Deployable Greenhouse for Food Production on Long-Duration Exploration Missions
An overview of the FY15 X-Hab project deployable greenhouse for food production on long-duration exploration missions from Oklahoma State University.
Kelsey Khoo↗
SEARCH · Engineering Papers
Results for “Oklahoma”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
How Should Machine Learning Be Successfully Used for Wind Speed Vertical Extrapolation?
An accurate characterization of the wind resource available at hub-height is required for an efficient and bankable wind farm project. However, direct measurement of wind speed at the constantly increasing height of the hub of commercial wind turbines is oftentimes challenging and expensive, so that it is common practice to vertically extrapolate the wind resource from lower and more easily accessible levels. Conventional techniques for wind speed vertical extrapolation include the use of a power law and a logarithmic profile. While simple, the limits in accuracy of these methods have been shown in various studies. Recently, machine learning has been proposed as a new method to vertically extrapolate winds. All the published studies on the topic assess the performance of machine learning techniques in vertically extrapolating the wind resource at the same location where the algorithm has been trained. However, in real-world applications, the wind resource is measured at the instrument location, but it then needs to be extrapolated at hub height at the location of the wind turbines within the find farm. To be able to fully recommend the use of machine learning techniques over the simple power law and logarithmic law, the spatial variability of the performance improvements of the machine learning approaches needs to be assessed. Here, we propose a round-robin validation of a machine learning-based method for wind speed extrapolation. We use 20 months of observations at four locations spanning a 100 km wide region at the Southern Great Plains (SGP) atmospheric observatory, in north-central Oklahoma. At each location, we train a random forest to predict 30-min average wind speed at 143 m AGL. We use as input features lidar wind speed at 65 m AGL, time of day, sonic anemometer wind speed at 4 m AGL, turbulent kinetic energy, and Obukhov length. First, we perform a same-site comparison of the performance of the proposed random forest against the conventional techniques for wind speed extrapolation (namely power law and logarithmic profile, with widely accepted stability corrections). We find that the random forest outperforms the power law in vertically extrapolating wind speed in all the considered stability regimes, with a 33% reduction in MAE for stable conditions, and a 31% reduction in unstable conditions. Similar results are found when comparing predictions of extrapolated winds from the logarithmic profile and the random forest with the observed values. Next, we propose a round-robin validation, to use the random forest trained at each site to extrapolate wind speed at the remaining three sites. We find that the performance of the random forest approach degrades when the algorithm is tested at a site different than the training one. However, even under those circumstances, the machine learning-based approach still outperforms the conventional techniques for wind speed extrapolation, with, on average, a reduction in mean absolute error between 15 and 20% over the conventional methods, with the largest benefits obtained under stable conditions.
Monte Carlo↗
CT Scanning in the Geosciences: Facilities Overview and Mudrock Case Study
Presented by NETL at Oklahoma State University, Caney Shale Viewing, Chesapeake Rock Lab, 02/20
Paronish, Thomas J.↗
Evaluation of Stripping Resistance of Organoclay-Modified Asphalt Binder and Aggregate Systems Using an Optical Contact Angle Analyzer
Organoclays, often referred to as nanoclays (NCs), are organically modified phyllosilicates. They are derived from naturally occurring clay minerals and possess unique characteristics in improving the physical and mechanical properties of polymers and rubbers. Recently, NCs have drawn interest in the modification of asphalt binders as micro-scale fillers. A few recent studies have revealed that the addition of NCs in asphalt binders improved binders’ stiffness, aging characteristics, and fatigue resistance. This study aims to evaluate the changes in moisture resistance of different NC-modified asphalt binders through the surface free energy (SFE) technique. This technique estimates SFE properties of binders and aggregates from static contact angle (SCA) data measured from an optical contact angle analyzer (OCA). Further, this study examines the changes in chemical compositions (functional groups) of binders due to the addition of selected NCs by using the Fourier Transformation Infrared (FTIR) technique. To this end, a commonly used performance grade (PG) binder (PG 64-22) modified with four different types (shape and size) of NCs, namely, Cloisite® 15 (C-15), Cloisite® 20 (C-20), Cloisite® Na+ (C-Na), and Cloisite® Ca++ (C-Ca) were evaluated in this study. The SFE data of five different types of aggregates from Oklahoma, namely, Davis Limestone (DL), Snyder Granite (SG), Dolese-Cooperton Limestone (DCL), Hanson-Davis Rhyolite (HDR), and Martin-Marietta-Mill-Creek Granite (MMMG), were used to perform their compatibility with the aforementioned NC-modified binders. The FTIR spectra revealed the presence of various alcohols, ethers, and esters in NC-modified asphalt binders. The moisture susceptibility analysis shows that the addition of NC results in an increase of SFE and cohesive energy of an asphalt binder, which are desired for improved moisture resistance. The addition of NC also shows improved compatibility in cases of all aggregates. Among the five aggregates, MMMCG showed the highest compatibility with all binders, followed by DCL, HDR, DL, and SG. In regard to NCs, the C-15 sample showed the highest compatibility followed by C-20, C-Na, and C-Ca.
