Cold Temperature Direct Air CO 2 Capture with Amine-Loaded Metal–Organic Framework Monoliths
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
SEARCH · Engineering Papers
Results for “Carbon support”
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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Stable and Efficient Single-Atom Zn Catalyst for CO2 Reduction to CH4
Explore the source record for details and available documents.
99 GENERAL AND MISCELLANEOUS↗
Dynamic control and quantification of active sites on ceria for CO activation and hydrogenation
Ceria (CeO 2 ) is a widely used oxide catalyst, yet the nature of its active sites remains elusive. This study combines model and powder catalyst studies to elucidate the structure-activity relationships in ceria-catalyzed CO activation and hydrogenation. Well-defined ceria clusters are synthesized on planar CeO 2 (111) and exhibit dynamic and tunable ranges of Ce coordination numbers, which enhance their interaction with CO. Reduced ceria clusters (e.g., Ce 3 O 3 ) bind CO strongly and facilitate its dissociation, while near-stoichiometric clusters (e.g., Ce 3 O 7 ) adsorb CO weakly and promote oxidation via carbonate formation. Unlike planar ceria surfaces, supported ceria clusters exhibit dynamic properties and enhanced catalytic activity, that mimic those of powder ceria catalysts. Insight from model studies provide a method to quantify active sites on powder ceria and guide further optimization of ceria catalysts for syngas conversion. This work marks a leap toward model-guided catalyst design and highlights the importance of site-specific catalysis.
03 NATURAL GAS↗
General synthesis of single-atom catalysts with high metal loading using graphene quantum dots
Transition-metal single-atom catalysts present extraordinary activity per metal atomic site, but suffer from low metal-atom densities (typically less than 5 wt% or 1 at.%), which limits their overall catalytic performance. Here we report a general method for the synthesis of single-atom catalysts with high transition-metal-atom loadings of up to 40 wt% or 3.8 at.%, representing several-fold improvements compared to benchmarks in the literature. Graphene quantum dots, later interweaved into a carbon matrix, were used as a support, providing numerous anchoring sites and thus facilitating the generation of high densities of transition-metal atoms with sufficient spacing between the metal atoms to avoid aggregation. A significant increase in activity in electrochemical CO 2 reduction (used as a representative reaction) was demonstrated on a Ni single-atom catalyst with increased Ni loading.
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Design of Ru-Ni diatomic sites for efficient alkaline hydrogen oxidation
Anion exchange membrane fuel cells are limited by the slow kinetics of alkaline hydrogen oxidation reaction (HOR). Here, we establish HOR catalytic activities of single-atom and diatomic sites as a function of *H and *OH binding energies to screen the optimal active sites for the HOR. As a result, the Ru-Ni diatomic one is identified as the best active center. Guided by the theoretical finding, we subsequently synthesize a catalyst with Ru-Ni diatomic sites supported on N-doped porous carbon, which exhibits excellent catalytic activity, CO tolerance, and stability for alkaline HOR and is also superior to single-site counterparts. In situ scanning electrochemical microscopy study validates the HOR activity resulting from the Ru-Ni diatomic sites. Furthermore, in situ x-ray absorption spectroscopy and computational studies unveil a synergistic interaction between Ru and Ni to promote the molecular H 2 dissociation and strengthen OH adsorption at the diatomic sites, and thus enhance the kinetics of HOR.
25 ENERGY STORAGE↗
'Omics and Big Data in Harmful Algal Bloom Research
Phytoplankton, a group including eukaryotic microalgae and cyanobacteria, play a crucial climate role converting CO 2 into organic carbon through global primary production. They support a wide range of life, both freshwater and marine, from zooplankton to fish and mammals. While they are essential in nutrient cycles, certain phytoplankton species can proliferate excessively under favorable conditions, leading to harmful algal blooms (HABs) that pose significant threats to human and ecosystem health through the toxins they produce.
