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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Evaluating Brightness and Stability of Cathodoluminescence from Colloidal Semiconductor Nanocrystals

Cathodoluminescence offers promise as a technique for correlation of atomic structure with electronic structure at the level of individual nanoparticles or even defects, with the ability to analyze complex nanostructures at length-scales far below those typically available to optical spectroscopy. Unlike other forms of electron microscopy, cathodoluminescence offers direct insights into the electronic structure of the visualized sample. Despite reports more than 10 years ago of individual nanoparticle cathodoluminescence, effective cathodoluminescence collection from colloidal semiconductor materials is relatively rare and remains challenging due to the instability of materials under the conditions of electron beam irradiation. In this work, to clarify the roadblocks for cathodoluminescence analysis of colloidal nanocrystals, we attempt a comprehensive study of the cathodoluminescence properties of semiconductor quantum shells, which have a thin concentric CdSe shell surrounding CdS nanoparticles, then surrounded by a further concentric CdS shell. These same materials were recently demonstrated to show promising scintillation performance in radioluminescence measurements, including high brightness (up to 100 ph/keV) and excellent durability. Comparative quantum yield measurements are designed to assess the brightness of semiconductor nanocrystal films, which show that the quantum shells are much less bright under electron irradiation compared to X-ray photons. Instability of CL emission is assigned to charging effects on the samples—and not thermal effects—through a series of voltage, current, dwell time, and atmospheric pressure experiments.

cathodoluminescence↗
DOE OSTI2020

Augmented Monitoring and Condition Assessment Program for SNF Wet Storage Life Extension - 20489

Approximately 27 MTHM of spent nuclear fuel (SNF) owned and managed by the U.S. Department of Energy, Office of Environmental Management is stored in the L Basin at the Savannah River Site (SRS). This 'DOE SNF' is comprised of approximately 12,000 aluminum-clad, aluminum-based fuel assemblies (∼7 MTHM), and approximately 2000 non-aluminum fuel assemblies (∼20 MTHM). A program is in progress to perform Non-Destructive Examination (NDE) of the fuel and their storage containers to characterize the materials' condition, and to evaluate the effects of service to enable continued safe wet storage of the SNF. The Augmented Monitoring and Condition Assessment Program (AMCAP), a two-part program to develop and implement remote underwater Non-Destructive Examination of the aluminum SNF, and of the containers of the non-aluminum SNF, respectively, is aimed at the characterization and evaluation of corrosion degradation of aluminum fuel and container materials. The predominant design of the aluminum SNF (ASNF) stored in L Basin is the Materials Test Reactor (MTR) equivalent design, a plate fuel design. These SNF are stored in 5'' diameter tubes or 5'' x 5'' squares (called bundles) that are nominally 12' or up to 14' long. The SNF is de-bundled and inspected using a custom-designed MTR Fuel Inspection Table. The inspection table provides for indexed fuel positioning for a video camera examination with controlled lighting. A total of 10 of the SNF originating from foreign research and test reactors were selected for examination based on burnup, enrichment, and prior damage caused by service/storage history. A special inspection campaign of these 10 assemblies is in progress. The observed corrosion damage included minor to moderate attack from general corrosion, pitting, crevice, end grain and galvanic corrosion. Example results from the completed inspections are shown and discussed. The focus is a comparison of the as-received condition versus the as-found current storage condition that will serve to validate Water Chemistry and Corrosion Monitoring Programs. The non-aluminum SNF (NASNF) stored in L Basin are of diverse design that includes various geometries with claddings of stainless steel, Zircaloy, and Hastelloy. The fuel core materials include uranium alloys, oxides/mixed oxides, and carbides. These SNF materials, originating from early experimental and test reactors, are in various physical forms including single fuel elements and cut pieces. The fuel is stored in L Basin in various configurations including in direct bundled storage in aluminum tubes and in isolation cans that are in the bundles or in a larger over-size storage container (OSC). Concern with inside-out corrosion and the potential loss of configuration control and ability to handle the storage containers prompted the development of remote NDE methods that include visual and UT technologies to assess the condition of the containers. Candidate stored materials were selected for a special inspection campaign; the development of the NDE methods for the inspection for galvanic, crevice and sediment-induced corrosion (inside-out) are discussed. A summary of the SNF storage in L Basin at the SRS, and an overview of the AMCAP to enable continued safe storage of DOE SNF are described. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

