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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Nebraska Integrated Carbon Capture and Storage Pre-Feasibility Study

In collaboration with the Nebraska Public Power District (NPPD), the Energy & Environmental Research Center (EERC) has conducted a pre-feasibility study for a commercial-scale carbon dioxide (CO 2 ) geologic storage complex in western Nebraska integrated with potential CO 2 capture at Gerald Gentleman Station (GGS). GGS is the largest coal-fired electricity-generating station in Nebraska, emitting 8.5 million metric tons (Mt) of CO 2 annually, and is located near the town of Sutherland. This pre-feasibility (Phase 1) project has been executed as part of the U.S. Department of Energy (DOE) CarbonSAFE program, a multiphase initiative to support the deployment of large-scale carbon capture and storage (CCS) projects. Each CarbonSAFE project is required to demonstrate the potential to capture and store at least 50 million tonnes (Mt) of CO 2 over a 25-year operational period. The EERC and NPPD established a coordination team to identify challenges to a potential Nebraska CCS project, comprising local stakeholder organizations, which met twice in Lincoln and via several Webinars, providing feedback and guidance throughout the pre-feasibility study. The EERC also secured the technical support of Schlumberger Carbon Services and Computer Modelling Group Ltd. (CMG). The project comprised four technical themes, all using published information sources. Regional and stakeholder analysis, including identification of sensitive environmental areas, potential resource conflicts, and strategies for public outreach. A review of geographic and socioeconomic characteristics, in combination with geologic characterization in the subbasinal analysis described below, identified an area to the southwest and within a 75-mile radius of GGS as the most prospective for development of a storage site. This area largely avoided lands with protected status such as wetlands. A public outreach plan has also been developed for implementation in any further phases of CCS assessment in western Nebraska, for example a CarbonSAFE Phase 2 feasibility study. Scenario analysis, addressing economic and regulatory factors. GGS is the only single major source of CO 2 emissions capable of satisfying the CarbonSAFE 50-Mt scale requirement within the study region. Chemical absorption using amines was identified as the most viable technology for postcombustion CO 2 capture at GGS. The total cost of a CCS project at GGS was estimated to be between $67/tonne CO 2 for capture and auxiliary boiler to minimize parasitic load and $70/tonne CO 2 avoided cost, using the Carnegie-Mellon University Integrated Environmental Control Model (IECM). The total avoided cost included the capture facility and parasitic load, a flue gas desulfurization plant required for the use of amine solvent technology, transport via pipeline, and dedicated storage infrastructure. Nebraska has no legislation in place to address typical CCS-specific issues, for example pore space ownership for storage. Long-term liability, therefore, falls under the U.S. Environmental Protection Agency Underground Injection Control (UIC) Class 6 program regulations. Subbasinal analysis, addressing the potential for a dedicated subsurface “container” to store the required 50-Mt quantity of CO 2 . Modeling and simulation studies identified an area to the southwest of GGS with the potential for storage of 50 Mt CO 2 in the Cloverly Formation, comprising sandstones with interbedded and intermingled shales. The area of review (AOR) that would be required for monitoring under a Class VI operating permit was estimated to be as high as 400–700 square miles, due to uncertain pressure effects. The viability of this storage option is subject to significant uncertainty due to the relatively limited amount of existing characterization data available to the pre-feasibility study; for example, dynamic simulation indicated that the proposed storage rate might require as little as two or as many as 14 injection wells. A key uncertainty is the relative proportion and distribution of sandstone and shale within the Cloverly Formation. A preliminary, semiquantitative risk assessment also suggested uncertainty over storage capacity and injectivity constitute the most significant project risks at this pre-feasibility stage. No assessed risks were considered to rule out the possibility of a project moving to deployment. National Risk Assessment Partnership (NRAP) validation, using software tools developed by the National Energy Technology Laboratory (NETL) to assess risks associated with the potential 50-Mt CO 2 storage complex. NRAP tools were used to assess hypothetical leakage scenarios. Results broadly supported the conclusion of the semiquantitative risk analysis – for example, even worst-case analysis of theoretical leakage scenarios found limited migration rates and impacts. In summary, the work undertaken in this Phase 1 pre-feasibility study has shown that western Nebraska has potential to host a commercial-scale CCS project, including a dedicated storage “container” for 50 Mt of CO 2 . However, the following key challenges would need to be overcome: The business case for deploying CCS projects is uncertain; recently announced federal tax credits and sales of CO 2 for enhanced oil recovery may not cover the full costs of a CCS project at GGS, as estimated by this pre-feasibility study. The potential 50-Mt CO 2 dedicated storage container defined in this pre-feasibility study should be regarded as having a relatively low level of readiness to support a CCS project. Public outreach would be a vital element in western Nebraska, where sensitivities around such environmental issues as water resource protection and pipeline construction would need to be carefully addressed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Real-time tracking and analysis of gas bubble dynamics in laser powder bed fusion using in-situ X-ray characterization and machine learning

