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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Comparison of Commercial, State-of-the-Art, Fossil-Based Ammonia Production

This NETL report provides a comprehensive techno-economic analysis of current, state-of-the-art, fossil-based ammonia production processes, explicitly utilizing natural gas as the feedstock. The study thoroughly investigates three distinct configurations: conventional Steam Methane Reforming (SMR) without carbon capture, SMR integrated with carbon capture and storage (CCS), and Autothermal Reforming (ATR) also with CCS. The analysis incorporates detailed equipment cost accounting as part of its methodology. The primary objective is to meticulously evaluate the cost and performance of these established and emerging technological pathways, considering factors such as capital expenditures, operational costs, and energy consumption. While the report acknowledges and quantifies environmental impacts, its central focus remains on the economic and technical feasibility of each process design employing these current technologies. The analysis provides a direct comparison of the Levelized Cost of Ammonia (LCOA) for each pathway, revealing how the integration of CCS within these state-of-the-art systems impacts the overall production cost. The ATR+CCS configuration, representing an advanced approach, emerged with a slightly more favorable LCOA compared to SMR+CCS. This benefit was attributed to its inherent process efficiencies, high carbon capture rates, and economy of scale advantages. The report details the energy consumption profiles for each case, including metrics like net energy consumption and thermal efficiency, which are critical for assessing the performance of these contemporary industrial processes. Sensitivity analyses further explore how variables such as natural gas price, capital costs, and capacity factors influence the LCOA across all scenarios, offering critical insights into the economic robustness and scalability of these current ammonia production technologies.

03 NATURAL GAS↗
DOE OSTI2026

Basin-scale analysis of Mokelumne River Formation for multi-well CO 2 injection

Large-scale carbon sequestration will likely require multiple projects injecting CO 2 into the same subsurface formation, raising concerns about safe operation and efficient use of storage capacity. This study evaluates the long-term response of the Mokelumne River Formation in California’s Sacramento Basin to multi-megaton CO 2 injection using three geologic models of the formation and the open-source simulator GEOS. The analysis focuses on three aspects of reservoir performance: (1) average pressure increase and dissolved CO 2 mass after 30 years for varying well counts and injection rates, (2) pressure interference in a multi-well configuration, and (3) dynamic storage capacity with identification of overpressure-prone regions. The results show that average formation pressure increases linearly with injected mass, while CO 2 dissolution exhibits mixed scaling: approximately linear with the number of wells but sublinear with injection rate, indicating that distributing injection across more wells enhances dissolution more effectively than increasing per-well rates. Pressure-interference effects are significant, with lower-permeability conditions delaying their onset but amplifying their magnitude at later times. Dynamic capacity, defined by the first occurrence of pressure exceeding the local overburden-based limit anywhere in the formation, varies across geologic models and assumed overburden pressure gradients. A lower fidelity geologic model predicts nearly twice the storage capacity of the two higher fidelity models, which consistently estimate approximately 1 Gt under the upper-bound overburden pressure gradient considered for the Sacramento Basin. In all model scenarios, overpressure develops away from injection wells, particularly in higher-elevation regions, highlighting the importance of basin-scale modelling for identifying risks beyond the immediate well vicinity.

Basin-scale↗
DOE OSTI2025

A Synthetic Pathway for Producing Carbon Dots for Detecting Iron Ions Using a Fiber Optic Spectrometer

Iron detection is of growing importance in the critical minerals sector, where unwanted iron ions are typically removed during the processing of target critical metals. The ideal sensor should utilize inexpensive, scalable materials along with a low-cost, robust, and easy-to-use analysis platform. Here, we demonstrate a simple acid–base synthesis of luminescent iron-responsive carbon dots by reacting ethanolamine, phosphoric acid, and m-phenylenediamine. The carbon dots exhibit selective, iron-specific emission quenching, with the ability to detect part-per-billion levels of iron ions even in 0.1 M HCl. After benchmarking the purified materials using a commercial spectrometer, a “low-cost” process is demonstrated in which carbon dots with minimal purification are coupled with a portable fiber-optic spectrometer for analyzing iron content. Carbon dot-coated paper strips are also evaluated as another convenient platform for iron analysis. Taken together, the sensing material and platforms demonstrated here are well-suited for detecting trace quantities of iron in environmentally relevant conditions, with potential applications in tracking iron removal processes during critical mineral production as one exciting area of interest.