59 BASIC BIOLOGICAL SCIENCES↗
Curating Carbon Storage Data for Reuse: Enabling Research and Modeling from Earth’s Surface to Subsurface
The volume of public geologic carbon storage (GCS) data resources has continued to increase in recent years as the result of an increase in funding from government, industry, and academia towards national, basin, regional and field scale studies to ensure carbon capture and storage becomes a commercially viable operation. Despite the increasing volume of data, GCS data applied towards analyses such as geologic, cost, and risk modeling continues to be multi-sourced and often disparate in nature, published across government agencies, websites, data repositories and buried in derivative reports and documents. Much of the time preparing for an analysis and derivative product development is spent collecting, aggregating, transforming and preparing input data. There have been significant efforts within the DOE National Energy Technology Laboratory’s Carbon Storage Program to optimize multi-source, multi-scale subsurface geologic data curation and aggregation to support data discovery, interoperability, and reuse. Methods include the use of artificial intelligence, machine learning, and data science techniques. This talk will discuss the workflows, best practices, and processes developed to support the aggregation and curation of data through the whole system – surface to subsurface data - that support multi-scale, multi-purpose analysis for carbon storage research.
Morkner, Paige↗
Dual Phase Membrane for CO2 Separation (Phase 1) (CRADA Final Report)
This was a collaborative effort between Lawrence Livermore National Security, LLC (LLNS), as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Saint-Gobain Ceramics & Plastics, Inc. (Participant/SG), to develop porous solid support materials for dual-phase carbon dioxide (CO2) separation membranes.
36 MATERIALS SCIENCE↗
Portable unit for metabolic analysis
A portable unit for metabolic analysis includes a manifold in fluid communication with a mouth of a test subject. A conduit extends from the manifold and defines a flow channel through which the breaths of the test subject travels. A carbon dioxide sensor is attached to the conduit. The carbon dioxide sensor includes an intermediate support housing enclosing a volume disposed along the flow channel to define a first part of the flow channel, an inner support housing attached to a first side of the intermediate support housing, a plurality of IR LEDs mounted to an interior surface of the inner support housing, an outer support housing attached to a second side of the intermediate support housing, and a photodetector attached to the outer support housing. The photodetector faces the flow channel and receives IR radiation emitted by the plurality of LEDs.
Dietrich, Daniel L.↗
CO oxidation over a ligand coordinated single site Rh catalyst: identification of the active complex
Single atom catalysis has evolved as a promising strategy to enhance atom utilization efficiency, lower reaction temperatures, and control reaction pathways in heterogeneous catalytic reactions. An important challenge using supported single atom catalysts is the stability of metal single atoms during reactions. Here, we present an approach to stabilize single rhodium atoms on a titania support via a metal–ligand coordination strategy. We explore the reaction activity and mechanism of CO oxidation, as well as the stability under oxidative reaction conditions. Kinetic studies suggest that, with an excess of oxygen in the feed gas, oxygen activation is more facile on defective titania surfaces than on pristine titania surfaces. In situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analysis shows that on the pristine titania surface, the 1,10-phenanthroline-5,6-dione (PDO) coordinated Rh catalyst (Rh–PDO/TiO 2 ) catalyzes CO oxidation via the formation of carbonate-like species, which is similar to what occurs on Rh nanoparticle catalysts. However, on the defective titania surface, no carbonate species form for Rh–PDO/def-TiO 2 . The supported Rh–ligand catalysts are also shown to be very stable in such a reaction environment at elevated temperatures, potentially allowing for wide applications.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Feedstock Carbon Intensity Calculator (FD-CIC) Users’ Manual and Technical Documentation
A transparent and easy-to-use tool for feedstock-specific, farm-level CI calculation of feedstocks is helpful. With the ARPA-E support, we have developed a tool–the Feedstock Carbon Intensity Calculator (FD-CIC). The first version of FD-CIC was released with the GREET® model in 2020 (Wang et al., 2020) so that corn feedstock producers could use this publicly available tool (https://greet.es.anl.gov/tool_fd_cic) to quantify corn grain CIs with farm-level input data and management practices. In the 2021 version, we expand the tool’s capabilities by including additional feedstocks such as soybeans, sorghum, and rice. Similar to corn, it calculates the farm-level CI for these feedstocks by allowing user-defined farm-level farming inputs and incorporating the GHG emission intensities of these inputs from GREET (in particular, GREET1, the fuel cycle model of GREET).
