Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “salinity”

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.

At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Incorporating corrosion design constraints in desalination process optimization: A case study in mechanical vapor compression

Corrosion is an expensive and complex challenge for desalination, yet current design approaches do not explicitly account for corrosion mechanisms in process modeling and technoeconomic analysis. Here, to address this gap, we present a workflow for incorporating corrosion design constraints directly into desalination process optimization models. We develop surrogate models for general and localized corrosion metrics as functions of temperature, pH, salinity, dissolved oxygen, and material using data from OLI Systems’ Corrosion Analyzer. We then integrate these surrogates as corrosion design constraints in a cost-optimization MVC model that minimizes the levelized cost of water (LCOW). For a case study of mechanical vapor compression (MVC) treating seawater across a range of recoveries, we find dissolved oxygen (DO) is the dominant driver of localized corrosion, and thus of cost-optimal material choice and operating conditions. Reducing the DO from 8 mg/L to 0.5 mg/L reduces the LCOW by 15-35%, informing the breakeven costs for implementing DO removal or selecting highly corrosion-resistant alloys. This framework is broadly applicable across corrosion types, materials, and components and enables desalination process design that minimizes capital costs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Critical review of lithium recovery from geothermal brines with implications for Smackover Formation, USA

The rapidly growing demand for lithium, a critical element for energy storage and national security technologies, has intensified concerns over the long-term availability and environmental impact of conventional lithium sources, such as hard-rock mining. To meet future demand, it is vital to explore unconventional resources that can provide sustainable domestic supplies. Geothermal brines, produced as a byproduct of geothermal energy generation, offer a promising alternative for lithium recovery by leveraging existing infrastructure and renewable energy production. In particular, the Smackover Formation, an extensive reservoir of high-salinity brines spanning Arkansas, Texas, Louisiana, Mississippi, and Alabama in the U.S. Gulf Coast, holds significant untapped lithium reserves. Co-producing geothermal energy and lithium from these brines aligns with sustainable extraction objectives while addressing resource scarcity. This review synthesizes current knowledge of lithium occurrence in the Smackover Formation and geothermal resources in the region, while also exploring how emerging tools such as machine learning can enhance resource targeting and co-production efficiency. Finally, we discuss key technical challenges and outline future research directions needed to advance lithium extraction from geothermal brines and secure a resilient domestic supply chain.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Explicit quantification of residence and flushing times in the Salish Sea using a sub-basin scale shoreline resolving model

The Salish Sea, located in the Pacific Northwest region of North America has complex currents and circulation features distributed over numerous interconnected deep basins with islands. Increased risk of exposure to oil spills and untreated wastewater from maritime emergencies and treatment plant failures have led to a need for quantifying residence and flushing characteristics at a sub-basin scale using a shoreline resolving hydrodynamic model. An unstructured grid model of the Salish Sea was developed using FVCOM with a ≈75-100m shoreline resolution. In addition to 7 tides and 23 salinity and temperature monitoring stations, an extensive currents data set from 135 stations collected over a span of three years was used for skill assessment and validation. Explicit forward computations were then conducted to define and quantify residence and flushing times in various sub-basins of interest using (a) Lagrangian particles and (b) Numerical/virtual dye experiments. The results in most basins show expected seasonal variability with longer flushing time associated with summer lower tides and lower freshwater inflows. However, contrary to expectation, flushing time is significantly longer in wintertime in large fjord-like basins such as Hood Canal (≈138 days), likely due to increased stratification and reduced mixing. The flushing time for the Puget Sound region of the Salish Sea is ≈115 days, while Georgia Basin is 240 days when analyzed as stand-alone basins with zero background concentrations. When examined as part of the flushing of the entire Puget Sound filled with virtual dye, the compounded flushing times for embedded sub-basins can be significantly longer in order of magnitudes and largely dictated by the flushing time of Puget Sound. The computed residence and flushing time scales tabulated over 36 sub-basins provide an improved understanding of water renewal in the system, informing pollution management actions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impacts of climate change on estuarine stratification and implications for hypoxia within a shallow subtropical system

