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At least 235 records · Page 13

Characterization of shale using Helium and Argon at high pressures

In order to estimate the shale gas in place and the eventual recovery during shale gas operations, one of the key requirements is to accurately characterize the shale’s petrophysical and transport properties such as porosity, permeability, diffusivity, and storage capacity. Despite the many efforts reported in the technical literature aiming to provide an improved understanding of the complex pore structures and the associated fluid flow in gas shales, complete characterization of organic-rich shale samples still poses a big challenge. Here, we have characterized mass transfer and sorption in shale at different length scales using Helium (He) and Argon (Ar) as probe gases. Thermogravimetric analysis (TGA) with a shale cube of ~1 cm 3 in size and gas expansion experiments with a full-diameter core (3.5” in diameter) were used to measure sorption kinetics/isotherms and mass transfer, respectively. Both samples are from the same depth/location in the Marcellus shale formation. The TGA steady-state technique was initially used to generate excess sorption isotherms for Ar, while dynamic TGA experiments were used to study its sorption kinetics. The TGA experiments demonstrate that Ar, which has a similar sorption potential as Methane, but is generally assumed to be inert, adsorbs onto the surfaces of the mesoporous and microporous regions of the shale samples according to a Langmuir-type behavior. Helium expansion experiments, on the full-diameter core, were used to measure the overall porosity, on the basis that He is a non-sorbing and inert gas as compared to Ar. The He expansion experiments, furthermore, allow us to delineate the mass transfer of gas across the inherent hierarchy of pore sizes, including macropores (macro- and microcracks), mesopores and micropores. Similar expansion experiments were also performed with Ar to study the combined impact of mass transfer and sorption. A triple-porosity model (TPM) was utilized to interpret the He expansion experiments with the shale core and to extract (estimate) relevant transport parameters. We report and compare here the diffusivities and permeabilities of the whole core for both He and Ar, as calculated from the modeling and fitting of the experimental data. On the premise that the shale cube is representative of the matrix region of the core, the Ar sorption kinetics from the cube experiments were subsequently combined with the transport parameters extracted from the He experiments to predict the behavior of the Ar expansion test with the full-diameter core. An excellent agreement is observed between the model predictions and the experimental data. The experimental observations and their interpretation indicate that one must be cautious when using Ar to estimate the true porosity and permeability of shales. In addition, we demonstrate that He and Ar probe gases, when used in tandem, can be employed effectively as a tool to characterize shales in terms of mass transfer and sorption dynamics across scales.

04 OIL SHALES AND TAR SANDS↗

MULTI-MODAL global surveillance methodology for predictive and on-demand characterization of localized processes using cube satellite platforms and deep learning techniques

This paper presents the work completed towards the development of a multi-modal global surveillance methodology using cube satellite (CubeSat) platforms and novel data analysis techniques. A CubeSat system equipped with adequate sensors and data analytics capabilities can autonomously characterize various phenomena of interest on the Earth’s surface. CubeSats are advantageous over conventional satellites in certain remote monitoring applications because of their reduced construction costs (due to the availability of commercially-off-the-shelf components) and are easier to launch. The CubeSat surveillance system developed in this paper focused on phenomena of interest surrounding the nuclear fuel cycle in support of nuclear non-proliferation and emergency response. To observe the phenomena, a constellation of 3U and 6U CubeSats deployed from the ISS with adequate components was chosen. Four different sensor configurations were identified for remote sensing: panchromatic/multispectral in the visible and near-infrared spectrum, multispectral in infrared spectrum, hyperspectral in infrared spectrum, and multispectral in ultraviolet spectrum. While a panchromatic/multispectral sensor configuration has CubeSat flight heritage at the required spatial resolutions, the other three sensor types need future 3 development to meet signature and system requirements. Once each sensor onboard the CubeSat system collects data on a target of interest, the onboard computers would then apply the deep learning-based characterization methodology developed in this paper to identify phenomena. Four surrogate datasets containing representative simplified “images” were created for each sensor type to train the characterization methodology. A convolutional neural network was applied to each dataset and produced recall rates for the phenomena between 89.7% - 99.3% and precision rates between 92.3% - 99.9%. Each phenomenon’s presence probability from each network is then combined into a final characterization solution for a target area. This paper covers multiple interdisciplinary areas to develop the foundation for a CubeSat surveillance system focused on phenomena surrounding the nuclear fuel cycle.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Characterization of transverse electron pulse trains using RF powered traveling wave metallic comb striplines

