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Results for “Carbon use efficiency”

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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Integrated Water-Gas-Shift Pre-combustion Carbon Capture Process

TDA Research, Inc (TDA) has developed a highly efficient integrated WGS pre-combustion carbon capture technology and demonstrated its techno-economic viability for use in the Integrated Gasification Combined Cycle (IGCC) power plants that process coal. The new system uses a warm gas CO 2 scrubber integrated with a Water-Gas-Shift (WGS) catalyst to capture greater than 90% of the carbon emissions, which does not increase the cost of electricity (COE) as much as conventional carbon capture technologies.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Wind-Driven Direct Air Capture System Using 3D Printed, Passive, Amine-Loaded Contactors (WEDAC)

This project advanced the development of a novel wind-driven direct air capture (WEDAC) system for removing carbon dioxide (CO 2 ) from the atmosphere. Our research focused on combining passive air contact with electrothermal desorption using specially designed carbon fiber modules, aiming to provide a scalable, low-cost, and energy-efficient alternative to conventional carbon capture systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Light Duty Engine Performance Characteristics with Dimethyl Ether and Propane

Here, this paper explores the performance characteristics of a compression ignition HYUNDAI 2.2L engine operating with Dimethyl Ether (DME). Test are carried out at three operating conditions that weigh heavily in the FTP75 certification cycle (1000rpm-12Nm, 1500rpm-50Nm, 2000rpm-100Nm). The engine features a high-pressure common rail fuel injection system designed to operate with liquified gases. The main component of the fuel system is a high-pressure pump that incorporates an electronic inlet metering valve commanded on a crank-angle base to control the rail pressure. The pump, which requires no pressure regulator, provides the flow needed to the injectors without flow returning to the inlet. This novel fueling system is leveraged in tests that are conducted to examine the impact of EGR, combustion phasing, injection pressure on efficiency and emissions. In addition, the impact of introducing 15% Propane by mass is examined. During the tests, the engine ECU is aided by an Engine Controller High Speed Oversight unit (ECHO) to provide combustion phasing control, improved cylinder-to-cylinder uniformity, and an effective optimization over the testing effort. The use of DME and Propane allowed for peak thermal efficiency of nearly 43%. These fuels enable significant carbon index (CI) reductions over the baseline Diesel fuel, with indications that 50% reduction in CO 2 over the Diesel engine are possible.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Regenerative adsorbents of modified amines on solid supports

The invention relates to regenerative, solid sorbents for adsorbing carbon dioxide from a gas mixture, including air, with the sorbent including a modified polyamine and a solid support. The modified polyamine is the reaction product of an amine and an epoxide. The sorbent provides structural integrity, as well as high selectivity and increased capacity for efficiently capturing carbon dioxide from gas mixtures, including the air. The sorbent is regenerative, and can be used through multiple cycles of adsorption-desorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Regenerative adsorbents of modified amines on solid supports

The invention relates to regenerative, solid sorbents for adsorbing carbon dioxide from a gas mixture, including air, with the sorbent including a modified polyamine and a solid support. The modified polyamine is the reaction product of an amine and an epoxide. The sorbent provides structural integrity, as well as high selectivity and increased capacity for efficiently capturing carbon dioxide from gas mixtures, including the air. The sorbent is regenerative, and can be used through multiple cycles of adsorption-desorption.

Goeppert, Alain↗
DOE OSTI2024

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

Presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗
DOE OSTI2024

Enhancing Fluid Flow Pressure and Saturation Prediction Accuracy and Reducing Uncertainty with Committee Machine – Illinois Basin Decatur Project (IBDP) as a Case Study

This is the conference paper accompanying an oral presentation at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. Carbon capture and storage (CCS) is a way to play a critical role in the global transition to a low-emission economy. Current progress is hampered by a number of factors, among which the lack of risk-informed design tools and decision support frameworks is seen as a major roadblock. Significant interest exists in using artificial intelligence to accelerate CCS site feasibility studies, as well as to facilitate the permit application process. Existing works commonly train a single deep learning model. This work investigates the feasibility of using a conventional ensemble learning (committee machine) technique to further improve prediction accuracy. Ensemble-based algorithms generally improve over individual base learners in terms of robustness and accuracy. Deep ensembles, however, are time-consuming to create and train. A pragmatic question is whether small-sized ensembles may lead to prediction improvement. Here we evaluated the efficacy of an ensemble learning technique using the latent spectral model (LSM), an efficient deep neural operator algorithm, as base learners. Preliminary results, obtained using the Illinois Basin-Decatur Project (IBDP) carbon sequestration data/model, show that small-sized ensembles can improve prediction over the base learners, achieving prediction accuracy of ~1.6 psi root mean square error (RMSE) on pressure (relative the average reservoir pressure of 3150 psi), and less than 1.3% for saturation.