Hossain, Zahid↗
Traceability of Surface Longwave Irradiance Measurements to SI Using the IRIS Radiometers: Preprint
The World Radiation Center at PMOD/WRC is operated on behalf of the WMO. The Infrared Radiometry Section of the WRC (WRC-IRS) provides traceability of downwelling atmospheric longwave radiation measured with pyrgeometers by comparison to the World Infrared Standard Group (WISG) [1]. As has been discussed previously [2], the current implementation of the WISG measures lower longwave irradiances than the two candidate reference radiometers IRIS (Infrared Integrating Sphere Radiometer) and the ACP (Absolute Cavity Pyrgeometer). To validate the findings reported in [2], additional measurements since that publication in 2014 have been performed and are discussed in this paper. Specifically, Measurements during cloud-free nights at PMOD/WRC between the WISG and IRIS radiometers, A field campaign at the Atmospheric Radiation Monitoring Site (ARM) at Southern Great Plains, Oklahoma with IRIS, ACP, AERI (Atmospheric Emittance Radiance Interferometer) and WISG traceable pyrgeometers, Laboratory comparison between the reference blackbody of PMOD/WRC with the hemispherical blackbody developed by PTB.
ACR↗
Investigation of Wind Plant Wake Effects at the AWAKEN Field Campaign
Wind plant wakes characterized by lower momentum flow with increased turbulent kinetic energy (TKE) have been shown to propagate for several kilometers and interact with neighboring plants. To better understand these interactions, an Oklahoma site hosting five wind plants is heavily instrumented as part of the American Wake Experiment (AWAKEN) field campaign. Upstream, interior-plant, and downstream flows are probed using a suite of remote sensing instruments to quantify wake properties such as the magnitude and extent of momentum deficit and TKE increase. The effects of atmospheric inflow (wind speed, turbulence, stability, etc.) are investigated. Under certain conditions, the impact of an upstream plant on its downstream neighbor can be observed using the performance data recorded by the downstream plant. In addition to providing insight into plant wake behavior, the results of this study will be used as a benchmark case for wind plant simulations.
AWAKEN↗
Mechanical Properties of Nominally Ductile and Brittle Zones within the Caney Shale Formation
We present a case study from the Caney Shale, which is an emerging hydrocarbon-bearing formation in Oklahoma. Open hole logs lead to a nominal distinction of five zones in an exploration well, two of which are designated “ductile” and three of which are designated as less ductile “reservoir” zones. Subsequently, a detailed mechanical characterization was carried out on core plugs taken from each of these zones. Results show nominally “ductile” zones are weaker in terms of UCS, tensile strength, fracture toughness, and confined compressive strength. However, by a variety of brittleness indices, it is found the nominal “ductile” regions do not behave as expected. They are weaker, but not consistently more ductile. Furthermore, some brittleness indices lead to contradictory conclusions. For example, zones which would be considered the most brittle according to the proportion of nonlinear stress-strain behavior prior to failure and/or by indices based on elastic properties would be considered the least brittle according to their internal friction angle.