acid mine draining↗
DOE OSTI2022

Challenges and Lessons Learned from an Analysis of Three Zero Energy Buildings

Zero energy buildings, or zero energy ready buildings, which are designed and operated by public or private commercial property owners can play an important role in reducing carbon emissions. This paper discusses lessons learned and key takeaways from an in-depth analysis of three zero energy buildings that took an integrated design and construction approach to significantly reduce energy use. Two of these projects are new construction and one is a retrofit to zero energy. Findings are based on project literature review, data analysis, and in-depth interviews with the building design teams and staff who were involved during the design, construction, and operation of the buildings. The paper addresses value proposition and cost data in such a way that other building owners can replicate the strategies and technology solutions in response to regulatory mandates or organizational goals. It also provides details on operational improvements taken at each zero energy building to enhance energy performance and increase the potential for load flexibility, and discusses challenges and lessons gleaned from design teams and building staff. The findings serve as a reference for building owners, designers, engineers, contractors, or others interested in, or involved with, the design, construction, or use of new or existing buildings. The paper also includes recommended pathways for widespread adoption of zero energy strategies that can be applied in various locations.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2024

A chemical kinetic analysis of knock propensity of methanol-to-gasoline fuel

Production of low carbon gasoline-like fuels such as methanol-to-gasoline (MTG) is a promising approach to achieve rapid greenhouse gas emission reduction of the transportation sector. Despite the fact that gasoline that meets the ASTM D4814 standard for automotive spark-ignition engine fuel can be readily produced from these processes, it is unclear how the composition of MTG may affect engine performance and emissions. Here, in this paper, a surrogate for an MTG is used to numerically study the effects of gasoline composition on knock propensity and on the sensitivity of knock to thermal and fuel stratification, to oxygen dilution and to nitric oxide from exhaust gas recirculation of residual gases. Simulations were performed in ANSYS CHEMKIN-PRO using a comprehensive chemical kinetic mechanism for gasoline surrogates, and results of the MTG surrogate were compared against those of a petroleum-based regular E10 gasoline, termed PACE-20. A premium-grade MTG fuel was also formulated by adding ethanol to the MTG surrogate, and results were compared against those of four premium-grade, gasoline-like fuels representative of future alternative gasoline formulations. Surrogates and mechanism were evaluated by comparison against experimental engine data, and the model showed high accuracy at stoichiometric conditions (mean absolute error of ignition timing equal to 1.46 crank angle degrees) but larger deviations at lean conditions (mean absolute error of ignition timing equal to 5.52 crank angle degrees). Despite the fact that the MTG surrogate has a RON 1.1 units higher than that of PACE-20, it may show higher knock propensity at medium temperature conditions due to a less intense NTC behavior. MTG autoignition was more temperature- and equivalence ratio-sensitive than that of PACE20, suggesting that MTG can benefit more from naturally-occurring thermal stratification or from induced fuel stratification of the end gas to mitigate knock intensity. The sensitivity of autoignition reactivity to oxygen dilution and to NO concentration was higher for MTG than for regular gasoline at medium loads, but the opposite trend was observed at high loads due to the effect of pressure on the low-temperature chemistry of regular gasoline. Approximately 14 % vol ethanol content was required to upgrade the octane rating of MTG from regular grade to premium grade. Adding 13.6 % vol ethanol made the fuel autoignition less sensitive to both oxygen dilution and NO content (ignition time varies approx. 17 % and 50 % less with oxygen dilution and NO addition, respectively, when adding ethanol at high engine loads).