09 BIOMASS FUELS↗
Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)
We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO2 EOR projects utilizing the water-alternating-gas (WAG) process. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.
02 PETROLEUM↗
Opportunity Assessment for Sustainable Aviation Fuel Production from Woody Biomass via Ex Situ Catalytic Fast Pyrolysis and Refinery Hydroprocessing
Biofuels have become a promising solution to reduce emissions in hard-to-electrify transportation sectors, such as aviation. However, several biofuel conversion pathways will likely be needed to scale sustainable aviation fuel (SAF) production to meet lower carbon intensity goals when biomass feedstock availability constraints are considered. This study evaluates the future potential of the catalytic fast pyrolysis (CFP) pathway to contribute to U.S. SAF production goals as outlined in the U.S. Department of Energy’s (DOE) SAF Grand Challenge, understanding that the CFP pathway is still under development toward maturity and scaleup. National forestland resource data from the DOE’s 2023 Billion Ton Study are integrated with recent experimental results demonstrating end-to-end woody biomass conversion to SAF via CFP and hydroprocessing in a novel bioeconomy optimization framework. U.S. refinery hydroprocessing capacity is also considered with repurposing and coprocessing strategies. Results indicate that the CFP process can contribute up to 4.6 billion gallons of SAF annually by 2040, meeting 13% of the 2050 SAF Grand Challenge target while reducing the carbon intensity (CI) of the U.S. jet fuel pool by 16%. The study further explores optimal processing strategies, suggesting that colocating CFP operations with existing petroleum refineries and repurposing some U.S. hydrocracking capacity may offer significant cost advantages and enhance the commercial viability of the CFP pathway. These results underscore the CFP pathway’s potential to support the global aviation industry’s lower carbon intensity objectives while producing other renewable fuels and products.
09 BIOMASS FUELS↗
California Natural and Working Lands Carbon and Greenhouse Gas Model (CALAND) v3.0.0
CALAND is a system of algorithms (.r files) and data developed to quantify the impacts of various suites of California State-supported land use and land management strategies on landscape carbon and greenhouse gas emissions (CO2, CH4, and optional black carbon) relative to a baseline scenario for the Draft California 2030 Natural and Working Lands Climate Change Implementation Plan (2019).
Di Vittorio, Alan↗
Electrostatic gating of ion transport in carbon nanotube porins: A modeling study
Carbon nanotube porins (CNTPs) are biomimetic membrane channels that demonstrate excellent biocompatibility and unique water and ion transport properties. Gating transport in CNTPs with external voltage could increase control over ion flow and selectivity. Herein, we used continuum modeling to probe the parameters that enable and further affect CNTP gating efficiency, including the size and composition of the supporting lipid membrane, slip flow in the carbon nanotube, and the intrinsic electronic properties of the nanotube. Our results show that the optimal gated CNTP device consists of a semiconducting CNTP inserted into a small membrane patch containing an internally conductive layer. Moreover, we demonstrate that the ionic transport modulated by gate voltages is controlled by the charge distribution along the CNTP under the external gate electric potential. The theoretical understanding developed in this study offers valuable guidance for the design of gated CNTP devices for nanofluidic studies, novel biomimetic membranes, and cellular interfaces in the future.