Advancements in ultrafast electron microscopy have allowed elucidation of spatially selective structural dynamics. However, as the spatial resolution and imaging capabilities have made progress, quantitative characterization of the electron pulse trains has not been reported at the same rate. In fact, inexperienced users have difficulty replicating the technique because only a few dedicated microscopes have been characterized thoroughly. Systems replacing laser driven photoexcitation with electrically driven deflectors especially suffer from a lack of quantified characterization because of the limited quantity. The primary advantages to electrically driven systems are broader frequency ranges, ease of use and simple synchronization to electrical pumping. Here, we characterize the technical parameters for electrically driven UEM including the shape, size and duration of the electron pulses using low and high frequency chopping methods. At high frequencies, pulses are generated by sweeping the electron beam across a chopping aperture. For low frequencies, the beam is continuously forced off the optic axis by a DC potential, then momentarily aligned by a countering pulse. Using both methods, we present examples that measure probe durations of 2 ns and 10 ps for the low and high frequency techniques, respectively. Here, we also discuss how the implementation of a pulsed probe affects STEM imaging conditions by adjusting the first condenser lens.

36 MATERIALS SCIENCE↗

Multiscale characterization and representation of variability in ceramic matrix composites

Low density, high strength, and high creep and oxidation resistance properties of ceramic matrix composites (CMCs) make them an ideal choice for use in extreme environments in space and military applications. This paper presents a detailed characterization study of structural and manufacturing flaws in Carbon fiber Silicon-Carbide-Nitride matrix (C/SiNC) CMCs at different length-scales. Energy-dispersive spectroscopy (EDS) is used for the chemical characterization of the material’s elemental constituents. High-resolution multiscale graphs obtained from scanning electron microscope (SEM) and confocal laser scanning microscope (LSM) are used to characterize the distribution and morphology of defects at different length scales. This is followed by the classification and quantification of the common manufacturing defects. An image processing algorithm based on the image segmentation process is developed to quantify the variability of various scale-dependent architectural parameters. Finally, a three-dimensional stochastic representative volume element (SRVE) generation algorithm is developed to provide precise representations of material textures at multiple length scales. The developed algorithm accurately accounts for material features and flaws based on a range of multiscale structural and defects characterization results.

36 MATERIALS SCIENCE↗

EVSE Characterization, A Next-Gen Profiles Project Report

As part of the U.S. DOE EVs@Scale consortium Next-Generation Profiles project, results and analysis from the characterization of high-power conductive and wireless charging infrastructure are presented. This characterization was conducted over a wide range of DC output current and DC voltage charging for nominal test conditions and off-nominal test conditions. Test plans and procedures were developed to define the test configurations and requirements, measurement parameters, and test procedures used throughout testing. Results from a 2023 study conducted on electric vehicle supply equipment (EVSE) characterization by Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) include one 350 kW capable EVSE using a liquid-cooled combined charging system-1 (CCS-1, North American version) cable and connector and an ORNL-developed 100-kW polyphase wireless charger. Characterization results during nominal operation show the AC-to-DC power transfer efficiency for the 350kW conductive EVSE is 95.1% peak and is >92% when the AC power is at least 50 kW. The power quality of the 350 kW conductive EVSE is also measured during nominal conditions. The power factor is >0.91 for power transfer above 50 kW AC input during nominal conditions with a maximum power factor of 0.975. The AC current harmonics produced by the EVSE as measured at the AC input connection to the EVSE is <25% harmonics for power transfer greater than 50 kW and <10% harmonics for power transfer greater than 180 kW.

