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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Effect of Stoichiometry on the Structure and Polarization of BaTiO 3

Barium titanate (BaTiO 3 ) is a material of interest for photonic device applications due to its strong optical non-linearity. However, BaTiO 3 -based devices have not found widespread adoption, in part due to the challenges associated with synthesizing high quality thin-films. Here, high-resolution scanning transmission electron microscope (STEM) imaging is used to investigate the atomic structure of both on- and off-stoichiometric BaTiO 3 synthesized by molecular beam epitaxy (MBE). Here, this investigation reveals an asymmetry in the way the BaTiO 3 atomic lattice accommodates off-stoichiometry growth and unveils features beyond what is expected from diffraction or surface characterization techniques. Excess titanium incorporates into the BaTiO 3 lattice to form pervasive defects despite titanium-rich films having a low surface roughness and high-quality appearance in diffraction. Excess barium forms a rough, water-soluble surface layer but does not significantly impact the quality of the BaTiO 3 lattice. STEM is used to map titanium atom displacement in real-space. The average displacement distance is 30–60 pm in the strained thin-films, higher than the <20 pm displacement in bulk BaTiO 3 . Additionally, the titanium atom displacement direction deviates from the c-axis of the unit cell, which may have implications for the material's electro-optic tensor and thus for electro-optic device design.

Cavanagh, Ashley E. [Harvard Univ., Cambridge, MA ↗
DOE OSTI2025

Quality Investigation of Pultruded Carbon Fiber Panels Subjected to Four-Point Flexure via Fiber Optic Sensing

Pultruded carbon fiber-reinforced composites are attractive to the wind energy industry due to the rapid production of highly aligned unidirectional composites with enhanced fiber volume fractions and increased specific strength and stiffness. However, high volume carbon fiber manufacturing remains cost-prohibitive. This study investigates the feasibility of a pultruded low-cost textile carbon fiber-reinforced epoxy composite as a promising material in spar cap production was undertaken based on mechanical response to four-point flexure loading. As spar caps are primarily subjected to flexural loading, large-span four-point flexure was considered, and coupon testing was restricted to tensile modulus and compression strength assessment. High-resolution spatial fiber optic strain sensing was utilized to determine spatial strain distribution during four-point flexure, revealing consistent strain along the length of the part and proved to be an excellent option for process manufacturing quality examination. Additionally, holes with diameters of 2.49 mm, 5.08 mm, and 1.93 mm were drilled through the thickness of full-width parts to determine the feasibility of structural health monitoring of pultruding parts internal to wind blades via fiber optic strain sensing.

Chemistry↗
DOE OSTI2025

Advanced Processing of Coal and Coal Waste to Produce Graphite for Fast-Charging Lithium-Ion Battery Anode

The University of North Dakota (UND) Energy & Environmental Research Center (EERC), in collaboration with the UND Center for Process Engineering Research (CPER), conducted a project to validate two technologies capable of converting North Dakota lignite and lignite coal waste to high-quality graphite for fast-charging lithium-ion battery (LIB) anode. The project was conducted over about 3 years from April 7, 2022, to July 6, 2025. The two technological paths pursued in this project include path A – direct conversion of coal or coal waste to graphite by the upgraded carbon ores to products (UCOP) process being developed at the EERC and path B – lignite-derived coal tar pitch (CTP) conversion to graphite (CTP2G) process being developed at CPER. The results from this project validate the two technological approaches and are expected to be an integral part of a portfolio of emerging technologies for making high-quality graphite not only from North Dakota lignite, but from all ranks of U.S. domestic coal and coal waste resources. The quality of the graphite produced by these technologies is high enough for various applications, including batteries for the fast-growing electric vehicle industry, energy storage applications, electric arc furnace electrodes for steel production, and graphene production, among others. Although the two technologies can produce high-quality graphite, they are fundamentally different in that the UCOP technology provides a direct path to transform coal to graphite, while the CTP2G technology needs to go through a CTP intermediate and a coking process for the intermediate, which requires a special facility to accomplish. For application in the industry, the UCOP process is designed to be more flexible, with feedstock to include potentially any carbonaceous material such as all coal ranks and biochar, while the CTP2G process is designed to utilize CTP as the starting precursor. The key project accomplishments include the following: • Successful preparation of high-quality synthetic graphite from North Dakota lignite coal/coal wastes and lignite-derived CTP. • Patent application has been filed for the UCOP process and an internal invention disclosure has been filed for the CTP2G process. • The produced graphite performs better than a commercial battery-grade sample in LIB coin cells, especially fast-charging capability, stability, and long-duration cycling. • Coin-type Li-ion half-cells with CTP2G graphite showed excellent performance, with >370 mAh/g capacity, >90% initial coulombic efficiency, and 93%/67% retention at 1C/2C rate, which outperforms commercial graphite in charging speed, stability, and cycling. • Results of fabricated 18650 cells were consistent with the observations in coin cells. • Preliminary techno-economic analysis (TEA) estimates for the UCOP technology indicate a manufacturing cost of about $\$$39/kg based on 50-metric ton/year capacity. • Preliminary TEA estimates for the CTP2G technology indicate a market price of about $\$$7107/ton ($\$$7/kg) based on 22,000-ton/year production capacity.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Decoupling Power Quality Issues in Grid-Microgrid Network Using Microgrid Building Blocks