Benge, Margaret↗
From Well Log to Formation Model: A Novel Laboratory Calibrated Methodology with Demonstration
This work demonstrates how the characterization and modeling of both elastic and creep properties are essential to describe zones in layered rock formations as either low-stress targets for stimulation or high-stress barriers to fracture growth. Prediction of fracture height is critical for designing stimulation operations in oil and gas wells. Ideally, fractures are placed in target zones which will produce hydrocarbons and should not propagate into zones expected to be unproductive or to produce unwanted fluids such as water which in turn must be treated and/or disposed. The essential task in designing stimulation plans is predicting which zones have low horizontal stresses and which will be high-stress barriers to fracture growth. Despite this importance, there are gaps in current knowledge and a complete workflow from laboratory characterization to a finite element model which includes time dependent rock deformation is required. While the research and methodology presented here also have application to CO 2or hydrogen storage, wastewater injection, and geothermal applications, the focus will be on hydrocarbon extraction. This thesis presents the results of a characterization-to-prediction workflow for the Caney shale, which is an emerging hydrocarbon resource in Oklahoma, USA. It begins with an investigation to enable critical evaluation of the Caney zonation into nominally “brittle” and “ductile” zones based on properties observed from well logs. It shows none of the zones are consistently “brittle” or “ductile” mechanical behavior based on the variety of definitions of these terms. However, the nominally ductile zones are weaker and more prone to creep. A laboratory investigation of samples including strength, elastic, and creep properties, is then used in a finite element model of stress evolution. The model includes both elastic deformation and viscoplastic creep. Results predict the least creep-prone layers to have the lowest horizontal stresses, therefore comprising hydraulic fracturing targets. The most creep-prone layers attain a horizontal stress similar to the vertical stress and therefore are predicted to be high stress barriers to hydraulic fracture stimulation. In addition to defining stimulation target intervals, the model shows how as tectonic strain rate increases, there is a transition from creep-dominated stresses to stresses dominated by elasticity.
Benge, Margaret↗
Investigation of acoustic waves under subsurface conditions to improve the predictions of rock mechanical properties and natural fracture characteristics
Mechanical properties and natural fracture characteristics are critical to investigate for subsurface engineering applications, including carbon storage, well drilling, and stimulation, as they govern rock stability, fluid flow, and mechanical behavior under stress. This dissertation integrates experimental and machine learning approaches to enhance the prediction and understanding of these properties by analyzing acoustic wave behavior under varied subsurface conditions. First, the influence of temperature, pore pressure, and supercritical CO2 (scCO2) saturation on poroelastic properties is examined using Gray Berea sandstone samples. The results show that temperature and pore pressure significantly affect the bulk modulus and Biot’s coefficient, while scCO2 saturation impacts rock compressibility, informing strategies for effective geological carbon storage. The study extends this understanding by experimentally evaluating the impact of reservoir depletion on the dynamic mechanical properties of the emerging Caney shale in South Oklahoma with the employment of unsupervised machine learning to predict static mechanical properties across the Caney shale. Integrating petrophysical data and chemostratigraphy, the workflow—featuring K-means clustering, principal component analysis (PCA), and inverse distance weighting (IDW)—improves stratigraphic characterization and the estimation of static-to-dynamic modulus ratios, which is vital for optimizing drilling and stimulation strategies. Finally, the work explores how natural fracture characteristics in shale influence acoustic waveforms and shear wave splitting (SWS) analysis. Experimental data on fractured samples under different stress and temperature conditions, combined with machine learning models such as K-nearest neighbors (KNN) and extreme gradient boosting (XGBoost), reveal key fracture properties impacting SWS and wave propagation. Together, these studies provide a comprehensive framework for linking acoustic wave behavior with rock properties, advancing the methods for monitoring and predicting geomechanical changes. The insights offered valuable implications for safer, more efficient CO2 injection, hydrocarbon extraction, and subsurface management.