25 ENERGY STORAGE↗

Characterization of Tank 9H Annulus Sample in Support of Residual Material Inventory Determinations

The Savannah River National Laboratory (SRNL) was requested by Savannah River Mission Completion (SRMC) to provide sample preparation and characterization of the Tank 9H annulus sample in support of Residual Material Inventory Determinations. One Tank 9H sample in three vials [HTF-9-25-13, HTF-9-25-14 and HTF-9-25-15], with each vial containing approximately 200 mL of the Tank 9H annulus salt solution, were delivered to the SRNL Shielded Cells for sample preparation and characterizations in February 2025. The density of the “as-received” solution contained in each of the three Tank 9H annulus sample vials were determined followed by a solid-liquid separation on each one using 0.45-micron Nalgene® nylon filter membranes. The resulting filtrates were combined to form the Tank 9H annulus sample with a total volume of about 600 mL. The combined wet solid fractions, about a total of 4.8 grams of salt material, remaining on the filter membranes were air-dried in the Shielded Cells for 72 hours. The total weight of the air-dried solids was 2.1 grams. These air-dried solids were washed with deionized water (DI water) at a phase ratio of 60 mL DI water/gram of solids to recover insoluble solids, if any. No visible or measurable quantity of insoluble solids were recovered after DI water washing of the air-dried solids because the air-dried solids completely dissolved in the DI water. The solid fraction-wash water was not combined with the 600 mL of the filtrate solution, and the resulting solution was not screened or analyzed for radionuclides. Aliquot sample volumes of the undiluted Tank 9H annulus sample were sent to the SRNL analytical services groups for radionuclides, elementals, anions and total mercury analysis by various methods including radiochemical separations/counting methods, inductively coupled plasma-atomic emission spectroscopy (ICP-AES), and Inductively Coupled Plasma Mass Spectroscopy (ICP-MS) and special preparations. All sample analyses were performed in triplicate. This report presents the analytical characterization results for the Tank 9H annulus sample. The results are also reported where analytical methods yielded additional analytes, other than those requested by SRMC. In the characterization of the Tank 9H annulus sample, the detection limits for all the analytes, as specified in the Technical Task Request (TTR) and Task Technical and Quality Assurance Plan (TTQAP), were met.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Seismic Characterization of the Blue Mountain Geothermal Field

Subsurface characterization is crucial for geothermal energy exploration and production. Yet hydrothermal reservoirs usually reside in highly fractured and faulted zones where accurate characterization is very challenging because of low signal-to-noise ratios of land seismic data and lack of coherent reflection signals. We perform an active-source seismic characterization for the Blue Mountain geothermal field in Nevada using active seismic data to reveal the elastic medium property complexity and fault distribution at this field. We first employ an unsupervised machine learning method to attenuate groundroll and near-surface guided-wave noise and enhance coherent reflection and scattering signals from noisy seismic data. We then build a smooth initial P-wave velocity model based on an existing magnetotellurics survey result, and use 3D first-arrival traveltime tomography to refine the initial velocity model. We then derive a set of elastic wave velocities and anisotropic parameters using elastic full-waveform inversion, and obtain PP and PS images using elastic reverse-time migration. We identify major faults by analyzing the variations of seismic velocities and anisotropy parameters, and reveal mid- to small-scale faults by applying a supervised machine learning method to the seismic migration images. Our characterization reveals complex velocity heterogeneities and anisotropies, as well as faults, with a high spatial resolution. These results can provide valuable information for optimal placement of future injection and production wells to increase geothermal energy production at the Blue Mountain geothermal power plant.

58 GEOSCIENCES↗

On a Unified Core Characterization Methodology to Support the Systematic Assessment of Rare Earth Elements and Critical Minerals Bearing Unconventional Carbon Ores and Sedimentary Strata