Vertical density stratification often plays an important role in the formation and expansion of coastal hypoxic zones through its effect on near-bed circulation and vertical oxygen flux. However, the impact of future climate change on estuarine circulation is widely unknown. Here, we developed and calibrated a three-dimensional hydrodynamic model for Pensacola Bay, a shallow subtropical estuary in the northeastern Gulf of Mexico. Model simulations based on years 2013–2017 were applied to examine changes in salinity, temperature, and density under future climate scenarios, including increased radiative forcing (IR) and temperature (T), increased freshwater discharge (D), sea level rise (SLR), and wind intensification (W). Simulations showed that the impacts of climate change on modeled state variables varied over time with external forcing conditions. The model demonstrated the potential for sea level rise and increased freshwater discharge to episodically increase vertical density gradients in the Bay. However, increased wind forcing destabilized vertical gradients, at times reducing the spatial extent and duration of stable stratification. For time periods with low freshwater discharge, moderate increases in wind speed (10%) can destabilize density gradients strengthened by increased discharge (10%) and sea level rise (0.48 m). In contrast, destruction of strong density gradients that form near the mid-Bay channel following flood events requires stronger wind forcing. Furthermore, these results highlight the importance of considering natural variability in freshwater and wind forcing, as well as local phenomena that are generally unresolved by global climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Non-mercury methylating microbial taxa are integral to understanding links between mercury methylation and elemental cycles in marine and freshwater sediments

The goal of this study was to explore the role of non-mercury (Hg) methylating taxa in mercury methylation and to identify potential links between elemental cycles and Hg methylation. Statistical approaches were utilized to investigate the microbial community and biochemical functions in relation to methylmercury (MeHg) concentrations in marine and freshwater sediments. Sediments were collected from the methylation zone (top 15 cm) in four Hg-contaminated sites. Both abiotic (e.g., sulfate, sulfide, iron, salinity, total organic matter, etc.) and biotic factors (e.g., hgcA, abundances of methylating and non-methylating taxa) were quantified. Random forest and stepwise regression were performed to assess whether non-methylating taxa were significantly associated with MeHg concentration. Co-occurrence and functional network analyses were constructed to explore associations between taxa by examining microbial community structure, composition, and biochemical functions across sites. Regression analysis showed that approximately 80% of the variability in sediment MeHg concentration was predicted by total mercury concentration, the abundances of Hg methylating taxa, and the abundances of the non-Hg methylating taxa. The co-occurrence networks identified Paludibacteraceae and Syntrophorhabdaceae as keystone non Hg methylating taxa in multiple sites, indicating the potential for syntrophic interactions with Hg methylators. Strong associations were also observed between methanogens and sulfate-reducing bacteria, which were likely symbiotic associations. The functional network results suggested that non-Hg methylating taxa play important roles in sulfur respiration, nitrogen respiration, and the carbon metabolism-related functions methylotrophy, methanotrophy, and chemoheterotrophy. Interestingly, keystone functions varied by site and did not involve carbon- and sulfur-related functions only. In conclusion, our findings highlight associations between methylating and non-methylating taxa and sulfur, carbon, and nitrogen cycles in sediment methylation zones, with implications for predicting and understanding the impact of climate and land/sea use changes on Hg methylation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Bio-distribution and deposition of wildfire smoke chemicals into olfactory bulb and brain of rats after intranasal instillation