Microgrids are evolving as promising options to enhance reliability of the connected transmission and distribution systems. Traditional design and deployment of microgrids require significant engineering analysis. However, Microgrid Building Blocks (MBB), consisting of modular blocks that integrate seamlessly to form effective microgrids, are promising technologies to enable faster and broader adoption of microgrids. Back-to-Back converter placed at the point of common coupling of microgrid is an integral part of MBB. This paper presents applications of MBB to decouple power quality issues in grid-microgrid network serving power quality sensitive critical loads such as data centers, new grid-edge technologies such as vehicle-to-grid generation, and emergency condition loads such as electric vehicle charging loads during evacuation prior disaster events. Simulation results show that MBB effectively decouple the power quality issues across networks and allow network with low power quality to transfer high-power quality power to connected networks during emergency conditions.

Acharya, Samrat S. [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2024

Selective Deposition and Fusion of AISI 316L: An Additive Manufacturing Process for Space Environments via Direct Ink Writing and Laser Processing

Unlocking the potential of additive manufacturing (AM) for space exploration hinges on overcoming key challenges, notably the ability to manufacture or repair parts on-site during exploration missions with consideration of quality, feedstock utilization, and challenges involved in microgravity environments. While there are multiple efforts to investigate the use of existing metal AM processes such as powder bed fusion (PBF), directed energy deposition (DED), and filament-based material extrusion, each process comes with a different set of challenges in space environments. Here, in this work, we introduce a new AM method that integrates the benefits of direct ink writing (DIW) to selectively deposit metallic pastes with laser-based processing to locally debind and subsequently melt and fuse metal powder, layer by layer, enabling the manufacturing of AISI 316L samples with densities exceeding 99.0%. The impact of process parameters on single-track dimensions, surface morphology, and porosity was characterized. The efficacy of laser debinding was assessed via secondary-ion mass spectrometry, permitting the carbon content to be estimated at 0.0152%, which is safely below the acceptable limit (0.03 wt%) for AISI 316L.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Framework and Tool for Artificial Intelligence & Machine Learning (AI/ML) Enabled Automated Non-Destructive Inspection of Composites Aerostructures Manufacturing

Vehicles and systems in the field of aerospace have two major requirements: a high demand for a large quantity and an expectation to perform for their lifetime with little to no failures. Thus, there is a need for a fast production rate of aerospace products with high quality. Improvements to production rate have many benefits, including a reduction in energy consumption per unit manufactured. This would be from factory energy usage, which is required to build and verify a product. Manufacturing process specifications require inspection of parts to determine if any flaws are present. Depending on factory planning and product quality, especially at higher rates, the evaluation process can pose a production rate bottleneck. This project was comprised of using artificial intelligence and machine learning (AI/ML) methods on inspection evaluations with the objective of reducing the required time to produce an aerospace structure or product and without reducing the final quality.