A significant gap exists in our understanding and ability to predict the spatial occurrence and extent of rare earth elements (REE) and certain critical minerals (CM) in sedimentary strata. This is largely due to a lack of existing, systematic, and well-distributed REE and CM samples and analyses in United States sedimentary basins. In addition, the type of sampling and characterization performed to date has generally lacked the resolution and approach required to constrain geologic and geographic heterogeneities typical of subsurface, mineral resources. Here, we describe a robust and systematic method for collecting core scale characterization data that can be applied to studies on the contextual and spatial attributes, the geologic history, and lithostratigraphy of sedimentary basins. The methods were developed using drilled cores from coal bearing sedimentary strata in the Powder River Basin, Wyoming (PRB). The goal of this effort is to create a unified core characterization methodology to guide systematic collection of key data to achieve a foundation of spatially and geologically constrained REEs and CMs. This guidance covers a range of measurement types and methods that are each useful either individually or in combination to support characterization and delineation of REE and CM occurrences. The methods herein, whether used in part or in full, establish a framework to guide consistent acquisition of geological, geochemical, and geospatial datasets that are key to assessing and validating REE and CM occurrences from geologic sources to support future exploration, assessment, and techno-economic related models and analyses.

54 ENVIRONMENTAL SCIENCES↗

Region-Based Convolutional Neural Network for Wind Turbine Wake Characterization in Complex Terrain

We present a proof of concept of wind turbine wake identification and characterization using a region-based convolutional neural network (CNN) applied to lidar arc scan images taken at a wind farm in complex terrain. We show that the CNN successfully identifies and characterizes wakes in scans with varying resolutions and geometries, and can capture wake characteristics in spatially heterogeneous fields resulting from data quality control procedures and complex background flow fields. The geometry, spatial extent and locations of wakes and wake fragments exhibit close accord with results from visual inspection. The model exhibits a 95% success rate in identifying wakes when they are present in scans and characterizing their shape. To test model robustness to varying image quality, we reduced the scan density to half the original resolution through down-sampling range gates. This causes a reduction in skill, yet 92% of wakes are still successfully identified. When grouping scans by meteorological conditions and utilizing the CNN for wake characterization under full and half resolution, wake characteristics are consistent with a priori expectations for wake behavior in different inflow and stability conditions.

17 WIND ENERGY↗

AGC 4 Graphite Specimen Postirradiation Characterization Plan

This characterization plan describes the thermal, physical, and mechanical measurement techniques that will be used to characterize graphite samples being tested in the fourth Advanced Graphite Creep experiment (AGC-4). Instruments, fixtures, and methods are currently in place for both pre and postirradiation material property measurements of bulk density, thermal diffusivity, coefficient of thermal expansion, elastic modulus, and electrical resistivity. Postirradiation testing procedures used to characterize the samples are described and discussed in the plan. Where they exist, American Society for Testing and Materials (ASTM) International testing standards will apply to the tests. Any departure from ASTM International testing standards or the approved laboratory procedures are documented within this characterization plan. Deviations that occur during testing will be documented in data reports.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Advanced Characterization Techniques for Overcoming Challenges of Perovskite Solar Cell Materials

Abstract In the last 10 years, organic–inorganic hybrid perovskite solar cells have achieved unprecedented advances, to the point where they now exhibit extremely high efficiency. However, long‐term stability and areal scalability limitations impede the commercial application of perovskite materials, and appropriate diagnosistic tools have become necessary to evaluate perovskite materials. Characterization of perovskite materials is regularly misinterpretated, due to unique intrinsic and extrinsic factors: degradation from the measurement source, ion migration, phase transition, and separation. Herein, studies on perovskites are reviewed that have used advanced characterization tools to overcome characterization challenges. Cryogenic temperature assisted measurements mitigate degradation or phase transitions induced by the measurement source. In situ measurements can track the variation of perovskite materials depending on external stimuli. Spatial material properties are able to be evaluated by the use of multidimensional mapping techniques. An overview of these advanced characterization tools that can overcome the challenges associated with established tools provides the opportunity for further understanding perovskite materials and solving the remaining challenges on the road to commercialization.