Epidemiological and experimental studies suggest wildfire smoke is a potential contributor to neurological dysfunction and associated with neuroinflammation. Using doses comparable to those encountered during intense wildfire events (200-300 μg/m 3 ), we explore the absorption, distribution, metabolism, and elimination (ADME) and pharmacokinetics of representative members of major chemical classes (acid, phenol, PAH, aldehyde) in inhaled wood smoke condensates. Male Sprague Dawley rats were intranasally instilled with smoldering eucalyptus woodsmoke extract (WSE) reconstituted in saline spiked with 14 C-labeled palmitic acid (PA), benzo[a]pyrene (B[a]P), catechol (CAT) or benzaldehyde (BZ). Serum was collected from 5 min to 2 weeks after exposure and tissues were collected at 0.5, 2, 4, 24 h and 2 weeks after exposure. Urine was collected over the 24 h exposure. Tissues were collected, rinsed in PBS and analyzed by accelerator mass spectrometry (AMS) for 14C-labeled chemicals. PA and B[a]P entered circulation slowly, reached maximum concentration (C max ) near 15 ng/mL at 2 h, and had circulating concentrations near 1/3 C max 24 h after exposure. CAT and BZ rapidly entered circulation and were mostly cleared at 2 h. Excess 14 C from all four chemicals was detected in olfactory bulb and brain over the first 24 h but only PA (or its metabolites) was retained in olfactory bulb, brain and kidney at 2 weeks post exposure. All excess 14 C was cleared from the lung at 2 weeks. Metabolite analysis of urine (CAT, BZ and B(a)P) dosed samples did not detect any parent compound. CAT and BZ were rapidly cleared. The slower uptake and clearance of PA or B[a]P or their reactive metabolites when dosed with WSE in brain and olfactory bulb potentially provide greater opportunity for inflammatory response. This study suggests that wildfire smoke chemicals can enter the brain directly from the nasal cavity to the olfactory bulb and via systemic circulation.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

A Physics-Constrained Deep Learning Model for Simulating Multiphase Flow in 3D Heterogeneous Porous Media

Physics-based simulators for multiphase flow in porous media emulate nonlinear processes with coupled physics, and usually require extensive computational resources for software development, maintenance and simulation execution. As a result, a huge demand exists for fast modeling of coupled processes in a wide range of subsurface applications including geological sequestration, hydrocarbon recovery and geothermal energy extraction. In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3-Dimensional (3D) heterogeneous porous media. The model fully leverages the spatial topology predictive capability of convolutional neural networks, specifically U-Net with successive contracting and expansive steps, and is coupled with an efficient continuity-based smoother to predict flow responses that need spatial continuity. Furthermore, the transient regions are penalized to steer the training process such that the model can accurately capture flow in these regions. The model takes inputs including properties of porous media, fluid properties and well controls, and predicts the temporal-spatial evolution of the state variables (pressure and saturation). While maintaining the continuity of fluid flow, the 3D spatial domain is decomposed into 2D images for reducing training cost, and the decomposition results in an increased number of training data samples and better training efficiency. Additionally, a surrogate model is separately constructed as a postprocessor to calculate well flow rate based on the predictions of state variables from the deep learning model. We use the example of CO 2 injection into saline aquifers, and apply the physics-constrained deep learning model that is trained from physics-based simulation data and emulates the physics process. The model performs prediction with a speedup of ~ 1400 times compared to physics-based simulations, and the average temporal errors of predicted pressure and saturation plumes are 0.27% and 0.099% respectively. Furthermore, water production rate is efficiently predicted by a surrogate model for well flow rate, with a mean error less than 5%. Therefore, with its unique scheme to cope with the fidelity in fluid flow in porous media, the physics-constrained deep learning model can become an efficient predictive model for computationally demanding inverse problems or other coupled processes.