Shopping For Danger: E-commerce techniques applied to collaboration in cyber security

Collaboration among cyber security analysts is essential to a successful protection strategy on the Internet today, but it is uncommonly practiced or encouraged in operating environments. Barriers to productive collaboration often include data sensitivity, time and effort to communicate, institutional policy, and protection of domain knowledge. We propose an ambient collaboration framework, Vulcan, designed to remove the barriers of time and effort and mitigate the others. Vulcan automated data collection, collaborative filtering, and asynchronous dissemination, eliminating the effort implied by explicit collaboration among peers. We instrumented two analytic applications and performed a mock analysis session to build a dataset and test the output of the system.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Percutaneous Decompression of Lumbar Spinal Stenosis with a New Interspinous Device

Objective: This study was designed to evaluate the feasibility of the implantation of a new interspinous device (Falena) in patients with lumbar spinal stenosis. The clinical outcomes and imaging results were assessed by orthostatic MR during an up to 6-month follow-up period. Methods: Between October 2008 and February 2010, the Falena was implanted at a single level in 26 patients (17 men; mean age, 69 (range, 54-82) years) who were affected by degenerative lumbar spinal stenosis. All of the patients were clinically evaluated before the procedure and at 1 and 3 months. Furthermore, 20 patients have completed a 6-month follow-up. Pain was assessed before and after the intervention using the Visual Analogue Scale score and the Oswestry Disability Index questionnaire. Orthostatic MR imaging was performed before the implantation and at 3 months to assess the correlation with the clinical outcome. Results: The mean ODI score decreased from 48.9 before the device implantation to 31.2 at 1 month (p < 0.0001). The mean VAS score decreased from 7.6 before to 3.9 (p < 0.0001) at 1 month and 3.6 at 3 months after the procedure (p = 0.0115). These values were stable at 6 months evaluation. No postimplantation major complications were recorded. MRI evaluation documented in most cases an increased size of the spinal canal area. Similarly a bilateral foraminal area improvement was found. The variation of the intervertebral space height measured on the posterior wall was not significant. Conclusions: In our preliminary experience with the Falena in a small cohort of patients, we obtained clinical and imaging results aligned to those reported with similar interspinous devices.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Suppressing Cation Migration in Triple-Cation Lead Halide Perovskites

Ion migration represents an intrinsic instability of metal halide perovskite solar cells. In this work, we show that triple-cation FA x MA y Cs 1–x–y PbI 3 [FA + = (NH 2 ) 2 CH + , MA + = CH 3 NH 3 + ] active layers with mixed orthorhombic, post-perovskite (δ ortho -CsPbI 3 ), and cubic perovskite (α) phases (i.e., α/δ-phase FA x MA y Cs 1–x–y PbI 3 ) exhibit improved cation stability against applied bias relative to pure α-phase perovskites (i.e., FA 0.85 Cs 0.15 PbI 3 and FA 0.76 MA 0.15 Cs 0.09 PbI 3 ). Infrared photothermal heterodyne imaging and time-of-flight secondary ion mass spectrometry are used to visualize exclusive α-phase perovskite lateral device A + cation accumulation (depletion) at perovskite negative (positive) electrode interfaces. The resulting compositional heterogeneities lead to degradation. Operational stability testing of solar cells reveals similar degradation behavior; α/δ-phase FA x MA y Cs 1–x–y PbI 3 lateral devices/solar cells, by contrast, show improved stabilities. Enhanced α/δ-FA x MA y Cs 1–x–y PbI 3 stability is rationalized by δortho-phase inclusions, acting as barriers through which A + cations do not easily migrate. This study thus provides new insights into cation migration in FA x MAyCs 1–x–y PbI 3 perovskites and suggests a materials design strategy toward suppressing cation instabilities in hybrid perovskites.