02 PETROLEUM↗
DOE OSTI2023

Analysis of bipolar membranes for electrochemical CO 2 capture from air and oceanwater

Carbon dioxide (CO 2 ) must be removed from the atmosphere to mitigate the negative effects of climate change. However, the most scalable methods for removing CO 2 from the air require heat from fossil-fuel combustion to produce pure CO 2 and continuously regenerate the sorbent. Bipolar-membrane electrodialysis (BPM-ED) is a promising technology that uses renewable electricity to dissociate water into acid and base to regenerate bicarbonate-based CO 2 capture solutions, such as those used in chemical loops of direct-air-capture (DAC) processes, and in direct-ocean capture (DOC) to promote atmospheric CO 2 drawdown via decarbonization of the shallow ocean. In this study, we develop an experimentally validated 1D model for the electrochemical regeneration of CO 2 from bicarbonate-based carbon capture solutions and seawater using BPM-ED. For DAC, our experimental and computational results demonstrate that pH swings induced by BPM water dissociation drive the formation of CO 2 at the cation-exchange layer|catholyte interface with energy-intensities of less than 150 kJ mol -1 . However, high rates of bubble formation increase energy intensity at current densities >100 mA cm -2 . Correspondingly, accelerating water dissociation catalysis and enacting bubble removal could enable CO 2 recovery at energy intensities <100 kJ mol -1 and current densities >100 mA cm -2 . For DOC, mass transport limitations associated with low carbon concentrations in oceanwater suggest that DOC is best suited for clean production of acid and base usable in downstream processes. Further, these results provide design principles for industrial-scale CO 2 recovery using BPM-ED.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Complementary Metagenomic Approaches Improve Reconstruction of Microbial Diversity in a Forest Soil

ABSTRACT Soil ecosystems harbor diverse microorganisms and yet remain only partially characterized as neither single-cell sequencing nor whole-community sequencing offers a complete picture of these complex communities. Thus, the genetic and metabolic potential of this “uncultivated majority” remains underexplored. To address these challenges, we applied a pooled-cell-sorting-based mini-metagenomics approach and compared the results to bulk metagenomics. Informatic binning of these data produced 200 mini-metagenome assembled genomes (sorted-MAGs) and 29 bulk metagenome assembled genomes (MAGs). The sorted and bulk MAGs increased the known phylogenetic diversity of soil taxa by 7.2% with respect to the Joint Genome Institute IMG/M database and showed clade-specific sequence recruitment patterns across diverse terrestrial soil metagenomes. Additionally, sorted-MAGs expanded the rare biosphere not captured through MAGs from bulk sequences, exemplified through phylogenetic and functional analyses of members of the phylum Bacteroidetes . Analysis of 67 Bacteroidetes sorted-MAGs showed conserved patterns of carbon metabolism across four clades. These results indicate that mini-metagenomics enables genome-resolved investigation of predicted metabolism and demonstrates the utility of combining metagenomics methods to tap into the diversity of heterogeneous microbial assemblages. IMPORTANCE Microbial ecologists have historically used cultivation-based approaches as well as amplicon sequencing and shotgun metagenomics to characterize microbial diversity in soil. However, challenges persist in the study of microbial diversity, including the recalcitrance of the majority of microorganisms to laboratory cultivation and limited sequence assembly from highly complex samples. The uncultivated majority thus remains a reservoir of untapped genetic diversity. To address some of the challenges associated with bulk metagenomics as well as low throughput of single-cell genomics, we applied flow cytometry-enabled mini-metagenomics to capture expanded microbial diversity from forest soil and compare it to soil bulk metagenomics. Our resulting data from this pooled-cell sorting approach combined with bulk metagenomics revealed increased phylogenetic diversity through novel soil taxa and rare biosphere members. In-depth analysis of genomes within the highly represented Bacteroidetes phylum provided insights into conserved and clade-specific patterns of carbon metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Chemistry data from soils and soil incubation experiments from the whole-soil warming experiment at Blodgett Forest, CA, 2018, from: “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile”