Sun, Alexander↗
DOE OSTI2021

Efficient Failure Probability Calculations and Modeling Interface Debonding in TRISO Particles with BISON

This document constitutes completion of the NEAMS milestone, which is titled Demonstrate efficiency improvements in TRISO failure probability calculations and the effect of debonding on fission product transport in TRISO fuel particles in Bison . In this report we present the development of the following: (1) the anisotropic elasticity model of pyrolytic carbon and extended material models using the local coordinate system for aspherical particle geometry; (2) a capability of modeling interface debonding in TRISO particles; and (3) an efficient high-fidelity approach to calculate the failure probability of TRISO particles. Benchmark problems and AGR-2 tests are used to verify the models and demonstrate these new capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A synthetic co-culture for bioproduction of ammonia from methane and air

Abstract Fixed nitrogen fertilizers feed 50% of the global population, but most fixed nitrogen production occurs using energy-intensive Haber–Bosch-based chemistry combining nitrogen (N2) from air with gaseous hydrogen (H2) from methane (CH4) at high temperatures and pressures in large-scale facilities sensitive to supply chain disruptions. This work demonstrates the biological transformation of atmospheric N2 into ammonia (NH3) using CH4 as the sole carbon and energy source in a single vessel at ambient pressure and temperature, representing a biological “room-pressure and room-temperature” route to NH3 that could ultimately be developed to support compact, remote, NH3 production facilities amenable to distributed biomanufacturing. The synthetic microbial co-culture of engineered methanotroph Methylomicrobium buryatense (now Methylotuvimicrobium buryatense) and diazotroph Azotobacter vinelandii converted three CH4 molecules to l-lactate (C3H6O3) and powered gaseous N2 conversion to NH3. The design used division of labor and mutualistic metabolism strategies to address the oxygen sensitivity of nitrogenase and maximize CH4 oxidation efficiency. Media pH and salinity were central variables supporting co-cultivation. Carbon concentration heavily influenced NH3 production. Smaller-scale NH3 production near dispersed, abundant, and renewable CH4 sources could reduce disruption risks and capitalize on untapped energy resources. One-Sentence Summary Co-culture of engineered microorganisms Methylomicrobium buryatense and Azotobacter vinelandii facilitated the use of methane gas as a sole carbon feedstock to produce ammonia in an ambient temperature, atmospheric pressure, single-vessel system.

Biotechnology & Applied Microbiology↗
DOE OSTI2022

Selective hydrodeoxygenation of 5-hydroxymethylfurfural (HMF) to 2,5-dimethylfuran (DMF) over carbon supported copper catalysts using isopropyl alcohol as a hydrogen donor

Selective hydrodeoxygenation (HDO) of 5-hydroxymethylfurfural to 2,5-dimethylfuran is of great importance. Here, we reveal a simple pathway for green and efficient HDO using readily available copper with in-situ hydrogen generation. A highly dispersed Cu/PBSAC catalyst consisting of small metallic Cu 0 nanoparticles carries out isopropyl alcohol (IPA) dehydrogenation and subsequent HDO of HMF. Density functional theory calculations reveal that the dehydrogenation of IPA is more favorable on Cu(211) with a lower energy barrier of ~0.6 eV. This facet exists in a higher ratio on nanosized catalysts. Batch reactions using Cu/PBSAC at 190 °C exhibited 91.9% HMF conversion and 71.7% DMF selectivity in 6 hr, and > 96% DMF yield in 10 hr. The mechanical strength of the carbon support is ideal for continuous processing for increased productivity; we demonstrate a > 90% DMF yield at 1/WHSV of 2.4 hr. The process demonstrated here can be integrated with upstream HMF separation utilizing carbon adsorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Engineering Enzymes for Environmental Sustainability