42 ENGINEERING↗
DOE OSTI2026

Establishing an acoustic-property relationship in laser powder bed fusion with machine learning

Quality control of Laser Powder Bed Fusion (PBF-LB) additively manufactured parts is an important hurdle inhibiting the technology’s use structural applications. Acoustic monitoring of the laser powder bed fusion process can detect defects in-situ that are known to degrade mechanical properties. However, processing-structure-property (PSP) relationships are required to extrapolate from detected defects to part performance. Here, this study explores how acoustics may be a suitable signature linking processing conditions to properties, thus effectively substituting for structure in the PSP relationship. Establishing such a relationship would enable a part’s mechanical performance to be directly predicted from its acoustic signature, reducing the need for destructive testing or microstructural analysis to ensure a part will meet performance requirements. One hundred CoCrFeMnNi high entropy alloy tensile bars were printed across 13 process conditions in a series of 6 prints. The acoustic signatures of these tensile bars were used to train machine learning models to predict each part’s mechanical properties. By using both process information and acoustic information to predict mechanical properties, yield strength was predicted 18% more accurately and ductility to failure was predicted 10% more accurately than is achieved when using duplicate parts to predict part performance. Finally, individual acoustic frequencies were investigated to determine why acoustic signatures improve mechanical property predictions and the potential physical origins of these signatures. This work demonstrates how blending acoustics, process information, and machine learning can provide in-situ diagnostics of mechanical properties and improve the reliability of the PBF-LB process.

Acoustic emission↗
DOE OSTI2024

Commercialization of High-Density High Assay Low Enriched Uranium Fuel Systems

The Office of Reactor Conversion and Uranium Supply (NA 231) at the National Nuclear Security Administration leads the conversion effort for the United States High Performance Research Reactors (USHPRR). These reactors are the final civilian reactors in the US to transition from High Enriched Uranium (HEU) to high assay low enriched uranium (HALEU). Each of these reactors represents unique capabilities and no currently available fuel system meets their needs for conversion. The Fuel Fabrication (FF) Pillar of the USHPRR project is responsible for the fabrication of experimental elements, conversion elements, and establishing a commercial economical production capability. FF is also responsible to share with the domestic and international community the theoretical knowledge gained. Other pillars within the USHPRR project provide the experimental and conversion fuel designs, assist the reactors with licensing activities, and ensure the entire fuel cycle is evaluated. Over the last decade, FF has worked with the production partners at Y-12 National Security Complex (Y-12) and BWXT Nuclear Operations Group, Research and Test Reactors (BWXT). Y-12 has begun processing the alloy feedstock for the conversion elements with a qualified process. BWXT has started the final fabrication of the experimental elements. Once the experimental elements are complete, BWXT will begin conversion element fabrication. The FF Pillar resides at Pacific Northwest National Laboratory (PNNL) and uses PNNL, universities, commercial vendors, and the DOE national laboratory system to evaluate process development activities to improve the process steps. FF supports the fabrication of two high density fuel systems, monolithic U-10Mo (Figure 1) and Uranium Silicide (Figure 2). The U-10Mo fuel system is further along the development process. FF assists in long term planning with the production partners. This includes ramping production of the elements from experimental quantities to annual steady state needs. As part of the ramp up, opportunities to improve yield and product quality are identified to ensure the fuel systems are cost effective.

Catalan, Michael A. [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2025

Air Dispersion Modeling for the Idaho National Laboratory Permit to Construct P-2020.0045 Facility Emission Cap Revision Request

The U.S. Department of Energy Idaho Operations Office (DOE-ID) is seeking to modify permit to construct (PTC) P-2020.0045 issued to U S Dept. of Energy – Idaho National Laboratory (INL) on January 29, 2021 by the Idaho Department of Environmental Quality (DEQ). This PTC allowed the INL to become a synthetic minor source of air pollutants using a facility emission cap (FEC). Air dispersion modeling was performed as part of the permit revision application process to demonstrate that the modifications will comply with the National Ambient Air Quality Standards (NAAQS). This report documents the modeling methodology and complete results for the air dispersion impact analysis and is supplied as an appendix to the permit revision request, Idaho National Laboratory Permit to Construct P-2020.0045 (INL 2025). All criteria air pollutants (CAPs) regulated under Section 109 of the Clean Air Act were modeled with the exception of lead (Pb) and ozone which are not required to be modeled by DEQ. Consistent with the original permit application, modeling was not performed for toxic air pollutants (TAPs) as uncontrolled emissions did not exceed screening emission levels for carcinogenic and non-carcinogenic TAPs. Acceptable model design values (concentrations) for each CAP and averaging period were summed with average background concentrations and compared to NAAQS. The results demonstrate the impacts of requested FEC limits for CAPs are less than applicable standards and demonstrate emissions up to FEC limits will not cause a violation of ambient air quality standards.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Biophysical model of eelgrass and water quality in Coos Bay, OR shows greater mitigation potential for ocean acidification than hypoxia