This dataset contains soil chemistry data of soils from the whole-soil warming experiment at Blodgett Forest in June 2018, and from laboratory incubation experiments conducted with a subset of those soils. Soil samples were collected at five different depths down to 80 cm from soil plots continuously heated by 4°C above ambient temperature for 4.5 years, and from the respective unheated control plots. Incubation experiments were conducted for 28 days with soils collected between 10-30 cm (“surface soils”) and 60-80 cm (“subsoils”) from heated and unheated field plots, amended in the laboratory with cellobiose (C, carbon amendment), or cellobiose plus ammonium and phosphate (CNP, combined carbon, nitrogen and phosphorus amendment). The dataset includes separate files for: (i) total carbon and nitrogen concentrations of initial field soils; (ii) carbon dioxide efflux rates at multiple times throughout the incubation experiments, and respective cumulative carbon dioxide efflux rates, as well as inorganic nitrogen concentrations at the beginning and end of the incubations, and net nitrogen mineralization rates and carbon use efficiency calculated at the end of the incubation. Analysis of these data has been published in Dove et al., (2021), “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile. Nat. Commun. 12:2089”, https://doi.org/10.1038/s41467-021-22408-5. This research was performed as part of the TES Belowground Biogeochemistry SFA project at Lawrence Berkeley National Laboratory.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Label-Free In Situ Chemical Characterization of Amyloid Plaques in Human Brain Tissues

The accumulation of amyloid plaques and increased brain redox burdens are neuropathological hallmarks of Alzheimer’s disease. Altered metabolism of essential biometals is another feature of Alzheimer’s, with amyloid plaques representing sites of disturbed metal homeostasis. Despite these observations, metal-targeting disease treatments have not been therapeutically effective to date. A better understanding of amyloid plaque composition and the role of the metals associated with them is critical. To establish this knowledge, the ability to resolve chemical variations at nanometer length scales relevant to biology is essential. Here, we present a methodology for the label-free, nanoscale chemical characterization of amyloid plaques within human Alzheimer’s disease tissue using synchrotron X-ray spectromicroscopy. Our approach exploits a C–H carbon absorption feature, consistent with the presence of lipids, to visualize amyloid plaques selectively against the tissue background, allowing chemical analysis to be performed without the addition of amyloid dyes that alter the native sample chemistry. Using this approach, we show that amyloid plaques contain elevated levels of calcium, carbonates, and iron compared to the surrounding brain tissue. Chemical analysis of iron within plaques revealed the presence of chemically reduced, low-oxidation-state phases, including ferromagnetic metallic iron. The zero-oxidation state of ferromagnetic iron determines its high chemical reactivity and so may contribute to the redox burden in the Alzheimer’s brain and thus drive neurodegeneration. Ferromagnetic metallic iron has no established physiological function in the brain and may represent a target for therapies designed to lower redox burdens in Alzheimer’s disease. Additionally, ferromagnetic metallic iron has magnetic properties that are distinct from the iron oxide forms predominant in tissue, which might be exploitable for the in vivo detection of amyloid pathologies using magnetically sensitive imaging. We anticipate that this label-free X-ray imaging approach will provide further insights into the chemical composition of amyloid plaques, facilitating better understanding of how plaques influence the course of Alzheimer’s disease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Methods—Kintsugi Imaging of Battery Electrodes: Distinguishing Pores from the Carbon Binder Domain using Pt Deposition

The mesostructure of porous electrodes used in lithium-ion batteries strongly influences cell performance. Accurate imaging of the distribution of phases in these electrodes would allow this relationship to be better understood through simulation. However, imaging the nanoscale features in these components is challenging. While scanning electron microscopy is able to achieve the required resolution, it has well established difficulties imaging porous media. This is because the flat imaging planes prepared using focused ion beam milling will intersect with the pores, which makes the images hard to interpret as the inside walls of the pores are observed. It is common to infiltrate porous media with resin prior to imaging to help resolve this issue, but both the nanoscale porosity and the chemical similarity of the resins to the battery materials undermine the utility of this approach for most electrodes. In this study, a technique is demonstrated which uses in situ infiltration of platinum to fill the pores and thus enhance their contrast during imaging. Reminiscent of the Japanese art of repairing cracked ceramics with precious metals, this technique is referred to as the kintsugi method. The images resulting from applying this technique to a conventional porous cathode are presented and then segmented using a multi-channel convolutional method. We show that while some cracks in active material particles were empty, others appear to be filled (perhaps with the carbon binder phase), which will have implications for the rate performance of the cell. Energy dispersive X-ray spectroscopy was used to validate the distribution of phases resulting from image analysis, which also suggested a graded distribution of the binder relative to the carbon additive. The equipment required to use the kintsugi method is commonly available in major research facilities and so we hope that this method will be rapidly adopted to improve the imaging of electrode materials and porous media in general.