Porosity defects remain a significant challenge in the laser powder bed fusion (LPBF) process, adversely affecting the mechanical properties and reliability of additively manufactured components. Here, this study investigates the real-time formation and trajectory of gas bubbles during LPBF of Al6061 alloy using advanced in-situ X-ray characterization and machine learning. The unsupervised Gaussian mixture model and particle tracking algorithm developed are able to precisely track and quantify the properties of gas bubbles and keyhole pores. Our analysis identified five distinct types of gas bubble formation and movement patterns, emphasizing the diverse origins and behaviors of these defects. It enables precise quantification of trajectories, velocities, and morphological changes of gas bubbles, offering a granular view of the subsurface dynamics within the melt pool. Additionally, we explored keyhole-induced pore dynamics, revealing the critical role of keyhole oscillation and collapse for the formation of both large and small gas pores. It defines four different regions of gas bubble movement within the melt pool, providing a clearer understanding of how local fluid dynamics affect pore behavior. The results underscore the importance of integrating in-situ experimental observation and automated machine learning to develop a more robust predictive model for defect formation in LPBF.

In-situ X-ray imaging↗
DOE OSTI2012

Updated Conceptual Model for the 300 Area Uranium Groundwater Plume

The 300 Area uranium groundwater plume in the 300-FF-5 Operable Unit is residual from past discharge of nuclear fuel fabrication wastes to a number of liquid (and solid) disposal sites. The source zones in the disposal sites were remediated by excavation and backfilled to grade, but sorbed uranium remains in deeper, unexcavated vadose zone sediments. In spite of source term removal, the groundwater plume has shown remarkable persistence, with concentrations exceeding the drinking water standard over an area of approximately 1 km2. The plume resides within a coupled vadose zone, groundwater, river zone system of immense complexity and scale. Interactions between geologic structure, the hydrologic system driven by the Columbia River, groundwater-river exchange points, and the geochemistry of uranium contribute to persistence of the plume. The U.S. Department of Energy (DOE) recently completed a Remedial Investigation/Feasibility Study (RI/FS) to document characterization of the 300 Area uranium plume and plan for beginning to implement proposed remedial actions. As part of the RI/FS document, a conceptual model was developed that integrates knowledge of the hydrogeologic and geochemical properties of the 300 Area and controlling processes to yield an understanding of how the system behaves and the variables that control it. Recent results from the Hanford Integrated Field Research Challenge site and the Subsurface Biogeochemistry Scientific Focus Area Project funded by the DOE Office of Science were used to update the conceptual model and provide an assessment of key factors controlling plume persistence.

300 Area↗
DOE OSTI2020

Microseismic Event Denoising: Removal of Borehole Waves

The vertical borehole array at Farnsworth Unit, TX is used to monitor microseismic activity in the subsurface around the Carbon Capture and Sequestration (CCS) reservoir. The array consists of 16 3-component seismometers spaced vertically in a single borehole. Tube or borehole waves traveling up or down the borehole can corrupt signals of interest, such as microseismic events. A denoising convolutional neural network (DCNN) was trained to remove borehole waves from seismic waveforms of microseismic events for the purpose of reducing unwanted signal detections and better characterizing events of interest. This R&D leverages the work of Sandia colleague Rigo Tibi, who used a DCNN developed by Greg Beroza at Stanford University to improve the signal-to-noise ratio (SNR) of teleseismic events detected by the International Monitoring System.