Seagrass beds provide important ecosystem services and are valued, in part, for their potential to mediate stressors such as ocean acidification and hypoxia (OAH) for sensitive species. However, the susceptibility of seagrasses to anthropogenic impacts and recent declines motivate the need to better understand the drivers of seagrass and the water quality consequences that occur with variation in seagrass abundance. To meet this need, we leveraged existing monitoring data (water quality and seagrass), hydrodynamic circulation model, and biogeochemical model framework with seagrass submodel, to produce a biophysical model of Coos Bay estuary, Oregon, U.S. The model includes biogeochemical processes involving water quality, plankton, seagrass, and sediment-water interactions. Ecosystem models like this are useful for evaluating complex estuarine systems because they allow us to extend our understanding of system dynamics beyond existing observations and perform experiments to identify the processes driving observed patterns. We used the biophysical model of Coos Bay to evaluate the dynamics of water quality and native eelgrass (Zostera marina) under three eelgrass abundance scenarios (zero eelgrass, current extent, and maximum observed extent) to elucidate the relationship between eelgrass and OAH. Including eelgrass in the Coos Bay model produced results that more closely resembled water quality observations - dissolved oxygen (DO) and pH were more dynamic in simulations with eelgrass, often having both higher highs and lower lows. While there were some areas of the estuary where DO improved with the addition of eelgrass to the model there was overall a small net increase in harmful DO conditions (based on a salmon physiological threshold). In contrast, ocean acidification conditions, pH and calcium carbonate saturation state for aragonite (Ω), were improved (based on oyster requirements) with the addition of eelgrass - although the magnitude of improvement differed seasonally and spatially. Our new model represents a useful tool - one which accounts for and controls the relevant physical and biogeochemical processes - to evaluate conditions that confer resilience or enhance vulnerability to OAH in an important Pacific Northwest coastal estuary and results can inform the OAH-related dynamics occurring in other eastern boundary current estuaries.

FVCOM-ICM↗
DOE OSTI2025

Chemical Imaging of Atmospheric Biomass Burning Particles from North American Wildfires

The effects of biomass burning aerosols (BBA) on radiative forcing and cloud formation depend on chemical composition and the internal structures of individual particles within smoke plumes. To improve our understanding of the chemical and physical properties of BBA emitted at different times of the day and their evolution during atmospheric aging, we conducted a study as a part of the Fire Influence on Regional to Global Environments and Air Quality field campaign. Particle samples were collected onboard a research aircraft from smoke plumes from a wildfire in eastern Oregon during late afternoon and nighttime flights on August 28, 2019. A time-resolved aerosol collector was used to collect samples on substrates for offline spectromicroscopic imaging to investigate the single-particle characteristics of BBA particles. Approximately 20,400 individual particles from 10 selected samples were analyzed using computer-controlled scanning electron microscopy coupled with energy-dispersive X-ray microanalysis, revealing their elemental composition, morphology, and viscosity. Elemental microanalysis indicated that aged potassium is likely found in the form of K 2 SO 4 , KNO 3 , and possible K-organic salts. Further chemical speciation and carbon bonding mapping within individual particles were conducted using synchrotron-based scanning transmission X-ray microscopy (STXM) coupled with near edge X-ray absorption fine structure (NEXAFS) spectroscopy. Real-time, water-soluble light absorption measurements were acquired using a particle-into-liquid sampler instrument coupled to a liquid waveguide capillary cell and total organic analyzer. In the late afternoon samples, 65% of the total particle number population consisted entirely of organic components, compared to 46% in the nighttime particles. These differences were attributed to discrepancies in composition at the time of emission and to the daytime condensation and accumulation of photochemically formed secondary organic material on existing BBA particles, a process that halts at night. Microscopy images indicated that particle viscosity was lower in the nighttime particles (<10 1 Pa·s), likely due to increased relative humidity and a higher contribution from hygroscopic inorganic components. The chemical heterogeneity of individual particles was quantified using STXM-derived mixing state parameters. The nature of carbon bonding within individual particles was inferred from the extent of carbon sp 2 hybridization derived from NEXAFS spectra. Average percentages of sp 2 hybridization range between 40% and 60%, with no noticeable differences between late afternoon and nighttime flights. These findings were compared with the online optical properties of both late afternoon and nighttime smoke plumes, providing valuable insights into the complex relationship between chemical composition and optical properties of BBA particles at different times of the day.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Beam results for the new super-conducting booster at Jefferson Lab