14 SOLAR ENERGY↗
DOE OSTI2026

Nanocrystal Geometry Governs Phase Transformation Pathways in Palladium Hydride

Pathways and structural dynamics of phase transformations impact performance of materials in energy and information storage technologies. Palladium hydride (PdH x ) nanocrystals are an ideal model system for studying solute-induced phase transformations, where elastic energy from lattice mismatch between α-PdH x and β-PdH x phases is often considered a key to determining the transformation pathways. α/β-PdH x interfacial elastic energy is affected by the confined geometry of a nanocrystal. However, how nanocrystal geometry influences phase transformation pathways is largely unknown. Using in situ liquid phase transmission electron microscopy, we directly visualize hydrogenation in Pd nanocrystals with two geometries, a nanocube and a hexagonal nanoplate. Both follow similar sequences of an initially curved nucleus, interface flattening, and reverse-stage nucleation; however, their evolving α/β-PdH x interfaces exhibit geometry-dependent crystallographic alignments. In nanocubes, {100}-aligned configurations conform to static elastic energy ordering, representing a pathway that maintains a local mechanical equilibrium, whereas nanoplates display both {110}- and {211}-aligned interfaces. Theoretical simulations show that geometry determines the accessibility of alternative phase transformation pathways as the system is driven far from equilibrium during hydrogenation. In conclusion, these findings identify geometry as a fundamental parameter for directing phase transformation pathways, offering design principles for accessing atypical configurations and improving properties of intercalation-based devices.

Lee, Daewon [Lawrence Berkeley National Laboratory↗
DOE OSTI2025

Atomic dynamics of gas-dependent oxide reducibility

Understanding oxide reduction is critical for advancing metal production, catalysis and energy technologies. Although carbon monoxide (CO) and hydrogen (H 2 ) are widely used reductants, the mechanisms by which they work are often presumed to be similar, both involving lattice oxygen removal. However, because of growing interest in replacing CO with H 2 to lower CO 2 emissions, distinguishing gas-specific reduction pathways is critical. Yet, capturing these atomic-scale processes under reactive gas and high-temperature conditions remains challenging. Here we use environmental transmission electron microscopy, which is capable of real-time, atomic-resolution imaging of gas–solid redox reactions to directly visualize the gas-dependent oxide reduction dynamics in NiO. We show that CO drives surface nucleation and the growth of metallic Ni islands, leading to self-limiting surface metallization. Conversely, H 2 activates a coupled surface-to-bulk transformation, where protons from dissociated H 2 infiltrate the oxide lattice to promote the inward migration of surface-generated oxygen vacancies and enabling bulk metallization. By contrast, oxygen vacancies formed by CO remain confined near the surface, where they rapidly form a metallic Ni layer that inhibits further reduction. Furthermore, these results reveal distinct atomistic pathways for CO and H 2 and provide insights that may guide metallurgical processes and catalyst design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

AutoAtlas: Neural Network for 3D Unsupervised Partitioning and Representation Learning

Here we present a novel neural network architecture called AutoAtlas for fully unsupervised partitioning and representation learning of 3D brain Magnetic Resonance Imaging (MRI) volumes. AutoAtlas consists of two neural network components: one neural network to perform multi-label partitioning based on local texture in the volume, and a second neural network to compress the information contained within each partition. We train both of these components simultaneously by optimizing a loss function that is designed to promote accurate reconstruction of each partition, while encouraging spatially smooth and contiguous partitioning, and discouraging relatively small partitions. We show that the partitions adapt to the subject specific structural variations of brain tissue while consistently appearing at similar spatial locations across subjects. AutoAtlas also produces very low dimensional features that represent local texture of each partition. We demonstrate prediction of metadata associated with each subject using the derived feature representations and compare the results to prediction using features derived from FreeSurfer anatomical parcellation. Since our features are intrinsically linked to distinct partitions, we can then map values of interest, such as partition-specific feature importance scores onto the brain for visualization.

42 ENGINEERING↗
DOE OSTI2024

Statistical Validation of Multiple Related Data Sets—Case Study Using Interstellar Boundary Explorer Satellite Data

Abstract Space scientists often face the question of whether data collected by different instruments are measurements of the same source population. This paper proposes a statistical validation method for evaluating the agreement between such related data sets. It offers a detailed case study focused on validating a new data set from the Interstellar Boundary Explorer (IBEX) mission, which serves as a practical how-to guide for similar analyses. Since 2008, the IBEX satellite has been gathering data on heliospheric energetic neutral atoms (ENAs) while being exposed to various sources of background noise, such as cosmic rays and solar energetic particles. The IBEX mission initially released only a qualified triple-coincidence (qABC) data product, which was designed to provide observations of ENAs free of background contamination. Further measurements revealed that the qABC data were in fact susceptible to contamination, having relatively low ENA counts and high background rates. To mitigate this issue, the mission team recently considered releasing a certain qualified double-coincidence (qBC) data product, which has roughly twice the detection rate of the qABC data product. This paper presents a simulation-based validation of the new qBC data product against the already-released qABC data product. The results show that the qBCs can plausibly be said to be measuring the same source population as the qABCs up to an average absolute deviation of 3.6%. Visual diagnostics provide additional confirmation of source rate coherence across data products. The framework introduced here is general and can be applied to other validation problems both within and outside the field of space physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Advancing Vision-based Feedback and Convolutional Neural Networks for Visual Outlier Detection