25 ENERGY STORAGE↗
DOE OSTI2021

The role of gas flow distributions on CO 2 mineralization within monolithic cemented composites: coupled CFD-factorial design approach

The carbonation kinetics of monolithic cementing composites are strongly affected by gas transport which is, in turn, influenced by microstructural resistances and the presence of liquid water within pore networks. The non-uniform gas flow distribution within the CO 2 mineralization reactor can impart mass transfer resistance in the monolith microstructure, which affects the uptake of CO 2 (“carbonation”) of the cementing composites. This paper demonstrates how the gas spatial distribution (velocity and flow rate; quantified by CFD analysis) and processing conditions (temperature, relative humidity, and flow rate; quantified by factorial design) affect drying and carbonation, and in turn, the engineering properties of a representative ‘monolithic’ carbonate-cemented concrete component (i.e., herein concrete masonry unit: CMUs, also known as concrete block). It is shown that the gas flow distribution affects drying front penetration and results in moisture and carbonation gradients within the monolith. Particularly, variations in drying kinetics caused by non-uniformity of the contacting gas velocity impose gradients in moisture saturation, which results in increasing microstructural resistance to CO 2 transport. The resultant non-uniform carbonate-mineral formation (i.e., carbonate cementation), if not controlled, can produce gradients in mechanical properties and may alter failure patterns upon loading. Finally, these insights inform the optimal design of gas flow distribution systems and processing conditions within CO 2 mineralization reactors for the manufacturing of low-CO 2 concrete components using CO 2 -dilute industrial flue gas streams.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Host analysis-guided selection and targeted engineering (HASTE) of Lipomyces tetrasporus for the conversion of CO2-derived feedstocks

Efficient and cost-competitive bioproduction calls for utilizing CO2-derived feedstocks, such as products from electro-reduction of CO2 and hydrolysate from lignocellulosic biomass. However, efficiently using all their carbon components, including acetate, glucose, and xylose, remains a challenge. Here, we characterize Lipomyces tetrasporus, a novel, robust yeast strain capable of effectively assimilating these carbon sources. We used an integrated systems biology approach combining ¹³C metabolic flux analysis, dynamic labeling experiments, and RNA sequencing. We conducted the first metabolic flux analysis for glucose, xylose, and acetate catabolism in this species. Dynamic labeling revealed a highly active TCA cycle during acetate metabolism, evidenced by rapid citrate and malate accumulation. The strain demonstrated strong NADH/NADPH production and acetyl-CoA synthase activity. Using insights and gene targets from this analysis, we engineered L. tetrasporus for malate production. The engineered strain produced 7.5 g/L malic acid (0.25 g/g yield) in shake flasks with glucose-acetate media and 28.8 g/L malic acid at a yield of 0.20 g/g in fed-batch mode with corn-stover hydrolysate. Together, these insights and rational strain engineering establish L. tetrasporus as a versatile, Crabtree-negative platform that is an energy-CO2-bioproduction nexus for channeling CO2 carbon into value-added bioproducts.

Xiao, Zhengyang↗
DOE OSTI2025

OpenCRUMS USA: An Open Machine Learning Framework for Characterizing Variability in Aerosol Reanalysis Data

Advances in artificial intelligence (AI) have called for exploring how these techniques can be used for exploring patterns in large climate datasets. To that regard, the U.S. Department of Energy AI for Earth System Predictability (AI4ESP) supported a pilot initiative called the Open Classification of Regimes in the Southeast USA (OpenCRUMS USA) project to explore how AI can be used to characterize modes of spatial variability in large climate datasets. For this study, we focus on comparing two methods for characterizing the modes of spatial variability of surface aerosol concentration over the Houston region: empirical orthogonal functions (EOFs) and layerwise relevance propagation (LRP) applied to a convolutional neural network (CNN) classifier. We show that EOF analysis typically attributes spatial variability modes that span all of southeast Texas, prohibiting the attribution of spatial variability to localized regions. However, using LRP on the CNN classifier resolves the explanatory parameters at a finer spatial resolution than EOFs. This allows for the attribution of the spatial variability of surface aerosols to local regions of organic carbon which was not possible using EOFs. In addition, the LRP analysis also suggests that synoptic-scale transport of dust is most prevalent during anticyclonic and pretrough synoptic conditions as categorized by self-organizing maps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Natural Gas Combined Cycle Power Plants with Carbon Capture and Exhaust Gas Recycle