Kim, Min‐cheol↗

A Review of Existing and Emerging Methods for Lithium Detection and Characterization in Li-Ion and Li-Metal Batteries

Whether attempting to eliminate parasitic Li metal plating on graphite (and other Li-ion anodes) or enabling stable, uniform Li metal formation in ‘anode-free’ Li battery configurations, the detection and characterization (morphology, microstructure, chemistry) of Li that cannot be reversibly cycled is essential to understand the behavior and degradation of rechargeable batteries. In this review, various approaches used to detect and characterize the formation of Li in batteries are discussed. Each technique has its unique set of advantages and limitations, and works towards solving only part of the full puzzle of battery degradation. Going forward, multimodal characterization holds the most promise towards addressing two pressing concerns in the implementation of the next generation of batteries in the transportation sector (viz. reducing recharging times and increasing the available capacity per recharge without sacrificing cycle life). Such characterizations involve combining several techniques (experimental- and/or modeling-based) in order to exploit their respective advantages and allow a more comprehensive view of cell degradation and the role of Li metal formation in it. Additionally, it is also discussed which individual techniques, or combinations thereof, can be implemented in real-world battery management systems on-board electric vehicles for early detection of potential battery degradation that would lead to failure.

25 ENERGY STORAGE↗

Characterizing Disorders Within Cathode Materials of Lithium‐Ion Batteries

The demand for developing high-energy density cathode materials has been increasing. The energy densities of cathode materials have been improved by adapting structural deviation from the ideal fully ordered α-NaFeO2 type, but that led to limitations in terms of structural stability and safety. Although disorders in cathode materials are closely related to their electrochemical properties, unfortunately, characterizing the disorder itself in cathode materials has been challenging due to its complex parasitic reaction and strong correlation with other disorders occurring during charge/discharge. In this review, we categorize various disorders by their scales of ordering from short-range to long-range. We addressed the principles of various characterization tools to figure out how they can help to identify the structural disorder in cathode materials. Specifically, we focused on the underlying principles of each characterization technique to correlate different disorder-driven phenomena through several case studies. It underscores the substantial importance of disorder-property relationships and the corresponding characterization methods, which can provide novel research strategies for developing high-energy density cathode materials with decent structural stability.

Lee, Hakwoo↗

Ultrasound Characterization of Plastic Bonded Explosives With Varied Binder Content and Density

Advanced explosive formulations and methods of production require rapid characterization for both processes and materials. Here, we present results for ultrasound characterization of a plastic bonded explosive (PBX) formulation as a function of binder weight percent and pressing density using through-transmission sound speed measurements. The explosive in this study was composed of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) combined with the fluoropolymer binder Kynar Ultraflex B. Binder content ranged from 2.6 wt.% to 11.5 wt.% with associated explosive formulation densities from 1.69 g/cc to 1.89 g/cc. We find linear and nonlinear changes in longitudinal and shear sound speeds, peak frequencies, and measured elastic properties for the different PBX formulations. These measured changes can differentiate the tested formulations, highlighting the potential for ultrasound as a nondestructive characterization method for newly-formulated PBXs. We also demonstrate through-transmission measurements using different coupling media and present results from an ultrasound technique called resonant ultrasound spectroscopy (RUS). Both transmission and RUS approaches may allow for rapid and even automated characterization of PBX components suitable for high-throughput manufacturing operations.

Engineering↗

Advanced mass balance characterization and fractionation of algal biomass composition

Abstract Opportunities associated with biomass production and bioproduct isolation from algae-derived feedstocks are plentiful and promising; however, there are challenges associated with realizing these applications. One of the most important, and often overlooked, challenges is the lack of availability of a strong foundation of compositional analysis methods validated on microalgal biomass. Currently, compositional analysis in algae is dominated by the use of interference-prone methods, a lack of full mass balance accounting, and the use of top-down approaches that bin all unaccounted-for mass into a single category, such as carbohydrates. We present here an approach based on a bottom-up algal biomass characterization aimed at moving towards, and highlighting the importance of, full and accurate mass closure to achieve the maximum economic potential from a sustainable and renewable feedstock. Algal biomass representing three genera, Nannochloropsis , Scenedesmus , and Monoraphidium , was subjected to a cell rupture and fractionation process, followed by detailed characterization of each fraction to determine the partitioning of measured and unknown components. The goal of this work is to identify where the missing components partition, and develop a strategy to close the mass balance or identify the unknowns, while utilizing a rigorous characterization approach for characterizing algal biomass. Although only 75–80% of the biomass was accounted for, the fractionation approach utilized here provides key insight into possible chemical components for future investigations.