58 GEOSCIENCES↗
DOE OSTI2022

Multimodal study of the impact of stimulation pH on shale pore structure, with an emphasis on organics behavior in alkaline environments

The tight nature of shale formations calls for hydraulic fracturing techniques able of altering the pore architecture to facilitate the production of hydrocarbon resources. The composition, pH, salinity, density and chemistry of Hydraulic Fracturing Fluids (HFF) vary substantially depending on reservoir characteristics. pH is among the most important stimulation fluid properties, ranging from very acidic, for carbonate reservoirs, to basic, in the case of clay-rich formations. pH regulates what geochemical reactions take place between the stimulation fluid and shale, as well as pore architecture alteration. The dissolution of carbonates and pyrite, and the precipitation of common minerals such as barite, gypsum and iron oxides in acidic environments have been extensively documented. In contrast, alkali stimulation environments and the role of organic components have received less attention. This research provides insight into the role of both minerals and organic components during alkaline stimulation, and the resulting pore architecture alterations. Here, a set of reactive experiments are performed using three different shales, with varying organic matter (OM) content, at different pH (3, 6, 8, 10, 12). The analysis of pore architecture alteration induced by the reaction was performed via nitrogen (N2) gas adsorption and Time-Domain Nuclear Magnetic Resonance (TD-NMR). Inductively Coupled Plasma - Optical Emission Spectrometry (ICP-OES) was used to measure the composition of the stimulation fluid post-reaction. The system with a larger impact on the pore architecture (pH 12) underwent a more extensive analysis through the application of Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) and x-ray Diffraction (XRD). Results show that mineral dissolution contributed to the creation of secondary porosity, mainly through dissolution of clays and silicates. We show that the abundance and distribution of organic matter both play a significant role in changes in pore architecture. Most samples showed an increase in inter-organic porosity, likely due to the organic acids within kerogen reacting with the stimulation fluid. Samples with a larger amount and more widespread distribution of organic matter show the most significant alterations. Finally, we also highlight the dissolution process of iron-rich minerals, including framboidal pyrite, as another important source of secondary porosity.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2023

Machine learning and deep learning for mineralogy interpretation and CO 2 saturation estimation in geological carbon Storage: A case study in the Illinois Basin

Carbon capture and storage (CCS) is a promising approach to simultaneously maintaining energy security and reducing carbon dioxide (CO 2 ) emissions under the current energy portfolio that is dominated by fossil fuel energy. Pre-injection formation characterization and post-injection CO 2 monitoring are two critical tasks to guarantee storage efficiency in CCS. The CCS projects in the Illinois Basin, the first large-scale CO 2 injection into saline aquifers in the United States, employed conventional and the latest pulsed neutron logging (PNL) tools for mineralogy interpretation and CO 2 saturation estimation, which provide valuable references for future CCS projects. Because of the inherent fuzziness of petrophysical measurements and complex subsurface heterogeneity, interpreting well-logging data is time-consuming, and its accuracy can be user-biased. In recent years, data-driven methods have been widely used to capture the non-linear patterns between input features and interpretation results. This work applied and evaluated four commonly used machine learning (ML) models, including ridge regression (RR), random forest (RF), gradient boosting regression (GBR), support vector regression (SVR), and one deep learning (DL) model, the artificial neural network (ANN). We optimized the hyperparameters of the four ML models and the DL model using the simulated annealing algorithm and the grid search strategy, respectively. The input features of the mineralogy interpretation models were eleven conventional well-logging parameters, and the label data (i.e., ground truth) were the porosity and volumetric fractions of six minerals, including quartz, feldspar, dolomite, calcite, clay, and iron minerals. The results demonstrated that the GBR and RF models were superior in predicting volumetric fractions of minerals and porosity; label data with low coefficient of variation (CV) values tended to yield better performance. For CO 2 saturation estimation, the RF was the best-performing model, followed by SVR, ANN, GBR, and RR. Furthermore, we conducted feature importance ranking using the permutation importance algorithm and found that the formation sigma and well pressure were the most important features in this study. In conclusion, the study of CCS projects in the Illinois Basin bridges the gap between the limited knowledge and understanding of geological carbon storage and the increasing demand for reliable, cost-effective, and sustainable energy solutions.