Elkholy, Sherif↗
PREPARATION OF CLAY-COATED GLASS SURFACES FOR MICROFLUIDICS-BASED STUDY ON CLAY-FLUID INTERACTIONS
Unique characteristics of clay, even though make any clay abundant shales a good source of adsorbed gas, make them equally difficult to produce. The clay-water interaction can cause significant swelling and fines migration in the shale formation, both of which can significantly impair the overall hydrocarbon recovery from shale. Geomaterial micromodels, developed by functionalizing traditional glass or PDMS surface with geomaterials (e.g., calcite, quartz, clay) can represent the physico-chemical properties of the natural porous media and have been used during the last few years to understand and evaluate the solid-fluid physicochemical interactions. This study focuses on developing a clay-coated geomaterial surface and investigates the effect of base fluid's salinity on clay adsorption to the glass surface. Glass capillary tubes and straight channel borosilicate glass micromodels are coated with Illite clay minerals to represent the pore-scale clay chemistry of Caney Shale, a Mississippian unconventional play in Southern Oklahoma, USA. 10 wt.% of Illite clay slurries made with brines of four different salinities are used to coat the glass-capillary tubes to understand the effect of salinity in clay adsorption on the glass surface and overall coating quality. To achieve a stable coating and evaluate the impact of heat treatment on coating's stability, straight channel glass flow cells coated with Illite clay are heat-treated at low (25 °C) and high temperature (125 °C). Dynamic flooding tests were carried out with brines on the coated surface to evaluate the stability of the coating. The experiments' outcome indicated a strong relationship between the brine's salinity and the adsorption of clay particles on the glass surface. An increase in brine concentration resulted in improved adsorption of clay particles on the glass surface. Experiments involving heat treating the glass surface following the coating demonstrated significant improvement in the stability of the coating.
02 PETROLEUM↗
Orientation microscopy–assisted grain boundary analysis for protonic ceramic cell electrolytes
Abstract Grain boundaries in protonic ceramic cell (PCC) electrolytes hinder proton transport, reducing interfacial conductivity. In multicomponent PCC electrolytes, the inclusion of sintering aids further accentuates the complexity of grain boundaries. In this study, we synthesize nanocrystalline BaCe 0.4 Zr 0.4 Y 0.1 Yb 0.1 O 3− δ thin films via pulsed laser deposition and analyze their grain boundary character distributions using orientation data collected by precession electron diffraction technique. The results reveal an anisotropic distribution of grain boundary characters, with notably high populations of 180°‐tilt and twist grain boundaries. These findings provide critical insights into identifying the predominant grain boundaries in this PCC electrolyte material, assessing the vast five‐dimensional grain boundary space.
Patel, Sooraj [School of Aerospace and Mechanical ↗
CMCSCFCB—Critical Minerals in Coaly Strata of the Cherokee-Forest City Basin
This report summarizes results of CMCSCFCB—Critical Minerals in Coaly Strata of the Cherokee-Forest City Basin, a multiyear and multidisciplinary study funded through DE-FOA-0002364 as part of the Department of Energy Office of Fossil Energy and Carbon Management (FECM) Carbon Ore, Rare Earth and Critical Minerals (CORE-CM) Initiative for U.S. Basins. Our working group of state and tribal agencies collected data and made interpretations included herein. It also surveyed the regional potential for critical mineral/material production.
01 COAL, LIGNITE, AND PEAT↗
Efficient Mn 2+ Doping in Non-Stoichiometric Cesium Lead Bromide Perovskite Quantum Dots
Doping magnetic transition metal ions (e.g., Mn 2+ ) into colloidal quantum dots endows novel optical and magnetic properties to the host materials. CsPbBr 3 quantum dots (QDs) are emerging light-emitting materials with high structural and chemical flexibility in the visible spectral regime. However, efficiently doping Mn 2+ ions in CsPbBr 3 QDs remains challenging, especially when size confinement and ensemble uniformity are needed for understanding the underexplored exciton-dopant exchange interaction. Here, we introduce a doping mechanism based on electrostatic surface Mn 2+ adsorption that enables efficient Mn 2+ incorporation in strongly confined CsPbBr 3 QDs. The resultant QDs are found to have a Cs-deficient stoichiometry compared to their undoped counterparts. A redox reaction-based purification method was developed to remove Mn 2+ cations that are tightly adsorbed on the surface to determine the concentration of lattice-incorporated Mn 2+ . Our synthesis enables a Mn 2+ doping/alloying concentration of up to ∼44% with a Mn 2+ photoluminescence efficiency exceeding 90%. This allows for the determination of the intrinsic exciton-to-dopant energy transfer rate.
