool significantly reduces manual intervention, enhances consistency, and accelerates data generation for structure–property modeling, process optimization, and digital materials research. The tool is intended for use by materials scientists, engineers, and researchers engaged in composite characterization, quality control, and machine learning-based microstructural studies.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗

Novel Proppant Logging Technique for Infill Drilling of Unconventional Shale Wells

Summary During the development of an unconventional play, wells are drilled and completed in batches, and depending on the development plans, current and expected energy market trends, as well as other developmental considerations, new wells are drilled and hydraulically fractured later near existing producing laterals. This creates challenges in terms of optimizing resource recovery and reducing interwell communication. A novel approach is proposed that utilizes systematic composite sampling and analysis of drilling mud returns to look for and quantitatively identify sand particles. The workflow involves cleaning, drying, and segregation of samples into sizes of interest to us (size distribution of pumped proppant in offset parent wells). These samples are imaged at a very high resolution and analyzed for grains using characteristic optical imaging properties to classify proppant sand particles using computer vision algorithms. Further analysis, such as elemental compositional analysis, is used to validate the results from the imaging workflow. We present a case study from the Permian Basin, where a new child well was used as a test case to prove this technology at the Hydraulic Fracturing Test Site (HFTS-2) in Delaware Basin. We introduce new proppant parameters that help identify sustained proppant zones vs. localized propped fractures. We have used additional diagnostics and data collected at the test site to validate observations from the proppant log and have successfully interpreted significantly propped vs. unpropped zones. A key finding from this test has been the significant proppant transport distances observed away from parent wells. Observable proppant was found at a lateral distance of approximately 425 m for one set of parent wells and more than 915 m for another set of parent wells. While a major limitation of this technique is the sampling rate, given adequate sampling, the proposed technology represents a systematic and one-of-a-kind interpretation of spatial proppant distribution while drilling infill wells. It provides us with unique opportunities to better understand the current state of the reservoir being targeted, including zones that are likely highly drained relative to others, and how the planned hydraulic fracturing of child wells can be improved.

Energy & Fuels↗

Orbitrap LC-MS Analysis of Nanoparticle Composition at the EPCAPE Mount Soledad site between 04 18 2023 and 06 14 2023

Weekly peak lists containing m/z, intensity, and assigned formula for filter samples, size selected for sub-100 nm particles. Filters were collected daily between 4/18/23 and 6/14/23, grouped based on calendar week for extraction, and analyzed via Thermo Scientific Q Exactive Plus Orbitrap LC-MS. Formulas were assigned to background-corrected peak lists and restricted to CHONS/CHONSNa atoms for the negative and positive modes respectively. Filters were grouped into calendar weeks 0-8 with dates provided in README text file.

54 ENVIRONMENTAL SCIENCES↗