59 BASIC BIOLOGICAL SCIENCES↗

Characterization of mechanical discontinuities based on data-driven classification of compressional-wave travel times

Wave propagation and diffusive transport phenomena are influenced by the mechanical discontinuities in material. Here this study shows that certain bulk properties of the network of low-velocity mechanical discontinuities (e.g. air-filled cracks) in a material can be characterized by processing compressional-wave travel times using traditional data-driven classification techniques. To that end, we perform three tasks in chronological order: (1) use the discrete fracture network (DFN) method to create two-dimensional (2D) numerical models of crack-bearing material embedded with various types of low-velocity mechanical discontinuities, (2) use the fast marching method (FMM) to simulate the propagation of the wave/diffusion front from a single source through the 2D crack-bearing material to multiple receivers placed on the boundary of the material, and (3) train 9 data-driven classifiers to characterize the crack-bearing materials (i.e. bulk properties of the network of mechanical discontinuities in the crack-bearing material) by learning from the simulations of travel times detected by multiple receivers placed around the crack-bearing material. The classifiers identified the orientation, spatial distribution, and dispersion of the low-velocity mechanical discontinuities. Voting classifier performs the best among the 9 classifiers. For the characterization of bulk dispersion and distribution of discontinuities, the sensors located on the adjacent boundaries are more important; whereas for the characterization of bulk orientation of discontinuities, the sensors located on the opposite side are more important.

42 ENGINEERING↗

The characterization of wear-causing particles and silica sand in particular

Erodants and abradants are two types of wear-causing particles (WCP). Despite their effects on the severity and rate of wear, WCP are inadequately characterized in a surprising number of publications, especially those involving impingement erosion and three-body abrasion. That shortfall makes it difficult to correlate features of WCP with the details of worn surfaces, or to develop wear models that account for those features. It is argued that the documentation of WCP should go beyond simply reporting their composition and mean particle size. In late 1985, ASTM Committee G2 on Wear and Erosion established a task group on the characterization of WCP. At that time, image analysis was slower and less sophisticated than it is today. While that ASTM task group failed to produce a consensus standard, computerized particle characterization methods were developing in fields other than tribology, fields like geoscience, heavy sand mining, materials processing, and pharmaceuticals. A notable exception to this is ferrography, which is a widely-used diagnostic for lubricated tribosystems. In the context of dry wear, it is useful to identify which features of WCP would be beneficial to document, and to identify some techniques and scales of detail appropriate to particular tribosystems. In this paper, examples are presented for the morphological and mechanical characterization of silica sand grains, as prompted by a triboanalysis of the abrasive and erosive wear of biomass pre-processing equipment. The authors propose a minimum level of documentation for WCP, one that can enrich tribosystem analysis both in laboratory tests and field studies.

36 MATERIALS SCIENCE↗

Discovery, characterization, and application of chromosomal integration sites for stable heterologous gene expression in Rhodotorula toruloides

Rhodotorula toruloides is a non-model, oleaginous yeast uniquely suited to produce acetyl-CoA-derived chemicals. However, the lack of well-characterized genomic integration sites has impeded the metabolic engineering of this organism. Here we report a set of computationally predicted and experimentally validated chromosomal integration sites in R. toruloides. We first implemented an in silico platform by integrating essential gene information and transcriptomic data to identify candidate sites that meet stringent criteria. We then conducted a full experimental characterization of these sites, assessing integration efficiency, gene expression levels, impact on cell growth, and long-term expression stability. Among the identified sites, 12 exhibited integration efficiencies of 50% or higher, making them sufficient for most metabolic engineering applications. Using selected high-efficiency sites, we achieved simultaneous double and triple integrations and efficiently integrated long functional pathways (up to 14.7 kb). Additionally, we developed a new inducible marker recycling system that allows multiple rounds of integration at our characterized sites. Here, we validated this system by performing five sequential rounds of GFP integration and three sequential rounds of MaFAR integration for fatty alcohol production, demonstrating, for the first time, precise gene copy number tuning in R. toruloides. These characterized integration sites should significantly advance metabolic engineering efforts and future genetic tool development in R. toruloides.

59 BASIC BIOLOGICAL SCIENCES↗