58 GEOSCIENCES↗
DOE OSTI2024

New opportunities in produced water management: A market-based approach to produced water trading

Produced water (PW) is a byproduct of oil and gas (O&G) production. Obtained alongside the more valuable energy products, PW is usually characterized by high levels of salinity and often contains many contaminants (chemicals, soluble and insoluble oil, organics, etc.) making it unsuitable for release without substantial treatment. Couple this with the fact that PW is typically obtained at multiple times the rate of oil or gas, and the added transport, treatment, and disposal costs become a serious challenge for operators. These realities have led to ad-hoc practices including cooperation between industry competitors to recycle, share, or otherwise mitigate PW costs. The National Energy Technology Laboratory (NETL) in partnership with the Ground Water Protection Council (GWPC) is pursuing novel technology solutions to address PW issues that complement or improve ad-hoc practices adopted by operators. In this paper, we observe that well-established market management practices used in electrical power generation have natural analogues in the PW supply chain. These parallels open up a new line of research where we view PW management as a market equilibrium problem, and explore solutions that foster active and data-based collaboration among operators through market structures similar to power markets, with the ultimate objective of improving PW management costs and recycling rates. Here, we make a case for our observations, present a PW market clearing optimization model that shows how such a market system could operate in the O&G space, and provide an illustrative case study for demonstration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Modeling CO 2 flow through faulted/fractured reservoirs using tEDFM in corner-point grids

The interest in underground CO 2 storage has increased significantly over the last decade because of the rising concern about global warming due to the growing levels of greenhouse gases in the atmosphere. Considering that CO 2 accounts for 80% of these greenhouse gases, carbon capture, utilization, and storage (CCUS) is regarded as one of the most direct approaches to achieving the net zero carbon target. Although CO 2 storage in deep saline aquifers and depleted gas reservoirs has been studied extensively, most studies use commercial simulators that model faults/fractures by simply modifying the transmissibility in the direction perpendicular to the fault surfaces. Here, this work shows that this simplistic approach ignores the accelerated flow in the directions parallel to the fault plane, leading to significantly higher leakage along the fault surface. To accurately model the flow of CO 2 in faulted reservoirs, we present the first transient embedded discrete fracture model for corner-point grids (tEDFM-CPG). By comparing the results of the tEDFM-CPG to high-resolution reference solutions, we show that this approach is accurate and efficient at predicting CO 2 flow in faulted/fractured reservoirs. Finally, this work presents the use of mixed reality (MR) to efficiently observe CO 2 gas migration in the interior of these corner-point grid systems.

25 ENERGY STORAGE↗
DOE OSTI2025

Effect of pore fluid chemistry on the mechanical behavior of a divalent compacted bentonite, an experimental and constitutive study

Ongoing research in isolating high-level nuclear waste and spent fuel has highlighted compacted bentonite as a suitable material for engineered barrier systems in deep geological repositories due to its extraordinary swelling and retention properties. This research focuses on the chemo-mechanical behavior of compacted bentonite exposed to different pore fluids with different concentrations and loading conditions. The study involves swelling pressure and compressibility experiments along with mineralogy analysis employing X-ray diffraction (XRD) and Cation exchange. The tests were conducted on BCV (a Mg/Ca- bentonite) compacted at a dry density of 1.48 ± .02 Mg/m 3 . An advanced chemical-mechanical constitutive model for unsaturated highly expansive clays was adopted to simulate the material response and better understand its behavior. The model is able to account for the main phenomena at both macro and microstructural levels and the interactions between them. The model successfully replicated experimental observations. The XRD analyses support the macroscopic observation, indicating that salinity impacts crystalline swelling as demonstrated by the reduction of basal spacing from 19.27 Å to 15.68 Å when the osmotic suction increases from 0 MPa to 33 MPa. The results suggested that the osmotic pressure generated by the concentration in the pore fluids promotes a reduction in swelling pressures, swelling strains, and crystalline swelling of clay minerals. Also, it affects the pre-consolidation stress and the compressibility of the compacted samples. In conclusion, it was also observed that both solution type and solution concentration impact the clay swelling pressure.