Hidayatova, Lamia [Univ. of Oklahoma, Norman, OK (↗
Towards non-blinking and photostable perovskite quantum dots
Surface defect-induced photoluminescence blinking and photodarkening are ubiquitous in lead halide perovskite quantum dots. Despite efforts to stabilize the surface by chemically engineering ligand binding moieties, blinking accompanied by photodegradation still poses barriers to implementing perovskite quantum dots in quantum emitters. To date, ligand tail engineering in the solid state has rarely been explored for perovskite quantum dots. We posit that attractive intermolecular interactions between low-steric ligand tails, such as π-π stacking, can promote the formation of a nearly epitaxial ligand layer that significantly reduces the quantum dot surface energy. Here, we show that single CsPbBr 3 quantum dots covered by stacked phenethylammonium ligands exhibit nearly non-blinking single photon emission with high purity (~98%) and extraordinary photostability (12 hours continuous operation and saturated excitations), allowing the determination of size-dependent exciton radiative rates and emission line widths of CsPbBr 3 quantum dots at the single particle level.
36 MATERIALS SCIENCE↗
Studying Aerosol, Clouds, and Air Quality in the Coastal Urban Environment of Southeastern Texas
A multi-agency succession of field campaigns was conducted in southeastern Texas during July 2021 through October 2022 to study the complex interactions of aerosols, clouds and air pollution in the coastal urban environment. As part of the Tracking Aerosol Convection interactions Experiment (TRACER), the TRACER- Air Quality (TAQ) campaign the Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) and the Convective Cloud Urban Boundary Layer Experiment (CUBE), a combination of ground-based supersites and mobile laboratories, shipborne measurements and aircraft-based instrumentation were deployed. These diverse platforms collected high-resolution data to characterize the aerosol microphysics and chemistry, cloud and precipitation micro- and macro-physical properties, environmental thermodynamics and air quality-relevant constituents that are being used in follow-on analysis and modeling activities. We present the overall deployment setups, a summary of the campaign conditions and a sampling of early research results related to: (a) aerosol precursors in the urban environment, (b) influences of local meteorology on air pollution, (c) detailed observations of the sea breeze circulation, (d) retrieved supersaturation in convective updrafts, (e) characterizing the convective updraft lifecycle, (f) variability in lightning characteristics of convective storms and (g) urban influences on surface energy fluxes. The work concludes with discussion of future research activities highlighted by the TRACER model-intercomparison project to explore the representation of aerosol-convective interactions in high-resolution simulations.
54 ENVIRONMENTAL SCIENCES↗
Modest functional diversity decline and pronounced composition shifts of microbial communities in a mixed waste-contaminated aquifer
Background: Microbial taxonomic diversity declines with increased environmental stress. Yet, few studies have explored whether phylogenetic and functional diversities track taxonomic diversity along the stress gradient. Here, we investigated microbial communities within an aquifer in Oak Ridge, Tennessee, USA, which is characterized by a broad spectrum of stressors, including extremely high levels of nitrate, heavy metals like cadmium and chromium, radionuclides such as uranium, and extremely low pH (< 3). Results: Both taxonomic and phylogenetic α-diversities were reduced in the most impacted wells, while the decline in functional α-diversity was modest and statistically insignificant, indicating a more robust buffering capacity to environmental stress. Differences in functional gene composition (i.e., functional β-diversity) were pronounced in highly contaminated wells, while convergent functional gene composition was observed in uncontaminated wells. The relative abundances of most carbon degradation genes were decreased in contaminated wells, but genes associated with denitrification, adenylylsulfate reduction, and sulfite reduction were increased. Compared to taxonomic and phylogenetic compositions, environmental variables played a more significant role in shaping functional gene composition, suggesting that niche selection could be more closely related to microbial functionality than taxonomy. Conclusions: Overall, we demonstrated that despite a reduced taxonomic α-diversity, microbial communities under stress maintained functionality underpinned by environmental selection.
