Life Cycle Analysis of Methanol Production via Photocatalytic Carbon Conversion
LCA modeling approach, scenario analysis, and key results of methanol production via photocatalytic carbon conversion.
White, John↗
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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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Integrative Modeling and Analysis of Fungal Central Carbon Metabolism
Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity
59 BASIC BIOLOGICAL SCIENCES↗
Multi-system analysis of offshore geologic carbon storage: a review of open-source data science solutions
Geologic carbon storage projects are maturing worldwide and the footprint of deployment in the offshore is expanding. At present, there are ten projects in operation or that have been completed, more than 50 in construction and development, and dozens of characterization studies completed or underway. Offshore geologic carbon storage offers potential benefits over onshore geologic carbon storage. These offshore projects are generally remote in location, distant from population centers, and avoid complicated pore space rights while having abundant prospective storage potential. Some offshore fields targeted for carbon storage have comparatively fewer prior borehole penetrations except for areas that have been explored for petroleum production, minimizing potential issues such as pressure interference and infrastructure impacts. Yet offshore geologic carbon storage projects face distinctive technical and economic challenges, such as seafloor geohazards (e.g., seabed instability), expensive maritime transport, and meteorological-oceanographic conditions that can damage infrastructure and impact operations. Analytical capabilities and improved computational speeds have advanced engineering, earth and energy sciences in the wake of the arrival of modern data science over the last decade. These advancements have created an opportunity for integrated, multi-systems modeling approaches utilizing artificial intelligence and machine learning that are no longer limited by computational issues. Analytical tools developed alongside this advancement in data science can be leveraged to calibrate the potential advantages and challenges of carbon storage operations in the offshore. New methods and approaches that incorporate data science to analyze multiple aspects of engineered and natural systems can provide insights that complement the characterization and onsite engineering that traditional commercial and operational software addresses. These new methods and approaches can potentially improve the outcome of energy operations and carbon storage. Providing multi-system, science-driven data analytics enhances the knowledge base that offshore developers, operators, and regulatory bodies may draw from to improve offshore site selection and operational efficiency. Here, we provide a brief synopsis of geologic carbon storage efforts to date, an overview of the engineered and natural systems involved in offshore geologic carbon storage, and a review of publicly available, open-source, offshore and/or carbon storage related data- and science-driven tools developed by 2010 or later that are suitable for screening and assessing regions for offshore geologic carbon storage.
artificial intelligence↗
Energy Exascale Earth System Model v2.1.0
First release of version 2.1 of the Energy Exascale Earth System Model. [ATM] The atmosphere component remains EAM. There are no major changes in the default configuration since 2.0. New features include: A semi-lagrangian tracer transport for theta-l dycore, a new algorithm for finding the tropopause, new RRM mesh configurations. Add and update SSP370 and SSP585 cases. Restore the FIDEAL case. [LAND] The land component is ELM. There are no major changes in the default configuration since 2.0. Several option features have been added including: implementation of topography-based subgrid structure (topounits) and accompanying parameterizations and atmospheric forcing downscaling methods; a new plant hydraulics scheme; two-way land-river hydrological coupling through the infiltration of floodplain water; an implementation of perennial crops; updates to the SNICAR-AD snow radiative transfer model; and implementation of soil erosion and sediment yield in ELM-Erosion. Each of these new changes is modular in design and can be turned on or off as the user specifies; they are currently being tested in different “BGC” configurations. [OCEAN] The ocean component remains MPAS-Ocean. Major change since version 2.0 include the addition of the Fox-Kemper et al. 2011 parameterization for submesocale eddies, a correction for barotropic thickness consistency that reduces divergence noise, and the addition of an ocean carbon conservation analysis member. [SEAICE] The sea-ice component remains MPAS-Seaice. Major changes since version 2.0 include: A correction to how shortwave parameters are interpolated in the snicar-ad 5-band radiation scheme, the addition of a sea ice carbon conservation analysis member, updates to the default sea ice biogeochemistry namelist parameters to be consistent with version 2.0 improvements to nitrogen cycling and a correction in the ice-ocean dissolved organic nitrogen coupling. [LAND ICE] The land-ice component remains MPAS-Albany-landIce (MALI). Major changes since 2.0 include an update to the MALI version and the Greenland mesh.[RIVER] The river model is MOSART. There are no major changes in the default configuration since 2.0. A major new optional feature is two-way river-ocean hydrological coupling between MOSART and MPAS-O. This change can be turned on or off as the user specifies, and is being tested in different configurations. [COUPLER] The coupler remains cpl7/MCT. Major changes since version 2.0 include: Carbon budget calculated when heat/water budgets active. Fix a bug in land-atm fluxes for tri-grid configurations. [OTHER] a small bug in the zenith angle calculation was fixed in the data models.