Chemo-mechanical constitutive model↗
DOE OSTI2021

On the influence of test speed and environment in the fatigue life of small diameter nitinol and stainless steel wire

Here, to better understand the complex interplay of speed and environment on metals commonly used in implants, rotary bend fatigue tests were conducted on stainless steel and nitinol wires. A range of alternating strains was tested to create ε-N curves at two speeds (physiologic and accelerated) and in three environments (deionized water at body temperature, phosphate buffered saline at body temperature, and laboratory air at ambient room temperature). Results indicate that speed and environment can affect the observed fatigue life in nuanced ways. An electropotential monitoring technique was demonstrated to characterize fatigue crack growth which may be useful in future investigations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Interpretation of bottom-hole temperature data from CO 2 injection projects

Although bottom-hole temperature (BHT) data is routinely collected with bottom-hole pressure (BHP) data during CO 2 injection in geological storage projects, it is seldom analyzed in a quantitative manner. However, the BHP and BHT signals do exhibit correlated behavior. This work proposes a practical approach for using BHT data from warmback (no injection) periods, in conjunction with the amplitude of BHP and BHT changes during the preceding injection event, to estimate formation permeability. The methodology is demonstrated using data from the AEP Mountaineer project in USA where CO 2 injection was carried out into a saline aquifer. Estimated permeability values from the proposed approach are in good agreement with those obtained from transient pressure analysis of BHP data from the falloff period.

42 ENGINEERING↗
DOE OSTI2020

Application of emerging monitoring techniques at the Illinois Basin – Decatur Project

The Illinois Basin – Decatur Project is a large-scale carbon capture and storage demonstration project located in Decatur, Illinois, USA. In this project, one million metric tons of carbon dioxide (CO 2 ) was captured from an ethanol production facility and successfully injected into a deep saline reservoir over a period of three years. The scale of this project presented an opportunity to explore emerging technologies for effective long-term monitoring of the carbon capture and storage site. This research documents the application of three emerging monitoring techniques: (1) a prototype “open-path” sensor, a method of continuously monitoring atmospheric CO 2 by applying tunable diode laser absorption spectroscopy to provide a warning system for personnel safety along pipelines and at wellheads; (2) the Greenhouse Gas Laser Imaging Tomography Experiment (GreenLITE), an automated system for measuring two-dimensional spatial distribution of atmospheric CO 2 concentrations; and (3) periodic aerial imagery, a method of documenting surface-vegetation dynamics to detect vegetative responses to CO 2 leaks. The objective of this work was to assess the advantages and limitations of these monitoring techniques and quantify their reliability over an extended deployment at an active industrial site. These results will aid in determining viability of long-term monitoring on a commercial scale.

42 ENGINEERING↗
DOE OSTI2020

Tracking natural CO 2 migration through a sandstone aquifer using Sr, U and C isotopes: Chimayó, New Mexico, USA

The geochemical and isotopic characteristics of groundwaters in Chimayó, New Mexico, reflect processes that affect water quality in the Tesuque Aquifer, which overlies a leaking natural CO 2 source in a structurally complex region. In this study, select isotopes (δ 13 C, 87 Sr/ 86 Sr, 234 U/ 238 U) are applied to groundwaters to better understand CO 2 transport mechanisms and related water-rock interactions that impact Chimayó groundwater. Carbon stable isotope ratios of dissolved inorganic carbon (DIC; δ 13 CDIC = -15.10‰ to 4.50‰) identify a distinct source of upward-migrating CO 2 that interacts with the groundwater. Additionally, groundwater 87 Sr/ 86 Sr compositions (0.7098 to 0.7154) reflect intrusion of varying amounts of saline water associated with the high CO 2 source, while 234 U/ 238 U ratios corroborate presence of deep groundwater and suggest impacts from distinctive natural uranium sources are affecting groundwater. Previous work proposed two CO 2 transport mechanisms at the site: (1) dissolved in deep brine that underlies the aquifer and (2) in the gas phase; this study uses isotope mixing models to identify wells that are affected by these CO 2 transport mechanisms and demonstrates that both transport mechanisms are associated with impaired groundwaters. Overall, this study demonstrates that applying multiple isotope systems (δ 13 CDIC, 87 Sr/ 86 Sr, 234 U/ 238 U) is a dynamic tool for identifying and measuring the impact of CO 2 leakage from a sequestration site.