Machine learning has matured into a technology that has immediate applicability to the surveillance needs of nuclear material storage containers. These containers at LANL are the barrier preventing release of radioactive material to the workers, public, and environment during the storage period of the material. Annual surveillance activities can only provide coverage on a handful of containers. There is a significant need for surveillance tools to identify potential issues and precursors to containment failure that can be used during opportunistic inspections and, more generally, outside of annual surveillance activities. In this report we provide details on the advancement of our proposed embodiment that combines an automation system for taking pictures and a high-accuracy machine learning-driven object detection software. We further showcase the improvements on the software side with progress on extracting unique identification features and advances in detecting damage. The current state of the system captures subject matter expert training and a space-conscious design whose implementation is envisioned in the near future.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

A product data network to enable faster, easier, and better planning of building envelopes

The building envelopes contributes significantly to the energy-efficiency of the building. Building performance simulation has made it possible to compare façade technologies regarding energy demand, daylighting, thermal and visual comfort in detail. Planners, such as architects and engineers, need experience to find product data with the right quality and level of detail, and to process the data to fit the calculation and the application. In the available time, planners can compare only a limited number of products, which means that better solutions could go unnoticed. This paper presents a new concept for making product data easily accessible for building façade planning. The concept consists of a network of databases for the efficient exchange and use of optical and calorimetric data of glazing units, shading devices, and combinations of both. The paper presents the research questions, an analysis of the current challenges, six design goals for the product data network and its implementation together with a discussion. Many product data sources can be connected to many planning software applications via the specified application programming interface. When planning software connects to the product data network, the planning of building envelopes can be much faster because planners do not need to spend so much time to search and process product data manually. The planning of building envelopes can also become much easier, especially for planners with limited experience. They do not need to understand all the details about which data fits which calculation if the software company implements this. The planning of building envelopes can become much more reliable when software companies validate their use of the product data network, because the current manual process is prone to errors. The planning of building envelopes can also improve because more products can be compared in the available time, allowing better solutions to be found.

Maurer, Christoph↗
DOE OSTI2026

Developing Scenario‐Based Strategies for Health, Climate, and Environmental Preparedness: The One Health, One Earth Approach

Climate change amplifies many threats to human health. Despite advances in understanding climate change dynamics and impacts, there remains a critical gap in translating scientific knowledge into equitable, and community-driven health interventions. The inaugural One Earth, One Health workshop sought to explore this gap through human-centered design exercises involving interdisciplinary researchers from climate and Earth sciences, engineering, epidemiology, microbiology, and environmental health. Although participants did not co-develop solutions with affected communities, they used stakeholder role-playing to guide ideation and lay groundwork for actionable plans. Through these methods, participants identified community needs and proposed prototype solutions to alleviate health threats exacerbated by global environmental change. Prototypes were organized around infectious diseases, extreme weather, and air quality, as illustrative themes rather than an exhaustive set of risks. Key solutions included strategies for anticipatory systems and early warning (e.g., integrating environmental signals with health data), inclusive communication and infrastructure needs for responding to extreme weather events, and integrated platforms visualizing air quality trends to support tailored, context-aware guidance beyond one-size-fits-all alerts. The workshop highlighted opportunities such as leveraging machine learning, Earth observation, and real-time surveillance to protect communities, but also noted barriers including data quality, technological redundancy, privacy, and governance challenges. Additionally, participants emphasized the need for interdisciplinary teams capable of collaborating across sectors, breaking down silos and addressing gaps in training and education. Overall, the workshop illustrates how process-driven, human-centered approaches can help surface user needs and generate testable prototype concepts, while underscoring the importance of direct community partnership for implementation.