The development and implementation of more efficient and sustainable technologies is key to delivering our net–zero targets. Here we review how engineered enzymes, with a focus on those developed using directed evolution, can be deployed to improve the sustainability of numerous processes and help to conserve our environment. Efficient and robust biocatalysts have been engineered to capture carbon dioxide (CO2) and have been embedded into new efficient metabolic CO2 fixation pathways. Enzymes have been refined for bioremediation, enhancing their ability to degrade toxic and harmful pollutants. Biocatalytic recycling is gaining momentum, with engineered cutinases and PETases developed for the depolymerization of the abundant plastic, PET. Finally, biocatalytic approaches for accessing petroleum–based feedstocks and chemicals are expanding, using optimized enzymes to convert plant biomass into biofuels or other high value products. Finally, through these examples, we hope to illustrate how enzyme engineering and biocatalysis can contribute to the development of more environmentally sustainable approaches, in order to protect our planet.

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

Recovering carbon losses in CO 2 electrolysis using a solid electrolyte reactor

The practical implementation of electrochemical CO 2 reduction technology is greatly challenged by notable CO 2 crossover to the anode side, where the crossed-over CO 2 is mixed with O 2 , via interfacial carbonate formation in traditional CO 2 electrolysers. Here we report a porous solid electrolyte reactor strategy to efficiently recover these carbon losses. Furthermore, by creating a permeable and ion-conducting sulfonated polymer electrolyte between cathode and anode as a buffer layer, the crossover carbonate can combine with protons generated from the anode to re-form CO 2 gas for reuse without mixing with anodic O 2 . Using a silver nanowire catalyst for CO 2 reduction to CO, we demonstrated up to 90% recovery of the crossover CO 2 in an ultrahigh gas purity form (>99%), while delivering over 90% CO Faradaic efficiency under a 200 mA cm -2 current. A high continuous CO 2 conversion efficiency of over 90% was achieved by recycling the recovered CO 2 to the CO 2 input stream.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Presence of aromatic-rich organic matter and its characterization in grout materials: Implications for radionuclide immobilization

Grout materials are commonly used to immobilize low-level radioactive waste. Organic moieties can be unintentionally present in common ingredients used to make these grout waste forms, which may result in the formation of organo-radionuclide species. These species can positively or negatively affect the immobilization efficiency. However, the presence of organic carbon compounds is rarely considered in models or characterized chemically. Here, we quantify the organic pool of grout formulations with and without slag, as well as the individual dry ingredients used to make the grout samples (ordinary Portland cement (OPC), slag and fly ash), including total organic carbon (TOC) and black carbon, followed by aromaticity evaluation and molecular characterization via Electro Spray Ionization Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry (ESI-FTICRMS). All dry grout ingredients contained significant amounts of organic carbon, ranging from 550 mg/kg to 6250 mg/kg for the TOC pool, with an averaged abundance of 2933 ± 2537 mg/kg, of which 60 ± 29% was composed of black carbon. The significant abundance of a black carbon pool implies the presence of the aromatic-like compounds, which was further identified by both phosphate buffer-assisted aromaticity evaluation (e.g., >1000 mg-C/kg as aromatic-like carbon in the OPC) and dichloromethane (DCM) extraction with ESIFTICRMS analysis. Besides aromatic-like compounds, other organic moieties were also detected in the OPC, such as carboxyl-containing aliphatic molecules. While the organic compound only consists of minor fractions of the grout materials investigated, our observations of the presence of various radionuclide-binding organic moieties suggests the potential formation of organo-radionuclides, such as radioiodine, which might be present at lower molar concentrations than TOC. Here, evaluating the role of organic carbon complexation in controlling the disposed radionuclides, especially for those radionuclides with strong association with organic carbon, has important implications for the long-term immobilization of radioactive waste in grout systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Intra-canopy leaf trait variation facilitates high LAI and compensatory growth in a clonal woody encroaching shrub in the tallgrass prairie