The performance results of a new super-conducting booster for the CEBAF injector at Jefferson Lab, could be of interest for other similar electron injectors. A recent addition of this new booster has provided us the ability to achieve a more adiabatic acceleration and therefore an improvement to the beam dynamics and beam brightness. It has also simplified the design and operation of the section of the injector responsible for accelerating the electron beam from a few hundred keV to several MeV (typically 6.7 MeV). The addition of the new booster was part of an upgrade to the CEBAF injector to improve the beam quality for future physics experiments with high sensitivity to beam quality. The booster consists of two cavities: a 2-cell cavity followed by a 7-cell cavity. This combination allows for a wide range of input electron beam energies, from 130 keV to more than 300 keV. In fact, during the last year, the booster was successfully operated with 140,180, and 200 keV input beam energies as the electron gun was being upgraded. This paper describes the new booster, presents beam optics data results from different beam studies, commissioning, and the physics quality beam operation.

Accelerator Physics↗
DOE OSTI2024

Low Purge and Mercury Recovery Testing with Sludge Batch 10 Tank 40 Simulant

Researchers at the Savannah River National Laboratory (SRNL) have completed testing as requested by Savannah River Mission Completion (SRMC) to perform experiments to determine the impact of using a lower or inert purge in Sludge Batch (SB) 10 processing under the Nitric-Glycolic Acid (NGA) flowsheet. A key objective of this testing was also to determine the mercury speciation and recovery during each experiment. The testing was performed as part of the SB10 Technical Task Request (TTR) and Task Technical and Quality Assurance Plan (TTQAP). Two sets of tests were performed, and a Run Plan was approved prior to each set of experiments to document the planned testing. Three initial experiments were completed to determine whether a low air purge would be beneficial to CPC processing at higher acid stoichiometry (110%) based on the Koopman minimum acid (KMA) equation (116% Hsu). One of the tests, an inert nitrogen purge experiment, was also completed to demonstrate that excluding oxygen did not introduce any new hazards. The experiments were designed to be identical except for the change in purge gas and purge flowrate from run to run. After reviewing the results from the initial three experiments, six additional tests were proposed by SRNL to support the lower purge study and to look for processing alternatives for improving mercury recovery. These additional six tests were all completed at a very low acid stoichiometry to mimic the pH experienced during processing in DWPF (~7). DWPF is processing SB10 sludge at an acid stoichiometry of 90% based on the Hsu equation. The additional SRNL experiments were performed at an acid stoichiometry of 62.5% KMA stoichiometry (66.3% Hsu) to produce a Sludge Receipt and Adjustment Tank (SRAT) product with a pH of about 7. All experiments used simulants of both SWPF streams, although no entrained solvent was added during any of the experiments

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Evaluating Hydropower Plants for Wildfire Resilient Microgrids

The increasing occurrence and severity of wildfires in recent years is severely impacting critical infrastructures, including the power grid, compromising the quality of life and provision of essential services, including electricity. The western parts of the United States, more specifically Washington, Oregon, and California, which are prone to large wildfires, are also rich in hydropower resources. Hydropower resources located close to communities vulnerable to wildfire can be utilized to develop wildfire-resilient microgrids to support critical needs of those communities. Therefore, this paper develops a framework to characterize hydropower plants and evaluate their feasibility to operate in microgrids during wildfire-related outages. In the proposed framework, hydropower plants are characterized using various plant and site attributes and evaluated in terms of capability and performance indicative metrics. A case study is carried out evaluating the Hills Creek hydropower plant located in a wildfire-prone region of Oregon for wildfire-resilient microgrid. The results of steady-state and dynamic simulations show that the hydropower plant is capable of providing the essential microgrid services and powering nearby communities during extended wildfire-related outages.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2025

Operational resilience of additively manufactured parts to stealthy cyberphysical attacks using geometric and process digital twins