58 GEOSCIENCES↗
DOE OSTI2021

Discovering Hidden Geothermal Signatures using Unsupervised Machine Learning

Discovering hidden geothermal resources is a very challenging task. It requires the mining of large datasets, including various diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used Play Fairway Analysis (PFA) typically relies on subject-matter expertise to analyze site or regional data to estimate geothermal conditions and prospectivity. Here, we demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset of Southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. However, most of these systems are poorly characterized because of insufficient existing data and limited past explorative studies. This study aims to discover hidden patterns and relationships in the SWNM geothermal dataset to better understand regional hydrothermal conditions. This is achieved by applying an unsupervised machine learning algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden (latent) signatures characterizing datasets, (2) the optimal number of these signatures, (3) dominant data attributes associated with each signature, and (4) spatial distribution of the extracted signatures. Here, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, geothermal attributes at 44 locations in SWNM. NMFk successfully finds data patterns and identifies the spatial associations of hydrothermal signatures with the four physiographic provinces in SWNM (Colorado Plateau, Volcanic Field, Basin and Range, and the Rio Grande rift). The algorithm identified up to 5 hydrothermal signatures in the SWNM datasets that differentiate between low- and medium-temperature hydrothermal systems in different provinces. Also, the algorithm identifies two medium-temperature hydrothermal systems in SWNM that require further exploration for geothermal resource development. Based on our analyses, 12 of the attributes are important to identify medium-temperature hydrothermal systems, and the remaining six attributes are critical to characterize low-temperature hydrothermal systems. Based on the obtained results, we identify potential physiographic provinces for further exploration to characterize them as geothermal resources. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored areas.

58 GEOSCIENCES↗
NASA NTRS2006

Development of Analytical Protocols For Organics and Isotopes Analysis on the 2009 MARS Science Laboratory.

The Mars Science Laboratory, under development for launch in 2009, is designed explore and quantitatively asses a local region on Mars as a potential habitat for present or past life. Its ambitious goals are to (1) assess the past or present biological potential of the target environment, (2) to characterize the geology and geochemistry at the MSL landing site, and (3) to investigate planetary processes that influence habitability. The planned capabilities of the rover payload will enable a comprehensive search for organic molecules, a determination of definitive mineralogy of sampled rocks and fines, chemical and isotopic analysis of both atmospheric and solid samples, and precision isotope measurements of several volatile elements. A range of contact and remote surface and subsurface survey tools will establish context for these measurements and will facilitate sample identification and selection. The Sample Analysis at Mars (SAM) suite of MSL addresses several of the mission's core measurement goals. It includes a gas chromatograph, a mass spectrometer, and a tunable laser spectrometer. These instruments will be designed to analyze either atmospheric samples or gases extracted from solid phase samples such as rocks and fines. We will describe the range of measurement protocols under development and study by the SAM engineering and science teams for use on the surface of Mars.

Mahaffy, P. R.↗
DOE OSTI2018

Utah FORGE: Well Data for Student Competition

Well 58-32 (previously labeled MU-ESW1) was drilled near Milford Utah during Phase 2B of the FORGE Project to confirm geothermal reservoir characteristics met requirements for the final FORGE site. Well Accord-1 was drilled decades ago for geothermal exploration purposes. While the conditions encountered in the well were not suitable for developing a conventional hydrothermal system, the information obtained suggested the region may be suitable for an enhanced geothermal system. Geophysical well logs were collected in both wells to obtain useful information regarding there nature of the subsurface materials. For the recent testing of 58-32, the Utah FORGE Project contracted with the well services company Schlumberger to collect the well logs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Riverbed Hydrologic Exchange Dynamics in a Large Regulated River Reach