ECP↗
Automated X-Ray Tomographic Defect Analysis in High Density Carbon Capsules
High density carbon capsule ablators are of primary interest for National Ignition Facility experiments. Two of the major contributors to hydrodynamic instabilities in these capsules are voids and high-density inclusions, where the quantity and size of these defects can result in lower yields in inertial confinement fusion. To aid in capsule selection, General Atomics developed a LabVIEW analysis routine to quantify these defects based off a large field of view tomographic dataset and provide insight into the quality of the capsule. Furthermore, this analysis determines if there are large voids or inclusions that may affect shot performance and helps rank which capsules should be used.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Influence of Alkyne Precursor Structure on Carbon Nanotube Chiral Distribution: Data-Dense Analysis Across Multiple Catalyst Types
Carbon nanotubes (CNTs) are a desirable material in the field of optoelectronics and semiconductors due to electronic properties (e.g., bandgap) that are dependent upon their chirality, defined by their diameter and lattice angle. Unfortunately, industrial-scale syntheses have yet to realize growth of a single desired chirality and instead rely on postsynthetic separation techniques to refine a chiral mixture, which increases process complexity and cost. Here, we studied the influence of precursor structure on chiral distribution, using a series of terminal alkyne precursors (acetylene, methylacetylene, vinylacetylene, 1-butyne, two enantiomers of 3-butyn-2-ol and a racemic mixture thereof) to grow CNTs across five transition-metal catalysts (Fe, FeMo, and three proportions of CoMo). Multiwavelength Raman spectroscopy on 5,145 spots (5 catalysts, 7 precursors, 3 lasers, and 49 distinct substrate locations on each) determined that acetylene grew the smallest diameter CNTs, while vinylacetylene produced fewer subnanometer CNTs. Though precursor structure did not dictate a uniform chiral shift, it was shown to broaden or narrow chiral distribution, while catalyst structure played a dominant role. In conclusion, this is consistent with metal-precursor binding occurring through unsaturated bonds in the hydrocarbons via the alkyne polymerization mechanism.
Carbon nanotubes↗
Metal-Catalyzed Thermo-Catalytic Decomposition and Continuous Catalyst Generation
In this study, metal dusting is utilized to initiate a two-stage thermo-catalytic decomposition (TCD) process. Stage 1 starts with metal-catalyzed TCD, and in stage 2 the metal-catalyzed carbon catalyzes additional TCD. TEM is presented of the early- versus late-stage TCD to qualitatively illustrate the second-stage TCD by the metal-catalyzed carbons. Corresponding SEM illustrates differences in growth type and surface density between early versus late reaction times, with backscattered imaging differentiating the first- versus second-stage TCD. TGA supports the microscopic inference of a second carbon phase by the presence of an early (low-temperature) reaction peak, characteristic of low-structure or disordered carbon as the second-stage TCD carbon. Raman analysis confirms that the second-stage carbon deposit is more disordered and unstructured, especially at 1000 °C, supported by the ID/IG and La value changes from 0.068 to 0.936 and 65 nm to 4.7 nm, respectively. To further confirm second-stage TCD occurrence upon pre-catalyzed carbons, two carbon blacks are tested. Exposing a combination of edge and basal or exclusively basal sites for the graphitized form, they afford a direct comparison of TCD carbon nanostructure dependence upon the initial carbon catalyst nanostructure. Pre-oxidation of the stainless-steel wool (SSW) prior to TCD is advantageous, accelerating TCD rates and increasing carbon yield relative to the nascent SSW for an equivalent reaction duration.
Chemistry↗
Tropical Red Macroalgae Cultivation with a Focus on Compositional Analysis
To create carbon efficient sources of bioenergy feedstocks and feedstuff for aquaculture and terrestrial livestock, it is critical to develop and commercialize the most efficient seaweed cultivation approach with a sustainable nutrient input supply. Here, we present data for a novel, onshore tropical macroalgae cultivation system, based on influent deep seawater as the nutrient and carbon sources. Two red algal species were selected, Agardhiella subulata and Halymenia hawaiiana, as the basis for growth optimization. Highest productivity in small-scale cultivation was demonstrated with A. subulata in the 10% deep seawater (64.7 µg N L−1) treatment, growing at up to 26% specific growth rate day−1 with highest yields observed at 247.5 g m−2 day−1 fresh weight. The highest yields for H. hawaiiana were measured with the addition of 10% deep seawater up to 8.8% specific growth rate day−1 and yields at 63.3 g fresh weight m−2 day−1 equivalent. Biomass should be culled weekly or biweekly to avoid density limitations, which likely contributed to a decrease in SGR over time. With a measured 30–40% carbon content of the ash-free dry weight (20–30% of the dry weight) biomass, this translates to an almost 1:1 CO2 capture to biomass ratio. The compositional fingerprint of the high carbohydrate content of both Agardhiella and Halymenia makes for an attractive feedstock for downstream biorefinery applications. By focusing on scaling and optimizing seaweed farming technologies for large-scale onshore farms, the opportunities for yield potential, adaptability to cultivation conditions, and meeting global sustainability goals through novel, carbon-negative biomass sources such as seaweed can be realized.