Abadi, Azar M. [University of Alabama, Birmingham,↗
DOE OSTI2013

Exploring Vector Fields with Distribution-based Streamline Analysis

Streamline-based techniques are designed based on the idea that properties of streamlines are indicative of features in the underlying field. In this paper, we show that statistical distributions of measurements along the trajectory of a streamline can be used as a robust and effective descriptor to measure the similarity between streamlines. With the distribution-based approach, we present a framework for interactive exploration of 3D vector fields with streamline query and clustering. Streamline queries allow us to rapidly identify streamlines that share similar geometric features to the target streamline. Streamline clustering allows us to group together streamlines of similar shapes. Based on users selection, different clusters with different features at different levels of detail can be visualized to highlight features in 3D flow fields. We demonstrate the utility of our framework with simulation data sets of varying nature and size.

Streamline Analysis↗
DOE OSTI2013

Idaho National Laboratory Cultural Resource Monitoring Report for 2013

This report describes the cultural resource monitoring activities of the Idaho National Laboratory’s (INL) Cultural Resource Management (CRM) Office during 2013. Throughout the year, thirty-eight cultural resource localities were revisited including: two locations with Native American human remains, one of which is also a cave; fourteen additional caves; seven prehistoric archaeological sites ; four historic archaeological sites; one historic trail; one nuclear resource (Experimental Breeder Reactor-I, a designated National Historic Landmark); and nine historic structures located at the Central Facilities Area. Of the monitored resources, thirty-three were routinely monitored, and five were monitored to assess project compliance with cultural resource recommendations along with the effects of ongoing project activities. On six occasions, ground disturbing activities within the boundaries of the Power Burst Facility/Critical Infrastructure Test Range Complex (PBF/CITRC) were observed by INL CRM staff prepared to respond to any additional finds of Native American human remains. In addition, two resources were visited more than once as part of the routine monitoring schedule or to monitor for additional damage. Throughout the year, most of the cultural resources monitored had no visual adverse changes resulting in Type 1determinations. However, Type 2 impacts were noted at eight sites, indicating that although impacts were noted or that a project was operating outside of culturally cleared limitations, cultural resources retained integrity and noted impacts did not threaten National Register eligibility. No new Type 3 or any Type 4 impacts that adversely impacted cultural resources and threatened National Register eligibility were observed at cultural resources monitored in 2013.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Advanced Collision Detection and Site Monitoring for Avian and Bat Species for Offshore Wind Energy (Final Technical Report)

This final technical report summarizes the outcomes from a project that aimed to design, build, and test a persistent and autonomous monitoring system for avian and bat collisions with offshore wind turbines blades and structures. The system comprises four primary sensor modules: 1) on-blade sensor modules for collision detection and dual-vision image capture on each blade with both visible light and near-infrared imagers; 2) additional on-blade collision sensors mounted further from the root; 3) a nacelle-mounted unit including a 360º camera and ultrasonic microphone array; and, 4) an on-blade, high-performance infrared camera module. Primary targeted outcomes were high sensitivity for the detection of blade strikes from bats and small birds, and automatically captured visual confirmation of the striking object; these features are critical for monitoring offshore wind turbine installations, where ground-based methods are not viable. In addition, local recording will provide a long-term sensor recording database. Following laboratory validation, field testing was conducted on an operational wind turbine in collaboration with the National Wind Technology Center at the NREL Flatirons campus over two planned field tests.

17 WIND ENERGY↗
DOE OSTI2018

Application of chord length distributions and principal component analysis for quantification and representation of diverse polycrystalline microstructures

Highlights: • Microstructure quantification based on directional chord length distribution and principal component analysis is presented • A boundary-based algorithm of calculations of chord length distributions is introduced • Utility of the quantification framework is shown in three case studies on synthetic, experimental, and simulation datasets • Angularly resolved chord length distribution captures essential details of grain size and shape in diverse microstructures • Low-dimensional representations of directional chord length distributions are obtained using principal component analysis - Abstract: Quantification of mesoscale microstructures of polycrystalline materials is important for a range of practical tasks of materials design and development. The current protocols of quantifying grain size and morphology often rely on microstructure metrics (e.g., mean grain diameter) that overlook important details of the mesostructure. In this work, we present a quantification framework based on directionally resolved chord length distribution and principal component analysis as a means of extracting additional information from 2-D microstructural maps. Towards this end, we first present in detail a method for calculating chord length distribution based on boundary segments available in modern digital datasets (e.g., from microscopy post-processing) and their low-rank representations by principal component analysis. The utility of the proposed framework for capturing grain size, morphology, and their anisotropy for efficient visualization, representation, and specification of polycrystalline microstructures is then demonstrated in case studies on datasets from synthetic generation, experiments (on Ni-base superalloys), and simulations (on steel during recrystallization).