Hydrologic exchange flux (HEF) is an important hydrologic component in river corridors that includes both bidirectional (hyporheic) and unidirectional (gaining/losing) surface water – groundwater exchanges. Quantifying HEF rates in a large regulated river is difficult due to the large spatial domains, complexity of geomorphologic features and subsurface properties, and the great stage variations created by dam operations at multiple time scales. In this study, we developed a method that combined numerical modeling and field measurements for estimating HEF rates across the river bed in a 7-km long reach of the highly regulated Columbia River. A high-resolution computational fluid dynamics (CFD) modeling framework was developed and validated by field measurements and other modeling results to characterize the HEF dynamics across the river bed. We found that about 85% of the time from 2008-2014 the river was losing water with an annual average net HEF rates across the river bed (Qz) of -2.3 m 3 s -1 (negative indicating downwelling). June was the only month that the river gained water, with monthly averaged Qz of 0.8 m 3 s -1 . We also found that the daily dam operations increased the hourly gross gaining and losing rate over an average year of 8% and 2%, respectively. By investigating the HEF feedbacks at various time scales, we suggest that the dam operations could reduce the HEF at seasonal time scale by decreasing the seasonal flow variations, while also enhance the HEF at sub-daily time scale by generating high frequency discharge variations. These changes could generate significant impacts on biogeochemical processes in the hyporheic zone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Harnessing Uncertainty through Functional Data Analysis in Gas Breakthrough Data

Detecting subsurface explosions from radionuclide gas migration through rock fractures is an effective way to identify nuclear activity. Los Alamos National Laboratory (LANL) has developed simulation methods, based on data from the 1962 Hardhat underground nuclear test, to predict gas breakthrough times at the surface. However, these methods rely on an imperfect understanding of the relationship between rock damage and fracture permeability. Our clinic project studies methods for predicting breakthrough curves that characterize total mass produced as a function of time, as well as quantifying the uncertainty associated with these predictions. The model that is currently employed to relate damage to permeability uses an empirically motivated power-law expression, with a range of parameter values that are compatible with the experimental Hardhat data. We develop emulators, built from functional data analysis techniques and trained on simulation data, that rapidly predict the gas breakthrough curve given a damage field and given the parameter values of the power-law equation. Using Bayesian regression, we address the problem of uncertainty quantification in our emulators. Finally, in order to test the robustness of the model, we further validate it on a damage field representing different physical conditions.

58 GEOSCIENCES↗
DOE OSTI2019

Evaluating the relative importance of precipitation, temperature and land-cover change in the hydrologic response to extreme meteorological drought conditions over the North American High Plains

Abstract. Drought is a natural disaster that may become more commonin the future under climate change. It involves changes to temperature,precipitation and/or land cover, but the relative contributions of each ofthese factors to overall drought severity is not clear. In this work we apply ahigh-resolution integrated hydrologic model of the High Plains to explorethe individual importance of each of these factors and the feedbacks betweenthem. The model was constructed using ParFlow-CLM, which represents surfaceand subsurface processes in detail with physically based equations.Numerical experiments were run to perturb vegetation, precipitation andtemperature separately and in combination. Results show that decreasedprecipitation caused larger anomalies in evapotranspiration, soil moisture,stream flow and water table levels than increased temperature ordisturbed land cover did. However, these factors are not linearly additive whenapplied in combination; some effects of multifactor runs came frominteractions between temperature, precipitation and land cover. Spatialscale was important in characterizing impacts, as unpredictable andnonlinear impacts at small scales aggregate to predictable, linear large-scale behavior.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

The Mars Environmental Compatibility Assessment (MECA)