This data package contains the data for Tooley et al. (2022) Intra-canopy leaf trait variation facilitates high leaf area index and compensatory growth in a clonal woody encroaching shrub. The purpose of this project was to evaluate the leaf ecophysiological traits of Cornus drummondii C.A. Mey to better understand how C. drummondii maximizes photosynthetic rates across large gradients of light availability in its short, dense canopies. We also evaluate how C. drummondii modifies its allocation of leaf traits in response to grassland disturbance. High LAI canopies and a compensatory growth response to disturbance are two key factors contributing to the success of C. drummondii and other woody species responsible for the encroachment of grasslands.The data package contains ecophysiological measurements, including leaf morphological, physiological, and chemical traits; photosynthetic measurements, leaf carbon and nitrogen stable isotopes, leaf area index, and photosynthetically active radiation. All measurements were taken vertically across canopies of the clonal woody-encroaching shrub Cornus drummondii under browsed, grazed, and control (unbrowsed and ungrazed) conditions.Files:SeasonalMeasurements_Archive.csv - Data for all seasonal measurements used in the study.LeafPhotoSeasonalRaw_Archive.zip - zip file containing raw data from an li-6400 for each sampling period in the study.LAI_Archive.xlsx - Data for LAI Measurements.ACiandLightCurveResults_Archive.xlsx - Contains parameters extracted from A-ci and Light Response curves along with the morphological and chemical traits for each leaf.ACiRaw Archive.xlsx - Raw data from Li-6400 for A-ci response curvesLightCurves_Raw.zip - zip file containing raw data for Li-6400 light response curves. Excel file format: "IslandID"-"Depth"-lc.xlsx (or .csv)DataCollectionMethods.docx - file containing the methods of data collection, processing, and QA/QC for all data files. File also contains a list of excel file headers, abbreviations, and their units.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Modeling of Synfuel Production Process: ASPEN Model of FT production with electricity demand provided at LWR scale

Synfuels, or electro-fuels (e-fuels) have the unique potential to significantly reduce greenhouse gas (GHG) emissions across the transportation sector. This is especially true for applications with substantial payloads and daily miles traveled, such as long-haul heavy-duty vehicles, rail locomotives, marine vessels and aviation aircrafts that are challenging to directly electrify via battery or fuel cell powertrain technologies. Synfuels, or electro-diesel/electro-jet fuels, have similar properties with the incumbent petroleum fuels, compatible with current infrastructure but have much lower GHG emissions relative to the petroleum counterpart, because they utilize waste carbon dioxide (CO2) streams and green hydrogen (H2) sourced from electrolysis. To achieve substantial reductions in GHG emissions, electricity sources must be zero carbon or near-zero carbon, which is the case with solar, wind, hydro and nuclear power. Compared to the intermittency of solar, wind and hydro, nuclear energy provides a steady energy source. In addition, it’s advantageous for nuclear power to produce synfuels because it provides not only near-zero carbon electricity to displace grid electricity, but also near-zero carbon steam to displace carbon-intensive natural gas combustion for steam generation. The availability of electricity and steam also enables more efficient green hydrogen production by using high-temperature electrolysis. In this work, Argonne National Laboratory (ANL) models a synfuel production process via the Fischer- Tropsch (FT) reaction by using nuclear power to provide electricity and steam. In 2021, using ASPEN Plus software, ANL established a detailed process model of a stand-alone FT production facility, assuming feedstocks of pure CO2 and H2. This stand-alone model can be expanded to integrate H2 production from nuclear power via low-temperature and high-temperature electrolysis at light-water reactor (LWR) scale. This report summarizes the stand-alone ASPEN Plus model results with a detailed mass and energy analysis. Our modeled facility produces 351 MT/day (130,000 gal/day) of FT fuel (a mixture of naphtha, jet fuel, and diesel) by converting 223 MT/day of H2 and 2,387 MT/day of CO2. The FT fuel production energy efficiency is 58% and the carbon conversion efficiency (from CO2 to FT fuel) is 46%. The production of green hydrogen requires 390–470 MWe of electricity, which is compared with the capacity of an LWR plant. For the stand-alone FT process, the detailed energy demand (electricity and heat) is summarized in the table below. Based on the energy supply source and the required temperature, potential insertion points of nuclear energy are identified. Based on the potential nuclear energy utilization, this report discusses potential modification options for expanding the system boundary to integrate nuclear power use, for example on-site hydrogen production via water electrolysis. Modeling of the integrated system is conducted by closely working with ANL and Idaho National Laboratory (INL) collaborators to harmonize design parameters of nuclear plants and the FT production process.