09 BIOMASS FUELS↗
Diverse organic carbon dynamics captured by radiocarbon analysis of distinct compound classes in a grassland soil
Soil organic carbon (SOC) is a large, dynamic reservoir composed of a complex mixture of plant- and microbe-derived compounds with a wide distribution of cycling timescales and mechanisms. The distinct residence times of individual carbon components within this reservoir depend on a combination of factors, including compound reactivity, mineral association, and climate conditions. To better constrain SOC dynamics, bulk radiocarbon measurements are commonly used to trace biosphere inputs into soils and to estimate timescales of SOC cycling. However, understanding the mechanisms driving the persistence of organic compounds in bulk soil requires analyses of SOC pools that can be linked to plant sources and microbial transformation processes. Here, we adapt approaches, previously developed for marine sediments, to isolate organic compound classes from soils for radiocarbon ( 14 C) analysis. We apply these methods to a soil profile from an annual grassland in Hopland, California (USA), to assess changes in SOC persistence with depth (down to 1 m). We measured the radiocarbon values of water-extractable organic carbon (WEOC), total lipid extracts (TLEs), total hydrolyzable amino acids (AAs), and an acid-insoluble (AI) fraction from bulk and physically separated size fractions (< 2 mm, 2 mm–63 µm, and < 63 µm). Our results show that Δ 14 C values of bulk soil, size fractions, and extracted compound classes became more depleted with depth, and individual SOC components have distinct age–depth distributions that suggest distinguishable cycling rates. We found that AAs and TLEs cycle faster than the bulk soils and the AI fraction. The AI was the most 14 C-depleted fraction, indicating that it is the most chemically inert in this soil. Our approach enables the isolation and measurement of SOC fractions that separate functionally distinct SOC pools that can cycle relatively quickly (e.g., plant and microbial residues) from more passive or inert SOC pools (associated with minerals or petrogenic) from bulk soils and soil physical fractions. With the effort to move beyond SOC bulk analysis, we find that compound class 14 C analysis can improve our understanding of SOC cycling and disentangle the physical and chemical factors driving OC cycling rates and persistence.
58 GEOSCIENCES↗
Carbon, Nitrogen, and Sulfur Analysis of the Cetama Viognier Standard Reference Material
The Viognier sample was analyzed for C, N, and S concentrations and stable isotope compositions using an Elementar Vario Isotope Cube Elemental Analyzer (EA) that is coupled to an IsoPrime PrecisION IRMS. Powder samples were placed in tin capsules and then loaded onto a rotary autosampler. The autosampler dropped samples into the EA, and samples were combusted at 1175 °C over tungsten oxide in a continuous stream of helium carrier gas. A pulse of oxygen is added to the gas stream resulting in flash combustion of the tin capsule containing the sample, which raises the reaction temperature to approximately 1800 °C for a few seconds. The combustion reaction produces SO 2 , N 2 and CO 2 from any sulfur, nitrogen and carbon present in the sample. The resulting gases were then passed through a reduced copper reactor that was heated to 850 °C, to reduce NO x to N 2 , reduce SO 3 to SO 2 , and trap any volatile halogen compounds on silver wool. Following water removal using an adsorption tube, the N 2 , CO 2 , and SO 2 analyte gases were separated and purified using purge-trap columns. The purified gases were then carried through a thermal conductivity detector. The detector signal was passed to software that calculated elemental abundances based on integrated peak areas. The sample gases were then passed to the IRMS and stable isotope ratios were measured. Raw sample peak areas were corrected by subtracting the average peak area from blanks consisting of empty tin capsules run using the same EA analysis method. Blanks were also run following each replicate to verify that all the material was combusted. The Viognier sample was analyzed in triplicate on two days (target sample masses: 30, 60 and 90 mg). The following standards were analyzed to calibrate EA-IRMS measurements: IAEA-C6, USGS-40, USGS-41, IAEA-S1, and IAEA-S2.