This is a presentation given at the 3rd International Conference on Energy and Environment. The presentation highlights analysis work conducted by NETL to assess the cost and performance for natural gas combined cycle (NGCC) power plants that incorporate solvent-based post combustion carbon dioxide (CO2) capture and exhaust gas recycle (EGR). Increasing the inlet CO2 concentration by EGR is expected to improve the efficiency of the capture system and reduce its cost, however the analysis results show that the cost improvement is minimal as is the cost of capture reduction.

Hackett, Gregory↗
DOE OSTI2024

Metaproteomics-informed stoichiometric modeling reveals the responses of wetland microbial communities to oxygen and sulfate exposure

Abstract Climate changes significantly impact greenhouse gas emissions from wetland soil. Specifically, wetland soil may be exposed to oxygen (O 2 ) during droughts, or to sulfate (SO 4 2- ) as a result of sea level rise. How these stressors – separately and together – impact microbial food webs driving carbon cycling in the wetlands is still not understood. To investigate this, we integrated geochemical analysis, proteogenomics, and stoichiometric modeling to characterize the impact of elevated SO 4 2- and O 2 levels on microbial methane (CH 4 ) and carbon dioxide (CO 2 ) emissions. The results uncovered the adaptive responses of this community to changes in SO 4 2- and O 2 availability and identified altered microbial guilds and metabolic processes driving CH 4 and CO 2 emissions. Elevated SO 4 2- reduced CH 4 emissions, with hydrogenotrophic methanogenesis more suppressed than acetoclastic. Elevated O 2 shifted the greenhouse gas emissions from CH 4 to CO 2 . The metabolic effects of combined SO 4 2- and O 2 exposures on CH 4 and CO 2 emissions were similar to those of O 2 exposure alone. The reduction in CH 4 emission by increased SO 4 2- and O 2 was much greater than the concomitant increase in CO 2 emission. Thus, greater SO 4 2- and O 2 exposure in wetlands is expected to reduce the aggregate warming effect of CH 4 and CO 2 . Metaproteomics and stoichiometric modeling revealed a unique subnetwork involving carbon metabolism that converts lactate and SO 4 2- to produce acetate, H 2 S, and CO 2 when SO 4 2- is elevated under oxic conditions. This study provides greater quantitative resolution of key metabolic processes necessary for the prediction of CH 4 and CO 2 emissions from wetlands under future climate scenarios.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Integrated flux and pool size analysis in plant central metabolism reveals unique roles of glycine and serine during photorespiration

Photorespiration is an essential process juxtaposed between plant carbon and nitrogen metabolism that responds to dynamic environments. Photorespiration recycles inhibitory intermediates arising from oxygenation reactions catalysed by Rubisco back into the C 3 cycle, but it is unclear what proportions of its nitrogen-containing intermediates (glycine and serine) are exported into other metabolisms in vivo and how these pool sizes affect net CO 2 gas exchange during photorespiratory transients. Here, to address this uncertainty, we measured rates of amino acid export from photorespiration using isotopically non-stationary metabolic flux analysis. This analysis revealed that ~23–41% of the photorespiratory carbon was exported from the pathway as serine under various photorespiratory conditions. Furthermore, we determined that the build-up and relaxation of glycine pools constrained a large portion of photosynthetic acclimation during photorespiratory transients. Furthermore, these results reveal the unique and important roles of glycine and serine in successfully maintaining various photorespiratory fluxes that occur under environmental fluctuations in nature and providing carbon and nitrogen for metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Hollow-core optical fibre sensors for operando Raman spectroscopy investigation of Li-ion battery liquid electrolytes