The Mars Environmental Compatibility Assessment (MECA) will evaluate the Martian environment for soil and dust-related hazards to human exploration as part of the Mars Surveyor Program 2001 Lander. Sponsored by the Human Exploration and Development of Space (HEDS) enterprise, MECA's goal is to evaluate potential geochemical and environmental hazards that may confront future martian explorers, and to guide HEDS scientists in the development of high fidelity Mars soil simulants. In addition to objectives related to human exploration, the MECA data set will be rich in information relevant to basic geology, paleoclimate, and exobiology issues. The integrated MECA payload contains a wet-chemistry laboratory, a microscopy station, an electrometer to characterize the electrostatics of the soil and its environment, and arrays of material patches to study the abrasive and adhesive properties of soil grains. MECA is allocated a mass of 10 kg and a peak power usage of 15 W within an enclosure of 35 x 25 x 15 cm (figures I and 2). The Wet Chemistry Laboratory (WCL) consists of four identical cells that will accept samples from surface and subsurface regions accessible to the Lander's robotic arm, mix them with water, and perform extensive analysis of the solution. Using an array of ion-specific electrodes (ISEs), cyclic voltammetry, and electrochemical techniques, the chemistry cells will wet soil samples for measurement of basic soil properties of pH, redox potential, and conductivity. Total dissolved material, as well as targeted ions will be detected to the ppm level, including important exobiological ions such as Na, K+, Ca++, Mg++, NH4+, Cl, S04-, HC03, as well as more toxic ions such as Cu++, Pb++, Cd++, Hg++, and C104-. MECA's microscopy station combines optical and atomic-force microscopy (AFM) to image dust and soil particles from millimeters to nanometers in size. Illumination by red, green, and blue LEDs is augmented by an ultraviolet LED intended to excite fluorescence in the sample. Substrates were chosen to allow experimental study of size distribution, adhesion, abrasion, hardness, color, shape, aggregation, magnetic and other properties. To aid in the detection of potentially dangerous quartz dust, an abrasion tool measures sample hardness relative to quartz and a hard glass (Zerodur).

Meloy, Thomas P.↗
NASA NTRS2021

The Enceladus Orbilander Mission Concept: Balancing Return and Resources in the Search for Life

Enceladus’s long-lived plume of ice grains and water vapor makes accessing oceanic material readily achievable from orbit (around Saturn or Enceladus) and from the moon’s surface. In preparation for the National Academies of Sciences, Engineering and Medicine 2023–2032 Planetary Science and Astrobiology Decadal Survey, we investigated four architectures capable of collecting and analyzing plume material from orbit and/or on the surface to address the most pressing questions at Enceladus: Is the subsurface ocean inhabited? Why, or why not? Trades specific to these four architectures were studied to allow an evaluation of the science return with respect to investment. The team found that Orbilander, a mission concept that would first orbit and then land on Enceladus, represented the best balance. Orbilander was thus studied at a higher fidelity, including a more detailed science operations plan during both orbital and landed phases, landing site characterization and selection analyses, and landing procedures. The Orbilander mission concept demonstrates that scientifically compelling but resource-conscious Flagship-class missions can be executed in the next decade to search for life at Enceladus.

Shannon M. MacKenzie↗
DOE OSTI2026

A compact, low-power epithermal neutron counter for lunar water detection

The detection and characterization of lunar water are critical for enabling sustainable human and robotic exploration of the Moon. Orbital neutron spectrometers, such as instruments on Lunar Prospector and the Lunar Reconnaissance Orbiter, have revealed hydrogen-rich regions near the poles but are limited by coarse spatial resolution and low counting efficiency. We present a compact, lightweight, and low-power epithermal neutron detector based on boron-coated silicon imagers, designed to probe subsurface hydrogen at decimeter scales from mobile platforms such as lunar rovers. This instrument leverages the high neutron capture cross-section of 10 B to convert epithermal neutrons into detectable α and 7 Li ions in a fully-depleted silicon imager, providing a unique event topology to identify neutrons while suppressing backgrounds. Monte Carlo simulations demonstrate that a 3 μm boron layer achieves optimal neutron detection efficiency, further enhanced with polyethylene moderation to improve sensitivity to the 0.4 eV–500 keV epithermal energy range. For a 10 cm 2 active area, the detector achieves sensitivity to H 2 O weight fractions as low as 0.01 wt% in a 15 minute measurement. This scalable, portable, low-mass design is well-suited for integration into upcoming Artemis and commercial lunar rovers, providing a transformative capability for in-situ resource prospecting and ground-truth validation of orbital measurements.