36 MATERIALS SCIENCE↗
Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape: Modeling Archive
This modeling archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025). This archive contains model input files and outputs from landscape-scale simulations conducted using ELM, the land model component of the Department of Energy’s Energy Exascale Earth System Model (E3SM), at the Council NGEE Arctic field site (Council Road mile marker 71) on Alaska’s Seward Peninsula. Input data and model output from two sets of ELM simulations are provided. The first set of simulations were conducted with the two default ELM Arctic plant functional types (PFTs; broadleaf deciduous boreal shrub and a C3 grass) and the second set of simulations were conducted with a set of nine Arctic-specific PFTs including nonvascular mosses and lichens, graminoids, forbs, evergreen dwarf shrubs, three height classes of deciduous shrubs (dwarf, low, and low to tall), and deciduous alder shrubs (Sulman et al., 2021). Parameter names and major parameter changes in the Arctic-specific PFT configuration are described in Sulman et al. (2021) and archived in the Sulman et al. (2021) dataset (see below). Simulations were spatially explicit, covering an approximately 6.4X3.3 km domain at the Council site with a spatial resolution of 100 m for a total of 2,112 simulated grid cells under each ELM PFT configuration. The modeling archive contains meteorological forcing (seven *.nc files and one *.txt file), a domain definition file (one *.nc files), land surface configuration files (two *.nc files), parameter files (two *.nc files), annual ELM output files spanning 1980-2014 (68 *.nc files), and a User’s Guide (*pdf file). Additional information on the provided files is in the “Modeling Archive Contents” section of the User’s Guide. Model outputs are aggregated to the column scale (i.e. PFT-specific outputs are not provided here).
Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
A Geodatabase Designed to Inform and Support Safe CO2 Transport-Route Planning
The National Energy Technology Laboratory developed the Carbon Capture and Storage (CCS) Pipeline Route Planning Database to inform safe and sustainable CO2 transport planning in support of decarbonization efforts. This comprehensive Esri Geodatabase contains over 90 GBs of data and 60+ spatial layers representing key considerations including natural hazards, infrastructure, energy, and social justice. Leveraging ArcGIS Pro, nationwide raster, and vector datasets containing millions of features were processed to be easily digestible for users and complex modeling software.
Romeo, Lucy↗
Cambered Bipyridyl Ligand with Extended Aryl System Enables Electrochemical Reduction of Carbon Dioxide and Bicarbonate by Mn(bpy)(CO) 3 Br-type Catalyst Immobilized on Carbon Nanotubes
Heterogeneous materials containing molecular catalytic sites show promise for electrocatalytic reduction of CO 2 to energy-enriched carbon products. Interactions between the catalyst and the heterogeneous support increasingly are recognized as important in governing product selectivity and rate. Recent work on Mn(R-bpy)(CO) 3 Br type catalysts immobilized on multiwalled carbon nanotubes (MWCNT) demonstrated control of electrocatalytic behavior with steric modification of the molecular catalyst. Phenyl groups installed in the 4,4' positions of the bipyridine ligand (ph-bpy) maximized performance through π–π interactions with the MWCNT support. Herein we report the outcome of extending the ligand π system with Mn(nap-bpy)(CO) 3 Br (nap-bpy = 4,4'-di(naphthalen-1-yl)-2,2'-bipyridine) and Mn(pyr-bpy)(CO) 3 Br (pyr-bpy = 4,4'-di(pyren-1-yl)-2,2'-bipyridine) immobilized on MWCNT. We demonstrate exceptional electrocatalysis with Mn(nap-bpy)(CO) 3 Br/MWCNT (FE CO > 92%; J CO = 16.5 mA/cm 2 ) and find that this catalyst electrochemically reduces bicarbonate in the absence of deliberately added CO 2 at a remarkable overall selectivity of >80% for carbon products (FE HCOO – = 52% and FE CO = 29%). We show diminishing returns to simply adding aromatic character to the bipyridyl ligand with Mn(pyr-bpy)(CO) 3 Br/MWCNT and observe a unique cambering of the Mn(nap-bpy)(CO) 3 Br bipyridyl ligand that we believe enables selective catalysis. Mechanistic studies were carried out on Mn(nap-bpy)(CO) 3 Br/MWCNT using a novel thin-film infrared spectroelectrochemical (IR-SEC) technique. These experiments observe the immobilized Mn(nap-bpy)(CO) 3 Br undergo single electron reduction to a Mn-centered radical that binds CO 2 in a reduction-coupled process.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