Improved analytical tools are urgently required to identify degradation and failure mechanisms in Li-ion batteries. However, understanding and ultimately avoiding these detrimental mechanisms requires continuous tracking of complex electrochemical processes in different battery components. Here, we report an operando spectroscopy method that enables monitoring the chemistry of a carbonate-based liquid electrolyte during electrochemical cycling in Li-ion batteries with a graphite anode and a LiNi 0.8 Mn 0.1 Co 0.1 O 2 cathode. By embedding a hollow-core optical fibre probe inside a lab-scale pouch cell, we demonstrate the effective evolution of the liquid electrolyte species by background-free Raman spectroscopy. The analysis of the spectroscopy measurements reveals changes in the ratio of carbonate solvents and electrolyte additives as a function of the cell voltage and show the potential to track the lithium-ion solvation dynamics. The proposed operando methodology contributes to understanding better the current Li-ion battery limitations and paves the way for studies of the degradation mechanisms in different electrochemical energy storage systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Southwest Regional Partnership on Carbon Sequestration: Phase III (Final Scientific/Technical Report)

The Southwest Regional Partnership on Carbon Sequestration (SWP) is one of 7 regional partnerships formed in 2003 under the U.S. Department of Energy’s (DOE) Regional Carbon Sequestration Partnerships (RCSPs) initiative. The overall purpose of the initiative was to help determine and implement the technology, infrastructure, and regulations most appropriate to promote carbon storage in different regions of the country. Covering Arizona, Colorado, New Mexico, Oklahoma, Utah, and parts of Texas, Wyoming, and Kansas, the SWP evaluated regional carbon storage and utilization potential and focused on technologies and sites that could complement the region’s strong position in energy production. The project progressed through three phases: • Phase I (2003–2005): Characterized regional geologic formations and CO 2 sources, assessed sequestration potential, and identified pilot test sites. • Phase II (2005–2013): Conducted small-scale field tests to validate sequestration methods, including geologic and terrestrial projects. • Phase III (2008–2022): Demonstrated large-scale CO 2 injection at a commercial oil field to test monitoring, verification, and long-term storage strategies. This report covers Phase III. The final project site, the Farnsworth Unit (FWU) in Texas, provided real-world testing of reservoir characterization, monitoring, and risk evaluation tools and processes that could be used in any commercial scale carbon capture, utilization, and storage (CCUS) project. Extensive data collection and analysis helped refine best practices for reservoir characterization, injection monitoring, and storage verification. The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Key lessons learned include the importance of robust data management, strategic site selection, regulatory navigation, and effective industry collaboration. The project’s findings will inform ongoing and future carbon storage initiatives. Task 1 (Regional Characterization) • The SWP continued to participate in national outreach efforts and NATCARB. • The SWP evaluated multiple potential sites before selecting the FWU as the primary field test location. Task 2 (Public Outreach and Education) • The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Task 3 (Permitting and Regulatory Compliance) • The SWP ensured compliance with federal and state regulations, including National Environmental Policy Act (NEPA) requirements. • The SWP obtained all necessary permits for drilling, injection, and monitoring activities. Task 4 (Site Characterization and Planning) • The SWP developed work plans for four key activities: characterization, simulation, monitoring and verification, and risk evaluation. • The SWP collected and synthesized legacy data from multiple sources to build initial static geological models and dynamic reservoir models demonstrating project feasibility. • The SWP conducted an initial risk evaluation and developed mitigation plans. Task 5 (Field Operations and Data Collection) • The SWP drilled, logged, and cored three characterization wells to gather critical subsurface data. • The SWP conducted multiple geophysical surveys, including 3D seismic, crosswell seismic, and vertical seismic profiling, to improve reservoir characterization. Task 6 (Monitoring and Verification) • The SWP performed extensive geological characterization using data from characterization wells and seismic surveys. • The SWP established a surface monitoring network to track CO 2 flux in soil gas, groundwater chemistry, and near-surface atmospheric CO 2 levels. • The SWP built and refined reservoir models to study the effects of relative permeability on simulation behavior and improve calibration with experimental data. Task 7 (Risk Assessment and Model Refinement) • The SWP conducted multiple studies to evaluate reservoir integrity, predict CO 2 plume behavior and improve predictive modeling capabilities. • The SWP refined geological models and used them to enhance the accuracy of simulation models. • The SWP continued quantitative risk assessment of top-ranked risks and strengthened the link between qualitative and quantitative risk methodologies.

02 PETROLEUM↗