38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
Parts-Per-Million Carbonate Mineral Quantification with Thermogravimetric Analysis–Mass Spectrometry
Mitigating the deleterious effects of climate change requires the development and implementation of carbon capture and storage technologies. To expand the monitoring, verification, and reporting (MRV) capabilities of geologic carbon mineralization projects, we developed a thermogravimetric analysis–mass spectrometry (TGA–MS) methodology to enable quantification of <100 ppm calcite (CaCO 3 ) in complex samples. We extended TGA–MS calcite calibration curves to enable a higher measurement resolution and lower limits of quantification for evolved CO 2 from a calcite–corundum mixture. We demonstrated <100 ppm carbonate mineral quantification with TGA–MS for the first time, an outcome applicable across earth, environmental, and materials science fields. We applied this carbonate quantification method to a suite of Columbia River Basalt Group (CRBG) well cuttings recovered in 2009 from Pacific Northwest National Laboratory’s Wallula #1 Well. Our execution of this new combined calcite and calcite–corundum calibration curve TGA–MS method on our CRBG sample suite indicated average carbonate contents of 0.050 wt % in flow interiors (caprocks) and 0.400 wt % in interflow zones (reservoirs) in the upper 1250 m of the Wallula #1 Well. Finally, by advancing our knowledge of continental flood basalt-hosted carbonates in the mafic subsurface and reaching new TGA–MS quantification limits for carbonate minerals, we expand MRV capabilities and support the commercial-scale deployment of carbon mineralization projects in the Pacific Northwest United States and beyond.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Life Cycle Analysis and Techno-Economic Analysis Tools to Evaluate Carbon Conversion Technologies
Description of NETL CO2U LCA Guidance Toolkit and TEA Toolkit that includes goals, key points, overview of toolkit elements and toolkit utilities.
Moni, Sheikh↗
CarbStor: Development, Analysis and Modification of Carbon Storing Model Soil Communities
Soil microbial communities carry out a number of key processes including plant growth promotion, bioremediation and cycling of nutrients. Carbon cycling is among the most important of these nutrients that are metabolized and processed by the soil microbial community. Many of the carbon inputs are converted to alternative organic forms of carbon that can be used by plants or act as biomass for microbial growth. However, inorganic forms of carbon can also be produced by soil microbial communities including calcium carbonate (CaCO 3 ). Production of calcium carbonate is beneficial for the ecosystem in several ways: it can stabilize soils and improve soil health, especially denser soils with high clay content, it can act as a method of bioremediation, it can serve as an alternative carbon source for plants and it can be a way to store carbon in soil in a stable, inorganic manner for the long term. While the chemistry surrounding individual species carrying out this process is well known what is lacking is an understanding of how species interact in a community to drive carbonate production. As all microbial species in soil exist in a community setting gaining this knowledge is critical to our predicting and controlling this microbial phenotype to greatly improve soil health. The CarbStor project is focused on developing, analyzing and modifying defined microbial soil consortia that express phenotypes at both the species and community level to convert carbon into recalcitrant stable sources such as precipitated carbonate or microbial necromass. To take full advantage of the soil community for this process we will need to fill several key knowledge gaps (KG), three of which are the focus of CarbStor. KG1: Whether and to what degree microbial communities can be developed that produce precipitated carbon via microbial metabolism. KG2: What interspecies interactions drive the individual member phenotypes in defined communities that lead to carbon precipitation. KG3: How can these interactions be modified to enhance carbon sequestration beyond what native communities are capable of. We hypothesize that in a carbon sequestering community only a subset of species will express phenotypes related to carbon storage processes. We also hypothesize that these phenotypes are expressed as a result of interactions with other species in the community that are not involved in carbon storage processes and that these interactions can be harnessed to enhance community carbon sequestration.
54 ENVIRONMENTAL SCIENCES↗
Biomass Environmental Analysis in Bioenergy with Carbon Capture and Storage Modeling
Goals, key points and updates of Bioenergy with Carbon Capture and Storage (BECCS) Tool.
Izar-Tenorio, Jorge↗
Process-oriented analysis of dominant sources of uncertainty in the land carbon sink
The observed global net land carbon sink is captured by current land models. All models agree that atmospheric CO 2 and nitrogen deposition driven gains in carbon stocks are partially offset by climate and land-use and land-cover change (LULCC) losses. However, there is a lack of consensus in the partitioning of the sink between vegetation and soil, where models do not even agree on the direction of change in carbon stocks over the past 60 years. This uncertainty is driven by plant productivity, allocation, and turnover response to atmospheric CO 2 (and to a smaller extent to LULCC), and the response of soil to LULCC (and to a lesser extent climate). Overall, differences in turnover explain ~70% of model spread in both vegetation and soil carbon changes. Further analysis of internal plant and soil (individual pools) cycling is needed to reduce uncertainty in the controlling processes behind the global land carbon sink.
54 ENVIRONMENTAL SCIENCES↗