Cyberphysical attacks on the digital backbone of Additive Manufacturing (AM) can compromise the printed part’s functionality. They can alter features in the digital geometry to introduce geometric defects (e.g., missing fillets) or alter process parameters to create local defects (e.g., voids). Addressing the downtime, waste, and quality deterioration associated with existing solutions requires operational resilience, i.e., rapid elimination or disruption of defect formation (to retain part function) without production stoppage or part disposal (to retain yield). This need is unmet due to the inherently unpredictable nature of attack-induced alterations, lack of access to the original geometric model for identification of altered geometric features, and in-process imposition of unknown process dynamics via attack-driven alteration of real-time-uncontrolled (or exogenous) parameters. This work establishes the above-mentioned operational resilience for the first time by creating two Digital Twins (DT). The Geometric DT (Geo-DT) is based on a unique physical-field-driven soft sensor and topology optimization method. The Process Digital Twin (Pro-DT) combines local defect quantification with a novel Reinforcement Learning formulation and training method. The importance of these methodological advances and the scalability of our approach are examined on a real AM testbed. It is shown that Geo-DT can correct geometric defects without access to the original digital geometry or explicit knowledge of attack-altered geometric features. Further, Pro-DT can accelerate real-time disruption of local defects despite attack-driven imposition of unknown process dynamics. We discuss how our framework goes beyond the contemporary focus on pre-attack security and in-attack detection towards resilience for AM and beyond.

Additive Manufacturing↗
DOE OSTI2024

Strong‐Yet‐Ductile Eutectic Alloys Employing Cocoon‐Like Nanometer‐Sized Dislocation Cells

Abstract Eutectic alloys (EAs) with superior fluidity are known to be the easiest to cast into high‐quality ingots, making them the alloys of choice for making large‐sized structural parts. However, conventional EAs (CEAs) have never reached strength–ductility combinations on par with the best in other alloy categories. Via thermomechanical processing of cast Ni‐32.88wt%Fe‐9.53wt%Al CEAs, a cocoon‐like nano‐meshed (as fine as 26 nm) network of dislocations (CNN‐D) is produced via recovery annealing, through the rearrangement of cold‐work‐accumulated dislocations anchored by dense pre‐existing nanoprecipitates. In lieu of traditional plasticity mechanisms, such as TWIP and TRIP, the CNN‐D is particularly effective in eutectic lamellae with alternating phases, as it instigates nanometer‐spaced planar slip bands that not only dynamically refine the microstructure but also transmit from the FCC (face‐centered‐cubic) layers into the otherwise brittle B2 layers. These additional mechanisms for strengthening and strain hardening sustain stable tensile flow, resulting in a striking elevation of both strength and ductility to outrank not only all previous CEAs, but also the state of the art—additively manufactured eutectic high‐entropy alloys. The CNN‐D thus adds a novel microstructural strategy for performance enhancement, especially for compositionally complex alloys that increasingly make use of nanoprecipitates or local chemical order.

Chemistry↗
DOE OSTI2025

Comparisons of the v11.1 Orbiting Carbon Observatory‐2 (OCO‐2) X CO2 Measurements With GGG2020 TCCON

The Orbiting Carbon Observatory 2 (OCO-2) is NASA's first Earth observation satellite mission dedicated to studying the sources and sinks of carbon dioxide (CO 2 ) on a global scale. The observations of reflected sunlight are inverted in a retrieval algorithm to produce estimates of the dry air mole-fractions of CO 2 (X CO2 ). The OCO-2 Level 2 data release, version 11.1 (v11.1) retrievals from the Atmospheric Carbon Observations from Space (ACOS) algorithm, includes significant improvements in the X CO2 data product compared to older OCO-2 data versions. This work compares the v11.1 X CO2 from OCO-2 against X CO2 estimates collected from a global ground-based network known as the Total Carbon Column Observing Network (TCCON), OCO-2's primary validation source. The OCO-2 project provides a version of the Level 2 data product, called “lite” files that include calibrated and bias-corrected XCO2 values, accessible together with all OCO-2 data products through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). This work shows that OCO-2 X CO2 observations made between September 2014 and December 2023, after quality filtering and the application of an averaging kernel correction, agree well with coincident TCCON data for all OCO-2 observational modes of land (nadir, glint, target) and ocean (glint). The aggregated, bias-corrected, and quality-filtered absolute average bias values are less than or equal to 0.20 parts per million (ppm) globally for all OCO-2 observation modes, where the biases do not indicate a statistically significant time dependence. The land nadir/glint mode has the lowest bias value of −0.03 ± 0.85 ppm.

54 ENVIRONMENTAL SCIENCES↗