Detector modelling and simulations I (interaction ↗
DOE OSTI2023

Soil architecture and subsurface stratigraphic heterogeneities across land-lake interfaces along Lake Erie.

Uploaded raw datasets from electrical resistivity tomography (ERT), ground penetrating radar (GPR), electromagnetic induction (EMI) and insitu sensors were acquired across land-lake interfaces along Lake Erie. These datasets were useful to delineate the soil architecture and subsurface stratigraphic heterogeneities. We combined multiple geophysical methods with lithostratigraphic logs from borehole cores and data from soil and borehole sensors to investigate spatial heterogeneities across land-lake interfaces. The apparent electrical conductivity (Eca) maps matched closely with the soil maps from public database and also detected additional soil units that were missing in the traditional soil maps. This implies that electromagnetic induction (EMI) could be relied upon for non invasive characterization of soils in sampling restricted sites where only non-invasive measurements are feasible. Results from electrical resistivity tomography (ERT) and Ground penetrating radar (GPR) are consistent with the surficial geology of the study area, and revealed that the vertical variabilities at the sites are mainly driven by stratigraphy.The ERT data (.stg) were acquired from three different sites portage river (PTR), crane creek (CRC) and old woman creek (OWC). The ".stg" files can be opened with ERT inversion software such as EarthImager, ResIpy or Res2DInv. The GPR data (.GPZ) were also acquired from the three sites, and the ".GPZ" data files can be opened with EKKO_project 5 software from Sensors & Software Inc., or with any other standard GPR software. The EM data (.csv) were acquired from the three sites while the soil sensor data (.csv) here were acquired only from crane creek site. The ".csv) files can be opened with MS Excel or any other spread sheet software.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mechanistic understanding of carbon mineralization in fracture systems using microfluidics

Carbon mineralization in mafic and ultramafic rocks presents an opportunity for permanent carbon storage in the Earth's subsurface. However, due to their lower permeability, pre-existing fracture networks are key for mineralization to occur. Therefore, to fully develop this technology, a mechanistic understanding of the mineralization behavior in fractures with the consideration of hydrodynamic components is required. We use high-pressure microfluidics to investigate key mechanisms influencing dissolution–precipitation in a fracture network. The experiments were conducted in micromodels made of natural rocks with a comb-shaped flow channel to mimic a fracture network. This enabled studying the effect of injection rate on coupled dissolution–precipitation in advection and diffusion-dominated flow paths. We used gypsum carbonation as an analog reaction to allow for realistic experimental time frames due to its rapid reaction kinetics. The experimental work is coupled with high-fidelity numerical simulations to enhance our understanding of the parameters affecting the mineralization reaction. Our results demonstrate the importance of flow rate on the rate and nature of the gypsum carbonation reaction revealing that higher flow rates enable deeper penetration of the mineral precipitation front into the dead-end channels. This is an important finding since for sustained mineralization in a fracture network, precipitation in dead-ends while still allowing for flowing fractures is critical. Detailed characterization of the precipitates showed that lower flow rates led to porous and loose precipitates in the form of aragonite while higher flow rates mimicked supersaturation behavior leading to the formation of calcite. The reactive transport simulations further demonstrated the significance of flow velocity in advection-dominated channels to influence the efficiency of carbon mineralization in diffusion-dominated channels, potentially clogging of dead-end channels. These findings highlight the need for coupling chemical, mechanical, and hydrodynamic processes to evaluate the nature and extent of carbon mineralization in fractured media critical for permanent storage in mafic and ultramafic formations. This research further highlights the need for more investigation in potential subsurface fracture generation techniques to aid carbon mineralization.