59 BASIC BIOLOGICAL SCIENCES↗
Rb 4 CuSb 2 Cl 11 and Rb 2 In 0.91(0.2) Sb 0.09 Cl 5 ·H 2 O: Wide Band Gap 0D Metal Halide Semiconductors
Herein, we report the discovery, structural and photophysical characterization of a new zero-dimensional (0D) lead-free all-inorganic halide, Rb 4 CuSb 2 Cl 11 , which adopts a new structure type. Single-crystal X-ray diffraction (SCXRD) shows that the structure consists of isolated, distorted seesaw [SbCl 4 ] − and trigonal planar [CuCl 3 ] 2− units, separated by Rb + cations that provide charge balance. Optoelectronic measurements and density functional theory (DFT) calculations indicate an indirect band gap of 2.89 eV, making it a candidate for wide-bandgap optoelectronic applications. Electrical resistivity was measured at 1.29 × 10 10 Ω·cm, and the trap-state density (n trap ) was found to be 7.44 × 10 10 cm −3 . Attempts to synthesize substitution analogs of Rb 4 CuSb 2 Cl 11 led to the synthesis of Rb 2 In 0.91(0.2) Sb 0.09 Cl 5 ·H 2 O, which was erroneously reported as Rb 2 SbCl 5 O in a previous study. Rb 2 In 0.91(0.2) Sb 0.09 Cl 5 ·H 2 O adopts a vacancyordered perovskite structure and exhibits broad-band yellow emission under UV excitation. The measured photoluminescence quantum yield (PLQY) for Rb 2 In 0.91 (0.2)Sb 0.09 Cl 5 ·H 2 O is 18.2%. These findings add to the growing class of quaternary metal halides with multiple cation and anion compositions, expanding the chemical phase space for the discovery of new materials with functional properties.
Crystal structure↗
Nano-Engineered Interfaces in Dual-Layer Electrodes for Protonic Ceramic Cells with Enhanced Stability and Kinetics
Enhancing interfacial stability and charge transfer in protonic ceramic cells (PCCs) remains a critical challenge, as structural degradation and interfacial resistance often compromise durability and efficiency. Here, we report a nanoengineered dual-layer oxygen electrode architecture designed to address these limitations by introducing a fine-grained nanoparticle interfacial contact layer beneath a porous catalytic backbone. The nanoscale powders, through enhanced sintering activity, densify into a robust interfacial layer that promotes strong chemical bonding, uniform adhesion, and continuous ionic/electronic pathways with the BCZYYb electrolyte. This hierarchical architecture mitigates delamination, redistributes mechanical stress, and establishes efficient charge and mass transport channels without relying on corrosive surface treatments. Electrochemical evaluation demonstrates that the dual-layer design markedly reduces interfacial polarization resistance and accelerates electrode kinetics. Compared to the single-layer counterpart, the architecture achieves a peel strength of 44.53 N/cm 2 , a 40% improvement in peak power density (0.96 W cm –2 at 600 °C), and a 130% enhancement in electrolysis current density (4.78 A cm –2 at 1.57 V). Faradaic efficiency remains as high as 88% under high steam concentrations, underscoring minimal charge loss during practical operation. Notably, the electrode retains stability across 450–600 °C and under transient voltage cycling, with impedance spectra confirming suppressed interfacial resistance growth over prolonged use. These results highlight nanoscale interface engineering as a powerful route to enhance both mechanical robustness and electrochemical kinetics in PCCs. The demonstrated scalability and durability of this architecture provide a versatile platform for advancing solid-state electrochemical systems, including reversible fuel cells and high-efficiency hydrogen production technologies.
Faradaic efficiency↗