Zang, Guiyan↗
DOE OSTI2025

Sorbent Mediated Electrocatalytic Reduction of Dilute CO 2 to Methane

Efficient CO 2 utilization is a critical component of closing the anthropogenic carbon cycle. Most studies have focused on the use of pure streams of CO 2 . However, CO 2 is generally available only in dilute streams, which requires capture by sorbents followed by energy-intensive regeneration to release concentrated CO 2 . Direct utilization of sorbed-CO 2 avoids the costly regeneration step, and the sorbent-CO 2 interaction can kinetically activate CO 2 to tune its reactivity toward products that could otherwise be inaccessible with direct CO 2 reduction. We demonstrate that an N-heterocyclic carbene, 1,3-bis(2,6-diisopropylphenyl)imidazol-2-ylidene (DPIy), quantitatively reacts with CO 2 from dilute streams (0.04 and 10%) to form the sorbent-CO 2 substrate 1,3-bis(2,6-diisopropylphenyl)imidazolium-2-carboxylate (DPICx). Electrocatalyst iron tetraphenylporphyrin chloride (Fe(TPP)Cl) typically reduces CO 2 to CO; however, with DPICx as the substrate, the eight-electron reduced product methane (CH 4 ) is produced with a high Faradaic efficiency (>85%) and regeneration of the sorbent DPIy. In addition to the overall energy and capital advantages of integrated CO 2 capture and conversion, this result illustrates how sorbents can serve a dual purpose for both CO 2 capture and chemical auxiliary purposes to access unique products. CO 2 has a spectrum of reactivity with different types of sorbents; thus, these studies demonstrate how sorbent-CO 2 interactions can be leveraged for integrated capture and utilization platforms to access a wider range of CO 2 -derived products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Generating high-resolution total canopy SIF emission from TROPOMI data: Algorithm and application

Solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in modeling global terrestrial gross primary production (GPP). Canopy total SIF emissions (SIF total ) are mechanistically linked to the plant photosynthesis, and can be estimated from satellite observed SIF (SIF obs ) through radiative transfer modeling. However, the current satellite SIF obs and thus SIF total are available only at coarse spatial resolutions from several kilometers to tens of kilometers, inhibiting the application at fine spatial scales. Here, in this work, we proposed an algorithm to generate both global high-resolution SIF total (HSIF total ) and high-resolution SIF obs (HSIF obs ) at 1 km from low-resolution SIF obs (LSIF obs ) from the TROPOspheric Monitoring Instrument (TROPOMI), which has a spatial resolution at nadir of 3.5 km by 5.6–7 km. Our statistical method is based on the law of energy conservation and uses satellite derived fraction of absorbed photosynthetically active radiation, fluorescence efficiency, and the escape probability of fluorescence. We evaluated the accuracy of our HSIF total using the Orbiting Carbon Observatory-2 SIF (R 2 = 0.78). We found that the spatial resolution had clear effects on the relationship between HSIF total and GPP. We also compared HSIF total to 8-day averaged tower GPP from 135 flux sites and found that they were better correlated when HSIF total was averaged over a 1-km radius around the tower than when averaged over a larger radius. Our study provided a unique high-resolution HSIF total product, which will advance the estimation of GPP by extrapolating site-level relationships to the global scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

How to Minimize Faradaic Efficiency Error in Electrochemical CO 2 Reduction for Gas Products

Faradaic efficiency (FE) is an important metric for evaluating electrochemical processes, such as carbon dioxide reduction, that is often used for performance comparisons. Although the equation to calculate FE is well-known, details needed to yield accurate values are often overlooked, potentially leading to errors exceeding 100%. Avoiding any errors is crucial for drawing correct conclusions, especially during a catalysis optimization process. Factors with high potential for FE errors include incorrect mass flow rates and temperature values, imprecise gas chromatography calibrations, and uncorrected gas viscosities, while factors with less potential are also identified. In conclusion, this manuscript presents FE calculation guidelines intended for both newcomers and experts in the field of electrochemical fuel production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