25 ENERGY STORAGE↗
NASA NTRS1993

Microscale characterization of dissolved organic matter production and uptake in marine microbial mat communities

Intertidal marine microbial mats exhibited biologically mediated uptake of low molecular weight dissolved organic matter (DOM), including D-glucose, acetate, and an L-amino acid mixture at trace concentrations. Uptake of all compounds occurred in darkness, but was frequently enhanced under natural illumination. The photosystem 2 inhibitor, 3-(3,4-dichlorophenyl)-1,1-dimethyl urea (DCMU) generally failed to inhibit light-stimulated DOM uptake. Occasionally, light plus DCMU-amended treatments led to uptake rates higher than light-incubated samples, possibly due to phototrophic bacteria present in subsurface anoxic layers. Uptake was similar with either 3H- or 14C-labeled substrates, indicating that recycling of labeled CO2 via photosynthetic fixation was not interfering with measurements of light-stimulated DOM uptake. Microautoradiographs showed a variety of pigmented and nonpigmented bacteria and, to a lesser extent, cyanobacteria and eucaryotic microalgae involved in light-mediated DOM uptake. Light-stimulated DOM uptake was often observed in bacteria associated with sheaths and mucilage surrounding filamentous cyanobacteria, revealing a close association of organisms taking up DOM with photoautotrophic members of the mat community. The capacity for dark- and light-mediated heterotrophy, coupled to efficient retention of fixed carbon in the mat community, may help optimize net production and accretion of mats, even in oligotrophic waters.

NASA Discipline Exobiology↗
DOE OSTI2019

Neural network modeling of in situ fluid-filled pore size distributions in subsurface shale reservoirs under data constraints

Subsurface nuclear magnetic resonance (NMR) logs acquired in the wellbore environment are sensitive to fluid-filled pore size distribution, fluid mobility, permeability, and porosity in the near-wellbore reservoir volume. NMR response of a formation layer is processed to extract the T2 distribution, which approximates the fluid-filled pore size distribution. NMR logs are acquired in limited number of wells due to financial and operational challenges, which adversely affects reservoir characterization. We developed here two neural-network-based machine learning techniques, long short-term memory (LSTM) network and variational autoencoder with a convolutional layer (VAEc) network, to process the ‘easy-to-acquire’ formation mineral and fluid saturation logs to generate synthetic NMR T2 distributions in the absence of ‘hard-to-acquire’ NMR T2 distribution log. Both the predictive models are trained and tested on limited wireline log measurements randomly selected from a 300-ft depth interval of the Bakken shale formation. Synthesis performances of LSTM and VAEc models in terms of R 2 are 0.78 and 0.75, respectively. Noise is inevitable in logging data due to the complex wellbore and formation conditions. Notably, both the predictive models robustly synthesize the fluid-filled pore size distributions in the presence of 50% noise in input logs and 30% noise in training T2 data. The performance of the proposed methodology improves with access to larger volume of training data from other formation types. The proposed method is critical to the synthesis of in situ fluid-filled pore size distributions in shale formations under data constraints due to financial and operational challenges.

58 GEOSCIENCES↗
DOE OSTI2016

Site-Specific Preparation of Intact Solid–Liquid Interfaces by Label-Free In Situ Localization and Cryo-Focused Ion Beam Lift-Out

Abstract Scanning transmission electron microscopy (STEM) allows atomic scale characterization of solid–solid interfaces, but has seen limited applications to solid–liquid interfaces due to the volatility of liquids in the microscope vacuum. Although cryo-electron microscopy is routinely used to characterize hydrated samples stabilized by rapid freezing, sample thinning is required to access the internal interfaces of thicker specimens. Here, we adapt cryo-focused ion beam (FIB) “lift-out,” a technique recently developed for biological specimens, to prepare intact internal solid–liquid interfaces for high-resolution structural and chemical analysis by cryo-STEM. To guide the milling process we introduce a label-free in situ method of localizing subsurface structures in suitable materials by energy dispersive X-ray spectroscopy (EDX). Monte Carlo simulations are performed to evaluate the depth-probing capability of the technique, and show good qualitative agreement with experiment. We also detail procedures to produce homogeneously thin lamellae, which enable nanoscale structural, elemental, and chemical analysis of intact solid–liquid interfaces by analytical cryo-STEM. This work demonstrates the potential of cryo-FIB lift-out and cryo-STEM for understanding physical and chemical processes at solid–liquid interfaces.

36 MATERIALS SCIENCE↗