58 GEOSCIENCES↗
DOE OSTI2022

Assessment of oil and gas fields in California as potential CO 2 storage sites

California's total annual greenhouse gas (GHG) emissions (425.3 MtCO 2 e) in 2018 were about 6.4% of the US total (6,677 MtCO 2 e) and around 1% of global emissions. About 39% of 2018 GHG emissions in California were from the industrial and electrical sectors. Many of these emissions were from large stationary point sources and were suitable for carbon capture retrofit with subsequent storage of the captured carbon dioxide (CO 2 ) in geological formations. Previous studies of California found suitable geology and CO 2 storage resource. This study refines and furthers prior work using a three-stage screening process of oil fields, gas fields, and underground natural gas storage (UGS) sites by combining criteria from previous studies while excluding sites that pose technical risk or are located in regions with surface restrictions including sensitive habitats and dense populations. In the first stage, 129 CO 2 storage sites in California were identified using qualification criteria based upon formation properties including geological conditions and pore pressure. The second stage identified sensitive sites by applying conservative screens including seismic activity, faulting, population density, restricted lands, and sensitive habitats. During the third stage, 61 CO 2 potential storage sites were identified by subtraction of stage 2 areas from stage 1. The potential storage volume in the third stage ranged from 1.0 to 2.0 GtCO 2 . Finally, we applied a scoring system with seven parameters to rank the 61 potential sites based on subsurface technical criteria. The scored sites are classified as high priority, medium priority, and sites for future study. Prospective CO 2 storage sites with high and moderate priority were selected and linked to CO 2 sources. There are 14 prospective sites (above 20 MtCO 2 storage resource per site) with a total storage resource of 1024 MtCO 2 distributed in Northern and Southern California. Of these sites, there are 9 potential CO 2 -EOR sites and 1 depleted oil field with a total estimated CO 2 storage volume of ~800 MtCO 2 in the Southern San Joaquin and Ventura Basin. These 10 prospective sites with a storage resource greater than 20 MtCO 2 could potentially deliver more than 20 years of storage with an average injection rate of 40 MtCO 2 /year. The remaining 4 highly prospective sites are in Northern California. Additionally, study results suggest that saline formations should be re-evaluated in concert with storage in oil, gas, and natural gas storage reservoirs.

58 GEOSCIENCES↗
DOE OSTI2023

Tetrapodal textured Janus textiles for accessible menstrual health

Menstruating individuals without access to adequate hygiene products often improvise with alternatives that pose health risks and limit their participation in society. We describe here a menstrual hygiene product based on low-cost materials, which are integrated onto fabrics to imbue unidirectional permeability. A body-facing "Janus" fabric top layer comprising ZnO tetrapods spray-coated onto polyester mosquito netting imparts hierarchical texturation, augmenting the micron-scale texturation derived from the weave of the underlying fabric. The asymmetric coating establishes a gradient in wettability, which underpins flash spreading and unidirectional permeability. The hygiene product accommodates a variety of absorptive media, which are sandwiched between the Janus layer and a second outward-facing coated densely woven fabric. An assembled prototype demonstrates outstanding ability to wick saline solutions and a menstrual fluid simulant while outperforming a variety of commercially alternatives. The results demonstrate a versatile menstrual health product that provides a combination of dryness, discretion, washability, and safety.

60 APPLIED LIFE SCIENCES↗