36 MATERIALS SCIENCE↗
DOE OSTI2020

Probing local electrochemistry via mechanical cyclic voltammetry curves

Understanding the mechanical response of an electrode during electrochemical cycling and its correlation to the device electrochemical performance is crucial to improving the performance of insertion-type energy storage devices, electrochemical actuators, water purification, ion separation and neuromorphic computing applications. Here, we visualized the electro-chemo-mechanical coupling behaviors during charge storage of anhydrous and hydrated WO 3 electrodes via in situ atomic force microscopy (AFM) and developed the concept of mechanical cyclic voltammetry (mCV) curves. The relationship between electrochemical current and strain was investigated with simplified models and the results revealed that the proton insertion/deinsertion process could be described through potential-dependent electro-chemo-mechanical coupling coefficients which might indicate changes in insertion processes during electrode cycling. The mCV mapping results highlight the local heterogeneity and show that the charging processes varied across the electrode. These local variations could be further correlated to local morphology, crystal orientations or chemical compositions with proper electrode designs.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Improved Characterization and Modeling of Tight Oil Formations for CO 2 Enhanced Oil Recovery Potential and Storage Capacity Estimation

Tight oil formations such as those in the Bakken petroleum system are known to hold hundreds of billions of barrels of oil in place; however, the primary recovery factor for these plays is typically less than 10%. Tight oil formations, including the Bakken Formation, therefore, may be attractive candidates for enhanced oil recovery (EOR) using CO 2 . Multiphase fluid behavior and flow in fluid-rich shales can vary substantially depending on the size of pore throats, and properties such as fluid viscosity and density are much different in nanoscale pores than in macroscale pores. Thus it is critical to understand the nature and distribution of nano-, micro-, and macroscale pores and fracture networks. To address these issues, the Energy & Environmental Research Center (EERC) has been conducting a research program entitled “Improved Characterization and Modeling of Tight Oil Formations for CO 2 Enhanced Oil Recovery Potential and Storage Capacity Estimation.” The objectives of the project are 1) the use of advanced characterization methods to better understand and quantify the petrophysical and geomechanical factors that control CO 2 and oil mobility within tight oil formation samples, 2) the determination of CO 2 permeation and oil extraction rates in tight reservoir rocks and organic-rich shales of the Bakken, and 3) the integration of the laboratory-based CO 2 permeation and oil extraction data and the characterization data into geologic models and dynamic simulations to develop predictions of CO 2 storage resource and EOR in the Bakken tight oil formation. A combination of standard and advanced petrophysical characterization techniques were applied to characterize samples of Bakken Formation tight reservoir rock and shales from multiple wells. Techniques included advanced computer tomography (CT) imaging, scanning electron microscopy (SEM) techniques, whole-core and micro x-ray CT imaging, field emission (FE) SEM, and focused ion beam (FIB) SEM. Selected samples were also analyzed for geomechanical properties. X-ray CT imaging yielded information on the occurrence of fractures, bedding planes, fossils, and bioturbation in core, as well as data on bulk density and photoelectric factor logs, which were used to interpret porosity, organic content, and mineralogy. FESEM was used for characterization of nano- and microscale features, including nanoscale pore visualization and micropore and pore throat mineralogy. FIBSEM yielded micro- to nanoscale visualization of fracture networks, porosity and pore-size distribution, connected versus isolated porosity, and distribution of organics. Results from the characterization activities provide insight on nanoscale fracture properties, pore throat mineralogy and connectivity, rock matrix characteristics, mineralogy, and organic content. Laboratory experiments demonstrated that CO 2 can permeate the tight matrix of Bakken shale and nonshale reservoir samples and mobilize oil from those samples. Geologic models were created at scales ranging from the core plug to the reservoir, and dynamic simulations were conducted. The data from the characterization and laboratory-based activities were integrated into modeling research activities to determine the fundamental mechanisms controlling fluid transport in the Bakken, which support EOR scheme design and estimation of CO 2 storage potential in tight oil formations. Simulation results suggest a CO 2 storage resource estimate range of 169 million to 1.5 billion tonnes for the Bakken in North Dakota, possibly resulting in 1.8 billion to 16 billion barrels of incremental oil.

04 OIL SHALES AND TAR SANDS↗